This document summarizes a research paper that proposes using Zernike moments and steerable Gaussian filters for effective image retrieval based on color, texture, and shape features. It describes extracting dominant colors from images using dynamic color quantization and clustering. Texture features are represented using steerable filter decomposition. Shape features are described using pseudo-Zernike moments. The proposed method combines these color, texture, and shape features to generate a robust feature set for image retrieval that provides better retrieval accuracy than other methods.
This document summarizes a research paper on color image segmentation using k-means clustering. It discusses how k-means clustering can be used to group color image pixels into a set number of classes without using training data. The clustering groups similar color pixels to obtain segmentation. This avoids calculating features for every pixel and provides efficient segmentation based on color similarity. The document outlines the k-means clustering process used and how it segments an image into distinct colored regions to extract important objects.
The document discusses appearance-based face recognition using PCA and LDA algorithms. It summarizes the steps of each algorithm and compares their performance on preprocessed face images from the Faces94 database. Image preprocessing techniques like grayscale conversion and modified histogram equalization are applied before PCA and LDA to enhance image quality and improve recognition rates. The paper aims to study PCA and LDA with respect to recognition accuracy and dimensionality.
A Novel Feature Extraction Scheme for Medical X-Ray ImagesIJERA Editor
X-ray images are gray scale images with almost the same textural characteristic. Conventional texture or color
features cannot be used for appropriate categorization in medical x-ray image archives. This paper presents a
novel combination of methods like GLCM, LBP and HOG for extracting distinctive invariant features from Xray
images belonging to IRMA (Image Retrieval in Medical applications) database that can be used to perform
reliable matching between different views of an object or scene. GLCM represents the distributions of the
intensities and the information about relative positions of neighboring pixels of an image. The LBP features are
invariant to image scale and rotation, change in 3D viewpoint, addition of noise, and change in illumination A
HOG feature vector represents local shape of an object, having edge information at plural cells. These features
have been exploited in different algorithms for automatic classification of medical X-ray images. Excellent
experimental results obtained in true problems of rotation invariance, particular rotation angle, demonstrate that
good discrimination can be achieved with the occurrence statistics of simple rotation invariant local binary
patterns.
Hierarchical Approach for Total Variation Digital Image InpaintingIJCSEA Journal
The art of recovering an image from damage in an undetectable form is known as inpainting. The manual work of inpainting is most often a very time consum ing process. Due to digitalization of this technique, it is automatic and faster. In this paper, after the user selects the regions to be reconstructed, the algorithm automatically reconstruct the lost regions with the help of the information surrounding them. The existing methods perform very well when the region to be reconstructed is very small, but fails in proper reconstruction as the area increases. This paper describes a Hierarchical method by which the area to be inpainted is reduced in multiple levels and Total Variation(TV) method is used to inpaint in each level. This algorithm gives better performance when compared with other existing algorithms such as nearest neighbor interpolation, Inpainting through Blurring and Sobolev Inpainting.
Improving Performance of Texture Based Face Recognition Systems by Segmenting...IDES Editor
Textures play an important role in recognition of
images. This paper investigates the efficiency of performance
of three texture based feature extraction methods for face
recognition. The methods for comparative study are Grey Level
Co_occurence Matrix (GLCM), Local Binary Pattern (LBP)
and Elliptical Local Binary Template (ELBT). Experiments
were conducted on a facial expression database, Japanese
Female Facial Expression (JAFFE). With all facial expressions
LBP with 16 vicinity pixels is found to be a better face
recognition method among the tested methods. Experimental
results show that classification based on segmenting face
region improves recognition accuracy.
This document presents a new framework for color image segmentation using a combination of watershed and seed region growing algorithms. It begins with an introduction to image segmentation and discusses challenges with traditional gray-scale methods when applied to color images. The document then proposes a method using automatic seed region growing integrated with the watershed algorithm. Experimental results on an input image are shown to demonstrate the segmentation process and output images. The framework is concluded to improve upon traditional gray-scale methods for segmenting the richer information in color images.
OBJECT SEGMENTATION USING MULTISCALE MORPHOLOGICAL OPERATIONSijcseit
Object segmentation plays an important role in human visual perception, medical image processing and content based image retrieval. It provides information for recognition and interpretation. This paper uses mathematical morphology for image segmentation. Object segmentation is difficult because one usually does not know a priori what type of object exists in an image, how many different shapes are there and what regions the image has. To carryout discrimination and segmentation several innovative segmentation methods, based on morphology are proposed. The present study proposes segmentation method based on multiscale morphological reconstructions. Various sizes of structuring elements have been used to segment simple and complex shapes. It enhances local boundaries that may lead to improve segmentation accuracy.The method is tested on various datasets and results shows that it can be used for both interactive and automatic segmentation.
This document presents a method for interactive image segmentation using constrained active contours. It begins with an overview of existing interactive segmentation techniques, including boundary-based methods like active contours/snakes and region-based methods like random walks and graph cuts. The proposed method initializes a contour using region-based segmentation then refines it using a convex active contour model that incorporates both regional information from seed pixels and boundary smoothness. This allows the contour to globally evolve to object boundaries while handling topology changes.
This document summarizes a research paper on color image segmentation using k-means clustering. It discusses how k-means clustering can be used to group color image pixels into a set number of classes without using training data. The clustering groups similar color pixels to obtain segmentation. This avoids calculating features for every pixel and provides efficient segmentation based on color similarity. The document outlines the k-means clustering process used and how it segments an image into distinct colored regions to extract important objects.
The document discusses appearance-based face recognition using PCA and LDA algorithms. It summarizes the steps of each algorithm and compares their performance on preprocessed face images from the Faces94 database. Image preprocessing techniques like grayscale conversion and modified histogram equalization are applied before PCA and LDA to enhance image quality and improve recognition rates. The paper aims to study PCA and LDA with respect to recognition accuracy and dimensionality.
A Novel Feature Extraction Scheme for Medical X-Ray ImagesIJERA Editor
X-ray images are gray scale images with almost the same textural characteristic. Conventional texture or color
features cannot be used for appropriate categorization in medical x-ray image archives. This paper presents a
novel combination of methods like GLCM, LBP and HOG for extracting distinctive invariant features from Xray
images belonging to IRMA (Image Retrieval in Medical applications) database that can be used to perform
reliable matching between different views of an object or scene. GLCM represents the distributions of the
intensities and the information about relative positions of neighboring pixels of an image. The LBP features are
invariant to image scale and rotation, change in 3D viewpoint, addition of noise, and change in illumination A
HOG feature vector represents local shape of an object, having edge information at plural cells. These features
have been exploited in different algorithms for automatic classification of medical X-ray images. Excellent
experimental results obtained in true problems of rotation invariance, particular rotation angle, demonstrate that
good discrimination can be achieved with the occurrence statistics of simple rotation invariant local binary
patterns.
Hierarchical Approach for Total Variation Digital Image InpaintingIJCSEA Journal
The art of recovering an image from damage in an undetectable form is known as inpainting. The manual work of inpainting is most often a very time consum ing process. Due to digitalization of this technique, it is automatic and faster. In this paper, after the user selects the regions to be reconstructed, the algorithm automatically reconstruct the lost regions with the help of the information surrounding them. The existing methods perform very well when the region to be reconstructed is very small, but fails in proper reconstruction as the area increases. This paper describes a Hierarchical method by which the area to be inpainted is reduced in multiple levels and Total Variation(TV) method is used to inpaint in each level. This algorithm gives better performance when compared with other existing algorithms such as nearest neighbor interpolation, Inpainting through Blurring and Sobolev Inpainting.
Improving Performance of Texture Based Face Recognition Systems by Segmenting...IDES Editor
Textures play an important role in recognition of
images. This paper investigates the efficiency of performance
of three texture based feature extraction methods for face
recognition. The methods for comparative study are Grey Level
Co_occurence Matrix (GLCM), Local Binary Pattern (LBP)
and Elliptical Local Binary Template (ELBT). Experiments
were conducted on a facial expression database, Japanese
Female Facial Expression (JAFFE). With all facial expressions
LBP with 16 vicinity pixels is found to be a better face
recognition method among the tested methods. Experimental
results show that classification based on segmenting face
region improves recognition accuracy.
This document presents a new framework for color image segmentation using a combination of watershed and seed region growing algorithms. It begins with an introduction to image segmentation and discusses challenges with traditional gray-scale methods when applied to color images. The document then proposes a method using automatic seed region growing integrated with the watershed algorithm. Experimental results on an input image are shown to demonstrate the segmentation process and output images. The framework is concluded to improve upon traditional gray-scale methods for segmenting the richer information in color images.
OBJECT SEGMENTATION USING MULTISCALE MORPHOLOGICAL OPERATIONSijcseit
Object segmentation plays an important role in human visual perception, medical image processing and content based image retrieval. It provides information for recognition and interpretation. This paper uses mathematical morphology for image segmentation. Object segmentation is difficult because one usually does not know a priori what type of object exists in an image, how many different shapes are there and what regions the image has. To carryout discrimination and segmentation several innovative segmentation methods, based on morphology are proposed. The present study proposes segmentation method based on multiscale morphological reconstructions. Various sizes of structuring elements have been used to segment simple and complex shapes. It enhances local boundaries that may lead to improve segmentation accuracy.The method is tested on various datasets and results shows that it can be used for both interactive and automatic segmentation.
This document presents a method for interactive image segmentation using constrained active contours. It begins with an overview of existing interactive segmentation techniques, including boundary-based methods like active contours/snakes and region-based methods like random walks and graph cuts. The proposed method initializes a contour using region-based segmentation then refines it using a convex active contour model that incorporates both regional information from seed pixels and boundary smoothness. This allows the contour to globally evolve to object boundaries while handling topology changes.
The development of multimedia system technology in Content based Image Retrieval (CBIR) System is
one in every of the outstanding area to retrieve the images from an oversized collection of database. The feature
vectors of the query image are compared with feature vectors of the database images to get matching images.It is
much observed that anyone algorithm isn't beneficial in extracting all differing kinds of natural images. Thus an
intensive analysis of certain color, texture and shape extraction techniques are allotted to spot an efficient CBIR
technique that suits for a selected sort of images. The Extraction of an image includes feature description and
feature extraction. During this paper, we tend to projected Color Layout Descriptor (CLD), grey Level Co-
Occurrences Matrix (GLCM), Marker-Controlled Watershed Segmentation feature extraction technique that
extract the matching image based on the similarity of Color, Texture and shape within the database. For
performance analysis, the image retrieval timing results of the projected technique is calculated and compared
with every of the individual feature.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
This document proposes a new method for segmenting outdoor images called Color Cluster Elimination (CCE) which utilizes color clustering and texture analysis. CCE performs color clustering in a multi-resolution pyramid to gradually eliminate larger color clusters, preventing them from dominating segmentation and allowing smaller clusters to emerge more clearly. It then examines regions for adjacent homochromatic objects with different textures, introducing Texture Sewn Response (TSR) to indicate texture strength across resolutions/directions. The method is evaluated on the BSDS500 dataset against other metrics, demonstrating satisfactory performance for outdoor scene segmentation.
A survey on feature descriptors for texture image classificationIRJET Journal
This document discusses various feature descriptors that can be used for texture image classification. It provides an overview of 8 different feature descriptors that have been proposed in recent research: local binary patterns (LBP), dominant local binary patterns (DLBP), completed local binary patterns (CLBP), Weber local descriptor (WLD), local binary count (LBC), discriminant face descriptor (DFD), local vector quantization pattern (LVQP), and dense micro-block difference (DMD). For each descriptor, it briefly explains the approach and compares the methods. The goal of the descriptors is to effectively capture textural features while addressing challenges like rotation, illumination changes, and noise.
An implementation of novel genetic based clustering algorithm for color image...TELKOMNIKA JOURNAL
The color image segmentation is one of most crucial application in image processing. It can apply to medical image segmentation for a brain tumor and skin cancer detection or color object detection on CCTV traffic video image segmentation and also for face recognition, fingerprint recognition etc. The color image segmentation has faced the problem of multidimensionality. The color image is considered in five-dimensional problems, three dimensions in color (RGB) and two dimensions in geometry (luminosity layer and chromaticity layer). In this paper the, L*a*b color space conversion has been used to reduce the one dimensional and geometrically it converts in the array hence the further one dimension has been reduced. The a*b space is clustered using genetic algorithm process, which minimizes the overall distance of the cluster, which is randomly placed at the start of the segmentation process. The segmentation results of this method give clear segments based on the different color and it can be applied to any application.
Performance Evaluation of 2D Adaptive Bilateral Filter For Removal of Noise F...CSCJournals
In this paper, we present the performance analysis of adaptive bilateral filter by pixel to noise ratio and mean square errors. It was evaluate changing the parameters of the adaptive filter half width values and standard deviations. In adaptive bilateral filter, the edge slope is enhanced by transforming the histogram via a range filter with adaptive offset and width. The variance of range filter can also be adaptive. The filter is applied to improve the sharpens of a gray level and color image by increasing the slope of the edges without producing overshoot or undershoots. The related graphs were plotted and the best filter parameters are obtained.
PDE BASED FEATURES FOR TEXTURE ANALYSIS USING WAVELET TRANSFORMIJCI JOURNAL
This document summarizes a research paper that proposes a novel method for texture analysis using wavelet transforms and partial differential equations (PDEs). The method involves applying wavelet transforms to images to obtain directional information. Anisotropic diffusion, a PDE technique, is then used on the directional information to compute a texture approximation. Various statistical features are extracted from the texture approximation. Linear discriminant analysis enhances class separability of the features before classification using k-nearest neighbors. The method is evaluated on the Brodatz texture dataset and results show it achieves better classification accuracy than other methods while having lower computational cost.
Face skin color based recognition using local spectral and gray scale featureseSAT Journals
Abstract Human face conveys more information about identity of person. Human face recognition is one of the most challenging problem and it can be used in many applications at different security places in airports, defense and banking sectors etc.In this work used colored features obtained from color segmentation because in real time scenario color provides the more information than gray scale image but it has a drawback. To overcome this drawback gray scale feature extracted from co-occurrence matrix of an image and for efficient face recognition of human Face under different illumination conditions spectral features can be extracted from face texture. These three feature vectors concatenated into a single feature vector and applied Lenc-Kral matching technique to measure similarity between the database and query image, the similarity is high then face is recognized. Keywords: Face recognition, illumination condition, local texture features, color segmentation.
Developing 3D Viewing Model from 2D Stereo Pair with its Occlusion RatioCSCJournals
We intend to make a 3D model using a stereo pair of images by using a novel method of local matching in pixel domain for calculating horizontal disparities. We also find the occlusion ratio using the stereo pair followed by the use of The Edge Detection and Image SegmentatiON (EDISON) system, on one the images, which provides a complete toolbox for discontinuity preserving filtering, segmentation and edge detection. Instead of assigning a disparity value to each pixel, a disparity plane is assigned to each segment. We then warp the segment disparities to the original image to get our final 3D viewing Model.
Performance analysis is basis on color based image retrieval techniqueIAEME Publication
This document discusses performance analysis of color-based image retrieval techniques. It proposes using foreground color extraction and K-nearest neighbor classification to retrieve similar images based on foreground objects. The key steps are segmenting images to separate foreground from background, categorizing foreground colors, and matching query images to images in a database based on dominant foreground color using K-nearest neighbor. An experimental analysis on a celebrity image dataset found the proposed technique achieved higher precision and recall than existing background-focused methods.
DEVELOPMENT OF AN ALPHABETIC CHARACTER RECOGNITION SYSTEM USING MATLAB FOR BA...Mohammad Liton Hossain
Character recognition technique, associates a symbolic identity with the image of the character, is an important area in pattern recognition and image processing. The principal idea here is to convert raw images (scanned from document, typed, pictured etcetera) into editable text like html, doc, txt or other formats. There is a very limited number of Bangla Character recognition system, if available they can’t recognize the whole alphabet set. Motivated by this, this paper demonstrates a MATLAB based Character Recognition system from printed Bangla writings. It can also compare the characters of one image file to another one. Processing steps here involved binarization, noise removal and segmentation in various levels, features extraction and recognition.
This document presents a method for recovering text from degraded document images. It involves several steps:
1. Constructing a contrast image to distinguish text from background by calculating local image contrast and gradient.
2. Detecting text stroke edges in the contrast image using Otsu's thresholding and Canny edge detection.
3. Estimating a local threshold for binarization based on mean and standard deviation of detected edge pixel intensities.
4. Converting the image to binary format above the threshold.
5. Post-processing to remove unwanted background pixels.
The method is tested on several degraded documents and shows good performance in recovering text contents in a short time period. It provides a
Automated Colorization of Grayscale Images Using Texture DescriptorsIDES Editor
The document proposes a novel automated process called ACTD for colorizing grayscale images using texture descriptors without human intervention. It analyzes sample color images to extract coherent texture regions, then uses Gabor filtering for texture-based segmentation. Texture descriptors and color information are computed and stored for each region. These are then used to colorize a new grayscale image based on texture matching. The method combines techniques such as Gabor filtering, fuzzy C-means clustering with a new "Gki factor" for noise tolerance, and content-based image retrieval of texture descriptors. Preliminary results found the approach viable but improvements were needed for scale and rotation invariance.
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.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
SYMMETRICAL WEIGHTED SUBSPACE HOLISTIC APPROACH FOR EXPRESSION RECOGNITIONijcsit
This document proposes a new method called Symmetrical Weighted 2D Principal Component Analysis (SW2DPCA) for facial expression recognition. SW2DPCA aims to reduce the dimensionality of the feature space extracted from face images using Gabor filters, while removing redundant information. It does this by decomposing the training images into odd and even symmetrical components, and applying weighted PCA to equalize the variance of principal components. The method is tested on the JAFFE database, achieving a recognition accuracy of 95.24% - higher than the 2DPCA baseline method.
Performance analysis is basis on color based image retrieval techniqueIAEME Publication
This document discusses performance analysis of color-based image retrieval techniques. It proposes using foreground color extraction and K-nearest neighbor classification to retrieve similar images based on foreground objects. The key steps are segmenting images to separate foreground from background, categorizing foreground colors, and matching query images to images in a database based on dominant foreground color using K-nearest neighbor. An experimental analysis on a celebrity image dataset found the proposed technique achieved higher precision and recall than existing background-focused methods.
A comparative study on content based image retrieval methodsIJLT EMAS
Content-based image retrieval (CBIR) is a method of
finding images from a huge image database according to persons’
interests. Content-based here means that the search involves
analysis the actual content present in the image. As database of
images is growing daybyday, researchers/scholars are searching
for better techniques for retrieval of images maintaining good
efficiency. This paper presents the visual features and various
ways for image retrieval from the huge image database.
Recognition of basic kannada characters in scene images using euclidean disIAEME Publication
The document describes a proposed methodology for recognizing basic Kannada characters in scene images using zone-wise horizontal and vertical profile-based features and an Euclidean distance classifier. The methodology involves preprocessing images, extracting 30 features from 15 horizontal and vertical zones, constructing a knowledge base from training images, and recognizing characters in test images by calculating distances between their features and the knowledge base. The method was evaluated on 460 Kannada character images with variations, achieving an average recognition accuracy of 91%.
Image Information Retrieval From Incomplete Queries Using Color and Shape Fea...sipij
Content based image retrieval (CBIR) is the task of searching digital images from a large database based on the extraction of features, such as color, texture and shape of the image. Most of the research in CBIR has been carried out with complete queries which were present in the database. This paper investigates utility of CBIR techniques for retrieval of incomplete and distorted queries. Studies were made in two categories of the query: first is complete and second is incomplete. The query image is considered to be distorted or incomplete image if it has some missing information, some undesirable objects, blurring, noise due to disturbance at the time of image acquisition etc. Color (hue, saturation and value (HSV) color space model) and shape (moment invariants and Fourier descriptor) features are used to represent the image. The algorithm was tested on database consisting of 1875 images. The results show that retrieval accuracy of incomplete queries is highly increased by fusing color and shape features giving precision of 79.87%. MATLAB ® 7.01 and its image processing toolbox have been used to implement the algorithm.
The document describes a method for multiresolution image fusion using nonsubsampled contourlet transform (NSCT). NSCT provides multiresolution analysis and captures directional information better than wavelets. The method uses NSCT to learn edges from a high-resolution panchromatic image and fuse it with low-resolution multispectral images. Maximum a posteriori estimation with a Markov random field prior is used to optimize the fused image. Experimental results on fusing QuickBird satellite images show the proposed method produces higher quality fused images compared to other fusion methods.
The development of multimedia system technology in Content based Image Retrieval (CBIR) System is
one in every of the outstanding area to retrieve the images from an oversized collection of database. The feature
vectors of the query image are compared with feature vectors of the database images to get matching images.It is
much observed that anyone algorithm isn't beneficial in extracting all differing kinds of natural images. Thus an
intensive analysis of certain color, texture and shape extraction techniques are allotted to spot an efficient CBIR
technique that suits for a selected sort of images. The Extraction of an image includes feature description and
feature extraction. During this paper, we tend to projected Color Layout Descriptor (CLD), grey Level Co-
Occurrences Matrix (GLCM), Marker-Controlled Watershed Segmentation feature extraction technique that
extract the matching image based on the similarity of Color, Texture and shape within the database. For
performance analysis, the image retrieval timing results of the projected technique is calculated and compared
with every of the individual feature.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
This document proposes a new method for segmenting outdoor images called Color Cluster Elimination (CCE) which utilizes color clustering and texture analysis. CCE performs color clustering in a multi-resolution pyramid to gradually eliminate larger color clusters, preventing them from dominating segmentation and allowing smaller clusters to emerge more clearly. It then examines regions for adjacent homochromatic objects with different textures, introducing Texture Sewn Response (TSR) to indicate texture strength across resolutions/directions. The method is evaluated on the BSDS500 dataset against other metrics, demonstrating satisfactory performance for outdoor scene segmentation.
A survey on feature descriptors for texture image classificationIRJET Journal
This document discusses various feature descriptors that can be used for texture image classification. It provides an overview of 8 different feature descriptors that have been proposed in recent research: local binary patterns (LBP), dominant local binary patterns (DLBP), completed local binary patterns (CLBP), Weber local descriptor (WLD), local binary count (LBC), discriminant face descriptor (DFD), local vector quantization pattern (LVQP), and dense micro-block difference (DMD). For each descriptor, it briefly explains the approach and compares the methods. The goal of the descriptors is to effectively capture textural features while addressing challenges like rotation, illumination changes, and noise.
An implementation of novel genetic based clustering algorithm for color image...TELKOMNIKA JOURNAL
The color image segmentation is one of most crucial application in image processing. It can apply to medical image segmentation for a brain tumor and skin cancer detection or color object detection on CCTV traffic video image segmentation and also for face recognition, fingerprint recognition etc. The color image segmentation has faced the problem of multidimensionality. The color image is considered in five-dimensional problems, three dimensions in color (RGB) and two dimensions in geometry (luminosity layer and chromaticity layer). In this paper the, L*a*b color space conversion has been used to reduce the one dimensional and geometrically it converts in the array hence the further one dimension has been reduced. The a*b space is clustered using genetic algorithm process, which minimizes the overall distance of the cluster, which is randomly placed at the start of the segmentation process. The segmentation results of this method give clear segments based on the different color and it can be applied to any application.
Performance Evaluation of 2D Adaptive Bilateral Filter For Removal of Noise F...CSCJournals
In this paper, we present the performance analysis of adaptive bilateral filter by pixel to noise ratio and mean square errors. It was evaluate changing the parameters of the adaptive filter half width values and standard deviations. In adaptive bilateral filter, the edge slope is enhanced by transforming the histogram via a range filter with adaptive offset and width. The variance of range filter can also be adaptive. The filter is applied to improve the sharpens of a gray level and color image by increasing the slope of the edges without producing overshoot or undershoots. The related graphs were plotted and the best filter parameters are obtained.
PDE BASED FEATURES FOR TEXTURE ANALYSIS USING WAVELET TRANSFORMIJCI JOURNAL
This document summarizes a research paper that proposes a novel method for texture analysis using wavelet transforms and partial differential equations (PDEs). The method involves applying wavelet transforms to images to obtain directional information. Anisotropic diffusion, a PDE technique, is then used on the directional information to compute a texture approximation. Various statistical features are extracted from the texture approximation. Linear discriminant analysis enhances class separability of the features before classification using k-nearest neighbors. The method is evaluated on the Brodatz texture dataset and results show it achieves better classification accuracy than other methods while having lower computational cost.
Face skin color based recognition using local spectral and gray scale featureseSAT Journals
Abstract Human face conveys more information about identity of person. Human face recognition is one of the most challenging problem and it can be used in many applications at different security places in airports, defense and banking sectors etc.In this work used colored features obtained from color segmentation because in real time scenario color provides the more information than gray scale image but it has a drawback. To overcome this drawback gray scale feature extracted from co-occurrence matrix of an image and for efficient face recognition of human Face under different illumination conditions spectral features can be extracted from face texture. These three feature vectors concatenated into a single feature vector and applied Lenc-Kral matching technique to measure similarity between the database and query image, the similarity is high then face is recognized. Keywords: Face recognition, illumination condition, local texture features, color segmentation.
Developing 3D Viewing Model from 2D Stereo Pair with its Occlusion RatioCSCJournals
We intend to make a 3D model using a stereo pair of images by using a novel method of local matching in pixel domain for calculating horizontal disparities. We also find the occlusion ratio using the stereo pair followed by the use of The Edge Detection and Image SegmentatiON (EDISON) system, on one the images, which provides a complete toolbox for discontinuity preserving filtering, segmentation and edge detection. Instead of assigning a disparity value to each pixel, a disparity plane is assigned to each segment. We then warp the segment disparities to the original image to get our final 3D viewing Model.
Performance analysis is basis on color based image retrieval techniqueIAEME Publication
This document discusses performance analysis of color-based image retrieval techniques. It proposes using foreground color extraction and K-nearest neighbor classification to retrieve similar images based on foreground objects. The key steps are segmenting images to separate foreground from background, categorizing foreground colors, and matching query images to images in a database based on dominant foreground color using K-nearest neighbor. An experimental analysis on a celebrity image dataset found the proposed technique achieved higher precision and recall than existing background-focused methods.
DEVELOPMENT OF AN ALPHABETIC CHARACTER RECOGNITION SYSTEM USING MATLAB FOR BA...Mohammad Liton Hossain
Character recognition technique, associates a symbolic identity with the image of the character, is an important area in pattern recognition and image processing. The principal idea here is to convert raw images (scanned from document, typed, pictured etcetera) into editable text like html, doc, txt or other formats. There is a very limited number of Bangla Character recognition system, if available they can’t recognize the whole alphabet set. Motivated by this, this paper demonstrates a MATLAB based Character Recognition system from printed Bangla writings. It can also compare the characters of one image file to another one. Processing steps here involved binarization, noise removal and segmentation in various levels, features extraction and recognition.
This document presents a method for recovering text from degraded document images. It involves several steps:
1. Constructing a contrast image to distinguish text from background by calculating local image contrast and gradient.
2. Detecting text stroke edges in the contrast image using Otsu's thresholding and Canny edge detection.
3. Estimating a local threshold for binarization based on mean and standard deviation of detected edge pixel intensities.
4. Converting the image to binary format above the threshold.
5. Post-processing to remove unwanted background pixels.
The method is tested on several degraded documents and shows good performance in recovering text contents in a short time period. It provides a
Automated Colorization of Grayscale Images Using Texture DescriptorsIDES Editor
The document proposes a novel automated process called ACTD for colorizing grayscale images using texture descriptors without human intervention. It analyzes sample color images to extract coherent texture regions, then uses Gabor filtering for texture-based segmentation. Texture descriptors and color information are computed and stored for each region. These are then used to colorize a new grayscale image based on texture matching. The method combines techniques such as Gabor filtering, fuzzy C-means clustering with a new "Gki factor" for noise tolerance, and content-based image retrieval of texture descriptors. Preliminary results found the approach viable but improvements were needed for scale and rotation invariance.
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.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
SYMMETRICAL WEIGHTED SUBSPACE HOLISTIC APPROACH FOR EXPRESSION RECOGNITIONijcsit
This document proposes a new method called Symmetrical Weighted 2D Principal Component Analysis (SW2DPCA) for facial expression recognition. SW2DPCA aims to reduce the dimensionality of the feature space extracted from face images using Gabor filters, while removing redundant information. It does this by decomposing the training images into odd and even symmetrical components, and applying weighted PCA to equalize the variance of principal components. The method is tested on the JAFFE database, achieving a recognition accuracy of 95.24% - higher than the 2DPCA baseline method.
Performance analysis is basis on color based image retrieval techniqueIAEME Publication
This document discusses performance analysis of color-based image retrieval techniques. It proposes using foreground color extraction and K-nearest neighbor classification to retrieve similar images based on foreground objects. The key steps are segmenting images to separate foreground from background, categorizing foreground colors, and matching query images to images in a database based on dominant foreground color using K-nearest neighbor. An experimental analysis on a celebrity image dataset found the proposed technique achieved higher precision and recall than existing background-focused methods.
A comparative study on content based image retrieval methodsIJLT EMAS
Content-based image retrieval (CBIR) is a method of
finding images from a huge image database according to persons’
interests. Content-based here means that the search involves
analysis the actual content present in the image. As database of
images is growing daybyday, researchers/scholars are searching
for better techniques for retrieval of images maintaining good
efficiency. This paper presents the visual features and various
ways for image retrieval from the huge image database.
Recognition of basic kannada characters in scene images using euclidean disIAEME Publication
The document describes a proposed methodology for recognizing basic Kannada characters in scene images using zone-wise horizontal and vertical profile-based features and an Euclidean distance classifier. The methodology involves preprocessing images, extracting 30 features from 15 horizontal and vertical zones, constructing a knowledge base from training images, and recognizing characters in test images by calculating distances between their features and the knowledge base. The method was evaluated on 460 Kannada character images with variations, achieving an average recognition accuracy of 91%.
Image Information Retrieval From Incomplete Queries Using Color and Shape Fea...sipij
Content based image retrieval (CBIR) is the task of searching digital images from a large database based on the extraction of features, such as color, texture and shape of the image. Most of the research in CBIR has been carried out with complete queries which were present in the database. This paper investigates utility of CBIR techniques for retrieval of incomplete and distorted queries. Studies were made in two categories of the query: first is complete and second is incomplete. The query image is considered to be distorted or incomplete image if it has some missing information, some undesirable objects, blurring, noise due to disturbance at the time of image acquisition etc. Color (hue, saturation and value (HSV) color space model) and shape (moment invariants and Fourier descriptor) features are used to represent the image. The algorithm was tested on database consisting of 1875 images. The results show that retrieval accuracy of incomplete queries is highly increased by fusing color and shape features giving precision of 79.87%. MATLAB ® 7.01 and its image processing toolbox have been used to implement the algorithm.
The document describes a method for multiresolution image fusion using nonsubsampled contourlet transform (NSCT). NSCT provides multiresolution analysis and captures directional information better than wavelets. The method uses NSCT to learn edges from a high-resolution panchromatic image and fuse it with low-resolution multispectral images. Maximum a posteriori estimation with a Markov random field prior is used to optimize the fused image. Experimental results on fusing QuickBird satellite images show the proposed method produces higher quality fused images compared to other fusion methods.
The document describes a method for multiresolution image fusion using nonsubsampled contourlet transform (NSCT). NSCT provides multiresolution analysis with shift invariance and directionality. The method uses NSCT to learn edges from a high-resolution panchromatic image and fuse it with low-resolution multispectral images. Maximum a posteriori estimation with a Markov random field prior is used to optimize the fused image. Experimental results on fusing QuickBird satellite images show the proposed method produces higher quality fused images compared to other fusion methods.
Comparative study on image fusion methods in spatial domainIAEME Publication
This document provides a comparative study of various image fusion methods in the spatial domain. It begins by introducing image fusion and its applications. Section 2 then describes several common fusion algorithms in the spatial domain, including average, select maximum/minimum, Brovey transform, intensity hue saturation (IHS), and principal component analysis (PCA). Section 3 defines image fusion quality measures like entropy, mean squared error, and normalized cross correlation. Section 4 provides a comparative analysis of the spatial domain fusion techniques based on parameters like simplicity, type of resources, and disadvantages. It finds that spatial domain methods provide high spatial resolution but have issues like image blurring and producing less informative outputs. The document concludes that while the best algorithm depends on the problem, spatial
Implementation of High Dimension Colour Transform in Domain of Image ProcessingIRJET Journal
This document discusses implementing a high-dimensional color transform method for salient region detection in images. It aims to extract salient regions by designing a saliency map using global and local image features. The creation of the saliency map involves mapping colors from RGB space to a high-dimensional color space to find an optimal linear combination of color coefficients. This allows composing an accurate saliency map. The performance is further improved by using relative location and color contrast between superpixels as features and resolving the saliency estimation from an initial trimap using a learning-based algorithm. The method is analyzed on a dataset of training images.
MMFO: modified moth flame optimization algorithm for region based RGB color i...IJECEIAES
Region-based color image segmentation is elementary steps in image processing and computer vision. The region-based color image segmentation has faced the problem of multidimensionality. The color image is considered in five-dimensional problems, in which three dimensions in color (RGB) and two dimensions in geometry (luminosity layer and chromaticity layer). In this paper, L*a*b color space conversion has been used to reduce the one dimension and geometrically it converts in the array hence the further one dimension has been reduced. This paper introduced, an improved algorithm modified moth flame optimization (MMFO) algorithm for RGB color image segmentation which is based on bio-inspired techniques. The simulation results of MMFO for region based color image segmentation are performed better as compared to PSO and GA, in terms of computation times for all the images. The experiment results of this method gives clear segments based on the different color and the different number of clusters is used during the segmentation process.
A version of watershed algorithm for color image segmentationHabibur Rahman
The document summarizes a master's thesis presentation on a new watershed algorithm for color image segmentation. The thesis addresses issues with existing watershed algorithms like over-segmentation and sensitivity to noise. The contributions of the thesis include an adaptive masking and thresholding mechanism to overcome over-segmentation and perform well on noisy images. The thesis is evaluated using five image quality assessment metrics on 20 classes of images, showing the proposed method performs better and has lower computational complexity than other algorithms. In conclusions, the adaptive watershed algorithm ensures accurate segmentation and is suitable for real-time applications.
The document summarizes an adaptive compressed image hashing method using modified Center Symmetric Local Binary Pattern (CSLBP) and color weight factors derived from the L*a*b* color space. The proposed method extracts texture features using modified CSLBP on the luminance channel of the L*a*b* color space. Color weight factors are then used adaptively, applying averaging for smooth regions and differencing for non-smooth regions, to enhance the discrimination capability of the generated hash. Experimental results using benchmarks like normalized hamming distance and ROC characteristics demonstrate the method can successfully differentiate between content-changing and content-preserving modifications of color images.
MONOGENIC SCALE SPACE BASED REGION COVARIANCE MATRIX DESCRIPTOR FOR FACE RECO...cscpconf
In this paper, we have presented a new face recognition algorithm based on region covariance
matrix (RCM) descriptor computed in monogenic scale space. In the proposed model, energy
information obtained using monogenic filter is used to represent a pixel at different scales to
form region covariance matrix descriptor for each face image during training phase. An eigenvalue
based distance measure is used to compute the similarity between face images. Extensive
experimentation on AT&T and YALE face database has been conducted to reveal the
performance of the monogenic scale space based region covariance matrix method and
comparative analysis is made with the basic RCM method and Gabor based region covariance matrix method to exhibit the superiority of the proposed technique.
Perceptual Weights Based On Local Energy For Image Quality AssessmentCSCJournals
This paper proposes an image quality metric that can effectively measure the quality of an image that correlates well with human judgment on the appearance of the image. The present work adds a new dimension to the structural approach based full-reference image quality assessment for gray scale images. The proposed method assigns more weight to the distortions present in the visual regions of interest of the reference (original) image than to the distortions present in the other regions of the image, referred to as perceptual weights. The perceptual features and their weights are computed based on the local energy modeling of the original image. The proposed model is validated using the image database provided by LIVE (Laboratory for Image & Video Engineering, The University of Texas at Austin) based on the evaluation metrics as suggested in the video quality experts group (VQEG) Phase I FR-TV test.
INFORMATION SATURATION IN MULTISPECTRAL PIXEL LEVEL IMAGE FUSIONIJCI JOURNAL
The availability of imaging sensors operating in multiple spectral bands has led to the requirement of
image fusion algorithms that would combine the image from these sensors in an efficient way to give an
image that is more informative as well as perceptible to human eye. Multispectral image fusion is the
process of combining images from different spectral bands that are optically acquired. In this paper, we
used a pixel-level image fusion based on principal component analysis that combines satellite images of the
same scene from seven different spectral bands. The purpose of using principal component analysis
technique is that it is best method for Grayscale image fusion and gives better results. The main aim of
PCA technique is to reduce a large set of variables into a small set which still contains most of the
information that was present in the large set. The paper compares different parameters namely, entropy,
standard deviation, correlation coefficient etc. for different number of images fused from two to seven.
Finally, the paper shows that the information content in an image gets saturated after fusing four images.
EFFICIENT IMAGE RETRIEVAL USING REGION BASED IMAGE RETRIEVALsipij
1) The document describes an efficient region-based image retrieval system that uses discrete wavelet transform and k-means clustering. It segments images into regions, each characterized by features like size, mean, and covariance.
2) The system pre-processes images by resizing, converting to HSV color space, performing DWT, and using k-means clustering on DWT coefficients to generate regions. It extracts features for each region and stores them in a database.
3) For retrieval, it pre-processes the query image similarly and calculates similarities between the query regions and database regions based on their features, returning similar images.
COMPUTATIONALLY EFFICIENT TWO STAGE SEQUENTIAL FRAMEWORK FOR STEREO MATCHINGijfcstjournal
Almost all the existing stereo algorithms fall under a common assumption that corresponding color or
intensity values will be similar like one another. On the other hand, it is also not that true in practice
where the image color or intensity values are regularly affected by different radiometric factors like
illumination direction, change in image device, illuminant color and so on. For this issue, the information
about the raw color of the images which is recorded by the camera should not depend on it totally, and
also the common assumptions on color consistency doesn’t influence good (great) between the stereo
images in real scenario. Therefore, most of the conventional stereo algorithms can be seriously degraded
in terms of performance under radiometric variations. In this work, we intend to develop a new stereo
matching algorithm which will be insensitive to change in radiometric conditions between stereo pairs i.e.
left image as well as right image. Unlike the other stereo algorithms, we propose a computationally
efficient two stage sequential framework for stereo matching which can handle the various radiometric
variations between the stereo pairs.Experimental results proves that the proposed method outperforms
extremely well compare to other state of the art stereo methods under change in various radiometric
conditions for a given stereo pair and it is also found from the results that the execution time is less
compare to existing methods.
This document reviews techniques for multi-image morphing. It discusses early cross-dissolve morphing methods and their limitations. Mesh warping and field morphing are introduced as improved techniques that use control points and line mappings to better align images during transition. The document also summarizes point distribution, critical point filters, and other common morphing methods. It concludes by noting that effective morphing requires mechanisms for feature specification, warp generation, and transition control.
Color is a widely used visual feature for content-based video retrieval. There are two main methods discussed in the document: block-based and global color feature extraction. The block-based method extracts color histograms from divided blocks of each video frame, while the global method extracts a single color histogram from the entire frame. These color features are then used to measure similarity between videos for retrieval. The document also discusses challenges with high-dimensional color histograms and methods to reduce dimensions like transforms and selecting significant colors. Overall the paper presents color-based video retrieval techniques and evaluates performance of the block-based and global methods.
The document discusses color-based video retrieval using block and global methods. It summarizes that color features are widely used in video retrieval and content analysis. It describes extracting color histograms globally and from divided blocks. Two methods are discussed: global color extracts overall color frequency while block color quantizes each divided region, maintaining some spatial data. Videos are retrieved by comparing feature vectors of queries to those in a database using distance metrics like Euclidean distance. MATLAB is used to implement the color feature extraction and retrieval methods.
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Similar to Zernike moment of invariants for effective image retrieval using gaussian filters (20)
Submission Deadline: 30th September 2022
Acceptance Notification: Within Three Days’ time period
Online Publication: Within 24 Hrs. time Period
Expected Date of Dispatch of Printed Journal: 5th October 2022
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...IAEME Publication
White layer thickness (WLT) formed and surface roughness in wire electric discharge turning (WEDT) of tungsten carbide composite has been made to model through response surface methodology (RSM). A Taguchi’s standard Design of experiments involving five input variables with three levels has been employed to establish a mathematical model between input parameters and responses. Percentage of cobalt content, spindle speed, Pulse on-time, wire feed and pulse off-time were changed during the experimental tests based on the Taguchi’s orthogonal array L27 (3^13). Analysis of variance (ANOVA) revealed that the mathematical models obtained can adequately describe performance within the parameters of the factors considered. There was a good agreement between the experimental and predicted values in this study.
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSIAEME Publication
The study explores the reasons for a transgender to become entrepreneurs. In this study transgender entrepreneur was taken as independent variable and reasons to become as dependent variable. Data were collected through a structured questionnaire containing a five point Likert Scale. The study examined the data of 30 transgender entrepreneurs in Salem Municipal Corporation of Tamil Nadu State, India. Simple Random sampling technique was used. Garrett Ranking Technique (Percentile Position, Mean Scores) was used as the analysis for the present study to identify the top 13 stimulus factors for establishment of trans entrepreneurial venture. Economic advancement of a nation is governed upon the upshot of a resolute entrepreneurial doings. The conception of entrepreneurship has stretched and materialized to the socially deflated uncharted sections of transgender community. Presently transgenders have smashed their stereotypes and are making recent headlines of achievements in various fields of our Indian society. The trans-community is gradually being observed in a new light and has been trying to achieve prospective growth in entrepreneurship. The findings of the research revealed that the optimistic changes are taking place to change affirmative societal outlook of the transgender for entrepreneurial ventureship. It also laid emphasis on other transgenders to renovate their traditional living. The paper also highlights that legislators, supervisory body should endorse an impartial canons and reforms in Tamil Nadu Transgender Welfare Board Association.
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSIAEME Publication
Since ages gender difference is always a debatable theme whether caused by nature, evolution or environment. The birth of a transgender is dreadful not only for the child but also for their parents. The pain of living in the wrong physique and treated as second class victimized citizen is outrageous and fully harboured with vicious baseless negative scruples. For so long, social exclusion had perpetuated inequality and deprivation experiencing ingrained malign stigma and besieged victims of crime or violence across their life spans. They are pushed into the murky way of life with a source of eternal disgust, bereft sexual potency and perennial fear. Although they are highly visible but very little is known about them. The common public needs to comprehend the ravaged arrogance on these insensitive souls and assist in integrating them into the mainstream by offering equal opportunity, treat with humanity and respect their dignity. Entrepreneurship in the current age is endorsing the gender fairness movement. Unstable careers and economic inadequacy had inclined one of the gender variant people called Transgender to become entrepreneurs. These tiny budding entrepreneurs resulted in economic transition by means of employment, free from the clutches of stereotype jobs, raised standard of living and handful of financial empowerment. Besides all these inhibitions, they were able to witness a platform for skill set development that ignited them to enter into entrepreneurial domain. This paper epitomizes skill sets involved in trans-entrepreneurs of Thoothukudi Municipal Corporation of Tamil Nadu State and is a groundbreaking determination to sightsee various skills incorporated and the impact on entrepreneurship.
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSIAEME Publication
The banking and financial services industries are experiencing increased technology penetration. Among them, the banking industry has made technological advancements to better serve the general populace. The economy focused on transforming the banking sector's system into a cashless, paperless, and faceless one. The researcher wants to evaluate the user's intention for utilising a mobile banking application. The study also examines the variables affecting the user's behaviour intention when selecting specific applications for financial transactions. The researcher employed a well-structured questionnaire and a descriptive study methodology to gather the respondents' primary data utilising the snowball sampling technique. The study includes variables like performance expectations, effort expectations, social impact, enabling circumstances, and perceived risk. Each of the aforementioned variables has a major impact on how users utilise mobile banking applications. The outcome will assist the service provider in comprehending the user's history with mobile banking applications.
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSIAEME Publication
Technology upgradation in banking sector took the economy to view that payment mode towards online transactions using mobile applications. This system enabled connectivity between banks, Merchant and user in a convenient mode. there are various applications used for online transactions such as Google pay, Paytm, freecharge, mobikiwi, oxygen, phonepe and so on and it also includes mobile banking applications. The study aimed at evaluating the predilection of the user in adopting digital transaction. The study is descriptive in nature. The researcher used random sample techniques to collect the data. The findings reveal that mobile applications differ with the quality of service rendered by Gpay and Phonepe. The researcher suggest the Phonepe application should focus on implementing the application should be user friendly interface and Gpay on motivating the users to feel the importance of request for money and modes of payments in the application.
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOIAEME Publication
The prototype of a voice-based ATM for visually impaired using Arduino is to help people who are blind. This uses RFID cards which contain users fingerprint encrypted on it and interacts with the users through voice commands. ATM operates when sensor detects the presence of one person in the cabin. After scanning the RFID card, it will ask to select the mode like –normal or blind. User can select the respective mode through voice input, if blind mode is selected the balance check or cash withdraw can be done through voice input. Normal mode procedure is same as the existing ATM.
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IAEME Publication
There is increasing acceptability of emotional intelligence as a major factor in personality assessment and effective human resource management. Emotional intelligence as the ability to build capacity, empathize, co-operate, motivate and develop others cannot be divorced from both effective performance and human resource management systems. The human person is crucial in defining organizational leadership and fortunes in terms of challenges and opportunities and walking across both multinational and bilateral relationships. The growing complexity of the business world requires a great deal of self-confidence, integrity, communication, conflict and diversity management to keep the global enterprise within the paths of productivity and sustainability. Using the exploratory research design and 255 participants the result of this original study indicates strong positive correlation between emotional intelligence and effective human resource management. The paper offers suggestions on further studies between emotional intelligence and human capital development and recommends for conflict management as an integral part of effective human resource management.
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYIAEME Publication
Our life journey, in general, is closely defined by the way we understand the meaning of why we coexist and deal with its challenges. As we develop the "inspiration economy", we could say that nearly all of the challenges we have faced are opportunities that help us to discover the rest of our journey. In this note paper, we explore how being faced with the opportunity of being a close carer for an aging parent with dementia brought intangible discoveries that changed our insight of the meaning of the rest of our life journey.
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...IAEME Publication
The main objective of this study is to analyze the impact of aspects of Organizational Culture on the Effectiveness of the Performance Management System (PMS) in the Health Care Organization at Thanjavur. Organizational Culture and PMS play a crucial role in present-day organizations in achieving their objectives. PMS needs employees’ cooperation to achieve its intended objectives. Employees' cooperation depends upon the organization’s culture. The present study uses exploratory research to examine the relationship between the Organization's culture and the Effectiveness of the Performance Management System. The study uses a Structured Questionnaire to collect the primary data. For this study, Thirty-six non-clinical employees were selected from twelve randomly selected Health Care organizations at Thanjavur. Thirty-two fully completed questionnaires were received.
Living in 21st century in itself reminds all of us the necessity of police and its administration. As more and more we are entering into the modern society and culture, the more we require the services of the so called ‘Khaki Worthy’ men i.e., the police personnel. Whether we talk of Indian police or the other nation’s police, they all have the same recognition as they have in India. But as already mentioned, their services and requirements are different after the like 26th November, 2008 incidents, where they without saving their own lives has sacrificed themselves without any hitch and without caring about their respective family members and wards. In other words, they are like our heroes and mentors who can guide us from the darkness of fear, militancy, corruption and other dark sides of life and so on. Now the question arises, if Gandhi would have been alive today, what would have been his reaction/opinion to the police and its functioning? Would he have some thing different in his mind now what he had been in his mind before the partition or would he be going to start some Satyagraha in the form of some improvement in the functioning of the police administration? Really these questions or rather night mares can come to any one’s mind, when there is too much confusion is prevailing in our minds, when there is too much corruption in the society and when the polices working is also in the questioning because of one or the other case throughout the India. It is matter of great concern that we have to thing over our administration and our practical approach because the police personals are also like us, they are part and parcel of our society and among one of us, so why we all are pin pointing towards them.
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...IAEME Publication
The goal of this study was to see how talent management affected employee retention in the selected IT organizations in Chennai. The fundamental issue was the difficulty to attract, hire, and retain talented personnel who perform well and the gap between supply and demand of talent acquisition and retaining them within the firms. The study's main goals were to determine the impact of talent management on employee retention in IT companies in Chennai, investigate talent management strategies that IT companies could use to improve talent acquisition, performance management, career planning and formulate retention strategies that the IT firms could use. The respondents were given a structured close-ended questionnaire with the 5 Point Likert Scale as part of the study's quantitative research design. The target population consisted of 289 IT professionals. The questionnaires were distributed and collected by the researcher directly. The Statistical Package for Social Sciences (SPSS) was used to collect and analyse the questionnaire responses. Hypotheses that were formulated for the various areas of the study were tested using a variety of statistical tests. The key findings of the study suggested that talent management had an impact on employee retention. The studies also found that there is a clear link between the implementation of talent management and retention measures. Management should provide enough training and development for employees, clarify job responsibilities, provide adequate remuneration packages, and recognise employees for exceptional performance.
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...IAEME Publication
Globally, Millions of dollars were spent by the organizations for employing skilled Information Technology (IT) professionals. It is costly to replace unskilled employees with IT professionals possessing technical skills and competencies that aid in interconnecting the business processes. The organization’s employment tactics were forced to alter by globalization along with technological innovations as they consistently diminish to remain lean, outsource to concentrate on core competencies along with restructuring/reallocate personnel to gather efficiency. As other jobs, organizations or professions have become reasonably more appropriate in a shifting employment landscape, the above alterations trigger both involuntary as well as voluntary turnover. The employee view on jobs is also afflicted by the COVID-19 pandemic along with the employee-driven labour market. So, having effective strategies is necessary to tackle the withdrawal rate of employees. By associating Emotional Intelligence (EI) along with Talent Management (TM) in the IT industry, the rise in attrition rate was analyzed in this study. Only 303 respondents were collected out of 350 participants to whom questionnaires were distributed. From the employees of IT organizations located in Bangalore (India), the data were congregated. A simple random sampling methodology was employed to congregate data as of the respondents. Generating the hypothesis along with testing is eventuated. The effect of EI and TM along with regression analysis between TM and EI was analyzed. The outcomes indicated that employee and Organizational Performance (OP) were elevated by effective EI along with TM.
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...IAEME Publication
By implementing talent management strategy, organizations would have the option to retain their skilled professionals while additionally working on their overall performance. It is the course of appropriately utilizing the ideal individuals, setting them up for future top positions, exploring and dealing with their performance, and holding them back from leaving the organization. It is employee performance that determines the success of every organization. The firm quickly obtains an upper hand over its rivals in the event that its employees having particular skills that cannot be duplicated by the competitors. Thus, firms are centred on creating successful talent management practices and processes to deal with the unique human resources. Firms are additionally endeavouring to keep their top/key staff since on the off chance that they leave; the whole store of information leaves the firm's hands. The study's objective was to determine the impact of talent management on organizational performance among the selected IT organizations in Chennai. The study recommends that talent management limitedly affects performance. On the off chance that this talent is appropriately management and implemented properly, organizations might benefit as much as possible from their maintained assets to support development and productivity, both monetarily and non-monetarily.
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...IAEME Publication
Banking regulations act of India, 1949 defines banking as “acceptance of deposits for the purpose of lending or investment from the public, repayment on demand or otherwise and withdrawable through cheques, drafts order or otherwise”, the major participants of the Indian financial system are commercial banks, the financial institution encompassing term lending institutions. Investments institutions, specialized financial institution and the state level development banks, non banking financial companies (NBFC) and other market intermediaries such has the stock brokers and money lenders are among the oldest of the certain variants of NBFC and the oldest market participants. The asset quality of banks is one of the most important indicators of their financial health. The Indian banking sector has been facing severe problems of increasing Non- Performing Assets (NPAs). The NPAs growth directly and indirectly affects the quality of assets and profitability of banks. It also shows the efficiency of banks credit risk management and the recovery effectiveness. NPA do not generate any income, whereas, the bank is required to make provisions for such as assets that why is a double edge weapon. This paper outlines the concept of quality of bank loans of different types like Housing, Agriculture and MSME loans in state Haryana of selected public and private sector banks. This study is highlighting problems associated with the role of commercial bank in financing Small and Medium Scale Enterprises (SME). The overall objective of the research was to assess the effect of the financing provisions existing for the setting up and operations of MSMEs in the country and to generate recommendations for more robust financing mechanisms for successful operation of the MSMEs, in turn understanding the impact of MSME loans on financial institutions due to NPA. There are many research conducted on the topic of Non- Performing Assets (NPA) Management, concerning particular bank, comparative study of public and private banks etc. In this paper the researcher is considering the aggregate data of selected public sector and private sector banks and attempts to compare the NPA of Housing, Agriculture and MSME loans in state Haryana of public and private sector banks. The tools used in the study are average and Anova test and variance. The findings reveal that NPA is common problem for both public and private sector banks and is associated with all types of loans either that is housing loans, agriculture loans and loans to SMES. NPAs of both public and private sector banks show the increasing trend. In 2010-11 GNPA of public and private sector were at same level it was 2% but after 2010-11 it increased in many fold and at present there is GNPA in some more than 15%. It shows the dark area of Indian banking sector.
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...IAEME Publication
An experiment conducted in this study found that BaSO4 changed Nylon 6's mechanical properties. By changing the weight ratios, BaSO4 was used to make Nylon 6. This Researcher looked into how hard Nylon-6/BaSO4 composites are and how well they wear. Experiments were done based on Taguchi design L9. Nylon-6/BaSO4 composites can be tested for their hardness number using a Rockwell hardness testing apparatus. On Nylon/BaSO4, the wear behavior was measured by a wear monitor, pinon-disc friction by varying reinforcement, sliding speed, and sliding distance, and the microstructure of the crack surfaces was observed by SEM. This study provides significant contributions to ultimate strength by increasing BaSO4 content up to 16% in the composites, and sliding speed contributes 72.45% to the wear rate
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...IAEME Publication
The majority of the population in India lives in villages. The village is the back bone of the country. Village or rural industries play an important role in the national economy, particularly in the rural development. Developing the rural economy is one of the key indicators towards a country’s success. Whether it be the need to look after the welfare of the farmers or invest in rural infrastructure, Governments have to ensure that rural development isn’t compromised. The economic development of our country largely depends on the progress of rural areas and the standard of living of rural masses. Village or rural industries play an important role in the national economy, particularly in the rural development. Rural entrepreneurship is based on stimulating local entrepreneurial talent and the subsequent growth of indigenous enterprises. It recognizes opportunity in the rural areas and accelerates a unique blend of resources either inside or outside of agriculture. Rural entrepreneurship brings an economic value to the rural sector by creating new methods of production, new markets, new products and generate employment opportunities thereby ensuring continuous rural development. Social Entrepreneurship has the direct and primary objective of serving the society along with the earning profits. So, social entrepreneurship is different from the economic entrepreneurship as its basic objective is not to earn profits but for providing innovative solutions to meet the society needs which are not taken care by majority of the entrepreneurs as they are in the business for profit making as a sole objective. So, the Social Entrepreneurs have the huge growth potential particularly in the developing countries like India where we have huge societal disparities in terms of the financial positions of the population. Still 22 percent of the Indian population is below the poverty line and also there is disparity among the rural & urban population in terms of families living under BPL. 25.7 percent of the rural population & 13.7 percent of the urban population is under BPL which clearly shows the disparity of the poor people in the rural and urban areas. The need to develop social entrepreneurship in agriculture is dictated by a large number of social problems. Such problems include low living standards, unemployment, and social tension. The reasons that led to the emergence of the practice of social entrepreneurship are the above factors. The research problem lays upon disclosing the importance of role of social entrepreneurship in rural development of India. The paper the tendencies of social entrepreneurship in India, to present successful examples of such business for providing recommendations how to improve situation in rural areas in terms of social entrepreneurship development. Indian government has made some steps towards development of social enterprises, social entrepreneurship, and social in- novation, but a lot remains to be improved.
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...IAEME Publication
Distribution system is a critical link between the electric power distributor and the consumers. Most of the distribution networks commonly used by the electric utility is the radial distribution network. However in this type of network, it has technical issues such as enormous power losses which affect the quality of the supply. Nowadays, the introduction of Distributed Generation (DG) units in the system help improve and support the voltage profile of the network as well as the performance of the system components through power loss mitigation. In this study network reconfiguration was done using two meta-heuristic algorithms Particle Swarm Optimization and Gravitational Search Algorithm (PSO-GSA) to enhance power quality and voltage profile in the system when simultaneously applied with the DG units. Backward/Forward Sweep Method was used in the load flow analysis and simulated using the MATLAB program. Five cases were considered in the Reconfiguration based on the contribution of DG units. The proposed method was tested using IEEE 33 bus system. Based on the results, there was a voltage profile improvement in the system from 0.9038 p.u. to 0.9594 p.u.. The integration of DG in the network also reduced power losses from 210.98 kW to 69.3963 kW. Simulated results are drawn to show the performance of each case.
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...IAEME Publication
Manufacturing industries have witnessed an outburst in productivity. For productivity improvement manufacturing industries are taking various initiatives by using lean tools and techniques. However, in different manufacturing industries, frugal approach is applied in product design and services as a tool for improvement. Frugal approach contributed to prove less is more and seems indirectly contributing to improve productivity. Hence, there is need to understand status of frugal approach application in manufacturing industries. All manufacturing industries are trying hard and putting continuous efforts for competitive existence. For productivity improvements, manufacturing industries are coming up with different effective and efficient solutions in manufacturing processes and operations. To overcome current challenges, manufacturing industries have started using frugal approach in product design and services. For this study, methodology adopted with both primary and secondary sources of data. For primary source interview and observation technique is used and for secondary source review has done based on available literatures in website, printed magazines, manual etc. An attempt has made for understanding application of frugal approach with the study of manufacturing industry project. Manufacturing industry selected for this project study is Mahindra and Mahindra Ltd. This paper will help researcher to find the connections between the two concepts productivity improvement and frugal approach. This paper will help to understand significance of frugal approach for productivity improvement in manufacturing industry. This will also help to understand current scenario of frugal approach in manufacturing industry. In manufacturing industries various process are involved to deliver the final product. In the process of converting input in to output through manufacturing process productivity plays very critical role. Hence this study will help to evolve status of frugal approach in productivity improvement programme. The notion of frugal can be viewed as an approach towards productivity improvement in manufacturing industries.
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTIAEME Publication
In this paper, we investigated a queuing model of fuzzy environment-based a multiple channel queuing model (M/M/C) ( /FCFS) and study its performance under realistic conditions. It applies a nonagonal fuzzy number to analyse the relevant performance of a multiple channel queuing model (M/M/C) ( /FCFS). Based on the sub interval average ranking method for nonagonal fuzzy number, we convert fuzzy number to crisp one. Numerical results reveal that the efficiency of this method. Intuitively, the fuzzy environment adapts well to a multiple channel queuing models (M/M/C) ( /FCFS) are very well.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. 💻
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Nunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdfflufftailshop
When it comes to unit testing in the .NET ecosystem, developers have a wide range of options available. Among the most popular choices are NUnit, XUnit, and MSTest. These unit testing frameworks provide essential tools and features to help ensure the quality and reliability of code. However, understanding the differences between these frameworks is crucial for selecting the most suitable one for your projects.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...alexjohnson7307
Predictive maintenance is a proactive approach that anticipates equipment failures before they happen. At the forefront of this innovative strategy is Artificial Intelligence (AI), which brings unprecedented precision and efficiency. AI in predictive maintenance is transforming industries by reducing downtime, minimizing costs, and enhancing productivity.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.