This document summarizes research on ship detection methods in visible light remote sensing images. It discusses both traditional and deep learning-based methods. Traditional methods detect ships through feature extraction and classification, but struggle with complex backgrounds. Deep learning methods using convolutional neural networks have achieved better performance than traditional methods. Recent work has focused on introducing rotating bounding boxes to detect ships in different orientations, as well as using semantic segmentation to improve detection accuracy. Overall, deep learning represents the most promising approach, but challenges remain in adapting these methods for remote sensing images.
Digital technologies have greatly advanced orthodontic diagnostic aids. Digital imaging uses electronic sensors instead of film and allows for image enhancement techniques like contrast optimization. Digitalized surface imaging uses laser scanning or stereophotogrammetry to create 3D surface models of the teeth and jaws. Digital casts can be obtained via direct interior scanning or indirect external scanning and offer advantages over physical casts like elimination of breakage and easy sharing. 3D occlusograms combine lateral ceph images and occlusal views to model the 3D occlusal relationship. These recent diagnostic technologies provide more detailed information to aid orthodontic treatment planning.
Digital cephalometrics involves recording cephalometric images digitally rather than on film. There are two main methods: indirect digital radiography (computed radiography) which uses photostimulable phosphor plates that are digitally scanned, and direct digital radiography which uses electronic sensors connected directly to a computer. Digital cephalometrics reduces radiation exposure and allows images to be enhanced, stored digitally, and analyzed using software. While a few parameters showed statistically significant differences between digital and conventional methods, the differences were deemed to not be clinically significant. Digital cephalometrics is now the preferred method over conventional film-based techniques.
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
offering a wide range of dental certified courses in different formats.for more details please visit
www.indiandentalacademy.com
Object detection for KRSBI robot soccer using PeleeNet on omnidirectional cameraTELKOMNIKA JOURNAL
Kontes Robot Sepak Bola Indonesia (KRSBI) is an annual event for contestants to compete their design and robot engineering in the field of robot soccer. Each contestant tries to win the match by scoring a goal toward the opponent's goal. In order to score a goal, the robot needs to find the ball, locate the goal, then kick the ball toward goal. We employed an omnidirectional vision camera as a visual sensor for a robot to perceive the object’s information. We calibrated streaming images from the camera to remove the mirror distortion. Furthermore, we deployed PeleeNet as our deep learning model for object detection. We fine-tuned PeleeNet on our dataset generated from our image collection. Our experiment result showed PeleeNet had the potential for deep learning mobile platform in KRSBI as the object detection architecture. It had a perfect combination of memory efficiency, speed and accuracy.
Gongpu Lan is an optical engineer and research associate at the University of Houston College of Optometry. He has over 15 years of experience in optical design, simulation, and evaluation. Some of his past roles include designing adaptive optics systems for retinal imaging and developing aerial camera lenses. He has authored several patents and publications in the fields of adaptive optics and biomedical imaging.
Robust Motion Detection and Tracking of Moving Objects using HOG Feature and ...CSCJournals
Detection and tracking of moving objects has gained significant importance due to intense technological progress in the field of computer science dealing with video surveillance systems. Human motion is generally nonlinear and non-Gaussian and thus many algorithms are not suitable for tracking. One of the applications to maintain universal security is crowd control. The main problem of video surveillance is continuous monitoring with regard to crime prevention. For security monitoring of live surveillance systems, target identification and tracking strategies can automatically send warnings to monitoring officers. In this paper, we propose a robust tracking of a specified person using the individuals' feature. The proposed method to determine automatic detection and tracking combines Histogram of Oriented Gradient (HOG) feature detection with a particle filter. The Histogram oriented Gradient features are applied to single detection window for the identification of human area, after we use particle filters for robust specific people tracking using color and skin color based on the characteristics of a target individual. We have been improving the implementation, evaluation system of our proposed methods. In our systems, for experiments, we choose structured crowded scenes. From our experimental results, we have achieved high accuracy detection rates and robust motion tracking for specific targets.
IRJET- Application of MCNN in Object DetectionIRJET Journal
This document discusses using a multi-column convolutional neural network (MCNN) for object detection in videos. The MCNN approach is compared to other methods like CNN and HOG-BOW-Gray pooling and is shown to achieve over 95% accuracy for pedestrian detection. The document outlines extracting frames from videos, dividing images into regions, classifying regions using CNNs, and combining results to detect objects. The MCNN approach is concluded to be useful for applications like medical imaging due to its high detection accuracy.
EFFECT OF SILICON - RUBBER (SR) SHEETS AS AN ALTERNATIVE FILTER ON HIGH AND L...AM Publications
A digital radiography delivers a radiation dose to patients; therefore it poses potential risk to the patients. One effort to reduce dose is carried out using a radiation filter, e.g. Silicone Rubber (SR) sheet. The purpose of this research was to determine the impact of the SR sheet on the high contrast objects (HCO) and the low contrast objects (LCO). The dose reduction was determined from attenuation x-rays before and after using the SR sheet. Assessment of HCO and LCO was observed from CDR TOR phantom at tube voltage of 48 kVp and tube current of 8 mAs. The physical parameter to assess image quality was the Signal to Noise Ratio (SNR) value in LCO. The maximum x-ray attenuation using the SR sheet is 48.82%. The visibility of the HCO remains the same, namely 16 objects; however the LCO slighly decreases from 14 objects to 13 objects after using the SR sheet. The SNR value decreases with an average value of 15.17%.Therefore, the SR sheet as a alternative filter has no effect on the HCO and has realtively little effect on the LCO. Thus, the SR sheet potentially is used for radiation protection in patients, especially on examinations that do not require low contrast resolution.
Digital technologies have greatly advanced orthodontic diagnostic aids. Digital imaging uses electronic sensors instead of film and allows for image enhancement techniques like contrast optimization. Digitalized surface imaging uses laser scanning or stereophotogrammetry to create 3D surface models of the teeth and jaws. Digital casts can be obtained via direct interior scanning or indirect external scanning and offer advantages over physical casts like elimination of breakage and easy sharing. 3D occlusograms combine lateral ceph images and occlusal views to model the 3D occlusal relationship. These recent diagnostic technologies provide more detailed information to aid orthodontic treatment planning.
Digital cephalometrics involves recording cephalometric images digitally rather than on film. There are two main methods: indirect digital radiography (computed radiography) which uses photostimulable phosphor plates that are digitally scanned, and direct digital radiography which uses electronic sensors connected directly to a computer. Digital cephalometrics reduces radiation exposure and allows images to be enhanced, stored digitally, and analyzed using software. While a few parameters showed statistically significant differences between digital and conventional methods, the differences were deemed to not be clinically significant. Digital cephalometrics is now the preferred method over conventional film-based techniques.
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
offering a wide range of dental certified courses in different formats.for more details please visit
www.indiandentalacademy.com
Object detection for KRSBI robot soccer using PeleeNet on omnidirectional cameraTELKOMNIKA JOURNAL
Kontes Robot Sepak Bola Indonesia (KRSBI) is an annual event for contestants to compete their design and robot engineering in the field of robot soccer. Each contestant tries to win the match by scoring a goal toward the opponent's goal. In order to score a goal, the robot needs to find the ball, locate the goal, then kick the ball toward goal. We employed an omnidirectional vision camera as a visual sensor for a robot to perceive the object’s information. We calibrated streaming images from the camera to remove the mirror distortion. Furthermore, we deployed PeleeNet as our deep learning model for object detection. We fine-tuned PeleeNet on our dataset generated from our image collection. Our experiment result showed PeleeNet had the potential for deep learning mobile platform in KRSBI as the object detection architecture. It had a perfect combination of memory efficiency, speed and accuracy.
Gongpu Lan is an optical engineer and research associate at the University of Houston College of Optometry. He has over 15 years of experience in optical design, simulation, and evaluation. Some of his past roles include designing adaptive optics systems for retinal imaging and developing aerial camera lenses. He has authored several patents and publications in the fields of adaptive optics and biomedical imaging.
Robust Motion Detection and Tracking of Moving Objects using HOG Feature and ...CSCJournals
Detection and tracking of moving objects has gained significant importance due to intense technological progress in the field of computer science dealing with video surveillance systems. Human motion is generally nonlinear and non-Gaussian and thus many algorithms are not suitable for tracking. One of the applications to maintain universal security is crowd control. The main problem of video surveillance is continuous monitoring with regard to crime prevention. For security monitoring of live surveillance systems, target identification and tracking strategies can automatically send warnings to monitoring officers. In this paper, we propose a robust tracking of a specified person using the individuals' feature. The proposed method to determine automatic detection and tracking combines Histogram of Oriented Gradient (HOG) feature detection with a particle filter. The Histogram oriented Gradient features are applied to single detection window for the identification of human area, after we use particle filters for robust specific people tracking using color and skin color based on the characteristics of a target individual. We have been improving the implementation, evaluation system of our proposed methods. In our systems, for experiments, we choose structured crowded scenes. From our experimental results, we have achieved high accuracy detection rates and robust motion tracking for specific targets.
IRJET- Application of MCNN in Object DetectionIRJET Journal
This document discusses using a multi-column convolutional neural network (MCNN) for object detection in videos. The MCNN approach is compared to other methods like CNN and HOG-BOW-Gray pooling and is shown to achieve over 95% accuracy for pedestrian detection. The document outlines extracting frames from videos, dividing images into regions, classifying regions using CNNs, and combining results to detect objects. The MCNN approach is concluded to be useful for applications like medical imaging due to its high detection accuracy.
EFFECT OF SILICON - RUBBER (SR) SHEETS AS AN ALTERNATIVE FILTER ON HIGH AND L...AM Publications
A digital radiography delivers a radiation dose to patients; therefore it poses potential risk to the patients. One effort to reduce dose is carried out using a radiation filter, e.g. Silicone Rubber (SR) sheet. The purpose of this research was to determine the impact of the SR sheet on the high contrast objects (HCO) and the low contrast objects (LCO). The dose reduction was determined from attenuation x-rays before and after using the SR sheet. Assessment of HCO and LCO was observed from CDR TOR phantom at tube voltage of 48 kVp and tube current of 8 mAs. The physical parameter to assess image quality was the Signal to Noise Ratio (SNR) value in LCO. The maximum x-ray attenuation using the SR sheet is 48.82%. The visibility of the HCO remains the same, namely 16 objects; however the LCO slighly decreases from 14 objects to 13 objects after using the SR sheet. The SNR value decreases with an average value of 15.17%.Therefore, the SR sheet as a alternative filter has no effect on the HCO and has realtively little effect on the LCO. Thus, the SR sheet potentially is used for radiation protection in patients, especially on examinations that do not require low contrast resolution.
Proposed Multi-object Tracking Algorithm Using Sobel Edge Detection operatorQUESTJOURNAL
ABSTRACT:Tracking of moving objects that is called video tracking is used for measuring motion parameters and obtaining a visual record of the moving objects, it is an important area of application in image processing. In general there are two different approaches to obtain object tracking: the first is Recognition-based Tracking, and the second is the Motion-based Tracking. Video tracking system raises a wide possibility in today’s society. This system is used in various applications such as military, security, monitoring, robotic, and nowadays in dayto-day applications. However the video tracking systems still have many open problems and various research activities in a video tracking system are explores. This paper presents an algorithm for video tracking of any moving targets with the uses of contour based detection technique that depends on the sobel operator. The proposed system is suitable for indoor and outdoor applications. Our approach has the advantage of extending the applicability of tracking system and also, as presented here improves the performance of the tracker making feasible high frame rate video tracking. The goal of the tracking system is to analyze the video frames and estimate the position of a part of the input video frame (usually a moving object), our approach can detect, tracked any object more than one object and calculate the position of the moving objects. Therefore, the aim of this paper is to construct a motion tracking system for moving objects. Where, at the end of this paper, the detail outcome and result are discussed using experiments results of the proposed technique
Recent advances in diagnosis & treatment plsning /certified fixed orthodonti...Indian dental academy
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and offering a wide range of dental certified courses in different formats.
Indian dental academy provides dental crown & Bridge,rotary endodontics,fixed orthodontics,
Dental implants courses.for details pls visit www.indiandentalacademy.com ,or call
0091-9248678078
Magnetic resonance imaging /certified fixed orthodontic courses by Indian de...Indian dental academy
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and offering a wide range of dental certified courses in different formats.
Indian dental academy provides dental crown & Bridge,rotary endodontics,fixed orthodontics,
Dental implants courses.for details pls visit www.indiandentalacademy.com ,or call
0091-9248678078
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and offering a wide range of dental certified courses in different formats.
Indian dental academy provides dental crown & Bridge,rotary endodontics,fixed orthodontics,
Dental implants courses.for details pls visit www.indiandentalacademy.com ,or call
00919248678078
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
offering a wide range of dental certified courses in different formats.for more details please visit
www.indiandentalacademy.com
Basics of computational assessment for COPD: IWPFI 2017Namkug Kim
1) The document discusses computational assessment methods for chronic obstructive pulmonary disease (COPD) using medical imaging data. It covers topics like lung segmentation, lobe segmentation, airway measurement, vessel quantification, and texture-based emphysema quantification.
2) Various algorithms are presented for tasks like robust lung and lobe segmentation, left/right lung splitting, airway skeletonization and labeling, and classification of pulmonary arteries and veins.
3) Quantitative image analysis methods are discussed for measuring airway wall thickness, quantifying emphysema heterogeneity, and classifying COPD patterns based on texture and shape features.
Recent advances in diagnosis and treatment planning1 /certified fixed orthod...Indian dental academy
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and offering a wide range of dental certified courses in different formats.
Indian dental academy provides dental crown & Bridge,rotary endodontics,fixed orthodontics,
Dental implants courses.for details pls visit www.indiandentalacademy.com ,or call
0091-9248678078
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and offering a wide range of dental certified courses in different formats.
Indian dental academy provides dental crown & Bridge,rotary endodontics,fixed orthodontics,
Dental implants courses.for details pls visit www.indiandentalacademy.com ,or call
00919248678078
Stereoscopic Display of Lung PET/CT DICOM Scans using PerspectiveCassidy Chen
This paper proposes a method to display lung PET/CT scans in 3D using a perspective projection technique. The method analyzes DICOM files to calculate standardized uptake values and generate a body mask. Two views are generated using a perspective projection and parallax adjustment to create a stereoscopic 3D effect when viewed with shutter glasses. An experiment shows various views from 0 to 280 degrees. The 3D display expands vision from 2D and helps distinguish depth. Future work involves a medical analysis system with real-time stereoscopic display and auto-stereoscopic capabilities.
IRJET- A Review on Moving Object Detection in Video Forensics IRJET Journal
This document reviews research on moving object detection in video forensics. It discusses challenges in analyzing large amounts of surveillance video data and summarizes several papers that propose methods for tasks like video synopsis, abandoned object detection, person identification, copy-move forgery detection, and assessing evidence quality. The goal is to develop techniques for efficiently analyzing video evidence and detecting anomalies or tampering.
Three-dimensional imaging techniques: A literature review By; Orhan Hakki Ka...Dr. Yahya Alogaibi
This literature review discusses various 3D imaging techniques used in dentistry and orthodontics. It begins by providing background on the development of 3D imaging since the discovery of X-rays. It then discusses disadvantages of traditional 2D cephalometry. The bulk of the review covers different 3D imaging modalities including CT, CBCT, MCT, 3D laser scanning, and their uses and advantages/disadvantages in orthodontics. Key applications discussed are impacted teeth detection, airway analysis, TMJ evaluation, and cleft lip/palate treatment planning.
principles, applications, advantages, disadvantages, guidelines, uses of cone beam computed tomography in the field of orthodontics and dentistry in general
Digital imaging /certified fixed orthodontic courses by Indian dental academy Indian dental academy
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and offering a wide range of dental certified courses in different formats.
Indian dental academy provides dental crown & Bridge,rotary endodontics,fixed orthodontics,
Dental implants courses.for details pls visit www.indiandentalacademy.com ,or call
0091-9248678078
Development of a Location Invariant Crack Detection and Localisation Model (L...CSCJournals
The document presents a model called LICDAL (Location Invariant Crack Detection and Localization) that was developed to detect and localize cracks in unconstrained oil pipeline images using deep convolutional neural networks. LICDAL applies transfer learning on Faster R-CNN to make the model location invariant by training it on images of cracked pipelines from various locations. When tested on 10 new images from different locations, LICDAL detected and localized cracks with a mean average precision of 97.3%, demonstrating high performance and location invariance. The model performance is compared to an existing crack detection model, showing LICDAL improves crack identification through localization.
1. The document discusses applying 3D printing to medical imaging by discussing medical image modeling.
2. It covers topics like virtual surgery modeling, 3D printers, image scanners, requirements for 3D printed medical models, and the medical imaging workflow from acquisition to 3D printing and post-processing.
3. Key aspects of medical image-based 3D printing discussed are image segmentation, surface modeling, and an in-house software for virtual simulated surgery.
Design of algorithm for detection of hidden objects from Tera hertz imagesIOSR Journals
This document presents an algorithm for detecting hidden objects in terahertz images using a three-stage approach. The first stage applies edge-based segmentation after smoothing the image. The second stage extracts shape descriptors like Gabor and GLCM texture features from regions of interest. Finally, a Euclidean distance criterion is used to classify objects by comparing a test feature vector to vectors in a database. The algorithm was tested on gun, knife and needle images, achieving a 1.04% detection error rate and 91.9% detection rate compared to ground truths. Potential applications are in security screening to detect weapons and explosives in public areas.
A New Approach for video denoising and enhancement using optical flow EstimationIRJET Journal
This document proposes a new approach for video denoising and enhancement using optical flow estimation. It discusses using motion compensation via optical flow estimation along with principal component analysis (PCA) to provide fine video details. However, PCA has limitations in fully eliminating noise. The proposed method aims to replace PCA with wavelet transformation, which provides multi-resolution analysis and sparsity advantages for better denoising results in terms of PSNR and RMSE compared to PCA. It involves estimating optical flow between frames for motion compensation before applying wavelet transformation for noise removal and video reconstruction.
Eye tracking system has played a significant role in many of today’s applications ranging from military
applications to automotive industries and healthcare sectors. In this paper, a novel system for eye tracking and
estimation of its direction of movement is performed. The proposed system is implemented in real time using an
arduino uno microcontroller and a zigbee wireless device. Experimental results show a successful eye tracking and
movement estimation in real time scenario using the proposed hardware interface.
The document summarizes an algorithm for object detection and tracking in moving backgrounds under different environmental conditions. The algorithm uses a discriminative learning approach to develop a more robust way of updating an adaptive appearance model. It aims to handle partial occlusions without significant drift and work well with minimal parameter tuning. The algorithm divides each frame into blocks and extracts features using a random Gaussian matrix method. A Gaussian classifier is used to get the tracking location with the highest response. The classifier is incrementally learned and updated using positive and negative samples to predict the object location in the next frame. The proposed algorithm is shown to outperform existing L1-tracker algorithms in terms of accuracy, computational efficiency, and robustness to appearance changes.
This document discusses the history and advances in digital imaging technology used in orthodontics. It describes how digital imaging has evolved from early cephalometric films to current digital systems. Key points include:
- Early cephalometric films from the 1930s allowed for analysis of malocclusions. Digital imaging now offers 3D analysis capabilities.
- Digital images are composed of pixels arranged in a grid, whereas analog films have continuous shades of gray. Digital offers advantages like enhanced images and lower radiation exposure.
- Factors like resolution, file format, and compression influence image quality for applications like orthodontic photos. Higher resolution TIFF files preserve quality better than JPEG.
Computer Vision Based 3D Reconstruction : A ReviewIJECEIAES
3D reconstruction are used in many fields starts from the object reconstruction such as site, and cultural artifacts in both ground and under the sea levels. The scientist are beneficial for these task in order to learn and keep the environment into 3D data due to the extinction. In this paper explained vision setup that is commonly used such as single camera, stereo camera, Kinect / Structured Light/ Time of Flight camera and fusion approach. The prior works also explained how the 3D reconstruction perform in many fields and using various algorithms.
MULTIPLE OBJECTS AND ROAD DETECTION IN UNMANNED AERIAL VEHICLEijcseit
Unmanned Aerial Vehicles have greater potential to widely used in military and civil applications.
Additionally equipped with the cameras can also be used in agriculture and surveillance. Aerial imagery
has its own unique challenges that differ from the training set of modern-day object detectors, since it is
made of images of larger areas compared to the regular datasets and the objects are very small on the
contrary. These problems do not allow us to use common object detection models. Currently there are
many computer vision algorithm that are designed using human centric photographs, But from the top view
imagery taken vertically the objects of interest are small and fewer features mostly appearing flat and
rectangular, certain objects closer to each other can also overlap. So detecting most of the objects from the
birds eye view is a challenging task. Hence the work will be focusing on detecting multiple objects from
those images using enhanced ResNet, FPN, FasterRCNN models thereby providing an effective
surveillance for the UAV and extraction of road networks from aerial images has fundamental importance.
Satellite and Land Cover Image Classification using Deep Learningijtsrd
Satellite imagery is very significant for many applications including disaster response, law enforcement and environmental monitoring. These applications require the manual identification of objects and facilities in the imagery. Because the geographic area to be covered are great and the analysts available to conduct the searches are few, automation is required. The traditional object detection and classification algorithms are too inaccurate, takes a lot of time and unreliable to solve the problem. Deep learning is a family of machine learning algorithms that can be used for the automation of such tasks. It has achieved success in image classification by using convolutional neural networks. The problem of object and facility classification in satellite imagery is considered. The system is developed by using various facilities like Tensor Flow, XAMPP, FLASK and other various deep learning libraries. Roshni Rajendran | Liji Samuel "Satellite and Land Cover Image Classification using Deep Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd32912.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/32912/satellite-and-land-cover-image-classification-using-deep-learning/roshni-rajendran
Proposed Multi-object Tracking Algorithm Using Sobel Edge Detection operatorQUESTJOURNAL
ABSTRACT:Tracking of moving objects that is called video tracking is used for measuring motion parameters and obtaining a visual record of the moving objects, it is an important area of application in image processing. In general there are two different approaches to obtain object tracking: the first is Recognition-based Tracking, and the second is the Motion-based Tracking. Video tracking system raises a wide possibility in today’s society. This system is used in various applications such as military, security, monitoring, robotic, and nowadays in dayto-day applications. However the video tracking systems still have many open problems and various research activities in a video tracking system are explores. This paper presents an algorithm for video tracking of any moving targets with the uses of contour based detection technique that depends on the sobel operator. The proposed system is suitable for indoor and outdoor applications. Our approach has the advantage of extending the applicability of tracking system and also, as presented here improves the performance of the tracker making feasible high frame rate video tracking. The goal of the tracking system is to analyze the video frames and estimate the position of a part of the input video frame (usually a moving object), our approach can detect, tracked any object more than one object and calculate the position of the moving objects. Therefore, the aim of this paper is to construct a motion tracking system for moving objects. Where, at the end of this paper, the detail outcome and result are discussed using experiments results of the proposed technique
Recent advances in diagnosis & treatment plsning /certified fixed orthodonti...Indian dental academy
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and offering a wide range of dental certified courses in different formats.
Indian dental academy provides dental crown & Bridge,rotary endodontics,fixed orthodontics,
Dental implants courses.for details pls visit www.indiandentalacademy.com ,or call
0091-9248678078
Magnetic resonance imaging /certified fixed orthodontic courses by Indian de...Indian dental academy
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and offering a wide range of dental certified courses in different formats.
Indian dental academy provides dental crown & Bridge,rotary endodontics,fixed orthodontics,
Dental implants courses.for details pls visit www.indiandentalacademy.com ,or call
0091-9248678078
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and offering a wide range of dental certified courses in different formats.
Indian dental academy provides dental crown & Bridge,rotary endodontics,fixed orthodontics,
Dental implants courses.for details pls visit www.indiandentalacademy.com ,or call
00919248678078
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
offering a wide range of dental certified courses in different formats.for more details please visit
www.indiandentalacademy.com
Basics of computational assessment for COPD: IWPFI 2017Namkug Kim
1) The document discusses computational assessment methods for chronic obstructive pulmonary disease (COPD) using medical imaging data. It covers topics like lung segmentation, lobe segmentation, airway measurement, vessel quantification, and texture-based emphysema quantification.
2) Various algorithms are presented for tasks like robust lung and lobe segmentation, left/right lung splitting, airway skeletonization and labeling, and classification of pulmonary arteries and veins.
3) Quantitative image analysis methods are discussed for measuring airway wall thickness, quantifying emphysema heterogeneity, and classifying COPD patterns based on texture and shape features.
Recent advances in diagnosis and treatment planning1 /certified fixed orthod...Indian dental academy
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and offering a wide range of dental certified courses in different formats.
Indian dental academy provides dental crown & Bridge,rotary endodontics,fixed orthodontics,
Dental implants courses.for details pls visit www.indiandentalacademy.com ,or call
0091-9248678078
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and offering a wide range of dental certified courses in different formats.
Indian dental academy provides dental crown & Bridge,rotary endodontics,fixed orthodontics,
Dental implants courses.for details pls visit www.indiandentalacademy.com ,or call
00919248678078
Stereoscopic Display of Lung PET/CT DICOM Scans using PerspectiveCassidy Chen
This paper proposes a method to display lung PET/CT scans in 3D using a perspective projection technique. The method analyzes DICOM files to calculate standardized uptake values and generate a body mask. Two views are generated using a perspective projection and parallax adjustment to create a stereoscopic 3D effect when viewed with shutter glasses. An experiment shows various views from 0 to 280 degrees. The 3D display expands vision from 2D and helps distinguish depth. Future work involves a medical analysis system with real-time stereoscopic display and auto-stereoscopic capabilities.
IRJET- A Review on Moving Object Detection in Video Forensics IRJET Journal
This document reviews research on moving object detection in video forensics. It discusses challenges in analyzing large amounts of surveillance video data and summarizes several papers that propose methods for tasks like video synopsis, abandoned object detection, person identification, copy-move forgery detection, and assessing evidence quality. The goal is to develop techniques for efficiently analyzing video evidence and detecting anomalies or tampering.
Three-dimensional imaging techniques: A literature review By; Orhan Hakki Ka...Dr. Yahya Alogaibi
This literature review discusses various 3D imaging techniques used in dentistry and orthodontics. It begins by providing background on the development of 3D imaging since the discovery of X-rays. It then discusses disadvantages of traditional 2D cephalometry. The bulk of the review covers different 3D imaging modalities including CT, CBCT, MCT, 3D laser scanning, and their uses and advantages/disadvantages in orthodontics. Key applications discussed are impacted teeth detection, airway analysis, TMJ evaluation, and cleft lip/palate treatment planning.
principles, applications, advantages, disadvantages, guidelines, uses of cone beam computed tomography in the field of orthodontics and dentistry in general
Digital imaging /certified fixed orthodontic courses by Indian dental academy Indian dental academy
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and offering a wide range of dental certified courses in different formats.
Indian dental academy provides dental crown & Bridge,rotary endodontics,fixed orthodontics,
Dental implants courses.for details pls visit www.indiandentalacademy.com ,or call
0091-9248678078
Development of a Location Invariant Crack Detection and Localisation Model (L...CSCJournals
The document presents a model called LICDAL (Location Invariant Crack Detection and Localization) that was developed to detect and localize cracks in unconstrained oil pipeline images using deep convolutional neural networks. LICDAL applies transfer learning on Faster R-CNN to make the model location invariant by training it on images of cracked pipelines from various locations. When tested on 10 new images from different locations, LICDAL detected and localized cracks with a mean average precision of 97.3%, demonstrating high performance and location invariance. The model performance is compared to an existing crack detection model, showing LICDAL improves crack identification through localization.
1. The document discusses applying 3D printing to medical imaging by discussing medical image modeling.
2. It covers topics like virtual surgery modeling, 3D printers, image scanners, requirements for 3D printed medical models, and the medical imaging workflow from acquisition to 3D printing and post-processing.
3. Key aspects of medical image-based 3D printing discussed are image segmentation, surface modeling, and an in-house software for virtual simulated surgery.
Design of algorithm for detection of hidden objects from Tera hertz imagesIOSR Journals
This document presents an algorithm for detecting hidden objects in terahertz images using a three-stage approach. The first stage applies edge-based segmentation after smoothing the image. The second stage extracts shape descriptors like Gabor and GLCM texture features from regions of interest. Finally, a Euclidean distance criterion is used to classify objects by comparing a test feature vector to vectors in a database. The algorithm was tested on gun, knife and needle images, achieving a 1.04% detection error rate and 91.9% detection rate compared to ground truths. Potential applications are in security screening to detect weapons and explosives in public areas.
A New Approach for video denoising and enhancement using optical flow EstimationIRJET Journal
This document proposes a new approach for video denoising and enhancement using optical flow estimation. It discusses using motion compensation via optical flow estimation along with principal component analysis (PCA) to provide fine video details. However, PCA has limitations in fully eliminating noise. The proposed method aims to replace PCA with wavelet transformation, which provides multi-resolution analysis and sparsity advantages for better denoising results in terms of PSNR and RMSE compared to PCA. It involves estimating optical flow between frames for motion compensation before applying wavelet transformation for noise removal and video reconstruction.
Eye tracking system has played a significant role in many of today’s applications ranging from military
applications to automotive industries and healthcare sectors. In this paper, a novel system for eye tracking and
estimation of its direction of movement is performed. The proposed system is implemented in real time using an
arduino uno microcontroller and a zigbee wireless device. Experimental results show a successful eye tracking and
movement estimation in real time scenario using the proposed hardware interface.
The document summarizes an algorithm for object detection and tracking in moving backgrounds under different environmental conditions. The algorithm uses a discriminative learning approach to develop a more robust way of updating an adaptive appearance model. It aims to handle partial occlusions without significant drift and work well with minimal parameter tuning. The algorithm divides each frame into blocks and extracts features using a random Gaussian matrix method. A Gaussian classifier is used to get the tracking location with the highest response. The classifier is incrementally learned and updated using positive and negative samples to predict the object location in the next frame. The proposed algorithm is shown to outperform existing L1-tracker algorithms in terms of accuracy, computational efficiency, and robustness to appearance changes.
This document discusses the history and advances in digital imaging technology used in orthodontics. It describes how digital imaging has evolved from early cephalometric films to current digital systems. Key points include:
- Early cephalometric films from the 1930s allowed for analysis of malocclusions. Digital imaging now offers 3D analysis capabilities.
- Digital images are composed of pixels arranged in a grid, whereas analog films have continuous shades of gray. Digital offers advantages like enhanced images and lower radiation exposure.
- Factors like resolution, file format, and compression influence image quality for applications like orthodontic photos. Higher resolution TIFF files preserve quality better than JPEG.
Computer Vision Based 3D Reconstruction : A ReviewIJECEIAES
3D reconstruction are used in many fields starts from the object reconstruction such as site, and cultural artifacts in both ground and under the sea levels. The scientist are beneficial for these task in order to learn and keep the environment into 3D data due to the extinction. In this paper explained vision setup that is commonly used such as single camera, stereo camera, Kinect / Structured Light/ Time of Flight camera and fusion approach. The prior works also explained how the 3D reconstruction perform in many fields and using various algorithms.
MULTIPLE OBJECTS AND ROAD DETECTION IN UNMANNED AERIAL VEHICLEijcseit
Unmanned Aerial Vehicles have greater potential to widely used in military and civil applications.
Additionally equipped with the cameras can also be used in agriculture and surveillance. Aerial imagery
has its own unique challenges that differ from the training set of modern-day object detectors, since it is
made of images of larger areas compared to the regular datasets and the objects are very small on the
contrary. These problems do not allow us to use common object detection models. Currently there are
many computer vision algorithm that are designed using human centric photographs, But from the top view
imagery taken vertically the objects of interest are small and fewer features mostly appearing flat and
rectangular, certain objects closer to each other can also overlap. So detecting most of the objects from the
birds eye view is a challenging task. Hence the work will be focusing on detecting multiple objects from
those images using enhanced ResNet, FPN, FasterRCNN models thereby providing an effective
surveillance for the UAV and extraction of road networks from aerial images has fundamental importance.
Satellite and Land Cover Image Classification using Deep Learningijtsrd
Satellite imagery is very significant for many applications including disaster response, law enforcement and environmental monitoring. These applications require the manual identification of objects and facilities in the imagery. Because the geographic area to be covered are great and the analysts available to conduct the searches are few, automation is required. The traditional object detection and classification algorithms are too inaccurate, takes a lot of time and unreliable to solve the problem. Deep learning is a family of machine learning algorithms that can be used for the automation of such tasks. It has achieved success in image classification by using convolutional neural networks. The problem of object and facility classification in satellite imagery is considered. The system is developed by using various facilities like Tensor Flow, XAMPP, FLASK and other various deep learning libraries. Roshni Rajendran | Liji Samuel "Satellite and Land Cover Image Classification using Deep Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd32912.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/32912/satellite-and-land-cover-image-classification-using-deep-learning/roshni-rajendran
Performance investigation of two-stage detection techniques using traffic lig...IAESIJAI
Using a camera to monitor an object or a group of objects over time is the process of object detection. It can be used for a variety of things, including security and surveillance, video communication, traffic light detection (TLD), object detection from compressed video in public places. In recent times, object tracking has become a popular topic in computer science particularly, the data science community, thanks to the usage of deep learning (DL) in artificial intelligence (AI). DL which convolutional neural network (CNN) as one of its techniques usually used two-stage detection methods in TLD. Despite all successes recorded in TLD through the use of two-stage detection methods, there is no study that has analyzed these methods in experimental research, studying the strength and witnesses by the researchers. Based on the needs this study analyses the applications of DL techniques in TLD. We implemented object detection for TLD using 5 two-stage detection methods with the traffic light dataset using a Jupyter notebook and the sklearn libraries. We present the achievements of two-stage detection methods in TLD, going by standard performance metrics used, FASTER-CNN was the best in detection accuracy, F1-score, precision and recall with 0.89, 0.93, 0.83 and 0.90 respectively.
Satellite Image Classification with Deep Learning Surveyijtsrd
Satellite imagery is important for many applications including disaster response, law enforcement and environmental monitoring etc. These applications require the manual identification of objects in the imagery. Because the geographic area to be covered is very large and the analysts available to conduct the searches are few, thus an automation is required. Yet traditional object detection and classification algorithms are too inaccurate and unreliable to solve the problem. Deep learning is a part of broader family of machine learning methods that have shown promise for the automation of such tasks. It has achieved success in image understanding by means that of convolutional neural networks. The problem of object and facility recognition in satellite imagery is considered. The system consists of an ensemble of convolutional neural networks and additional neural networks that integrate satellite metadata with image features. Roshni Rajendran | Liji Samuel ""Satellite Image Classification with Deep Learning: Survey"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30031.pdf
Paper Url : https://www.ijtsrd.com/engineering/computer-engineering/30031/satellite-image-classification-with-deep-learning-survey/roshni-rajendran
Satellite Image Classification and Analysis using Machine Learning with ISRO ...IRJET Journal
This document summarizes a research project that aims to classify objects in high-resolution satellite images using machine learning. The researchers developed a system to automatically extract features from satellite images provided by ISRO and classify the objects without manual effort. Convolutional neural networks are used for feature extraction and classification. The system identifies the number of bands in each image and converts it into precise data for processing using CNNs. This allows for efficient and accurate classification of objects like crops, buildings, and vehicles from satellite imagery. The researchers conducted a literature review on existing satellite image processing techniques to inform the development of their automated image classification system.
IRJET- A Survey on Object Detection using Deep Learning TechniquesIRJET Journal
1) The document discusses object detection and tracking using deep learning techniques such as convolutional neural networks, YOLO, and Single Shot Detector. It reviews literature on existing approaches and proposes a system for multi-purpose security applications using mobile camera detection.
2) Common object detection methods discussed are Faster R-CNN, YOLO, and Single Shot Detectors (SSDs). The proposed system would use these deep learning techniques for automated detection and tracking from mobile cameras.
3) Applications mentioned include surveillance, people counting, drowsiness detection, and more. The growth of mobile phones makes them suitable for real-time detection and tracking technologies.
Person Detection in Maritime Search And Rescue OperationsIRJET Journal
This document discusses recent research on using computer vision and machine learning techniques for person detection in maritime search and rescue operations from images and video captured by drones. Specifically, it summarizes 12 research papers on this topic, covering approaches such as training convolutional neural networks on bird's eye view datasets to detect people from aerial images, using multiple detection methods like sliding windows and precise localization, combining data from multiple drones and sensors to optimize search efforts, and evaluating models on both RGB and thermal image datasets. The goal of this research is to automate part of the search process to make maritime rescue operations more efficient and effective.
Person Detection in Maritime Search And Rescue OperationsIRJET Journal
1) The document discusses using machine learning and computer vision techniques for person detection in maritime search and rescue operations using drones/UAVs. It aims to automatically detect people in images/videos captured by drones to help with search efforts.
2) A key challenge is that people appear small in drone footage and are often obscured by vegetation or terrain. The models need to be trained on similar bird's eye view data to achieve high accuracy. The document reviews different person detection models and their use in search and rescue.
3) It discusses recent work involving using efficient neural networks like MobileNet for object detection from drones. Other work involves using depth sensors and pose estimation for person tracking, as well as using distributed deep learning
Inclined Image Recognition for Aerial Mapping using Deep Learning and Tree ba...TELKOMNIKA JOURNAL
One of the important capabilities of an unmanned aerial vehicle (UAV) is aerial mapping. Aerial mapping is an image registration problem, i.e., the problem of transforming different sets of images into one coordinate system. In image registration, the quality of the output is strongly influenced by the quality of input (i.e., images captured by the UAV). Therefore, selecting the quality of input images becomes important and one of the challenging task in aerial mapping because the ground truth in the mapping process is not given before the UAV flies. Typically, UAV takes images in sequence irrespective of its flight orientation and roll angle. These may result in the acquisition of bad quality images, possibly compromising the quality of mapping results, and increasing the computational cost of a registration process. To address these issues, we need a recognition system that is able to recognize images that are not suitable for the registration process. In this paper, we define these unsuitable images as “inclined images,” i.e., images captured by UAV that are not perpendicular to the ground. Although we can calculate the inclination angle using a gyroscope attached to the UAV, our interest here is to recognize these inclined images without the use of additional sensors in order to mimic how humans perform this task visually. To realize that, we utilize a deep learning method with the combination of tree-based models to build an inclined image recognition system. We have validated the proposed system with the images captured by the UAV. We collected 192 images and labelled them with two different levels of classes (i.e., coarse- and fine-classification). We compared this with several models and the results showed that our proposed system yielded an improvement of accuracy rate up to 3%.
Depth Estimation from Defocused Images: a SurveyIJAAS Team
An important step in 3D data generation is the generation of depth map. Depth map is a black and white image which has exactly the same size of the original captured 2D image that indicates the relative distance of each pixel from the observer to the objects in the real world. This paper presents a survey of Depth Perception from Defocused or blurs images as well as image from motion. The change of distance of the object from the camera has direct relation with the amount of blurring of object in the image. The amount of blurring will be calculated with a comparison in front of the camera directly and can be seen with the changes at gray level around the edges of objects.
Detection of immovable objects on visually impaired people walking aidsTELKOMNIKA JOURNAL
One consequence of a visually impaired (blind) person is a lack of ability in the activities related to the orientation and mobility. Blind person uses a stick as a tool to know the objects that surround him/her.The objective of this research is to develop a tool for blind person which is able to recognize what object in front of him/her when he/she is walking. An attached camera will obtain an image of an object which is then processed using template matching method to identify and trace the image of the object. After getting the image of the object, furthermore calculate and compare it with the data training. The output is produced in the form of sound that in accordance with the object. The result of this research is that the best slope and distance for the template matching method to properly detect silent objects is 90 degrees and 2 meters.
REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEMS AM Publications
Remote sensing technology's increasing accessibility helps us observe research and learn about our globe in ways we could only imagine a generation ago. Guides to profound knowledge of historical, conceptual and practical uses of remote sensing which is increasing GIS technology. This paper will go briefly through remote sensing benefits, history, technology and the GIS and remote sensing integration and their applications. Remote sensing (RS) is used in mapping the predicted and actual species and dominates the ecosystem canopy.
IRJET- A Review Analysis to Detect an Object in Video Surveillance SystemIRJET Journal
This document reviews techniques for detecting objects in video surveillance systems. It discusses common object detection methods like frame differencing, optical flow, and background subtraction. Frame differencing detects motion by calculating pixel differences between frames but cannot detect still objects. Optical flow estimates pixel motion between frames to detect objects. Background subtraction models the static background and detects objects by subtracting current frames from the background model. The document analyzes these techniques and their use in video surveillance applications like traffic monitoring and security. It concludes more research is needed to improve object classification accuracy and handle challenges like camera motion.
IEEE CASE 2016 On Avoiding Moving Objects for Indoor Autonomous QuadrotorsPeter SHIN
This document presents a method called Motion-vector-based Moving Objects Detection (MMOD) for detecting and avoiding moving obstacles in real-time using stereo motion vectors from a vision system on indoor autonomous quadrotors. MMOD detects moving objects by analyzing motion vectors from stereo images and categorizing them as either ego-motion from the quadrotor's movement or object-motion from moving obstacles. It then estimates distances to detected moving objects and determines safe areas for the quadrotor to navigate while avoiding collisions. The method was implemented and tested on a 3D Robotics IRIS+ quadrotor equipped with a Raspberry Pi and stereo camera. Experimental results demonstrated the ability of MMOD to detect and allow the quadrotor
Survey on video object detection & trackingijctet
This document summarizes previous work on video object detection and tracking techniques. It discusses research papers that used techniques like active contour modeling, gradient-based attraction fields, neural fuzzy networks, and region-based contour extraction for object tracking. Background subtraction, frame differencing, optical flow, spatio-temporal features, Kalman filtering, and contour tracking are described as common video object detection techniques. The challenges of multi-object data association and state estimation for tracking multiple objects are also mentioned.
A Survey on Smart Devices for Object and Fall DetectionIRJET Journal
This document summarizes a survey on smart devices for object and fall detection. It discusses how sensors and microcontrollers can be used to create wearable alert devices for the elderly that detect falls and send location information to concerned contacts. It also describes how ultrasonic sensors and smart glasses can detect obstacles to help blind or visually impaired people navigate safely. The document reviews several existing studies on vision-based and sensor-based fall detection systems and identifies challenges in real-world deployment, usability, and user acceptance of emerging technologies.
Real Time Object Detection with Audio Feedback using Yolo v3ijtsrd
In this paper, we propose a system that combines real time object detection using the YOLOv3 algorithm with audio feedback to assist visually impaired individuals in locating and identifying objects in their surroundings. The YOLOv3 algorithm is a state of the art object detection algorithm that has been used in numerous studies for various applications. Audio feedback has also been studied in previous research as a useful tool for assisting visually impaired individuals. Our proposed system builds on the effectiveness of both these technologies to provide a valuable tool for improving the independence and quality of life of visually impaired individuals. We present the architecture of our proposed system, which includes a YOLOv3 model for object detection and a text to speech engine for providing audio feedback. We also present the results of our experiments, which demonstrate the effectiveness of our system in detecting and identifying objects in real time. Our proposed system can be used in various settings, such as indoor and outdoor environments, and can assist visually impaired individuals in various activities such as the navigation and object identification. Dr. K. Nagi Reddy | K. Sreeja | M. Sreenivasulu Reddy | K. Sireesha | M. Triveni "Real Time Object Detection with Audio Feedback using Yolo_v3" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-2 , April 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd55158.pdf Paper URL: https://www.ijtsrd.com.com/engineering/electronics-and-communication-engineering/55158/real-time-object-detection-with-audio-feedback-using-yolov3/dr-k-nagi-reddy
Real Time Detection of Moving Object Based on Fpgaiosrjce
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
1. The document describes a method for real-time detection of moving objects based on background subtraction and its implementation on an FPGA. A static camera is used to capture video frames. The first frame is used as the reference background frame. Pixels in subsequent frames are compared to the background frame and objects are detected where pixel differences exceed a threshold.
2. The method was tested on sample surveillance videos. Background subtraction accurately detected moving objects in test videos in real-time. Future work may include identifying objects using face or palm recognition and activity recognition for visual surveillance applications.
INDOOR AND OUTDOOR NAVIGATION ASSISTANCE SYSTEM FOR VISUALLY IMPAIRED PEOPLE ...IRJET Journal
This document describes a proposed system to assist visually impaired individuals using object detection. The system uses YOLO (You Only Look Once) deep learning for fast and reliable object detection in images captured by a webcam in real-time. Detected objects are identified and conveyed to the user via text-to-speech. This allows visually impaired users to navigate indoor and outdoor environments with information about surrounding objects. The proposed system aims to address challenges faced by existing assistive technologies through improved accuracy and real-time performance of object recognition compared to other methods.
Similar to Research on Ship Detection in Visible Remote Sensing Images (20)
‘Six Sigma Technique’ A Journey Through its Implementationijtsrd
The manufacturing industries all over the world are facing tough challenges for growth, development and sustainability in today’s competitive environment. They have to achieve apex position by adapting with the global competitive environment by delivering goods and services at low cost, prime quality and better price to increase wealth and consumer satisfaction. Cost Management ensures profit, growth and sustainability of the business with implementation of Continuous Improvement Technique like Six Sigma. This leads to optimize Business performance. The method drives for customer satisfaction, low variation, reduction in waste and cycle time resulting into a competitive advantage over other industries which did not implement it. The main objective of this paper ‘Six Sigma Technique A Journey Through Its Implementation’ is to conceptualize the effectiveness of Six Sigma Technique through the journey of its implementation. Aditi Sunilkumar Ghosalkar "‘Six Sigma Technique’: A Journey Through its Implementation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64546.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64546/‘six-sigma-technique’-a-journey-through-its-implementation/aditi-sunilkumar-ghosalkar
Edge Computing in Space Enhancing Data Processing and Communication for Space...ijtsrd
Edge computing, a paradigm that involves processing data closer to its source, has gained significant attention for its potential to revolutionize data processing and communication in space missions. With the increasing complexity and data volume generated by modern space missions, traditional centralized computing approaches face challenges related to latency, bandwidth, and security. Edge computing in space, involving on board processing and analysis of data, offers promising solutions to these challenges. This paper explores the concept of edge computing in space, its benefits, applications, and future prospects in enhancing space missions. Manish Verma "Edge Computing in Space: Enhancing Data Processing and Communication for Space Missions" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64541.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/64541/edge-computing-in-space-enhancing-data-processing-and-communication-for-space-missions/manish-verma
Dynamics of Communal Politics in 21st Century India Challenges and Prospectsijtsrd
Communal politics in India has evolved through centuries, weaving a complex tapestry shaped by historical legacies, colonial influences, and contemporary socio political transformations. This research comprehensively examines the dynamics of communal politics in 21st century India, emphasizing its historical roots, socio political dynamics, economic implications, challenges, and prospects for mitigation. The historical perspective unravels the intricate interplay of religious identities and power dynamics from ancient civilizations to the impact of colonial rule, providing insights into the evolution of communalism. The socio political dynamics section delves into the contemporary manifestations, exploring the roles of identity politics, socio economic disparities, and globalization. The economic implications section highlights how communal politics intersects with economic issues, perpetuating disparities and influencing resource allocation. Challenges posed by communal politics are scrutinized, revealing multifaceted issues ranging from social fragmentation to threats against democratic values. The prospects for mitigation present a multifaceted approach, incorporating policy interventions, community engagement, and educational initiatives. The paper conducts a comparative analysis with international examples, identifying common patterns such as identity politics and economic disparities. It also examines unique challenges, emphasizing Indias diverse religious landscape, historical legacy, and secular framework. Lessons for effective strategies are drawn from international experiences, offering insights into inclusive policies, interfaith dialogue, media regulation, and global cooperation. By scrutinizing historical epochs, contemporary dynamics, economic implications, and international comparisons, this research provides a comprehensive understanding of communal politics in India. The proposed strategies for mitigation underscore the importance of a holistic approach to foster social harmony, inclusivity, and democratic values. Rose Hossain "Dynamics of Communal Politics in 21st Century India: Challenges and Prospects" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64528.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/history/64528/dynamics-of-communal-politics-in-21st-century-india-challenges-and-prospects/rose-hossain
Assess Perspective and Knowledge of Healthcare Providers Towards Elehealth in...ijtsrd
Background and Objective Telehealth has become a well known tool for the delivery of health care in Saudi Arabia, and the perspective and knowledge of healthcare providers are influential in the implementation, adoption and advancement of the method. This systematic review was conducted to examine the current literature base regarding telehealth and the related healthcare professional perspective and knowledge in the Kingdom of Saudi Arabia. Materials and Methods This systematic review was conducted by searching 7 databases including, MEDLINE, CINHAL, Web of Science, Scopus, PubMed, PsycINFO, and ProQuest Central. Studies on healthcare practitioners telehealth knowledge and perspectives published in English in Saudi Arabia from 2000 to 2023 were included. Boland directed this comprehensive review. The researchers examined each connected study using the AXIS tool, which evaluates cross sectional systematic reviews. Narrative synthesis was used to summarise and convey the data. Results Out of 1840 search results, 10 studies were included. Positive outlook and limited knowledge among providers were seen across trials. Healthcare professionals like telehealth for its ability to improve quality, access, and delivery, save time and money, and be successful. Age, gender, occupation, and work experience also affect health workers knowledge. In Saudi Arabia, healthcare professionals face inadequate expert assistance, patient privacy, internet connection concerns, lack of training courses, lack of telehealth understanding, and high costs while performing telemedicine. Conclusions Healthcare practitioners telehealth perceptions and knowledge were examined in this systematic study. Its collection of concerned experts different personal attitudes and expertise would help enhance telehealths implementation in Saudi Arabia, develop its healthcare delivery alternative, and eliminate frequent problems. Badriah Mousa I Mulayhi | Dr. Jomin George | Judy Jenkins "Assess Perspective and Knowledge of Healthcare Providers Towards Elehealth in Saudi Arabia: A Systematic Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64535.pdf Paper Url: https://www.ijtsrd.com/medicine/other/64535/assess-perspective-and-knowledge-of-healthcare-providers-towards-elehealth-in-saudi-arabia-a-systematic-review/badriah-mousa-i-mulayhi
The Impact of Digital Media on the Decentralization of Power and the Erosion ...ijtsrd
The impact of digital media on the distribution of power and the weakening of traditional gatekeepers has gained considerable attention in recent years. The adoption of digital technologies and the internet has resulted in declining influence and power for traditional gatekeepers such as publishing houses and news organizations. Simultaneously, digital media has facilitated the emergence of new voices and players in the media industry. Digital medias impact on power decentralization and gatekeeper erosion is visible in several ways. One significant aspect is the democratization of information, which enables anyone with an internet connection to publish and share content globally, leading to citizen journalism and bypassing traditional gatekeepers. Another aspect is the disruption of conventional media industry business models, as traditional organizations struggle to adjust to the decrease in advertising revenue and the rise of digital platforms. Alternative business models, such as subscription models and crowdfunding, have become more prevalent, leading to the emergence of new players. Overall, the impact of digital media on the distribution of power and the weakening of traditional gatekeepers has brought about significant changes in the media landscape and the way information is shared. Further research is required to fully comprehend the implications of these changes and their impact on society. Dr. Kusum Lata "The Impact of Digital Media on the Decentralization of Power and the Erosion of Traditional Gatekeepers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64544.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/political-science/64544/the-impact-of-digital-media-on-the-decentralization-of-power-and-the-erosion-of-traditional-gatekeepers/dr-kusum-lata
Online Voices, Offline Impact Ambedkars Ideals and Socio Political Inclusion ...ijtsrd
This research investigates the nexus between online discussions on Dr. B.R. Ambedkars ideals and their impact on social inclusion among college students in Gurugram, Haryana. Surveying 240 students from 12 government colleges, findings indicate that 65 actively engage in online discussions, with 80 demonstrating moderate to high awareness of Ambedkars ideals. Statistically significant correlations reveal that higher online engagement correlates with increased awareness p 0.05 and perceived social inclusion. Variations across colleges and a notable effect of college type on perceived social inclusion highlight the influence of contextual factors. Furthermore, the intersectional analysis underscores nuanced differences based on gender, caste, and socio economic status. Dr. Kusum Lata "Online Voices, Offline Impact: Ambedkar's Ideals and Socio-Political Inclusion - A Study of Gurugram District" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64543.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/political-science/64543/online-voices-offline-impact-ambedkars-ideals-and-sociopolitical-inclusion--a-study-of-gurugram-district/dr-kusum-lata
Problems and Challenges of Agro Entreprenurship A Studyijtsrd
Noting calls for contextualizing Agro entrepreneurs problems and challenges of the agro entrepreneurs and for greater attention to the Role of entrepreneurs in agro entrepreneurship research, we conduct a systematic literature review of extent research in agriculture entrepreneurship to overcome the study objectives of complications of agro entrepreneurs through various factors, Development of agriculture products is a key factor for the overall economic growth of agro entrepreneurs Agro Entrepreneurs produces firsthand large scale employment, utilizes the labor and natural resources, This research outlines the problems of Weather and Soil Erosions, Market price fluctuation, stimulates labor cost problems, reduces concentration of Price volatility, Dependency on Intermediaries, induces Limited Bargaining Power, and Storage and Transportation Costs. This paper mainly devoted to highlight Problems and challenges faced for the sustainable of Agro Entrepreneurs in India. Vinay Prasad B "Problems and Challenges of Agro Entreprenurship - A Study" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64540.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64540/problems-and-challenges-of-agro-entreprenurship--a-study/vinay-prasad-b
Comparative Analysis of Total Corporate Disclosure of Selected IT Companies o...ijtsrd
Disclosure is a process through which a business enterprise communicates with external parties. A corporate disclosure is communication of financial and non financial information of the activities of a business enterprise to the interested entities. Corporate disclosure is done through publishing annual reports. So corporate disclosure through annual reports plays a vital role in the life of all the companies and provides valuable information to investors. The basic objectives of corporate disclosure is to give a true and fair view of companies to the parties related either directly or indirectly like owner, government, creditors, shareholders etc. in the companies act, provisions have been made about mandatory and voluntary disclosure. The IT sector in India is rapidly growing, the trend to invest in the IT sector is rising and employment opportunities in IT sectors are also increasing. Therefore the IT sector is expected to have fair, full and adequate disclosure of all information. Unfair and incomplete disclosure may adversely affect the entire economy. A research study on disclosure practices of IT companies could play an important role in this regard. Hence, the present research study has been done to study and review comparative analysis of total corporate disclosure of selected IT companies of India and to put forward overall findings and suggestions with a view to increase disclosure score of these companies. The researcher hopes that the present research study will be helpful to all selected Companies for improving level of corporate disclosure through annual reports as well as the government, creditors, investors, all business organizations and upcoming researcher for comparative analyses of level of corporate disclosure with special reference to selected IT companies. Dr. Vaibhavi D. Thaker "Comparative Analysis of Total Corporate Disclosure of Selected IT Companies of India" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64539.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64539/comparative-analysis-of-total-corporate-disclosure-of-selected-it-companies-of-india/dr-vaibhavi-d-thaker
The Impact of Educational Background and Professional Training on Human Right...ijtsrd
This study investigated the impact of educational background and professional training on human rights awareness among secondary school teachers in the Marathwada region of Maharashtra, India. The key findings reveal that higher levels of education, particularly a master’s degree, and fields of study related to education, humanities, or social sciences are associated with greater human rights awareness among teachers. Additionally, both pre service teacher training and in service professional development programs focused on human rights education significantly enhance teacher’s knowledge, skills, and competencies in promoting human rights principles in their classrooms. Baig Ameer Bee Mirza Abdul Aziz | Dr. Syed Azaz Ali Amjad Ali "The Impact of Educational Background and Professional Training on Human Rights Awareness among Secondary School Teachers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64529.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/64529/the-impact-of-educational-background-and-professional-training-on-human-rights-awareness-among-secondary-school-teachers/baig-ameer-bee-mirza-abdul-aziz
A Study on the Effective Teaching Learning Process in English Curriculum at t...ijtsrd
“One Language sets you in a corridor for life. Two languages open every door along the way” Frank Smith English as a foreign language or as a second language has been ruling in India since the period of Lord Macaulay. But the question is how much we teach or learn English properly in our culture. Is there any scope to use English as a language rather than a subject How much we learn or teach English without any interference of mother language specially in the classroom teaching learning scenario in West Bengal By considering all these issues the researcher has attempted in this article to focus on the effective teaching learning process comparing to other traditional strategies in the field of English curriculum at the secondary level to investigate whether they fulfill the present teaching learning requirements or not by examining the validity of the present curriculum of English. The purpose of this study is to focus on the effectiveness of the systematic, scientific, sequential and logical transaction of the course between the teachers and the learners in the perspective of the 5Es programme that is engage, explore, explain, extend and evaluate. Sanchali Mondal | Santinath Sarkar "A Study on the Effective Teaching Learning Process in English Curriculum at the Secondary Level of West Bengal" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd62412.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/62412/a-study-on-the-effective-teaching-learning-process-in-english-curriculum-at-the-secondary-level-of-west-bengal/sanchali-mondal
The Role of Mentoring and Its Influence on the Effectiveness of the Teaching ...ijtsrd
This paper reports on a study which was conducted to investigate the role of mentoring and its influence on the effectiveness of the teaching of Physics in secondary schools in the South West Region of Cameroon. The study adopted the convergent parallel mixed methods design, focusing on respondents in secondary schools in the South West Region of Cameroon. Both quantitative and qualitative data were collected, analysed separately, and the results were compared to see if the findings confirm or disconfirm each other. The quantitative analysis found that majority of the respondents 72 of Physics teachers affirmed that they had more experienced colleagues as mentors to help build their confidence, improve their teaching, and help them improve their effectiveness and efficiency in guiding learners’ achievements. Only 28 of the respondents disagreed with these statements. With majority respondents 72 agreeing with the statements, it implies that in most secondary schools, experienced Physics teachers act as mentors to build teachers’ confidence in teaching and improving students’ learning. The interview qualitative data analysis summarized how secondary school Principals use meetings with mentors and mentees to promote mentorship in the school milieu. This has helped strengthen teachers’ classroom practices in secondary schools in the South West Region of Cameroon. With the results confirming each other, the study recommends that mentoring should focus on helping teachers employ social interactions and instructional practices feedback and clarity in teaching that have direct measurable impact on students’ learning achievements. Andrew Ngeim Sumba | Frederick Ebot Ashu | Peter Agborbechem Tambi "The Role of Mentoring and Its Influence on the Effectiveness of the Teaching of Physics in Secondary Schools in the South West Region of Cameroon" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64524.pdf Paper Url: https://www.ijtsrd.com/management/management-development/64524/the-role-of-mentoring-and-its-influence-on-the-effectiveness-of-the-teaching-of-physics-in-secondary-schools-in-the-south-west-region-of-cameroon/andrew-ngeim-sumba
Design Simulation and Hardware Construction of an Arduino Microcontroller Bas...ijtsrd
This study primarily focuses on the design of a high side buck converter using an Arduino microcontroller. The converter is specifically intended for use in DC DC applications, particularly in standalone solar PV systems where the PV output voltage exceeds the load or battery voltage. To evaluate the performance of the converter, simulation experiments are conducted using Proteus Software. These simulations provide insights into the input and output voltages, currents, powers, and efficiency under different state of charge SoC conditions of a 12V,70Ah rechargeable lead acid battery. Additionally, the hardware design of the converter is implemented, and practical data is collected through operation, monitoring, and recording. By comparing the simulation results with the practical results, the efficiency and performance of the designed converter are assessed. The findings indicate that while the buck converter is suitable for practical use in standalone PV systems, its efficiency is compromised due to a lower output current. Chan Myae Aung | Dr. Ei Mon "Design Simulation and Hardware Construction of an Arduino-Microcontroller Based DC-DC High-Side Buck Converter for Standalone PV System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64518.pdf Paper Url: https://www.ijtsrd.com/engineering/mechanical-engineering/64518/design-simulation-and-hardware-construction-of-an-arduinomicrocontroller-based-dcdc-highside-buck-converter-for-standalone-pv-system/chan-myae-aung
Sustainable Energy by Paul A. Adekunte | Matthew N. O. Sadiku | Janet O. Sadikuijtsrd
Energy becomes sustainable if it meets the needs of the present without compromising the ability of future generations to meet their own needs. Some of the definitions of sustainable energy include the considerations of environmental aspects such as greenhouse gas emissions, social, and economic aspects such as energy poverty. Generally far more sustainable than fossil fuel are renewable energy sources such as wind, hydroelectric power, solar, and geothermal energy sources. Worthy of note is that some renewable energy projects, like the clearing of forests to produce biofuels, can cause severe environmental damage. The sustainability of nuclear power which is a low carbon source is highly debated because of concerns about radioactive waste, nuclear proliferation, and accidents. The switching from coal to natural gas has environmental benefits, including a lower climate impact, but could lead to delay in switching to more sustainable options. “Carbon capture and storage” can be built into power plants to remove the carbon dioxide CO2 emissions, but this technology is expensive and has rarely been implemented. Leading non renewable energy sources around the world is fossil fuels, coal, petroleum, and natural gas. Nuclear energy is usually considered another non renewable energy source, although nuclear energy itself is a renewable energy source, but the material used in nuclear power plants is not. The paper addresses the issue of sustainable energy, its attendant benefits to the future generation, and humanity in general. Paul A. Adekunte | Matthew N. O. Sadiku | Janet O. Sadiku "Sustainable Energy" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64534.pdf Paper Url: https://www.ijtsrd.com/engineering/electrical-engineering/64534/sustainable-energy/paul-a-adekunte
Concepts for Sudan Survey Act Implementations Executive Regulations and Stand...ijtsrd
This paper aims to outline the executive regulations, survey standards, and specifications required for the implementation of the Sudan Survey Act, and for regulating and organizing all surveying work activities in Sudan. The act has been discussed for more than 5 years. The Land Survey Act was initiated by the Sudan Survey Authority and all official legislations were headed by the Sudan Ministry of Justice till it was issued in 2022. The paper presents conceptual guidelines to be used for the Survey Act implementation and to regulate the survey work practice, standardizing the field surveys, processing, quality control, procedures, and the processes related to survey work carried out by the stakeholders and relevant authorities in Sudan. The conceptual guidelines are meant to improve the quality and harmonization of geospatial data and to aid decision making processes as well as geospatial information systems. The established comprehensive executive regulations will govern and regulate the implementation of the Sudan Survey Geomatics Act in all surveying and mapping practices undertaken by the Sudan Survey Authority SSA and state local survey departments for public or private sector organizations. The targeted standards and specifications include the reference frame, projection, coordinate systems, and the guidelines and specifications that must be followed in the field of survey work, processes, and mapping products. In the last few decades, there has been a growing awareness of the importance of geomatics activities and measurements on the Earths surface in space and time, together with observing and mapping the changes. In such cases, data must be captured promptly, standardized, and obtained with more accuracy and specified in much detail. The paper will also highlight the current situation in Sudan, the degree to which survey standards are used, the problems encountered, and the errors that arise from not using the standards and survey specifications. Kamal A. A. Sami "Concepts for Sudan Survey Act Implementations - Executive Regulations and Standards" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63484.pdf Paper Url: https://www.ijtsrd.com/engineering/civil-engineering/63484/concepts-for-sudan-survey-act-implementations--executive-regulations-and-standards/kamal-a-a-sami
Towards the Implementation of the Sudan Interpolated Geoid Model Khartoum Sta...ijtsrd
The discussions between ellipsoid and geoid have invoked many researchers during the recent decades, especially during the GNSS technology era, which had witnessed a great deal of development but still geoid undulation requires more investigations. To figure out a solution for Sudans local geoid, this research has tried to intake the possibility of determining the geoid model by following two approaches, gravimetric and geometrical geoid model determination, by making use of GNSS leveling benchmarks at Khartoum state. The Benchmarks are well distributed in the study area, in which, the horizontal coordinates and the height above the ellipsoid have been observed by GNSS while orthometric heights were carried out using precise leveling. The Global Geopotential Model GGM represented in EGM2008 has been exploited to figure out the geoid undulation at the benchmarks in the study area. This is followed by a fitting process, that has been done to suit the geoid undulation data which has been computed using GNSS leveling data and geoid undulation inspired by the EGM2008. Two geoid surfaces were created after the fitting process to ensure that they are identical and both of them could be counted for getting the same geoid undulation with an acceptable accuracy. In this respect, statistical operation played an important role in ensuring the consistency and integrity of the model by applying cross validation techniques splitting the data into training and testing datasets for building the geoid model and testing its eligibility. The geometrical solution for geoid undulation computation has been utilized by applying straightforward equations that facilitate the calculation of the geoid undulation directly through applying statistical techniques for the GNSS leveling data of the study area to get the common equation parameters values that could be utilized to calculate geoid undulation of any position in the study area within the claimed accuracy. Both systems were checked and proved eligible to be used within the study area with acceptable accuracy which may contribute to solving the geoid undulation problem in the Khartoum area, and be further generalized to determine the geoid model over the entire country, and this could be considered in the future, for regional and continental geoid model. Ahmed M. A. Mohammed. | Kamal A. A. Sami "Towards the Implementation of the Sudan Interpolated Geoid Model (Khartoum State Case Study)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63483.pdf Paper Url: https://www.ijtsrd.com/engineering/civil-engineering/63483/towards-the-implementation-of-the-sudan-interpolated-geoid-model-khartoum-state-case-study/ahmed-m-a-mohammed
Activating Geospatial Information for Sudans Sustainable Investment Mapijtsrd
Sudan is witnessing an acceleration in the processes of development and transformation in the performance of government institutions to raise the productivity and investment efficiency of the government sector. The development plans and investment opportunities have focused on achieving national goals in various sectors. This paper aims to illuminate the path to the future and provide geospatial data and information to develop the investment climate and environment for all sized businesses, and to bridge the development gap between the Sudan states. The Sudan Survey Authority SSA is the main advisor to the Sudan Government in conducting surveying, mappings, designing, and developing systems related to geospatial data and information. In recent years, SSA made a strategic partnership with the Ministry of Investment to activate Geospatial Information for Sudans Sustainable Investment and in particular, for the preparation and implementation of the Sudan investment map, based on the directives and objectives of the Ministry of Investment MI in Sudan. This paper comes within the framework of activating the efforts of the Ministry of Investment to develop technical investment services by applying techniques adopted by the Ministry and its strategic partners for advancing investment processes in the country. Kamal A. A. Sami "Activating Geospatial Information for Sudan's Sustainable Investment Map" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63482.pdf Paper Url: https://www.ijtsrd.com/engineering/information-technology/63482/activating-geospatial-information-for-sudans-sustainable-investment-map/kamal-a-a-sami
Educational Unity Embracing Diversity for a Stronger Societyijtsrd
In a rapidly changing global landscape, the importance of education as a unifying force cannot be overstated. This paper explores the crucial role of educational unity in fostering a stronger and more inclusive society through the embrace of diversity. By examining the benefits of diverse learning environments, the paper aims to highlight the positive impact on societal strength. The discussion encompasses various dimensions, from curriculum design to classroom dynamics, and emphasizes the need for educational institutions to become catalysts for unity in diversity. It highlights the need for a paradigm shift in educational policies, curricula, and pedagogical approaches to ensure that they are reflective of the diverse fabric of society. This paper also addresses the challenges associated with implementing inclusive educational practices and offers practical strategies for overcoming barriers. It advocates for collaborative efforts between educational institutions, policymakers, and communities to create a supportive ecosystem that promotes diversity and unity. Mr. Amit Adhikari | Madhumita Teli | Gopal Adhikari "Educational Unity: Embracing Diversity for a Stronger Society" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64525.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/64525/educational-unity-embracing-diversity-for-a-stronger-society/mr-amit-adhikari
Integration of Indian Indigenous Knowledge System in Management Prospects and...ijtsrd
The diversity of indigenous knowledge systems in India is vast and can vary significantly between different communities and regions. Preserving and respecting these knowledge systems is crucial for maintaining cultural heritage, promoting sustainable practices, and fostering cross cultural understanding. In this paper, an overview of the prospects and challenges associated with incorporating Indian indigenous knowledge into management is explored. It is found that IIKS helps in management in many areas like sustainable development, tourism, food security, natural resource management, cultural preservation and innovation, etc. However, IIKS integration with management faces some challenges in the form of a lack of documentation, cultural sensitivity, language barriers legal framework, etc. Savita Lathwal "Integration of Indian Indigenous Knowledge System in Management: Prospects and Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63500.pdf Paper Url: https://www.ijtsrd.com/management/accounting-and-finance/63500/integration-of-indian-indigenous-knowledge-system-in-management-prospects-and-challenges/savita-lathwal
DeepMask Transforming Face Mask Identification for Better Pandemic Control in...ijtsrd
The COVID 19 pandemic has highlighted the crucial need of preventive measures, with widespread use of face masks being a key method for slowing the viruss spread. This research investigates face mask identification using deep learning as a technological solution to be reducing the risk of coronavirus transmission. The proposed method uses state of the art convolutional neural networks CNNs and transfer learning to automatically recognize persons who are not wearing masks in a variety of circumstances. We discuss how this strategy improves public health and safety by providing an efficient manner of enforcing mask wearing standards. The report also discusses the obstacles, ethical concerns, and prospective applications of face mask detection systems in the ongoing fight against the pandemic. Dilip Kumar Sharma | Aaditya Yadav "DeepMask: Transforming Face Mask Identification for Better Pandemic Control in the COVID-19 Era" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64522.pdf Paper Url: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/64522/deepmask-transforming-face-mask-identification-for-better-pandemic-control-in-the-covid19-era/dilip-kumar-sharma
Streamlining Data Collection eCRF Design and Machine Learningijtsrd
Efficient and accurate data collection is paramount in clinical trials, and the design of Electronic Case Report Forms eCRFs plays a pivotal role in streamlining this process. This paper explores the integration of machine learning techniques in the design and implementation of eCRFs to enhance data collection efficiency. We delve into the synergies between eCRF design principles and machine learning algorithms, aiming to optimize data quality, reduce errors, and expedite the overall data collection process. The application of machine learning in eCRF design brings forth innovative approaches to data validation, anomaly detection, and real time adaptability. This paper discusses the benefits, challenges, and future prospects of leveraging machine learning in eCRF design for streamlined and advanced data collection in clinical trials. Dhanalakshmi D | Vijaya Lakshmi Kannareddy "Streamlining Data Collection: eCRF Design and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63515.pdf Paper Url: https://www.ijtsrd.com/biological-science/biotechnology/63515/streamlining-data-collection-ecrf-design-and-machine-learning/dhanalakshmi-d
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
2. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD35823 | Volume – 5 | Issue – 1 | November-December 2020 Page 56
characteristics of a large amount of data, complex
background, small target size, and so on. At the same time,
because the remote sensing image is a top view, different
projection directions make the same target has different
rotation angles, which makes the angle direction of the
target arbitrary. Due to the particularity of remote sensing
image, the current mainstream general target detection
method based on deep learning cannot play an optimal role
in remote sensing image target detection. Therefore, it is of
great significance to study how to apply deep learning
methods to target detection in satellite visible light remote
sensing images to effectively improve the accuracy of target
detection and reduce the detection time.
II. Related work on target detection
Target detection [4] is a basic research task in computer
vision, which is mainly used to identify the types and
locations of targets in images. Target detectiontechnology is
widely used in industrial product detection, airport security
inspection, robot navigation, video monitoring, target
tracking, remote sensing, and many other fields. Through
using computer technology toreplacethetraditional manual
detection, it is an important practical significance for
improving production efficiency and reducing production
cost. Therefore, target detection has become a hot topic in
the academic and industrial circles this year. At the same
time, as an important branch of computer vision, target
detection technology also plays an important role in the
following target tracking, semantic segmentation [5,6],
instance segmentation [7].
The traditional target detectionalgorithmismainlybased on
SIFT [8] and HOG [9] to extract features manually. In 2012,
Alexnet [10] made a breakthrough in the ILSVRCimage
classification competition, and researchers began to use the
deep convolution neural network method tosolvecomputer
vision problems. Atpresent, thecommonnetwork structures
include Google net [11], VGG [12], Darknet[13],ResNet[14],
DenseNet [15], etc., which are designed to improve the
accuracy and speed of feature extraction from different
aspects. At present, the general target detection methods
based on convolutional neural networks can be divided into
two categories: the one-stage detectionmethodandthetwo-
stage detection method. In the two-stage detection method,
candidate regions are generated from the image firstly, and
then the candidate regions are classified. The main methods
are R-CNN, Fast R-CNN, FasterR-CNN [16].One-stage
detection methods mainly include YOLO, YOLO9000,
YOLOv3[17], SSD[18], etc.
III. Ship detection methods
With the development of remote sensing technology,people
can understand the earthfroma betterperspective.Inrecent
years, with the improvement of remote sensing image
resolution, ship detectionin optical remotesensingimagesis
a research hotspot, and many different methods have been
proposed. Generally speaking, these methodscanbedivided
into two categories: traditional methods and deep learning
methods. The traditional ship detectionmethodsaredivided
into three steps: the first step is the separation of land and
sea, which aims at separating the target from the ocean, the
second step is candidate detection, which shows that pixels
represent possible ships, and the last step is classification,
which identifies one of all the detected candidates in the
previous step of the real target. Traditional methods are
mainly based on geometric features of images.
Yang et al [19] proposed a detection method based on sea
surface analysis and used a newlinear function combining
pixel and region features to select candidate ships. Shi et al
[20] extended the existing HOGfeaturesandsomeadditional
information to improve the abilityofshipidentification.Qiet
al [21] used visual saliency to extract candidate regions and
improved the hand feature based on HOG. Traditional
detection methods mainly use manual features to detect
ships. These methods have achieved good results in open
waters, but it is difficult to detect in complex backgrounds.
With the development of deep learning, the methods based
on convolutional neural networks have surpassed the
traditional methods in many computervisiontasks.Inspired
by the successful application of convolutional neural
networks in natural scenes, many detection methods based
on deep learning have been applied to ship detection in
remote sensing images. To improve the detection accuracy,
Huang et al [22] proposed a squeeze excitation hop
connection path network (SESPNets) using a path-level hop
connection structure to improve the feature extraction
ability. Zhang et al [23] improved the original Fast R-CNN
structure to improve the detection results of small-scale
distributed ships. You et al [24] proposed a DCNN
framework to deal with multi-scale ship detection. You et al.
[25] proposed an end-to-end method called scene mask R-
CNN to reduce onshore false-positives.Thesemethodsbased
on CNN improve the efficiency and detection accuracy and
liberate researchers from the tedious feature processing.
However, these methods can only generate horizontal
boundary boxes, which are not suitable for targets placed in
any direction in remote sensing images.
Due to the great differences between remote sensingimages
and natural scenery images, it is still difficult to apply it
directly to remote sensing images. Different from natural
images, remote sensing imagesaretakenwithanaerial view.
Targets may exist in any direction. When detecting density
targets, especially with a high length-width ratio, ordinary
targets often are missed in the NMS step by relying on the
horizontal bounding box method. In contrast, the rotating
bounding box with an arbitrary rotation angle is more
suitable for ship detection. To solve this problem,
researchers began to introduce a rotating bounding box,
which was initially used for text detection. Yang et al. [26]
proposed a framework calledrotationdensefeaturepyramid
network (R-DFPN), which can effectively detect ships in
different scenes such as ocean and port. Ma et al. [27]
proposed a two-stage CNN ship detection method based on
ship center and azimuth prediction, which can accurately
detect ships in any direction in optical remote sensing
images. Tian et al. [28] proposed a framework integrating
multi-scale feature fusion network, rotating region
recommendation network, and context pool, which realized
accurate positioning and false alarm suppression. Zhang et
al. [29] proposed a rotating area recommendation network
(R2PN), which uses the azimuth information of ships to
generate multi-directional suggestions. At present, most of
the methods are two-stage. These methods can predict the
direction of the target and improve detection accuracy.
However, due to the existence of RPN network, these
methods use complex network structures and affect the
detection velocity.
3. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD35823 | Volume – 5 | Issue – 1 | November-December 2020 Page 57
IV. Semantic segmentation methods
The semantic segmentation combines image classification,
target detection, and image segmentation. Image semantic
segmentation is to classify every pixel in the image. By
semantic segmentation of remote sensing images, we can
separate the specific semantic pixels and obtain boundary
information to improve the accuracy of target detection.
Image semantic segmentation methods include traditional
methods and methods based on convolution neural
networks. The traditional semantic segmentation methods
mainly include threshold-based segmentation, edge-based
segmentation, region-based segmentation, and so on.
A. Image segmentation methods based on threshold
The threshold-based segmentation is to calculate one or
more gray thresholds based onthegraycharacteristicsof the
image, compare the gray value of each pixel with the
threshold, and finally classify the target into appropriate
categories according to the pixel comparison results.
The advantages of threshold-basedsegmentationaresimple,
high efficiency, and speed. The global threshold can
effectively segment different targetsand backgroundswitha
great difference in the gray level. Local thresholdordynamic
threshold is more suitable for the targets with little
difference. Although the threshold-based segmentation
method is simple and efficient, it also has some limitations.
The method only considers the gray value of the pixel itself,
generally does not considerthespatial characteristics,soitis
very sensitive to noise. In practical application, the
threshold-based methods are usually combined with other
methods.
B. Image segmentation methods based on edge
The edge refers to the set of continuous pixels on the
boundary of two different regions in the image, which
reflects the discontinuity of local features and the mutation
of image characteristics such as gray, color, texture, etc. The
edge-based segmentationmethoddetectsthe edgeaccording
to the gray value and divides the imageintodifferentparts.It
is based on the observation that the gray value of the edge
will show a step change.
C. Image segmentation technology based on Region
The image is divided into different regions according to the
similarity criterion. It mainly uses the local space
information of the image and can avoid the defect of small
segmentation space brought by other algorithms. However,
this kind of segmentation method is slow in large area
segmentation and has poor anti-noise performance, which
often results in meaningless region segmentation or over-
segmentation of image. In general, it will be combined with
other methods to give full play to their advantages to obtain
a better segmentation effect.
With the rapid development of deep learning, it isfoundthat
image semantic segmentation based on deep learning can
greatly improve accuracy. Most of the traditional
segmentation methodsconsiderthevisual informationof the
image pixel itself without training. Although the time
complexity is not high, the accuracy is low, and it cannot
effectively process thescenewithcomplexbackgrounds. The
primary difference between the semantic segmentation
method based on convolutional neural networks and the
traditional semantic segmentation method is that the
network can automatically learn the features of the image
and carry out end-to-end classification learning, which
greatly improvestheaccuracyofsemanticsegmentation. The
main idea of the imagesemanticsegmentationmethodbased
on deep learning is that a large number of original image
data are directly inputted into the deep network without
artificial design features. According to the designed deep
network algorithm, the imagedata isprocessedcomplexlyto
obtain high-level abstract features. The output is no longera
simple classification category or target positioning but the
segmentation image with pixel category label.
Long et al. [30] proposed a semantic segmentation model of
a full convolution network. Firstly, the features were
extracted by convolution operation, and then the feature
map was up sampled and restored to the input size. The
result of up sampling is fuzzy. It is not sensitive to thedetails
of the image, and the segmentation accuracy is poor. Vijay et
al. [31] proposed the SegNet symmetric semantic
segmentation model, which can reduce the loss of pixel
information, improve the resolution, and accurately locate
the image segmentation boundary. Chen et al.[32]proposed
the Deeplab model and added CRF based on FCN to improve
the boundarysegmentation accuracy.Ronnebergeretal.[33]
proposed a U-net network to improvethedetectionaccuracy
by adding feature fusion. When the convolution network is
used for semantic segmentation, the input image usually
needs to be adjusted to the input size of the model for the
fixed-size model. After semantic segmentation, it is restored
to the original size. Because the modification of image size
will lose useful information, especially for the small target,it
increases the difficulty of target segmentation.
V. Conclusion
Due to the great difference between remote sensing image
and natural scenery image, it is still difficult to apply it
directly to the remote sensing image. Different from natural
images, remote sensing images are taken from an aerial
view. Targets in remote sensing images may exist in any
direction. When detecting densely packedobjects,especially
targets with a large aspect ratio, ordinary targets oftenare
missed targets in the NMS step by relying on the horizontal
bounding box method, as shown in Figure 1. The method
retains the boundary box A with the maximum probability,
removes other boundary boxes B and C, which results in the
omission of the real target.
Figure 1falsedetection caused by NMS
When the full convolution network is used for semantic
segmentation, the input image usually needs to be adjusted
to the input size of the model for a fixed size model. After
semantic segmentation, it is restored totheoriginal size.The
process of semantic segmentation is shown in Figure 2.
4. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD35823 | Volume – 5 | Issue – 1 | November-December 2020 Page 58
scale
Semantic segmentation
network
reduction
fuzzy boundaries
Figure 2 semantic segmentation flow based on
convolutional neural network
For example, the above network limits the input image to
480 * 320. Because the modification of image resolution will
lose useful information in the image, especially for small
targets. The size in the feature map is very small after down
sampling, and it is difficult to include all the information
about the target, which makes it more difficult to segment
the target. For targets with complex boundaries, the
detection results are restored to the original image. And the
boundary is not smooth enough, and it is not sensitive to the
details of the image.
At present, the methods based on deep learning in remote
sensing target detection achieve some achievements, which
are mainly from the improvement of the target detection
algorithm in natural scenes. Therearesignificantdifferences
between remote sensing images and natural scene images,
especially in the aspects of target rotation, scale change, and
complex background. Although researchers have explored
and studied the ship target detection and recognition
technology in optical remote sensing image, there are still
many problems and challenges in ship target detection
algorithm based on remote sensing image
1. The environment in optical remote sensingimageis
complex
Due to the transmission characteristics of optical sensors,
camera angles, light intensity, weather, and sea background,
and other factors, the target will be blocked, or incomplete
and the contrast is low, which makes it more difficult to
detect the target.
2. Detection of inshore ships
Different from the ship on the sea, because the inshore ship
is often connected with the coast, which has similar
grayscale and texture of the buildings on the shore and is
affected by the shadow and side-by-side berthing. Thus, the
conventional ship detection methodcannotachievetheideal
detection results for the inshore ship. It is also difficult to
extract the ship target quickly and accurately from the
complex port environment.
3. Real-time performance of ship detection algorithm
At present, some target detection algorithms have a high
recognition rate. But because of its highcomplexityandslow
detection speed, it cannot meet the real-time requirements.
With the development of deep learning technology, remote
sensing image target detection technology is still an open
problem to be further studied.
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