The emergence of event-focused social networks has led to a significant increase in online group memberships and event invitations for millions of people. Unlike traditional social platforms, event networks require physical attendance at gatherings or events as a crucial aspect of user engagement. However, managing event announcements, dates, times, and attendee information can be cumbersome, highlighting the necessity for an efficient event management system that simplifies event discovery and attendance while fostering social interactions among users. Such a system can substantially enhance the event experience for attendees while facilitating streamlined event planning for organizers. EventMingle, a web platform, addresses this need by providing a unique approach to connecting people in diverse locations to enrich their lives. Unlike conventional social networks, EventMingle revolves around arranging offline, in-person meetings rather than merely discussing shared interests online. These gatherings often take place in public venues such as cafes, parks, and occasionally private residences. By offering a platform for users to connect and engage in shared activities, EventMingle creates opportunities to forge new friendships, actively participate in the local community, and pursue passions more actively. Organizers utilize the website to create events, enabling individuals with common interests to connect and share their enthusiasm for specific topics. EventMingle serves as a user-friendly tool for discovering and attending events in one's local area. Given the abundance of events occurring daily, keeping track of everything, particularly for newcomers or those seeking specific types of events can be challenging. EventMingle simplifies this process by facilitating event discovery based on users' interests and providing comprehensive details such as dates, times, and locations. The platform's Meet-In feature allows users to find like-minded individuals, leading to the formation of close-knit communities centered around shared passions. This aspect of EventMingle is especially valuable for combating feelings of isolation and disconnection among users. Furthermore, EventMingle offers a valuable platform for personal growth and development. By connecting users with others who share similar interests. Meetup groups encourage mutual motivation and support, leading to personal growth opportunities. This feature proves particularly beneficial for individuals seeking motivation or fresh opportunities for self-improvement and advancement.
{"title":"EventMingle Management System","authors":"Madhavi Waghmare, Archana Ekbote, Anagha Patil, Vaishali Shirsath","doi":"10.17010/ijcs/2023/v8/i4/173265","DOIUrl":"https://doi.org/10.17010/ijcs/2023/v8/i4/173265","url":null,"abstract":"The emergence of event-focused social networks has led to a significant increase in online group memberships and event invitations for millions of people. Unlike traditional social platforms, event networks require physical attendance at gatherings or events as a crucial aspect of user engagement. However, managing event announcements, dates, times, and attendee information can be cumbersome, highlighting the necessity for an efficient event management system that simplifies event discovery and attendance while fostering social interactions among users. Such a system can substantially enhance the event experience for attendees while facilitating streamlined event planning for organizers. EventMingle, a web platform, addresses this need by providing a unique approach to connecting people in diverse locations to enrich their lives. Unlike conventional social networks, EventMingle revolves around arranging offline, in-person meetings rather than merely discussing shared interests online. These gatherings often take place in public venues such as cafes, parks, and occasionally private residences. By offering a platform for users to connect and engage in shared activities, EventMingle creates opportunities to forge new friendships, actively participate in the local community, and pursue passions more actively. Organizers utilize the website to create events, enabling individuals with common interests to connect and share their enthusiasm for specific topics. EventMingle serves as a user-friendly tool for discovering and attending events in one's local area. Given the abundance of events occurring daily, keeping track of everything, particularly for newcomers or those seeking specific types of events can be challenging. EventMingle simplifies this process by facilitating event discovery based on users' interests and providing comprehensive details such as dates, times, and locations. The platform's Meet-In feature allows users to find like-minded individuals, leading to the formation of close-knit communities centered around shared passions. This aspect of EventMingle is especially valuable for combating feelings of isolation and disconnection among users. Furthermore, EventMingle offers a valuable platform for personal growth and development. By connecting users with others who share similar interests. Meetup groups encourage mutual motivation and support, leading to personal growth opportunities. This feature proves particularly beneficial for individuals seeking motivation or fresh opportunities for self-improvement and advancement.","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136035172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-31DOI: 10.17010/ijcs/2023/v8/i4/173267
Deepak Jain
Supplier management became important in the 1970s and 1980s for manufacturing companies. This was driven by globalization and an expanding supplier base. The focus was then on a structured onboarding process and performance management. There was not much system support. Today, Supplier Relationship Management (SRM) has become a strategic tool to achieve competitive advantage through collaborations and partnerships. This paper focuses on how SRM software can be used to achieve this. It covers the SRM process, architecture and features of SRM software.
{"title":"Supplier Relationship Management","authors":"Deepak Jain","doi":"10.17010/ijcs/2023/v8/i4/173267","DOIUrl":"https://doi.org/10.17010/ijcs/2023/v8/i4/173267","url":null,"abstract":"Supplier management became important in the 1970s and 1980s for manufacturing companies. This was driven by globalization and an expanding supplier base. The focus was then on a structured onboarding process and performance management. There was not much system support. Today, Supplier Relationship Management (SRM) has become a strategic tool to achieve competitive advantage through collaborations and partnerships. This paper focuses on how SRM software can be used to achieve this. It covers the SRM process, architecture and features of SRM software.","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136036058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Potatoes are one of the most extensively consumed foods item, ranking as the 3rd largest staple food consumed throughout the world. Also, the demand for potato is expanding dramatically in the market, particularly due to the worldwide Coronavirus pandemic. However, potato diseases are the major cause of loss in the quality and quantity of the yield. Potato leaf blight is one of the most damaging global plant diseases because it impairs the productivity and quality of potato crop and badly impacts both individual farmers and the agricultural economy. Inappropriate classification and late diagnosis of the disease's type will severely impair the state of the potato plant. This study describes an architecture developed for potato leaf blight classification. This design depends on Deep Convolutional Neural Network (CNN). The methodology also takes use of Data Augmentation. The training dataset is visibly separated into three categories, namely, healthy leaves, early blight leaves and late blight leaves. The number of photos in the collection is 3000. The proposed design achieved an overall mean testing accuracy of 98%. The testing accuracy of the proposed approach was compared with that of comparable works, and the proposed architecture achieved improved accuracy compared to the related works.
{"title":"Potato Leaf Disease and its Classification Using Deep Learning","authors":"Sahil Patil, Aniket Korgaonkar, Shashank Nadankar, Archana Ekbote","doi":"10.17010/ijcs/2023/v8/i4/173264","DOIUrl":"https://doi.org/10.17010/ijcs/2023/v8/i4/173264","url":null,"abstract":"Potatoes are one of the most extensively consumed foods item, ranking as the 3rd largest staple food consumed throughout the world. Also, the demand for potato is expanding dramatically in the market, particularly due to the worldwide Coronavirus pandemic. However, potato diseases are the major cause of loss in the quality and quantity of the yield. Potato leaf blight is one of the most damaging global plant diseases because it impairs the productivity and quality of potato crop and badly impacts both individual farmers and the agricultural economy. Inappropriate classification and late diagnosis of the disease's type will severely impair the state of the potato plant. This study describes an architecture developed for potato leaf blight classification. This design depends on Deep Convolutional Neural Network (CNN). The methodology also takes use of Data Augmentation. The training dataset is visibly separated into three categories, namely, healthy leaves, early blight leaves and late blight leaves. The number of photos in the collection is 3000. The proposed design achieved an overall mean testing accuracy of 98%. The testing accuracy of the proposed approach was compared with that of comparable works, and the proposed architecture achieved improved accuracy compared to the related works.","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136034948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-20DOI: 10.21817/indjcse/2023/v14i4/231404002
Seun Ebiesuwa S, Obumneme Ukandu, Taye Falana, A. Adio, R. Kanu
This study investigates the impact of business intelligence and analytics (BIA) on decision-making in online reservation systems within the hospitality sector. This study presents a comprehensive review of ten research papers in the field of BIA within the hospitality sector. The findings indicate that organizations effectively leveraging BIA experience enhanced decision-making, improved operational efficiency, revenue growth, and customer satisfaction. Integration of BIA leads to improved customer experiences through personalization and recommendation systems. Adopting BIA tools results in significant operational efficiency gains by addressing issues in real-time. Effective utilization of BIA positively impacts revenue growth through optimized pricing strategies and demand forecasting. Despite implementation challenges, this study highlights the practical significance and benefits of BIA in online reservation systems, while providing recommendations for organizations. Future research directions include exploring artificial intelligence, examining ethical considerations, conducting industry-specific analyses, and assessing long-term impacts of BIA implementation in the hospitality sector
{"title":"IMPACT OF BUSINESS INTELLIGENCE AND ANALYTICS ON DECISIONMAKING IN ONLINE RESERVATION SYSTEMS WITHIN THE HOSPITALITY SECTOR","authors":"Seun Ebiesuwa S, Obumneme Ukandu, Taye Falana, A. Adio, R. Kanu","doi":"10.21817/indjcse/2023/v14i4/231404002","DOIUrl":"https://doi.org/10.21817/indjcse/2023/v14i4/231404002","url":null,"abstract":"This study investigates the impact of business intelligence and analytics (BIA) on decision-making in online reservation systems within the hospitality sector. This study presents a comprehensive review of ten research papers in the field of BIA within the hospitality sector. The findings indicate that organizations effectively leveraging BIA experience enhanced decision-making, improved operational efficiency, revenue growth, and customer satisfaction. Integration of BIA leads to improved customer experiences through personalization and recommendation systems. Adopting BIA tools results in significant operational efficiency gains by addressing issues in real-time. Effective utilization of BIA positively impacts revenue growth through optimized pricing strategies and demand forecasting. Despite implementation challenges, this study highlights the practical significance and benefits of BIA in online reservation systems, while providing recommendations for organizations. Future research directions include exploring artificial intelligence, examining ethical considerations, conducting industry-specific analyses, and assessing long-term impacts of BIA implementation in the hospitality sector","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44853621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-20DOI: 10.21817/indjcse/2023/v14i4/231404048
Omkar Bhosale, Aryan Dande, Sagar Abhyankar, Sarang A. Joshi
This paper presents an analysis of the performance of a convolutional neural network (CNN) for the classification of controlled and uncontrolled fires. The study focuses on the incorporation of custom features such as standard deviation, spikes, fall, vertical intensity arrays (VIA), and arc length to improve the accuracy of the model. These features were individually concatenated with the features selected by the neural network to test the cumulative performance. The paper also puts forth the comparison between a logical (decision tree) classifier and a black box (neural net) classifier and the corresponding performance analysis.
{"title":"INTEGRATION OF LOGICAL FEATURES WITH NEURAL NETWORKS FOR CONTROLLED VS UNCONTROLLED FIRE CLASSIFICATION: A COMPARATIVE STUDY","authors":"Omkar Bhosale, Aryan Dande, Sagar Abhyankar, Sarang A. Joshi","doi":"10.21817/indjcse/2023/v14i4/231404048","DOIUrl":"https://doi.org/10.21817/indjcse/2023/v14i4/231404048","url":null,"abstract":"This paper presents an analysis of the performance of a convolutional neural network (CNN) for the classification of controlled and uncontrolled fires. The study focuses on the incorporation of custom features such as standard deviation, spikes, fall, vertical intensity arrays (VIA), and arc length to improve the accuracy of the model. These features were individually concatenated with the features selected by the neural network to test the cumulative performance. The paper also puts forth the comparison between a logical (decision tree) classifier and a black box (neural net) classifier and the corresponding performance analysis.","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48619071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-20DOI: 10.21817/indjcse/2023/v14i4/231404086
Dr. Thippanna G., D. Albert, Ramachandra E.
In this review article explored massive amounts of data from big data are expected to revolutionize artificial intelligence (AI). The idea of Next-Gen Big Data Intelligence is the key component that powers AI platforms and helps to release its enormous and untapped potential for mass production and targeted consumption, which will have a significant impact on our society. When offering Big Data Intelligence, such game-changing technology must do so with openness, justice, trust, and reduced prejudice. Sadly, the current Big Data technologies veer off this course, where AI platforms typically operate within centralized proprietary organizations that manage, and control them, exposing critical issues of AI algorithmic and data bases, along with insidious and pervasive reinforcement of discriminatory societal practices. When utilizing unprocessed, noisy, or unintentionally biased data to train AI models, this is particularly troublesome.
{"title":"A REVIEW ON BIG DATA INTEGRATION's DIFFICULTIES WITH AI","authors":"Dr. Thippanna G., D. Albert, Ramachandra E.","doi":"10.21817/indjcse/2023/v14i4/231404086","DOIUrl":"https://doi.org/10.21817/indjcse/2023/v14i4/231404086","url":null,"abstract":"In this review article explored massive amounts of data from big data are expected to revolutionize artificial intelligence (AI). The idea of Next-Gen Big Data Intelligence is the key component that powers AI platforms and helps to release its enormous and untapped potential for mass production and targeted consumption, which will have a significant impact on our society. When offering Big Data Intelligence, such game-changing technology must do so with openness, justice, trust, and reduced prejudice. Sadly, the current Big Data technologies veer off this course, where AI platforms typically operate within centralized proprietary organizations that manage, and control them, exposing critical issues of AI algorithmic and data bases, along with insidious and pervasive reinforcement of discriminatory societal practices. When utilizing unprocessed, noisy, or unintentionally biased data to train AI models, this is particularly troublesome.","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45023197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Impact of Information Systems on Operational Efficiency: A Comprehensive Analysis","authors":"Ebiesuwa Seun, Gegeleso Babajide, Falana Taye, Adegbenjo Aderonke, Bamisile Olabode","doi":"10.21817/indjcse/2023/v14i4/231404013","DOIUrl":"https://doi.org/10.21817/indjcse/2023/v14i4/231404013","url":null,"abstract":"","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43922474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-20DOI: 10.21817/indjcse/2023/v14i4/231404107
A. T. Akinola, M. Adigun
The problem of network flow interference within a data centre network has been addressed by several scholars in the literature with a number of solutions provided. However, many of such solutions does not take into cognisance the relative cost effect of the proposals on the service providers and end-users. The solutions are either on the benefit of the service providers at the expense of the end-users and vice versa. We proposed a Multi-Criteria Optimization Crosspoint Queue which was able to address the traffic flow interference that results into both network instability and unbalanced provider-user relationship. The experimental results showed that the proposed approach is able to maintain a stable specified QoS metric as a single-parameter amidst several QoS and likewise balanced the cost effects on either side of the stakeholders. The solution is relevant to the network organization in prioritizing network quality to adapt to changing business requirements and market demands.
{"title":"BALANCING SERVICE PROVIDER AND END-USER REQUEST INTEREST IN AN SDN-ORIENTED DATA CENTRE NETWORK","authors":"A. T. Akinola, M. Adigun","doi":"10.21817/indjcse/2023/v14i4/231404107","DOIUrl":"https://doi.org/10.21817/indjcse/2023/v14i4/231404107","url":null,"abstract":"The problem of network flow interference within a data centre network has been addressed by several scholars in the literature with a number of solutions provided. However, many of such solutions does not take into cognisance the relative cost effect of the proposals on the service providers and end-users. The solutions are either on the benefit of the service providers at the expense of the end-users and vice versa. We proposed a Multi-Criteria Optimization Crosspoint Queue which was able to address the traffic flow interference that results into both network instability and unbalanced provider-user relationship. The experimental results showed that the proposed approach is able to maintain a stable specified QoS metric as a single-parameter amidst several QoS and likewise balanced the cost effects on either side of the stakeholders. The solution is relevant to the network organization in prioritizing network quality to adapt to changing business requirements and market demands.","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44037776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-20DOI: 10.21817/indjcse/2023/v14i4/231404068
Drakshayini K B, Anusuya M A
Handling and addressing the issues in disfluent speech is a challenging task. It is very tedious to identify and remove repetition at the pre-processing step. Many speech related applications such as speech to text alignment, voice based interactive system face these hurdles while designing an automatic disfluent speech recognition system. Since speaker can utter the repeated words partially or miss some words in between makes it challenging. Spectral parameters such as Energy, Entropy, Zero Crossing Rate and centroid are used to detect repetitions. The similarity scores between phonemes and syllabus are detected and computed by employing Dynamic time warping (DTW) and polynomial curve fitting (PCF) approaches. The reconstructed speech signal features are extracted using SWEC-multi tapering window of MFCC procedure. The extracted features are modelled using SVM yielding 85% of recognition accuracy with repetition detection accuracy as 78.04% automatically.
{"title":"Repetition Detection using Spectral Parameters and Multi tapering features","authors":"Drakshayini K B, Anusuya M A","doi":"10.21817/indjcse/2023/v14i4/231404068","DOIUrl":"https://doi.org/10.21817/indjcse/2023/v14i4/231404068","url":null,"abstract":"Handling and addressing the issues in disfluent speech is a challenging task. It is very tedious to identify and remove repetition at the pre-processing step. Many speech related applications such as speech to text alignment, voice based interactive system face these hurdles while designing an automatic disfluent speech recognition system. Since speaker can utter the repeated words partially or miss some words in between makes it challenging. Spectral parameters such as Energy, Entropy, Zero Crossing Rate and centroid are used to detect repetitions. The similarity scores between phonemes and syllabus are detected and computed by employing Dynamic time warping (DTW) and polynomial curve fitting (PCF) approaches. The reconstructed speech signal features are extracted using SWEC-multi tapering window of MFCC procedure. The extracted features are modelled using SVM yielding 85% of recognition accuracy with repetition detection accuracy as 78.04% automatically.","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43510818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-20DOI: 10.21817/indjcse/2023/v14i4/231404099
Mohammad A. Kausar
Most Universities now use websites as their main source of information where students can interact and exchange their pertinent information. Web accessibility refers to the creation and design of websites, platforms, and tools for all people (abled/disabled). This study analyzes the usability of 15 of India's best universities as determined by Webometrics/QS Ranking 2023. Three key assessment tools—TAW, WAVE, and EIII—are customized for the website analysis. These tools show us the findings of a website's compliance with the WCAG 2.1 (Web Content Accessibility Guidelines). The assessment also identified a few recurring mistakes that could be fixed by simply including accessibility features. The total analysis's findings also emphasized the need for these sites' usability to be improved. The paper offers a list of errors that, if fixed, will benefit user groups with various disabilities, as well as useful recommendations for enhancing these websites' accessibility so that their intended audiences can access the information they provide without any hindrance.
{"title":"Website Assessment and Feature Metrics of University's Website Accessibility: An Evaluation of 15 Top-Ranked Universities of India","authors":"Mohammad A. Kausar","doi":"10.21817/indjcse/2023/v14i4/231404099","DOIUrl":"https://doi.org/10.21817/indjcse/2023/v14i4/231404099","url":null,"abstract":"Most Universities now use websites as their main source of information where students can interact and exchange their pertinent information. Web accessibility refers to the creation and design of websites, platforms, and tools for all people (abled/disabled). This study analyzes the usability of 15 of India's best universities as determined by Webometrics/QS Ranking 2023. Three key assessment tools—TAW, WAVE, and EIII—are customized for the website analysis. These tools show us the findings of a website's compliance with the WCAG 2.1 (Web Content Accessibility Guidelines). The assessment also identified a few recurring mistakes that could be fixed by simply including accessibility features. The total analysis's findings also emphasized the need for these sites' usability to be improved. The paper offers a list of errors that, if fixed, will benefit user groups with various disabilities, as well as useful recommendations for enhancing these websites' accessibility so that their intended audiences can access the information they provide without any hindrance.","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46455416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：