This document discusses surface reconstruction from point cloud data. It describes how surface reconstruction involves three phases: initial surface estimation, mesh optimization, and smooth surface optimization. The crust algorithm and umbrella filtering are discussed as methods for surface reconstruction from point clouds. Challenges in surface reconstruction like noise, lack of normal vectors, non-uniform sampling, and holes are also outlined. The document reviews several related studies on surface reconstruction techniques.
Method of Fracture Surface Matching Based on Mathematical StatisticsIJRESJOURNAL
ABSTRACT: Fracture surface matching is an important part of point cloud registration. In this paper, a method of fracture surface matching based on mathematical statistics is proposed. We reconstruct a coordinate system of the fractured surface points, and analyze the characteristics of the point cloud in the new coordinate system, using the theory of mathematical statistcs. The general distribution of the points is determined. The method can realize the matching relation among some point cloud.
This document compares the accuracy of determining volumes using close range photogrammetry versus traditional methods. It presents a case study where the volume of a test field was calculated using both approaches. Using traditional methods with 425 control points, the volume was calculated as 221475.14 m3 using trapezoidal rules, 221424.52 m3 using Simpson's rule, and 221484.05 m3 using Simpson's 3/8 rule. Using close range photogrammetry with 42 control points and 574 generated points, the volume was calculated as 215310.60 m3 using trapezoidal rules, 215300.43 m3 using Simpson's rule, and 215304.12 m3 using Simpson's 3
Extended hybrid region growing segmentation of point clouds with different re...csandit
In the recent years, 3D city reconstruction is one of the active researches in the field of
photogrammetry. The goal of this work is to improve and extend region growing based
segmentation in the X-Y-Z image in the form of 3D structured data with combination of spectral
information of RGB and grayscale image to extract building roofs, streets and vegetation. In
order to process 3D point clouds, hybrid segmentation is carried out in both object space and
image space. Our experiments on two case studies verify that updating plane parameters and
robust least squares plane fitting improves the results of building extraction especially in case
of low accurate point clouds. In addition, region growing in image space has been derived to
the fact that grayscale image is more flexible than RGB image and results in more realistic
building roofs.
This paper proposes a novel technique for detecting point landmarks in 3D medical images based on phase congruency (PC). A bank of 3D log-Gabor filters is used to compute energy maps from the images. These energy maps are combined to form the PC measure, which is invariant to intensity variations and provides good feature localization. Significant 3D point landmarks are detected by analyzing the eigenvectors of PC moments computed at each point. The method is demonstrated on head and neck images for radiation therapy planning.
International Journal of Engineering Inventions (IJEI) provides a multidisciplinary passage for researchers, managers, professionals, practitioners and students around the globe to publish high quality, peer-reviewed articles on all theoretical and empirical aspects of Engineering and Science.
Effect of sub classes on the accuracy of the classified imageiaemedu
This document discusses image classification techniques in remote sensing. It begins with an overview of the need for geometric corrections and rectification of satellite images to account for distortions. It then describes supervised and unsupervised classification methods for extracting land cover information from images. Supervised classification involves using training data to classify pixels, while unsupervised classification groups pixels into spectral classes based on natural clusters. The maximum likelihood algorithm assumes normal distributions and assigns pixels to the most probable class. Classification accuracy is assessed using an error matrix to evaluate omission and commission errors between the classified and reference maps. Increasing the number of classes in a classified image can reduce accuracy by making spectral distinctions between classes less clear.
Automatic rectification of perspective distortion from a single image using p...ijcsa
Perspective distortion occurs due to the perspective projection of 3D scene on a 2D surface. Correcting the distortion of a single image without losing any desired information is one of the challenging task in the field of Computer Vision. We consider the problem of estimating perspective distortion from a single still image of an unstructured environment and to make perspective correction which is both quantitatively accurate as well as visually pleasing. Corners are detected based on the orientation of the image. A method based on plane homography and transformation is used to make perspective correction. The algorithm infers frontier information directly from the images, without any reference objects or prior knowledge of the camera parameters. The frontiers are detected using geometric context based segmentation. The goal of this paper is to present a framework providing fully automatic and fast perspective correction.
A HYBRID MORPHOLOGICAL ACTIVE CONTOUR FOR NATURAL IMAGESIJCSEA Journal
Morphological active contours for image segmentation have become popular due to their low computational complexity coupled with their accurate approximation of the partial differential equations
involved in the energy minimization of the segmentation process. In this paper, a morphological active contour which mimics the energy minimization of the popular Chan-Vese Active Contour without Edges is coupled with a morphological edge-driven segmentation term to accurately segment natural images. By using morphological approximations of the energy minimization steps, the algorithm has a low computational complexity. Additionally, the coupling of the edge-based and region-based segmentation techniques allows the proposed method to be robust and accurate. We will demonstrate the accuracy and robustness of the algorithm using images from the Weizmann Segmentation Evaluation Database and report on the segmentation results using the Sorensen-Dice similarity coefficient.
Method of Fracture Surface Matching Based on Mathematical StatisticsIJRESJOURNAL
ABSTRACT: Fracture surface matching is an important part of point cloud registration. In this paper, a method of fracture surface matching based on mathematical statistics is proposed. We reconstruct a coordinate system of the fractured surface points, and analyze the characteristics of the point cloud in the new coordinate system, using the theory of mathematical statistcs. The general distribution of the points is determined. The method can realize the matching relation among some point cloud.
This document compares the accuracy of determining volumes using close range photogrammetry versus traditional methods. It presents a case study where the volume of a test field was calculated using both approaches. Using traditional methods with 425 control points, the volume was calculated as 221475.14 m3 using trapezoidal rules, 221424.52 m3 using Simpson's rule, and 221484.05 m3 using Simpson's 3/8 rule. Using close range photogrammetry with 42 control points and 574 generated points, the volume was calculated as 215310.60 m3 using trapezoidal rules, 215300.43 m3 using Simpson's rule, and 215304.12 m3 using Simpson's 3
Extended hybrid region growing segmentation of point clouds with different re...csandit
In the recent years, 3D city reconstruction is one of the active researches in the field of
photogrammetry. The goal of this work is to improve and extend region growing based
segmentation in the X-Y-Z image in the form of 3D structured data with combination of spectral
information of RGB and grayscale image to extract building roofs, streets and vegetation. In
order to process 3D point clouds, hybrid segmentation is carried out in both object space and
image space. Our experiments on two case studies verify that updating plane parameters and
robust least squares plane fitting improves the results of building extraction especially in case
of low accurate point clouds. In addition, region growing in image space has been derived to
the fact that grayscale image is more flexible than RGB image and results in more realistic
building roofs.
This paper proposes a novel technique for detecting point landmarks in 3D medical images based on phase congruency (PC). A bank of 3D log-Gabor filters is used to compute energy maps from the images. These energy maps are combined to form the PC measure, which is invariant to intensity variations and provides good feature localization. Significant 3D point landmarks are detected by analyzing the eigenvectors of PC moments computed at each point. The method is demonstrated on head and neck images for radiation therapy planning.
International Journal of Engineering Inventions (IJEI) provides a multidisciplinary passage for researchers, managers, professionals, practitioners and students around the globe to publish high quality, peer-reviewed articles on all theoretical and empirical aspects of Engineering and Science.
Effect of sub classes on the accuracy of the classified imageiaemedu
This document discusses image classification techniques in remote sensing. It begins with an overview of the need for geometric corrections and rectification of satellite images to account for distortions. It then describes supervised and unsupervised classification methods for extracting land cover information from images. Supervised classification involves using training data to classify pixels, while unsupervised classification groups pixels into spectral classes based on natural clusters. The maximum likelihood algorithm assumes normal distributions and assigns pixels to the most probable class. Classification accuracy is assessed using an error matrix to evaluate omission and commission errors between the classified and reference maps. Increasing the number of classes in a classified image can reduce accuracy by making spectral distinctions between classes less clear.
Automatic rectification of perspective distortion from a single image using p...ijcsa
Perspective distortion occurs due to the perspective projection of 3D scene on a 2D surface. Correcting the distortion of a single image without losing any desired information is one of the challenging task in the field of Computer Vision. We consider the problem of estimating perspective distortion from a single still image of an unstructured environment and to make perspective correction which is both quantitatively accurate as well as visually pleasing. Corners are detected based on the orientation of the image. A method based on plane homography and transformation is used to make perspective correction. The algorithm infers frontier information directly from the images, without any reference objects or prior knowledge of the camera parameters. The frontiers are detected using geometric context based segmentation. The goal of this paper is to present a framework providing fully automatic and fast perspective correction.
A HYBRID MORPHOLOGICAL ACTIVE CONTOUR FOR NATURAL IMAGESIJCSEA Journal
Morphological active contours for image segmentation have become popular due to their low computational complexity coupled with their accurate approximation of the partial differential equations
involved in the energy minimization of the segmentation process. In this paper, a morphological active contour which mimics the energy minimization of the popular Chan-Vese Active Contour without Edges is coupled with a morphological edge-driven segmentation term to accurately segment natural images. By using morphological approximations of the energy minimization steps, the algorithm has a low computational complexity. Additionally, the coupling of the edge-based and region-based segmentation techniques allows the proposed method to be robust and accurate. We will demonstrate the accuracy and robustness of the algorithm using images from the Weizmann Segmentation Evaluation Database and report on the segmentation results using the Sorensen-Dice similarity coefficient.
A HYBRID MORPHOLOGICAL ACTIVE CONTOUR FOR NATURAL IMAGESIJCSEA Journal
Morphological active contours for image segmentation have become popular due to their low computational complexity coupled with their accurate approximation of the partial differential equations involved in the energy minimization of the segmentation process. In this paper, a morphological active contour which mimics the energy minimization of the popular Chan-Vese Active Contour without Edges is coupled with a morphological edge-driven segmentation term to accurately segment natural images. By using morphological approximations of the energy minimization steps, the algorithm has a low computational complexity. Additionally, the coupling of the edge-based and region-based segmentation techniques allows the proposed method to be robust and accurate. We will demonstrate the accuracy and robustness of the algorithm using images from the Weizmann Segmentation Evaluation Database and report on the segmentation results using the Sorensen-Dice similarity coefficient.
EVALUATION OF THE VISUAL ODOMETRY METHODS FOR SEMI-DENSE REAL-TIMEacijjournal
This document summarizes the evaluation of visual odometry methods for semi-dense real-time reconstruction. It discusses two popular visual odometry approaches, LSD-SLAM and ORB-SLAM2, and evaluates their performance on three datasets. It then proposes a new approach that combines feature-based and feature-less methods for real-time odometry with a stereo camera, matching images semi-densely and reconstructing 3D environments directly on pixels with gradients.
Dynamic texture based traffic vehicle monitoring systemeSAT Journals
Abstract Dynamic Textures are function of both space and time which exhibit spatio-temporal stationary property. They have spatially repetitive patterns which vary with time. In this paper, importance of phase spectrum in the signals is utilized and a novel method for vehicle monitoring is proposed with the help of Fourier analysis, synthesis and image processing. Methods like Doppler radar or GPS navigation are used commonly for tracking. The proposed image based approach has an added advantage that the clear image of the object (vehicle) can be used for future reference like proof of incidence, identification of owner and registration number. Keywords-Fourier Transform, dynamic texture, phase spectrum
This document summarizes a research paper that proposes a novel approach for enhancing digital images using morphological operators. The approach aims to improve contrast in images with poor lighting conditions. It uses two morphological operators based on Weber's law - the first employs blocked analysis while the second uses opening by reconstruction to define a multi-background. The performance of the proposed operators is evaluated on images with various backgrounds and lighting conditions. Key steps include dividing images into blocks, estimating minimum/maximum intensities in each block to determine background criteria, and applying contrast enhancement transformations based on the criteria. Opening by reconstruction is also used to approximate image background without modifying structures. Experimental results demonstrate the approach enhances images with poor lighting.
Bio medical image segmentation using marker controlled watershed algorithm a ...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
A MORPHOLOGICAL MULTIPHASE ACTIVE CONTOUR FOR VASCULAR SEGMENTATIONijbbjournal
This paper presents a morphological active contour ideal for vascular segmentation in biomedical images.
The unenhanced images of vessels and background are successfully segmented using a two-step
morphological active contour based upon Chan and Vese’s Active Contour without Edges. Using dilation
and erosion as an approximation of curve evolution, the contour provides an efficient, simple, and robust
alternative to solving partial differential equations used by traditional level-set Active Contour models. The
proposed method is demonstrated with segmented data set images and compared to results garnered from
multiphase Active Contour without Edges, morphological watershed, and Fuzzy C-means segmentations.
This document proposes new methods for horizon line detection in marine images captured using infrared or visible light cameras. It discusses existing methods like edge detection and Hough transform (EDHT) and introduces improvements. A new histogram-based method is proposed that segments an image into sky and sea regions by comparing regional probability distribution functions (PDFs) or histograms and selecting the line that maximizes the statistical distance between the PDFs. The document also describes combining EDHT with a statistical criterion to select the optimal line among candidate lines detected in the image. It compares these methods quantitatively and visually on test images and concludes that the introduced methods can benefit applications like tracking, navigation and target recognition from marine imagery.
A digital image forensic approach to detect whether
an image has been seam carved or not is investigated herein.
Seam carving is a content-aware image retargeting technique
which preserves the semantically important content of an image
while resizing it. The same technique, however, can be used
for malicious tampering of an image. 18 energy, seam, and
noise related features defined by Ryu [1] are produced using
Sobel’s [2] gradient filter and Rubinstein’s [3] forward energy
criterion enhanced with image gradients. An extreme gradient
boosting classifier [4] is trained to make the final decision.
Experimental results show that the proposed approach improves
the detection accuracy from 5 to 10% for seam carved images
with different scaling ratios when compared with other state-ofthe-
art methods.
Formation and morphology of architectural surfaces designIJSRED
This document summarizes a study that examines the relationship between the fractal dimension of solid surfaces and the size and composition of particles that form the surfaces. Specifically, the study experimentally determines how the fractal dimension of surfaces formed from cement-stone dust mixtures varies with the surface area and composition of the stone dust particles. The fractal dimension, a measure of surface roughness, was calculated from images of 12 sample surfaces that varied in particle size and cement concentration. Statistical analysis found the fractal dimension was significantly influenced by the specific surface area of particles but not their composition.
This document compares two analytical optimization methods for designing coils that generate magnetic field gradients. The first method is based on work by Mansfield and involves nulling unnecessary terms in the Taylor expansion of the magnetic field. The second method is the Target Field Method developed by Turner, which uses inverse Fourier transforms to estimate the required current density. Both methods are applied to design coils producing linear magnetic field gradients. The results show optimizations for coils modeled as BM3, CAP3, CAP5 and CAP7, which null different orders of terms in the field expansion to achieve higher linearity. Simulations demonstrate the designed field gradients.
Change Detection of Water-Body in Synthetic Aperture Radar ImagesCSCJournals
Change detection is the art of quantifying the changes in the Synthetic Aperture Radar (SAR) images that have happened over a period of time. Remote sensing has been the parental technique to perform change detection analysis. This paper empirically investigates the impact of applying the combination of texture features for different classification techniques to separate water body from non-water body. At first, the images are classified using unsupervised Principle Component Analysis (PCA) based K-means clustering for dimension reduction. Then the texture features like Energy, Entropy, Contrast , Inverse Differential Moment , Directional Moment and the Median are extracted using Gray Level Co-occurrence Matrix (GLCM) and these features are utilized in Linear Vector Quantization (LVQ) and Support Vector Machine (SVM) classifiers. This paper aims to apply a combination of the texture features in order to significantly improve the accuracy of detection. The utility of detection analysis, influences management and policy decision making for long-term construction projects by predicting the preventable losses.
Image fusion using nsct denoising and target extraction for visual surveillanceeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document discusses using texture features extracted from statistical matrices to classify mammograms for content-based retrieval. It examines gray level co-occurrence matrices (GLCM), gray level aura matrices (GLAM), and gray level neighbors matrices (GLNM) to extract 13 statistical texture features. An experiment is conducted on mammograms from the MIAS database to evaluate the classification accuracy and retrieval time of the different statistical matrices and identify their relative performance for mammogram classification and retrieval.
Image processing techniques applied for pitting corrosion analysiseSAT Journals
Abstract
In order to study the behavior of the early stage of pitting corrosion, an image analysis based on discrete wavelet packet transform
and fractals was used. Image feature parameters were extracted and analyzed to characterize the pitting corrosion development with
test time. It was found that the feature parameters: Shannon entropy, energy, fractal dimension and intercept increased with the test
time. Therefore the image processing techniques were promising and effective tools to analyze and detect the pitting corrosion.
Keywords: corrosion, pitting corrosion, surface topography, surface analysis, carbon steel, tap water
An Improved TRICKS Method for Dynamic Contrast-Enhanced Tumor ImagingMike Aref
3D dynamic contrast-enhanced (DCE) imaging is a widely used technique for tumor diagnosis. A major challenge in this
application is to fast sample the dynamic signal variations while keeping the spatial resolution. TRICKS is a reduced-encoding imaging method
where k-space data are temporally subsampled during data acquisition and then recovered by linear interpolation before image reconstruction.
Significant errors can be introduced by the linear interpolation when underlying signal variations show nonlinear behavior, for example, in DCE
experiments where the signals show a rapid enhancement phase followed by a slow decay phase. This abstract presents a new image reconstruction
scheme to improve the TRICKS method. Using a nonlinear interpolation scheme, the new method can capture dynamic signal variations more accurately. Experimental results from a DCE mice tumor study are presented to demonstrate the effectiveness of the proposed method.
IRJET-A Review on Implementation of High Dimension Colour Transform in Domain...IRJET Journal
This document reviews algorithms for detecting salient regions in images using high dimensional color transforms. It summarizes several existing methods that use color contrast, frequency analysis, and superpixel segmentation. A key method discussed creates a saliency map by finding the optimal linear combination of color coefficients in a high dimensional color space. This allows more accurate detection of salient objects versus methods using only RGB color. The performance of this high dimensional color transform method is improved by also utilizing relative location and color contrast between superpixels as learned features.
Shape analysis using conformal mapping is a technique that analyzes geometric shapes by mapping their connections and distributions into computer programs. It is useful in fields like archaeology, architecture, medical imaging, and computer design. Conformal mapping preserves angles between shapes and can map 2D and 3D shapes onto each other. For brain mapping specifically, spherical harmonics equations are used to compress brain surface data and compare different brain scans. Conformal mapping proves useful for medical applications due to its ability to uniformly map points on brain surfaces without distortion.
Surface Traping in Silicon Nanowire Dual material engineered Cylindrical gate...IJARTES
In this paper, the effect of gate field screening by surface
trap charges are studied using COMSOL 5.0. A nano wire
dual material Cylindrical gate (DMCG) MOSFET is
modeled and shift of turn on voltage due to the screening
effect is computed. It is shown that DMCG design increase
the drain current enhancement .However here the concept
of work function difference also present in term of gate bias
and comprehensive study of short channel effect of DMCG
has been focused .The objective of this paper is focus on
Current vs Gate voltage, Energy Band diagram,
CurrentDensity, electron and hole concentration and
Electric field when MOSFET is turn on. It is also examined
that Cylindrical MOSFET the minimum surface potential in
the channel reduces which resulting increasing in electron
velocity and thereby improving carrier transport efficiency.
FIFA has announced news today regarding soccer tournaments. A new tournament format will be tested involving grouping teams together in a preliminary stage. Further details about tournament changes and team placements will be shared in the coming weeks.
Synthesis and Spectral Characterization of UO2(VI), Th(IV) and ZrO(IV) Complexes with benzimidazolyl-2-hydrazones of diacetyl monoxime and benzil monoxime
Ranjan Kumar Mohapatra1, Pradeep Kumar Das2
This document discusses using support vector machines for language identification from speech data. It describes extracting mel frequency cepstral coefficients from speech samples in 5 different languages as features, and using these features to train SVM models for each language. The models were tested on held-out speech data to identify the language, achieving accuracy ranging from 67-93% depending on the language. Support vector machines were able to effectively handle the high-dimensional feature vectors and identify the language of new speech samples by finding the model with the highest probability.
A HYBRID MORPHOLOGICAL ACTIVE CONTOUR FOR NATURAL IMAGESIJCSEA Journal
Morphological active contours for image segmentation have become popular due to their low computational complexity coupled with their accurate approximation of the partial differential equations involved in the energy minimization of the segmentation process. In this paper, a morphological active contour which mimics the energy minimization of the popular Chan-Vese Active Contour without Edges is coupled with a morphological edge-driven segmentation term to accurately segment natural images. By using morphological approximations of the energy minimization steps, the algorithm has a low computational complexity. Additionally, the coupling of the edge-based and region-based segmentation techniques allows the proposed method to be robust and accurate. We will demonstrate the accuracy and robustness of the algorithm using images from the Weizmann Segmentation Evaluation Database and report on the segmentation results using the Sorensen-Dice similarity coefficient.
EVALUATION OF THE VISUAL ODOMETRY METHODS FOR SEMI-DENSE REAL-TIMEacijjournal
This document summarizes the evaluation of visual odometry methods for semi-dense real-time reconstruction. It discusses two popular visual odometry approaches, LSD-SLAM and ORB-SLAM2, and evaluates their performance on three datasets. It then proposes a new approach that combines feature-based and feature-less methods for real-time odometry with a stereo camera, matching images semi-densely and reconstructing 3D environments directly on pixels with gradients.
Dynamic texture based traffic vehicle monitoring systemeSAT Journals
Abstract Dynamic Textures are function of both space and time which exhibit spatio-temporal stationary property. They have spatially repetitive patterns which vary with time. In this paper, importance of phase spectrum in the signals is utilized and a novel method for vehicle monitoring is proposed with the help of Fourier analysis, synthesis and image processing. Methods like Doppler radar or GPS navigation are used commonly for tracking. The proposed image based approach has an added advantage that the clear image of the object (vehicle) can be used for future reference like proof of incidence, identification of owner and registration number. Keywords-Fourier Transform, dynamic texture, phase spectrum
This document summarizes a research paper that proposes a novel approach for enhancing digital images using morphological operators. The approach aims to improve contrast in images with poor lighting conditions. It uses two morphological operators based on Weber's law - the first employs blocked analysis while the second uses opening by reconstruction to define a multi-background. The performance of the proposed operators is evaluated on images with various backgrounds and lighting conditions. Key steps include dividing images into blocks, estimating minimum/maximum intensities in each block to determine background criteria, and applying contrast enhancement transformations based on the criteria. Opening by reconstruction is also used to approximate image background without modifying structures. Experimental results demonstrate the approach enhances images with poor lighting.
Bio medical image segmentation using marker controlled watershed algorithm a ...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
A MORPHOLOGICAL MULTIPHASE ACTIVE CONTOUR FOR VASCULAR SEGMENTATIONijbbjournal
This paper presents a morphological active contour ideal for vascular segmentation in biomedical images.
The unenhanced images of vessels and background are successfully segmented using a two-step
morphological active contour based upon Chan and Vese’s Active Contour without Edges. Using dilation
and erosion as an approximation of curve evolution, the contour provides an efficient, simple, and robust
alternative to solving partial differential equations used by traditional level-set Active Contour models. The
proposed method is demonstrated with segmented data set images and compared to results garnered from
multiphase Active Contour without Edges, morphological watershed, and Fuzzy C-means segmentations.
This document proposes new methods for horizon line detection in marine images captured using infrared or visible light cameras. It discusses existing methods like edge detection and Hough transform (EDHT) and introduces improvements. A new histogram-based method is proposed that segments an image into sky and sea regions by comparing regional probability distribution functions (PDFs) or histograms and selecting the line that maximizes the statistical distance between the PDFs. The document also describes combining EDHT with a statistical criterion to select the optimal line among candidate lines detected in the image. It compares these methods quantitatively and visually on test images and concludes that the introduced methods can benefit applications like tracking, navigation and target recognition from marine imagery.
A digital image forensic approach to detect whether
an image has been seam carved or not is investigated herein.
Seam carving is a content-aware image retargeting technique
which preserves the semantically important content of an image
while resizing it. The same technique, however, can be used
for malicious tampering of an image. 18 energy, seam, and
noise related features defined by Ryu [1] are produced using
Sobel’s [2] gradient filter and Rubinstein’s [3] forward energy
criterion enhanced with image gradients. An extreme gradient
boosting classifier [4] is trained to make the final decision.
Experimental results show that the proposed approach improves
the detection accuracy from 5 to 10% for seam carved images
with different scaling ratios when compared with other state-ofthe-
art methods.
Formation and morphology of architectural surfaces designIJSRED
This document summarizes a study that examines the relationship between the fractal dimension of solid surfaces and the size and composition of particles that form the surfaces. Specifically, the study experimentally determines how the fractal dimension of surfaces formed from cement-stone dust mixtures varies with the surface area and composition of the stone dust particles. The fractal dimension, a measure of surface roughness, was calculated from images of 12 sample surfaces that varied in particle size and cement concentration. Statistical analysis found the fractal dimension was significantly influenced by the specific surface area of particles but not their composition.
This document compares two analytical optimization methods for designing coils that generate magnetic field gradients. The first method is based on work by Mansfield and involves nulling unnecessary terms in the Taylor expansion of the magnetic field. The second method is the Target Field Method developed by Turner, which uses inverse Fourier transforms to estimate the required current density. Both methods are applied to design coils producing linear magnetic field gradients. The results show optimizations for coils modeled as BM3, CAP3, CAP5 and CAP7, which null different orders of terms in the field expansion to achieve higher linearity. Simulations demonstrate the designed field gradients.
Change Detection of Water-Body in Synthetic Aperture Radar ImagesCSCJournals
Change detection is the art of quantifying the changes in the Synthetic Aperture Radar (SAR) images that have happened over a period of time. Remote sensing has been the parental technique to perform change detection analysis. This paper empirically investigates the impact of applying the combination of texture features for different classification techniques to separate water body from non-water body. At first, the images are classified using unsupervised Principle Component Analysis (PCA) based K-means clustering for dimension reduction. Then the texture features like Energy, Entropy, Contrast , Inverse Differential Moment , Directional Moment and the Median are extracted using Gray Level Co-occurrence Matrix (GLCM) and these features are utilized in Linear Vector Quantization (LVQ) and Support Vector Machine (SVM) classifiers. This paper aims to apply a combination of the texture features in order to significantly improve the accuracy of detection. The utility of detection analysis, influences management and policy decision making for long-term construction projects by predicting the preventable losses.
Image fusion using nsct denoising and target extraction for visual surveillanceeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document discusses using texture features extracted from statistical matrices to classify mammograms for content-based retrieval. It examines gray level co-occurrence matrices (GLCM), gray level aura matrices (GLAM), and gray level neighbors matrices (GLNM) to extract 13 statistical texture features. An experiment is conducted on mammograms from the MIAS database to evaluate the classification accuracy and retrieval time of the different statistical matrices and identify their relative performance for mammogram classification and retrieval.
Image processing techniques applied for pitting corrosion analysiseSAT Journals
Abstract
In order to study the behavior of the early stage of pitting corrosion, an image analysis based on discrete wavelet packet transform
and fractals was used. Image feature parameters were extracted and analyzed to characterize the pitting corrosion development with
test time. It was found that the feature parameters: Shannon entropy, energy, fractal dimension and intercept increased with the test
time. Therefore the image processing techniques were promising and effective tools to analyze and detect the pitting corrosion.
Keywords: corrosion, pitting corrosion, surface topography, surface analysis, carbon steel, tap water
An Improved TRICKS Method for Dynamic Contrast-Enhanced Tumor ImagingMike Aref
3D dynamic contrast-enhanced (DCE) imaging is a widely used technique for tumor diagnosis. A major challenge in this
application is to fast sample the dynamic signal variations while keeping the spatial resolution. TRICKS is a reduced-encoding imaging method
where k-space data are temporally subsampled during data acquisition and then recovered by linear interpolation before image reconstruction.
Significant errors can be introduced by the linear interpolation when underlying signal variations show nonlinear behavior, for example, in DCE
experiments where the signals show a rapid enhancement phase followed by a slow decay phase. This abstract presents a new image reconstruction
scheme to improve the TRICKS method. Using a nonlinear interpolation scheme, the new method can capture dynamic signal variations more accurately. Experimental results from a DCE mice tumor study are presented to demonstrate the effectiveness of the proposed method.
IRJET-A Review on Implementation of High Dimension Colour Transform in Domain...IRJET Journal
This document reviews algorithms for detecting salient regions in images using high dimensional color transforms. It summarizes several existing methods that use color contrast, frequency analysis, and superpixel segmentation. A key method discussed creates a saliency map by finding the optimal linear combination of color coefficients in a high dimensional color space. This allows more accurate detection of salient objects versus methods using only RGB color. The performance of this high dimensional color transform method is improved by also utilizing relative location and color contrast between superpixels as learned features.
Shape analysis using conformal mapping is a technique that analyzes geometric shapes by mapping their connections and distributions into computer programs. It is useful in fields like archaeology, architecture, medical imaging, and computer design. Conformal mapping preserves angles between shapes and can map 2D and 3D shapes onto each other. For brain mapping specifically, spherical harmonics equations are used to compress brain surface data and compare different brain scans. Conformal mapping proves useful for medical applications due to its ability to uniformly map points on brain surfaces without distortion.
Surface Traping in Silicon Nanowire Dual material engineered Cylindrical gate...IJARTES
In this paper, the effect of gate field screening by surface
trap charges are studied using COMSOL 5.0. A nano wire
dual material Cylindrical gate (DMCG) MOSFET is
modeled and shift of turn on voltage due to the screening
effect is computed. It is shown that DMCG design increase
the drain current enhancement .However here the concept
of work function difference also present in term of gate bias
and comprehensive study of short channel effect of DMCG
has been focused .The objective of this paper is focus on
Current vs Gate voltage, Energy Band diagram,
CurrentDensity, electron and hole concentration and
Electric field when MOSFET is turn on. It is also examined
that Cylindrical MOSFET the minimum surface potential in
the channel reduces which resulting increasing in electron
velocity and thereby improving carrier transport efficiency.
FIFA has announced news today regarding soccer tournaments. A new tournament format will be tested involving grouping teams together in a preliminary stage. Further details about tournament changes and team placements will be shared in the coming weeks.
Synthesis and Spectral Characterization of UO2(VI), Th(IV) and ZrO(IV) Complexes with benzimidazolyl-2-hydrazones of diacetyl monoxime and benzil monoxime
Ranjan Kumar Mohapatra1, Pradeep Kumar Das2
This document discusses using support vector machines for language identification from speech data. It describes extracting mel frequency cepstral coefficients from speech samples in 5 different languages as features, and using these features to train SVM models for each language. The models were tested on held-out speech data to identify the language, achieving accuracy ranging from 67-93% depending on the language. Support vector machines were able to effectively handle the high-dimensional feature vectors and identify the language of new speech samples by finding the model with the highest probability.
This document compares four clustering algorithms (K-means, hierarchical, EM, and density-based) using the WEKA tool. It applies the algorithms to a dataset of software classes and evaluates them based on number of clusters, time to build models, squared errors, and log likelihood. The results show that K-means performs best in terms of time to build models, while density-based clustering performs best in terms of log likelihood. Overall, the document concludes that K-means is the best algorithm for this dataset because it balances low runtime and good clustering accuracy.
The document describes an Adaptive Source Provision System (ASPS) proposed to control traffic rates and ensure load balancing in WiMAX networks. The system considers relay stations and uses an adaptive resource management approach. When new users arrive, their data rates are computed and compared to relay station data rates. If a user's rate is lower, the base station's rate is also compared. Connections are switched from congested to non-congested stations to minimize network load and balance traffic. The system aims to improve traffic management and load balancing compared to existing approaches.
1) The document presents a framework for automatic generation control (AGC) in a two-area restructured power system with non-linear governor characteristics, including hydro-hydro systems.
2) It models the addition of a frequency stabilizer equipped with an energy storage system to stabilize frequency and tie-line power oscillations under disturbances.
3) The gains of controllers and parameters of the stabilizer are optimized using genetic algorithms. Simulations show the response of the optimized load frequency controller under different transactions in the restructured electricity market.
The document discusses stress analysis and durability studies of spur gears using finite element analysis tools. It outlines how FEA can be used to model contact stresses and bending stresses in gears to better understand gear failure from factors like pitting. The analysis aims to reduce transmission error and thereby noise generated by more accurately predicting stresses, stiffness, and life of gears.
VANET Clustering for Protected and Steady Network
Mukesh Bathre1, Alok Sahelay2
Abstract— Vehicular on demand ad-hoc network (VANET) is understood as a necessary issue of good Transportation systems. The key advantage of VANET communication is looked in dynamic protection systems, that objective to improve security of travelers by exchanging caution messages between vehicles. Alternative applications and private services also are allowed so as to lower management expenses and to market VANET exploitation. To effectively established VANET, security is one amongst key challenges that has got to be tackled. Another vital concern is measurability could be a serious issue for a network designer a way to maintain stable communication and services in VANET. Extraordinarily dynamic atmosphere of VANETs looks it troublesome. This paper introduced an automatic reliability management method for VANETs that uses machine learning to categories nodes as malicious. Cluster creation is one effective method for the measurability drawback. Here conjointly given associate entropy-based WCA (EWCA) cluster maintained method which may handle the steady of the automobile network.
Security Issues in Biomedical Wireless Sensor Networks Applications: A SurveyIJARTES
Abstract The use of wireless sensor networks in healthcare
applications is growing in a fast pace. Numerous applications
such as heart rate monitor, blood pressure monitor and
endoscopic capsule are already in use. To address the growing
use of sensor technology in this area, a new field known as
wireless body area networks has emerged. As most devices
and their applications are wireless in nature, security and
privacy concerns are among major areas of concern. Body
area networks can collect information about an individual’s
health, fitness and energy expenditure. Comprising body
sensors that communicate wirelessly with the patients
control device for monitoring and external communication.
This paper provides the challenges of using the wireless
sensor network in biomedical field and how to solve most of
these issues. To analyze the different security strategies in
Wireless Sensor Networks and propose this system to give
highest quality medical care with full security in their
reliability
Study and Analysis on Heat Treatment Process and Microstructure of Low Carbon...IJARTES
The document summarizes a study on the heat treatment process and microstructure of low carbon steel. It describes various heat treatment processes like annealing, normalizing, hardening, austempering, and tempering. Experimental details are provided on specimen preparation, heat treatment processes, hardness and tensile testing, and microstructure analysis. Results show that hardness decreases and ductility increases with higher tempering temperature and longer time. Austempering provides an optimal combination of properties. Microstructure analysis found that martensite fraction increases with higher annealing temperature. In conclusion, mechanical properties vary by heat treatment process, and austempering yields the best balance of properties for many applications.
Power Generation from Speed Breaker Using Crank ShaftIJARTES
Power Generation from Speed Breaker Using
Crank Shaft
This paper attempts to show how energy can
tapped and used at a commonly used system the load speed
breaker. As the demand of electric power is increasing day-byday
for the working of various appliances. Producing
electricity from various sources is needed like from a speed
breaker is a new concept that is an undergoing research. The
number of vehicles on road is increase rapidly and if we
convert some of the kinetic energy of this vehicle into
rotational motion of roller then we can produce considerable
amount of electricity. The demand of the hour is to have some
source of green energy which can be produce with less (or) no
harmful by-products. Our project is to develop an alternative
green source of energy by moving vehicles on the road ways
Alhena propose des stratégies de marketing d'influence.
Utilisation de la blogosphère, création de notoriété et visibilité. Etudes sémantiques, RP 2.0
Etudes, audits.
IRJET- 3D Reconstruction of Surface Topography using Ultrasonic TransducerIRJET Journal
This document describes a study that aims to reconstruct 3D images of surface topography using an ultrasonic transducer. The transducer scans target objects by firing ultrasonic pulses and receiving reflected signals. Digital signal processing is used to analyze the reflected waveforms and generate graphs representing the objects' surface areas. MATLAB and LabVIEW are used to perform computations and render 3D images of the targets' actual shapes from the collected data. The methodology involves using an ultrasonic transducer, oscilloscope, and pulse receiver to scan target objects in steps and reconstruct their surface topographies based on variations in reflected signal amplitudes. The targets tested are an adjustable wrench and a 5 rupee coin.
Development of depth map from stereo images using sum of absolute differences...nooriasukmaningtyas
This article proposes a framework for the depth map reconstruction using stereo images. Fundamentally, this map provides an important information which commonly used in essential applications such as autonomous vehicle navigation, drone’s navigation and 3D surface reconstruction. To develop an accurate depth map, the framework must be robust against the challenging regions of low texture, plain color and repetitive pattern on the input stereo image. The development of this map requires several stages which starts with matching cost calculation, cost aggregation, optimization and refinement stage. Hence, this work develops a framework with sum of absolute difference (SAD) and the combination of two edge preserving filters to increase the robustness against the challenging regions. The SAD convolves using block matching technique to increase the efficiency of matching process on the low texture and plain color regions. Moreover, two edge preserving filters will increase the accuracy on the repetitive pattern region. The results show that the proposed method is accurate and capable to work with the challenging regions. The results are provided by the Middlebury standard dataset. The framework is also efficiently and can be applied on the 3D surface reconstruction. Moreover, this work is greatly competitive with previously available methods.
Surface generation from point cloud.pdfssuserd3982b1
This document summarizes research on generating 3D surface models from point clouds acquired using a vision-based laser scanning sensor. It discusses using adaptive filters to reduce noise in the point clouds and generating triangular meshes from the point clouds to create an initial surface model. It then covers using NURBS (Non-Uniform Rational B-Splines) to optimize the surface model for accuracy by fitting parametric surfaces to the triangular mesh. The goal is to develop accurate 3D surface models of turbine blades for robotic welding applications to repair flaws.
An efficient image segmentation approach through enhanced watershed algorithmAlexander Decker
This document proposes an efficient image segmentation approach combining an enhanced watershed algorithm and color histogram analysis. The watershed algorithm is applied to preprocessed images after merging the results with an enhanced edge detection. Over-segmentation issues are addressed through a post-processing step applying color histogram analysis to each segmented region, improving overall performance. The document provides background on image segmentation techniques, reviews related work applying watershed algorithms, and discusses challenges like over-segmentation that watershed approaches can face.
EXTENDED HYBRID REGION GROWING SEGMENTATION OF POINT CLOUDS WITH DIFFERENT RE...cscpconf
In the recent years, 3D city reconstruction is one of the active researches in the field of photogrammetry. The goal of this work is to improve and extend region growing based
segmentation in the X-Y-Z image in the form of 3D structured data with combination of spectral information of RGB and grayscale image to extract building roofs, streets and vegetation. In order to process 3D point clouds, hybrid segmentation is carried out in both object space and
image space. Our experiments on two case studies verify that updating plane parameters and robust least squares plane fitting improves the results of building extraction especially in case of low accurate point clouds. In addition, region growing in image space has been derived to the fact that grayscale image is more flexible than RGB image and results in more realistic
building roofs.
A Review on Deformation Measurement from Speckle Patterns using Digital Image...IRJET Journal
This document reviews digital image correlation (DIC) for deformation measurement using speckle patterns. DIC is a non-contact optical method that uses digital images of a speckle pattern on a surface before and after deformation. By comparing the speckle patterns in the images, DIC can determine displacement and strain fields with high accuracy. The document discusses speckle pattern types, the DIC process, related works that have improved DIC methods, and applications of DIC such as for high-temperature testing. DIC provides full-field measurements and greater accuracy compared to conventional contact methods.
AUTOMATIC IDENTIFICATION OF CLOUD COVER REGIONS USING SURF ijcseit
Weather forecasting has become an indispensable application to predict the state of the atmosphere for a
future time based on cloud cover identification. But it generally needs the experience of a well-trained
meteorologist. In this paper, a novel method is proposed for automatic cloud cover estimation, typical to
Indian Territory Speeded Up Robust Feature Transform(SURF) is applied on the satellite images to obtain
the affine corrected images. The extracted cloud regions from the affine corrected images based on Otsu
threshold are superimposed on the artistic grids representing latitude and longitude over India. The
segmented cloud and grid composition drive a look up table mechanism to identify the cloud cover regions.
Owing to its simplicity, the proposed method processes the test images faster and provides accurate
segmentation for cloud cover regions.
Stereo matching based on absolute differences for multiple objects detectionTELKOMNIKA JOURNAL
This article presents a new algorithm for object detection using stereo camera system. The problem to get an accurate object detion using stereo camera is the imprecise of matching process between two scenes with the same viewpoint. Hence, this article aims to reduce the incorrect matching pixel with four stages. This new algorithm is the combination of continuous process of matching cost computation, aggregation, optimization and filtering. The first stage is matching cost computation to acquire preliminary result using an absolute differences method. Then the second stage known as aggregation step uses a guided filter with fixed window support size. After that, the optimization stage uses winner-takes-all (WTA) approach which selects the smallest matching differences value and normalized it to the disparity level. The last stage in the framework uses a bilateral filter. It is effectively further decrease the error on the disparity map which contains information of object detection and locations. The proposed work produces low errors (i.e., 12.11% and 14.01% nonocc and all errors) based on the KITTI dataset and capable to perform much better compared with before the proposed framework and competitive with some newly available methods.
Gravity Map Production Using General Regression Neural NetworkIRJET Journal
This document discusses using an artificial neural network (ANN) called a General Regression Neural Network (GRNN) to produce a gravity map of Khartoum City, Sudan from satellite imagery. 301 training patterns were generated from a satellite image and existing gravity map of the area. The GRNN model was trained on these patterns and tested on 75 additional patterns, with the output results subjected to statistical analysis. The GRNN accurately predicted the gravity patterns, indicating ANNs are able to produce gravity maps from satellite images to help identify locations for oil exploration.
Stereo matching algorithm using census transform and segment tree for depth e...TELKOMNIKA JOURNAL
This article proposes an algorithm for stereo matching corresponding process that will be used in many applications such as augmented reality, autonomous vehicle navigation and surface reconstruction. Basically, the proposed framework in this article is developed through a series of functions. The final result from this framework is disparity map which this map has the information of depth estimation. Fundamentally, the framework input is the stereo image which represents left and right images respectively. The proposed algorithm in this article has four steps in total, which starts with the matching cost computation using census transform, cost aggregation utilizes segment-tree, optimization using winner-takes-all (WTA) strategy, and post-processing stage uses weighted median filter. Based on the experimental results from the standard benchmarking evaluation system from the Middlebury, the disparity map results produce an average low noise error at 9.68% for nonocc error and 18.9% for all error attributes. On average, it performs far better and very competitive with other available methods from the benchmark system.
Fault diagnosis using genetic algorithms and principal curveseSAT Journals
Abstract Several applications of nonlinear principal component analysis (NPCA) have appeared recently in process monitoring and fault diagnosis. In this paper a new approach is proposed for fault detection based on principal curves and genetic algorithms. The principal curve is a generation of linear principal component (PCA) introduced by Hastie as a parametric curve passes satisfactorily through the middle of data. The existing principal curves algorithms employ the first component of the data as an initial estimation of principal curve. However the dependence on initial line leads to a lack of flexibility and the final curve is only satisfactory for specific problems. In this paper we extend this work in two ways. First, we propose a new method based on genetic algorithms to find the principal curve. Here, lines are fitted and connected to form polygonal lines (PL). Second, potential application of principal curves is discussed. An example is used to illustrate fault diagnosis of nonlinear process using the proposed approach. Index Terms: Principal curve, Genetic Algorithm, Nonlinear principal component analysis, Fault detection.
Corner distance matching Technique is proposed, which find the interest of
points of every rived pieces. Any corner detector can be used window for finding where the
intensity value is change most and mark that point as a corner. Points of interest are found
and then for matching them distance between them is calculated. Distance can be matched
and based on that it can be found that which two edges are of piece are matching.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
Review paper on segmentation methods for multiobject feature extractioneSAT Journals
Abstract Feature extraction and representation plays a vital role in multimedia processing. It is still a challenge in computer vision system to extract ideal features that represents intrinsic characteristics of an image. Multiobject feature extraction system means a system that can extract features and locations of multiple objects in an image. In this paper we have discuss various methods to extract location and features of multiple objects and describe a system that can extract locations and features of multiple objects in an image by implementing an algorithm as hardware logic on a field-programmable gate array-based platform. There are many multiobject extraction methods which can be use for image segmentation based on motion, color intensity and texture. By calculating zeroth and first order moments of objects it is possible to obtain locations and sizes of multiple objects in an image. Keywords: multiobject extraction, image segmentation
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Nicholas Chagnon constructed an interferometer to measure residual stress in 3D woven composites. He assembled the optical setup, programmed image capture software, and developed processing code. Testing revealed issues with phase map decorrelation near drilled holes. Future work includes optimizing strain measurement and characterizing residual stress in selected composite regions by drilling holes and capturing images. The interferometer will enable engineers to evaluate process modifications for reducing residual stresses.
The document proposes a novel algorithm called Intermediate Skeletal Model (ISM) for modeling unsegmented cloud point data. ISM grows a sphere recursively over data points to connect feature points and build a skeletal model. It is modified to use an adaptive radius for the sphere to better capture features. With a fixed radius, features may be lost, but an adaptive sphere can take on different shapes like a disc or ellipsoid to segment the data during modeling based on local curvature. This approach models and segments simultaneously without requiring separate steps.
Unsupervised Building Extraction from High Resolution Satellite Images Irresp...CSCJournals
The document discusses an unsupervised method for extracting buildings from high resolution satellite images regardless of rooftop structures. The method first calculates NDVI and chromaticity ratios to segment vegetation and shadows. Rooftops and roads are then detected and eliminated. Principal component analysis and area analysis are performed to accurately extract buildings. The algorithm aims to eliminate inhomogeneities caused by varying building hierarchies by focusing on eliminating non-building regions rather than detecting building regions of interest. The methodology is tested on Quickbird satellite imagery and results indicate it can extract buildings in complex environments irrespective of rooftop shape.
Numerical simulation of wind flow over complex terrain (yangon city)Zin Soul
This document describes a numerical simulation of wind flow over the complex terrain of Yangon City, Myanmar. The study uses the OpenFOAM computational fluid dynamics (CFD) toolbox to model wind flow for different directions using the k-epsilon turbulence model. Vertical wind speed profiles are simulated for various locations in Yangon and compared to measured field data. The results show the influence of Yangon's topography on wind directions. Accounting for more wind direction sectors could improve the vertical wind profile predictions. This research aims to help engineers better understand wind conditions for building design in Yangon.
Integration of Other Software Components with the Agricultural Expert Systems...IJARTES
Expert System is a rapidly growing technology in
the field of Artificial Intelligence. It is a computer program
which captures the knowledge of a human expert on a given
problem, and uses this knowledge to solve problems in a
fashion similar to the expert. The system can assist the expert
during problem-solving, or act in the place of the expert in
those situations where the expertise is lacking. Expert systems
have been developed in such diverse areas as agriculture,
science, engineering, business, and medicine. In these areas,
they have increased the quality, efficiency, and competitive
leverage of the organizations employing the technology. This
paper highlights the major characteristics of expert systems,
reviews several systems developed for application in the area
of agriculture and an overview about the integration of other
software components with the agricultural expert systems.
Short term Multi Chain Hydrothermal Scheduling Using Modified Gravitational S...IJARTES
This paper proposes the modified Gravitational
search algorithm (GSA) to solve short term multi chain
hydrothermal scheduling problem while satisfying all
operational and physical constraints. The effect of the valve
point loading has been considered. Gravitational search
algorithm is based on the Newton’s law of gravitation. All
objects attract each other and global movement is towards
the heavier masses .However GSA has certain randomness
in search direction resulting in the weak local search ability.
In modified GSA, a time varying maximum velocity equation
is used which controls the exploration and improves the
convergence rate which strengthens its local search ability
and the quality of the hydrothermal solution.
Investigation of Heat Dissipation in Petrol Engine Cylinder during Explosion ...IJARTES
The current work determines the rate of heat flow
from an engine cylinder. The heat addition during the heat
addition stage or during explosion is determined by using the
classical equations. The heat dissipation from the cylinder is
enhanced by the fins provided around the cylinder. The results
which are obtained are validated with the finite element
analysis software ANSYS APDL. A study is conducted by
considering various materials to obtain optimum material
selection to enhance the better flow of heat from the system.
Integrated Air Conditioning Unit for AutomobilesIJARTES
This document summarizes several research papers on using waste heat from vehicle exhaust to power an absorption refrigeration system for automotive air conditioning. The key points are:
1) Absorption refrigeration systems can utilize low-grade waste heat from exhaust to run the air conditioning, unlike vapor compression which increases fuel use. Measured COP of a proposed system is 0.85 to 1.04.
2) A study designed a generator heat exchanger to transfer exhaust heat to the refrigerant in the generator. Experimental results showed exhaust is a viable alternative heating source.
3) Other studies analyzed using exhaust heat to power ammonia-water and lithium bromide absorption systems for vehicle air conditioning. Re
Influence of Process Parameters on AA7075 in TIG WeldingIJARTES
Influence of Process Parameters on AA7075 in
TIG Welding
Aluminium Alloy is containing high strength,
light weight and good Corrosion resistance. Then Gas
tungsten arc welding (GTAW) is an important joining
method for high strength aluminium alloys using
applications in transport applications like that marine,
aerospace, bicycle components, marine Engine components,
External throw away tanks for military aircrafts and other
industries. Gas tungsten arc welding have been used to
investigate the Weldability of high strength aluminium
alloys. Some important GTAW process parameters and their
effects on weld quality are discussed. Mechanical properties
of welds such as tensile strength and hardness properties are
discussed. The aim of the report is to investigation in GTAW
of high strength aluminium alloy 7075 and to provide a basis
for follow-on research.
Ijartes v2-i1-001Evaluation of Changeability Indicator in Component Based Sof...IJARTES
The maintaining of software system is a major
cost concern. The maintaining of a software system depends
on how the changes made to it. The maintainability of a system
depending on the folw of software, its design pattern and
CBSS. In Maintainability phase of a sotware system there are
4 parts, like analyzing, testing, stability, and changes made to
it. In some side areas, these systems emerged very rapidly.
There are many companies which purchase software instead
of developing it .These companies do not have any interst in
the testing of the system but wants to like smoothness in the
flow of the system during changes.
Changeability is one of the characteristics of maintainability.
Software changeability is associated with refactoring which
makes code simpler and easier to maintain (enable all
programmers to improve their code).Factors that affect
changeability include coupling between the modules, lack of
code comments, naming of functions and variables.
Basically,”changeabilty” is the ability of a product or software
to be able to change the structure of the program. It is the rate
the product allows the modification to its components.
In this paper changeability based cost estimation is done.
Initially we take four components; these components are
evaluated based on the coupling, cohesion and Interface
metrix. Next some changes are made to the existing
components and than again these components are evaluated.
Now, on the basis of these two evaluations some conclusion is
made for changeability cost.
Web Personalization Using Usage Based Clustering
In today’s internet environment it is more difficult to
access the relevant information from the web. Because
www is a vast data warehouse of web pages and links .On
internet huge amount of information is available which
are approximately 1 millions of pages are added day to
day. To get the “right” information from such warehouse
to the user and to avoid website exploration web
personalization get needed. It is the life blood of web
usages mining and e-learning process to improve the
system and its design as per the user’s interest. It acts as
a tool to avoid the content over loading on websites for
effective web navigation. Here we present web
personalization which introduces web mining that is
application of a data mining.
This document summarizes research on enhancing the DSR routing protocol to prevent distributed denial of service (DDoS) attacks in mobile ad hoc networks (MANETs). It discusses how DDoS attacks work, the challenges they present for MANETs due to their dynamic nature, and existing research on DDoS attack detection and prevention. The document reviews literature on analyzing DDoS attack behaviors and properties, characterizing attack traffic patterns, and using statistical analysis and neural networks to identify attacks. The goal of the research is to develop an enhanced DSR protocol that can detect and mitigate DDoS attacks in MANETs more effectively than previous approaches.
This document analyzes power density in LTE femtocells. It discusses how femtocells can be deployed to improve coverage in areas where LTE networks have little to no coverage, such as inside buildings. The document describes an experiment conducted using NS-3 simulation software to analyze how transmitted power and power consumption are affected by increasing the number of femtocells. The results show that transmitted power increases linearly with additional femtocells up to a threshold, but rises more sharply above the threshold, while power consumption increases linearly with no sharp rises.
This document summarizes research on recognizing handwritten characters in the Odia language. It discusses two main approaches to Odia character recognition: template matching and feature extraction. The document also reviews several papers on Odia handwritten character recognition, describing the different techniques used, such as neural networks, genetic algorithms, and rule-based methods. Overall, the document surveys existing work on developing systems for Odia optical character recognition (OCR) and handwritten character recognition.
This document presents the results of an experimental study on the effect of cutting speed on tool wear of uncoated and coated cemented carbide tools during dry turning of AISI 316 austenitic stainless steel. Turning tests were conducted at three cutting speeds (100, 150, and 200 m/min) with depth of cut and feed rate kept constant. Tool wear was measured and tool life was compared between uncoated and TiN-TiCN-Al2O3-ZrCN multilayer coated inserts. The results showed that cutting speed significantly affected tool wear and tool life decreased with increasing speed. The multilayer coated insert demonstrated superior wear resistance and 25-40% longer tool life compared to the uncoated insert
Abstract
Part of speech tagging plays an important role in developing natural language processing software. Part of speech tagging means assigning part of speech tag to each word of the sentence. The part of speech tagger takes a sentence as input and it assigns respective/appropriate part of speech tag to each word of that sentence. In this article I surveys the different work have done about odia POS tagging.
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Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.