This document summarizes a research paper that reviews different methods for scene text detection and the challenges associated with it. The paper begins with an introduction that describes the overall process of automated scene text detection systems. It then provides a literature review of various text detection methods proposed in previous research, which can be categorized as connected component based methods or texture based methods. Some example methods are described. The paper discusses challenges in scene text detection, such as variable imaging conditions, complex backgrounds, and a wide range of text sizes and fonts. Finally, it discusses performance metrics like precision, recall, and f-measure that are used to evaluate scene text detection methods based on a standard dataset.
Anatomical Survey Based Feature Vector for Text Pattern DetectionIJEACS
The vital objective of artificial intelligence is to discover and understand the human competences, one of which is the capability to distinguish several text objects within one or more images exhibited on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However it needs to technologically verify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed.
A Survey On Thresholding Operators of Text Extraction In VideosCSCJournals
ideo indexing is an important problem that has interested by the communities of visual information in image processing. The detection and extraction of scene and caption text from unconstrained, general purpose video is an important research problem in the context of content-based retrieval and summarization. In this paper, the technique presented is for detection text from frames video. Finding the textual contents in images is a challenging and promising research area in information technology. Consequently, text detection and recognition in multimedia had become one of the most important fields in computer vision due to its valuable uses in a variety of recent technical applications. The work in this paper consists using morphological operations for extract text appearing in the video frames. The proposed scheme well as preprocessing to differentiate among where it as the high similarity between text and background information. Experimental results show that the resultant image is the image with only text. The evaluated criteria are applied with the image result and one obtained bay different operator.
Text detection and recognition from natural sceneshemanthmcqueen
Text characters in natural scenes and surroundings provide us with valuable information about the place and even provide us with some legal/important information. Hence it’s very important for us to detect such text and recognise them which helps a lot. But , it’s not really easy to recognize those text information because of the diverse backgrounds and fonts used for the text. In this paper, a method is proposed to extract the text information from the surroundings. First, a character descriptor is designed with existing standard detectors and descriptors. Then, character structure is modeled at each character class by designing stroke configuration maps.In natural scenes , the text part is generally found on nearby sign boards and other objects. The extraction of such text is difficult because of noisy backgrounds and diverse fonts and text sizes. But many applications have been proven to be efficient in extraction of text from surroundings. For this , the method of text extraction is divided into two processes;
Text detection
Text recognition
Anatomical Survey Based Feature Vector for Text Pattern DetectionIJEACS
The vital objective of artificial intelligence is to discover and understand the human competences, one of which is the capability to distinguish several text objects within one or more images exhibited on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However it needs to technologically verify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed.
A Survey On Thresholding Operators of Text Extraction In VideosCSCJournals
ideo indexing is an important problem that has interested by the communities of visual information in image processing. The detection and extraction of scene and caption text from unconstrained, general purpose video is an important research problem in the context of content-based retrieval and summarization. In this paper, the technique presented is for detection text from frames video. Finding the textual contents in images is a challenging and promising research area in information technology. Consequently, text detection and recognition in multimedia had become one of the most important fields in computer vision due to its valuable uses in a variety of recent technical applications. The work in this paper consists using morphological operations for extract text appearing in the video frames. The proposed scheme well as preprocessing to differentiate among where it as the high similarity between text and background information. Experimental results show that the resultant image is the image with only text. The evaluated criteria are applied with the image result and one obtained bay different operator.
Text detection and recognition from natural sceneshemanthmcqueen
Text characters in natural scenes and surroundings provide us with valuable information about the place and even provide us with some legal/important information. Hence it’s very important for us to detect such text and recognise them which helps a lot. But , it’s not really easy to recognize those text information because of the diverse backgrounds and fonts used for the text. In this paper, a method is proposed to extract the text information from the surroundings. First, a character descriptor is designed with existing standard detectors and descriptors. Then, character structure is modeled at each character class by designing stroke configuration maps.In natural scenes , the text part is generally found on nearby sign boards and other objects. The extraction of such text is difficult because of noisy backgrounds and diverse fonts and text sizes. But many applications have been proven to be efficient in extraction of text from surroundings. For this , the method of text extraction is divided into two processes;
Text detection
Text recognition
With so much of our lives computerized, it is vitally important that machines and humans can understand one another and pass information back and forth. Mostly computers have things their way we have to & talk to them through relatively crude devices such as keyboards and mice so they can figure out what we want them to do. However, when it comes to processing more human kinds of information, like an old-fashioned printed book or a letter scribbled with a fountain pen, computers have to work much harder. That is where optical character recognition (OCR) comes in. Here we process the image, where we apply various pre-processing techniques like desk wing, binarization etc. and algorithms like Tesseract to recognize the characters and give us the final document. T.Gnana Prakash | K. Anusha"Text Extraction from Image using Python" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6 , October 2017, URL: http://www.ijtsrd.com/papers/ijtsrd2501.pdf http://www.ijtsrd.com/computer-science/simulation/2501/text-extraction-from-image-using-python/tgnana-prakash
Text detection and recognition in scene images or natural images has applications in computer
vision systems like registration number plate detection, automatic traffic sign detection, image retrieval
and help for visually impaired people. Scene text, however, has complicated background, blur image,
partly occluded text, variations in font-styles, image noise and ranging illumination. Hence scene text
recognition could be a difficult computer vision problem. In this paper connected component method
is used to extract the text from background. In this work, horizontal and vertical projection profiles,
geometric properties of text, image binirization and gap filling method are used to extract the text from
scene images. Then histogram based threshold is applied to separate text background of the images.
Finally text is extracted from images.
Skin Detection Based on Color Model and Low Level Features Combined with Expl...IJERA Editor
Skin detection is active research area in the field of computer vision which can be applied in the application of
face detection, eye detection, etc. These detection helps in various applications such as driver fatigue monitoring
system, surveillance system etc. In Computer vision applications, the color model and representations of the
human image in color model is one of major module to detect the skin pixels. The mainstream technology is
based on the individual pixels and selection of the pixels to detect the skin part in the whole image. In this thesis
implementation, we presents a novel technique for skin color detection incorporating with explicit region based
and parametric based approach which gives the better efficiency and performances in terms of skin detection in
human images. Color models and image quantization technique is used to extract the regions of the images and
to represent the image in a particular color model such as RGB and HSV, and then the parametric based
approach is applied by selecting the low level skin features are applied to extract the skin and non-skin pixels of
the images. In the first step, our technique uses the state-of-the-art non-parametric approach which we call the
template based technique or explicitly defined skin regions technique. Then the low level features of the human
skin are being extracted such as edge, corner detection which is also known as parametric method. The
experimental results depict the improvement in detection rate of the skin pixels by this novel approach. And in
the end we discuss the experimental results to prove the algorithmic improvements.
Texture features based text extraction from images using DWT and K-means clus...Divya Gera
Text extraction from different kind of images document, caption and scene text images. Discret wavelet transform was used to exract horizontal, vertical and diagonal features and k-means clustering was used to cluster the features into text and background cluster. For simple images k = 2 worked i.e. text and backgroud cluster while for complex images k=3 was used i.e. text cluster, complex background ad simple background.
K2 Algorithm-based Text Detection with An Adaptive Classifier ThresholdCSCJournals
In natural scene images, text detection is a challenging study area for dissimilar content-based image analysis tasks. In this paper, a Bayesian network scores are used to classify candidate character regions by computing posterior probabilities. The posterior probabilities are used to define an adaptive threshold to detect text in scene images with accuracy. Therefore, candidate character regions are extracted through maximally stable extremal region. K2 algorithm-based Bayesian network scores are learned by evaluating dependencies amongst features of a given candidate character region. Bayesian logistic regression classifier is trained to compute posterior probabilities to define an adaptive classifier threshold. The candidate character regions below from adaptive classifier threshold are discarded as non-character regions. Finally, text regions are detected with the use of effective text localization scheme based on geometric features. The entire system is evaluated on the ICDAR 2013 competition database. Experimental results produce competitive performance (precision, recall and harmonic mean) with the recently published algorithms.
SCENE TEXT RECOGNITION IN MOBILE APPLICATION BY CHARACTER DESCRIPTOR AND STRU...Cheriyan K M
In text detection, our
previously proposed algorithms are applied to obtain text regions
from scene image. First, we design a discriminative character
descriptor by combining several state-of-the-art feature detectors
and descriptors. Second, we model character structure at each
character class by designing stroke configuration maps.
Bangla Optical Digits Recognition using Edge Detection MethodIOSR Journals
Abstract:This paper is based on Bangla Optical Digit Recognition (ODR) by the Edge detection technique. In this method, Bangla digit image converted into gray-scale which distributed by an M by N array form. Here input data are considered off-line printed digit’s image which collected from computer generated image, scanned documents or printed text. After addressing the gray-scale image against a variable in the form of an M by N array, where the value of array pointers are shown 255 for total white space, 0 (zero) for total dark space and value between 255 and 0 for mix of white and dark space of the image. At the next process, four edgestouch points as well as each touch point’s ratio use as parameters to determine each Bangla digit uniquely. Keywords-Edge, image,gray-scale, Matrix,ODR.
TEXT DETECTION AND EXTRACTION FROM VIDEOS USING ANN BASED NETWORKijscai
With fast intensification of existing multimedia documents and mounting demand for information indexing and retrieval, much endeavor has been done on extracting the text from images and videos. The prime intention of the projected system is to spot and haul out the scene text from video. Extracting the scene text from video is demanding due to complex background, varying font size, different style, lower resolution and blurring, position, viewing angle and so on. In this paper we put forward a hybrid method where the two most well-liked text extraction techniques i.e. region based method and connected component (CC) based method comes together. Initially the video is split into frames and key frames obtained. Text region indicator (TRI) is being developed to compute the text prevailing confidence and
candidate region by performing binarization. Artificial Neural network (ANN) is used as the classifier and Optical Character Recognition (OCR) is used for character verification. Text is grouped by constructing the minimum spanning tree with the use of bounding box distance.
A colour-based building recognition using support vector machineTELKOMNIKA JOURNAL
Many applications apply the concept of image recognition to help human in recognising objects simply by just using digital images. A content-based building recognition system could solve the problem of using just text as search input. In this paper, a building recognition system using colour histogram is proposed for recognising buildings in Ipoh city, Perak, Malaysia. The colour features of each building image will be extracted. A feature vector combining the mean, standard deviation, variance, skewness and kurtosis of gray level will be formed to represent each building image. These feature values are later used to train the system using supervised learning algorithm, which is Support Vector Machine (SVM). Lastly, the accuracy of the recognition system is evaluated using 10-fold cross validation. The evaluation results show that the building recognition system is well trained and able to effectively recognise the building images with low misclassification rate.
A Survey On Thresholding Operators of Text Extraction In VideosCSCJournals
Video indexing is an important problem that has interested by the communities of visual information in image processing. The detection and extraction of scene and caption text from unconstrained, general purpose video is an important research problem in the context of content-based retrieval and summarization. In this paper, the technique presented is for detection text from frames video. Finding the textual contents in images is a challenging and promising research area in information technology. Consequently, text detection and recognition in multimedia had become one of the most important fields in computer vision due to its valuable uses in a variety of recent technical applications. The work in this paper consists using morphological operations for extract text appearing in the video frames. The proposed scheme well as preprocessing to differentiate among where it as the high similarity between text and background information. Experimental results show that the resultant image is the image with only text. The evaluated criteria are applied with the image result and one obtained bay different operator.
Optical Character Recognition from Text ImageEditor IJCATR
Optical Character Recognition (OCR) is a system that provides a full alphanumeric recognition of printed or handwritten
characters by simply scanning the text image. OCR system interprets the printed or handwritten characters image and converts it into
corresponding editable text document. The text image is divided into regions by isolating each line, then individual characters with
spaces. After character extraction, the texture and topological features like corner points, features of different regions, ratio of
character area and convex area of all characters of text image are calculated. Previously features of each uppercase and lowercase
letter, digit, and symbols are stored as a template. Based on the texture and topological features, the system recognizes the exact
character using feature matching between the extracted character and the template of all characters as a measure of similarity.
With so much of our lives computerized, it is vitally important that machines and humans can understand one another and pass information back and forth. Mostly computers have things their way we have to & talk to them through relatively crude devices such as keyboards and mice so they can figure out what we want them to do. However, when it comes to processing more human kinds of information, like an old-fashioned printed book or a letter scribbled with a fountain pen, computers have to work much harder. That is where optical character recognition (OCR) comes in. Here we process the image, where we apply various pre-processing techniques like desk wing, binarization etc. and algorithms like Tesseract to recognize the characters and give us the final document. T.Gnana Prakash | K. Anusha"Text Extraction from Image using Python" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6 , October 2017, URL: http://www.ijtsrd.com/papers/ijtsrd2501.pdf http://www.ijtsrd.com/computer-science/simulation/2501/text-extraction-from-image-using-python/tgnana-prakash
Text detection and recognition in scene images or natural images has applications in computer
vision systems like registration number plate detection, automatic traffic sign detection, image retrieval
and help for visually impaired people. Scene text, however, has complicated background, blur image,
partly occluded text, variations in font-styles, image noise and ranging illumination. Hence scene text
recognition could be a difficult computer vision problem. In this paper connected component method
is used to extract the text from background. In this work, horizontal and vertical projection profiles,
geometric properties of text, image binirization and gap filling method are used to extract the text from
scene images. Then histogram based threshold is applied to separate text background of the images.
Finally text is extracted from images.
Skin Detection Based on Color Model and Low Level Features Combined with Expl...IJERA Editor
Skin detection is active research area in the field of computer vision which can be applied in the application of
face detection, eye detection, etc. These detection helps in various applications such as driver fatigue monitoring
system, surveillance system etc. In Computer vision applications, the color model and representations of the
human image in color model is one of major module to detect the skin pixels. The mainstream technology is
based on the individual pixels and selection of the pixels to detect the skin part in the whole image. In this thesis
implementation, we presents a novel technique for skin color detection incorporating with explicit region based
and parametric based approach which gives the better efficiency and performances in terms of skin detection in
human images. Color models and image quantization technique is used to extract the regions of the images and
to represent the image in a particular color model such as RGB and HSV, and then the parametric based
approach is applied by selecting the low level skin features are applied to extract the skin and non-skin pixels of
the images. In the first step, our technique uses the state-of-the-art non-parametric approach which we call the
template based technique or explicitly defined skin regions technique. Then the low level features of the human
skin are being extracted such as edge, corner detection which is also known as parametric method. The
experimental results depict the improvement in detection rate of the skin pixels by this novel approach. And in
the end we discuss the experimental results to prove the algorithmic improvements.
Texture features based text extraction from images using DWT and K-means clus...Divya Gera
Text extraction from different kind of images document, caption and scene text images. Discret wavelet transform was used to exract horizontal, vertical and diagonal features and k-means clustering was used to cluster the features into text and background cluster. For simple images k = 2 worked i.e. text and backgroud cluster while for complex images k=3 was used i.e. text cluster, complex background ad simple background.
K2 Algorithm-based Text Detection with An Adaptive Classifier ThresholdCSCJournals
In natural scene images, text detection is a challenging study area for dissimilar content-based image analysis tasks. In this paper, a Bayesian network scores are used to classify candidate character regions by computing posterior probabilities. The posterior probabilities are used to define an adaptive threshold to detect text in scene images with accuracy. Therefore, candidate character regions are extracted through maximally stable extremal region. K2 algorithm-based Bayesian network scores are learned by evaluating dependencies amongst features of a given candidate character region. Bayesian logistic regression classifier is trained to compute posterior probabilities to define an adaptive classifier threshold. The candidate character regions below from adaptive classifier threshold are discarded as non-character regions. Finally, text regions are detected with the use of effective text localization scheme based on geometric features. The entire system is evaluated on the ICDAR 2013 competition database. Experimental results produce competitive performance (precision, recall and harmonic mean) with the recently published algorithms.
SCENE TEXT RECOGNITION IN MOBILE APPLICATION BY CHARACTER DESCRIPTOR AND STRU...Cheriyan K M
In text detection, our
previously proposed algorithms are applied to obtain text regions
from scene image. First, we design a discriminative character
descriptor by combining several state-of-the-art feature detectors
and descriptors. Second, we model character structure at each
character class by designing stroke configuration maps.
Bangla Optical Digits Recognition using Edge Detection MethodIOSR Journals
Abstract:This paper is based on Bangla Optical Digit Recognition (ODR) by the Edge detection technique. In this method, Bangla digit image converted into gray-scale which distributed by an M by N array form. Here input data are considered off-line printed digit’s image which collected from computer generated image, scanned documents or printed text. After addressing the gray-scale image against a variable in the form of an M by N array, where the value of array pointers are shown 255 for total white space, 0 (zero) for total dark space and value between 255 and 0 for mix of white and dark space of the image. At the next process, four edgestouch points as well as each touch point’s ratio use as parameters to determine each Bangla digit uniquely. Keywords-Edge, image,gray-scale, Matrix,ODR.
TEXT DETECTION AND EXTRACTION FROM VIDEOS USING ANN BASED NETWORKijscai
With fast intensification of existing multimedia documents and mounting demand for information indexing and retrieval, much endeavor has been done on extracting the text from images and videos. The prime intention of the projected system is to spot and haul out the scene text from video. Extracting the scene text from video is demanding due to complex background, varying font size, different style, lower resolution and blurring, position, viewing angle and so on. In this paper we put forward a hybrid method where the two most well-liked text extraction techniques i.e. region based method and connected component (CC) based method comes together. Initially the video is split into frames and key frames obtained. Text region indicator (TRI) is being developed to compute the text prevailing confidence and
candidate region by performing binarization. Artificial Neural network (ANN) is used as the classifier and Optical Character Recognition (OCR) is used for character verification. Text is grouped by constructing the minimum spanning tree with the use of bounding box distance.
A colour-based building recognition using support vector machineTELKOMNIKA JOURNAL
Many applications apply the concept of image recognition to help human in recognising objects simply by just using digital images. A content-based building recognition system could solve the problem of using just text as search input. In this paper, a building recognition system using colour histogram is proposed for recognising buildings in Ipoh city, Perak, Malaysia. The colour features of each building image will be extracted. A feature vector combining the mean, standard deviation, variance, skewness and kurtosis of gray level will be formed to represent each building image. These feature values are later used to train the system using supervised learning algorithm, which is Support Vector Machine (SVM). Lastly, the accuracy of the recognition system is evaluated using 10-fold cross validation. The evaluation results show that the building recognition system is well trained and able to effectively recognise the building images with low misclassification rate.
A Survey On Thresholding Operators of Text Extraction In VideosCSCJournals
Video indexing is an important problem that has interested by the communities of visual information in image processing. The detection and extraction of scene and caption text from unconstrained, general purpose video is an important research problem in the context of content-based retrieval and summarization. In this paper, the technique presented is for detection text from frames video. Finding the textual contents in images is a challenging and promising research area in information technology. Consequently, text detection and recognition in multimedia had become one of the most important fields in computer vision due to its valuable uses in a variety of recent technical applications. The work in this paper consists using morphological operations for extract text appearing in the video frames. The proposed scheme well as preprocessing to differentiate among where it as the high similarity between text and background information. Experimental results show that the resultant image is the image with only text. The evaluated criteria are applied with the image result and one obtained bay different operator.
Optical Character Recognition from Text ImageEditor IJCATR
Optical Character Recognition (OCR) is a system that provides a full alphanumeric recognition of printed or handwritten
characters by simply scanning the text image. OCR system interprets the printed or handwritten characters image and converts it into
corresponding editable text document. The text image is divided into regions by isolating each line, then individual characters with
spaces. After character extraction, the texture and topological features like corner points, features of different regions, ratio of
character area and convex area of all characters of text image are calculated. Previously features of each uppercase and lowercase
letter, digit, and symbols are stored as a template. Based on the texture and topological features, the system recognizes the exact
character using feature matching between the extracted character and the template of all characters as a measure of similarity.
A Texture Based Methodology for Text Region Extraction from Low Resolution Na...CSCJournals
Automated systems for understanding display boards are finding many applications useful in guiding tourists, assisting visually challenged and also in providing location aware information. Such systems require an automated method to detect and extract text prior to further image analysis. In this paper, a methodology to detect and extract text regions from low resolution natural scene images is presented. The proposed work is texture based and uses DCT based high pass filter to remove constant background. The texture features are then obtained on every 50x50 block of the processed image and potential text blocks are identified using newly defined discriminant functions. Further, the detected text blocks are merged and refined to extract text regions. The proposed method is robust and achieves a detection rate of 96.6% on a variety of 100 low resolution natural scene images each of size 240x320.
BLOB DETECTION TECHNIQUE USING IMAGE PROCESSING FOR IDENTIFICATION OF MACHINE...ijiert bestjournal
Optical character recognition systems have been effectively developed for the recognition of p rinted characters. Optical character recognition is an awesome computer vision technique with various applications ranging from saving real time scripts digitally and deriving context based intelligence using natural language processing from the texts. One such application is the recognition of machine printed characters. This paper illustrates the technique to identify machine printed characters using Blob detection method and Image processing. In many cases of such machine printed characters there is simi larity between character colour and background colour. There is mix up of reflected light and scattered light. Colour is not consistent across character area or background area. Paper explains how Blob detection technique is used for recognition of these m achines printed characters.
Character recognition of kannada text in scene images using neuralIAEME Publication
Character recognition in scene images is one of the most fascinating and challenging
areas of pattern recognition with various practical application potentials. It can contribute
immensely to the advancement of an automation process and can improve the interface
between man and machine in many applications. Some practical application potentials of
character recognition system are: reading aid for the blind, traffic guidance systems, tour
guide systems, location aware systems and many more. In this work, a novel method for
recognizing basic Kannada characters in natural scene images is proposed. The proposed
method uses zone wise horizontal and vertical profile based features of character images. The
method works in two phases. During training, zone wise vertical and horizontal profile based
features are extracted from training samples and neural network is trained. During testing, the
test image is processed to obtain features and recognized using neural network classifier. The
method has been evaluated on 490 Kannada character images captured from 2 Mega Pixels
cameras on mobile phones at various sizes 240x320, 600x800 and 900x1200, which contains
samples of different sizes, styles and with different degradations, and achieves an average
recognition accuracy of 92%. The system is efficient and insensitive to the variations in size
and font, noise, blur and other degradations.
Digital camera and mobile document image acquisition are new trends arising in the world of Optical Character Recognition and text detection. In some cases, such process integrates many distortions and produces poorly scanned text or text-photo images and natural images, leading to an unreliable OCR digitization. In this paper, we present a novel nonparametric and unsupervised method to compensate for
undesirable document image distortions aiming to optimally improve OCR accuracy. Our approach relies on a very efficient stack of document image enhancing techniques to recover deformation of the entire document image. First, we propose a local brightness and contrast adjustment method to effectively handle lighting variations and the irregular distribution of image illumination. Second, we use an optimized greyscale conversion algorithm to transform our document image to greyscale level. Third, we sharpen the
useful information in the resulting greyscale image using Un-sharp Masking method. Finally, an optimal global binarization approach is used to prepare the final document image to OCR recognition. The proposed approach can significantly improve text detection rate and optical character recognition
accuracy. To demonstrate the efficiency of our approach, an exhaustive experimentation on a standard dataset is presented.
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.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...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 the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.