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A Two-Level Multi-Modal Analysis for Depression Detection From Online Social Media 在线社交媒体抑郁检测的两层次多模态分析
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.309114
Dhrubasish Sarkar, Piyush Kumar, Poulomi Samanta, Suchandra Dutta, M. Chatterjee
{"title":"A Two-Level Multi-Modal Analysis for Depression Detection From Online Social Media","authors":"Dhrubasish Sarkar, Piyush Kumar, Poulomi Samanta, Suchandra Dutta, M. Chatterjee","doi":"10.4018/ijsi.309114","DOIUrl":"https://doi.org/10.4018/ijsi.309114","url":null,"abstract":"According to World Health Organization statistics, depression is a prominent cause of concern worldwide, leading to suicide in the majority of these cases if left untreated. Nowadays, social media is a great place for users to express themselves through text, emoticons, images, etc., which reflect their thoughts and moods. This has opened up the possibility of studying social networks in order to better comprehend the mental states of their participants. The primary goal of the research is to examine Twitter user personas and tweets in order to uncover traits that may signal depressive symptoms among online users. A two-level depression detection method is proposed in which suspected depressed individuals are identified using social media features, personality traits, temporal and sentiment analysis of user biographies. Using the support vector machine classifier, these qualities are integrated with additional linguistic and topic features to achieve an accuracy of 89%. According to the research, effective feature selection and their combinations aid in enhancing performance.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123648341","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}
引用次数: 1
Popularity Prediction of Video Content Over Cloud-Based CDN Using End User Interest 基于终端用户兴趣的基于云的CDN视频内容流行度预测
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.301227
R. Gupta, Shabbir Kurabadwala, P. Tiwari, Ankit Mundra
{"title":"Popularity Prediction of Video Content Over Cloud-Based CDN Using End User Interest","authors":"R. Gupta, Shabbir Kurabadwala, P. Tiwari, Ankit Mundra","doi":"10.4018/ijsi.301227","DOIUrl":"https://doi.org/10.4018/ijsi.301227","url":null,"abstract":"It is often believed that more is better, but that is not true in the case of data. As online data is increasing briskly, we are not able to handle such enormous data. With the increasing trends of speedy and uninterrupted access to data usage, CDNs have become quite popular in today’s world. However, it has become difficult to store all the content on CDN servers. This paper aims towards optimizing one of the aspects of CDN’s cached data that is video content. We propose a push-based caching approach by finding appropriate popular videos in accordance with a region to improve an end user’s quality of experience. A semi-supervised machine learning approach has been implemented to classify videos as low, medium, or highly popular. Popularity Prediction research has increased in energy lately. In any case, there has been little work done dependent on prior and significant video parameters for popularity prediction purposes. The experimental results show good accuracy, justifying the selection of parameters and the processing associated with them","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126462212","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}
引用次数: 0
Depression Identification Through Tweet Clusters 通过Tweet聚类识别抑郁症
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.297916
Abhishek Masand, Suryansh Chauhan, Tarun Jain
{"title":"Depression Identification Through Tweet Clusters","authors":"Abhishek Masand, Suryansh Chauhan, Tarun Jain","doi":"10.4018/ijsi.297916","DOIUrl":"https://doi.org/10.4018/ijsi.297916","url":null,"abstract":"Over the past few years, the awareness and popularity of Mental health have been on a rapid rise and people are becoming more aware of the surrounding problems. This has helped for mental illnesses like Depression to become recognized and be treated appropriately. Social media has played an integral part in this uproar due to its increased popularity and ease of use. This has allowed people to spread awareness, seek help and vent out their emotions. Our paper is a comparative study of different models for detecting depression with real-time Twitter data and proposing the best performing model. For depression detection, a collection of tweets per user spread over time was used. The data was augmented and then passed through the deep learning model to identify depression in Twitter users based on their Time-Distributed tweets. The proposed model achieved an accuracy of over 90%.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124633746","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}
引用次数: 1
A Secure Group Data Encryption Scheme in Intelligent Manufacturing Systems for IIoT 面向IIoT的智能制造系统安全组数据加密方案
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.312577
Ming-Te Chen
{"title":"A Secure Group Data Encryption Scheme in Intelligent Manufacturing Systems for IIoT","authors":"Ming-Te Chen","doi":"10.4018/ijsi.312577","DOIUrl":"https://doi.org/10.4018/ijsi.312577","url":null,"abstract":"In recent years, there are many industries that imported intelligent systems to help them make the intelligent factory and get product record analysis to evaluate product rate. These intelligent systems could generate product records, store them to the on-line database, and provide product rate analysis from these records. Due to the rapid development of internet of things (IoT), the stockholder can construct its own smart factory with the smart intelligent system to develop its own industrial internet of things (IIoT) architecture. With the help of IIoT, the smart intelligence system can collect data information with IoT sensors embedded into each machine in the production line. However, there are some security issues arising between smart intelligent systems and IoT devices. In addition, the authors also discovered that there are fewer methodologies to talk about the data security during the machine transmitting its censored data to the other machines under the same network environment.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114665843","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}
引用次数: 0
An Efficient Approach of Vehicle Detection Based on Deep Learning Algorithms and Wireless Sensors Networks 基于深度学习算法和无线传感器网络的高效车辆检测方法
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.309722
Cherifa Nakkach, A. Zrelli, T. Ezzedine
{"title":"An Efficient Approach of Vehicle Detection Based on Deep Learning Algorithms and Wireless Sensors Networks","authors":"Cherifa Nakkach, A. Zrelli, T. Ezzedine","doi":"10.4018/ijsi.309722","DOIUrl":"https://doi.org/10.4018/ijsi.309722","url":null,"abstract":"Machine learning is applied to analyze and classify automatically images. Artificial intelligence (AI) is considered very successful in this area. Therefore, AI is exploited to evaluate the opportunities of big data and to extract value from massive and varied data sources. In order to detect any event (person, vehicle, dog, eyes, traffic, terrorist activity), ML is explored. Hence, advanced ML techniques recur to multimedia wireless sensor networks (MWSN) to detect any event in the considered area. In this work, the authors propose an enhanced architecture MWSN, which is able fly any event detection. In this context, this paper addresses the problem of vehicle detection using convolutional neural networks using a proposed architecture MWSN. Therefore, to reach this goal, the authors assess the performance of three state-of-the-art CNN algorithms, namely faster R-CNN, which is the most popular region-based algorithm; YOLO, which is known to be the fastest one; and SSD, which takes one single shot to detect multiple objects within the image.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114771592","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}
引用次数: 4
Geolocation-Based Mobile Application 基于地理位置的移动应用程序
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.297513
Twana Mustafa, Zardasht Abdulaziz Shwany, Shwan Hadi Saeed, Karwan Khoshnaw, Shayda Khudhur Ismail, Rzgar Farooq Rashid
{"title":"Geolocation-Based Mobile Application","authors":"Twana Mustafa, Zardasht Abdulaziz Shwany, Shwan Hadi Saeed, Karwan Khoshnaw, Shayda Khudhur Ismail, Rzgar Farooq Rashid","doi":"10.4018/ijsi.297513","DOIUrl":"https://doi.org/10.4018/ijsi.297513","url":null,"abstract":"Geolocation denotes the position of an object in a geographical context. The geolocation algorithm is characterized by four M’s: which Measurements are used, the Map, the Motion model used for describing the motion of the object, and the filtering Method. In this paper describe a general framework for geolocation based on the particle filter and android studio will use for design and programming also google firebase will use as a database for save location and to display only the ones that are within one kilometer’s radius from the user carnet location. In this app when locations save or select or make filtering the app describes a place and will show all information about the place that has been selected on the map. Several examples based on real data are used to illustrate various combinations of sensors and maps for geolocation. Finally, and aim of this paper, investigate efficient ways to store geolocation in google firebase as a set of latitude and longitude based on mobile and web.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116648382","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}
引用次数: 2
Orrs Orchestration of a Resource Reservation System Using Fuzzy Theory in High-Performance Computing: Lifeline of the Computing World 基于模糊理论的高性能计算资源预留系统的编排:计算世界的生命线
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.297923
Ashish Tiwari, R. Garg
{"title":"Orrs Orchestration of a Resource Reservation System Using Fuzzy Theory in High-Performance Computing: Lifeline of the Computing World","authors":"Ashish Tiwari, R. Garg","doi":"10.4018/ijsi.297923","DOIUrl":"https://doi.org/10.4018/ijsi.297923","url":null,"abstract":"In the computing world, every company is focusing on the early reservation system. In the early reservation the price, quality of service, time, and everything is maintained and reserved for the user on the due interval. ORRS is a step toward this global vision and specifically designed to act as a flexible reservation supporting multiple services according to user's need and pricing (such as traditional immediate reservation (TIR) request and ORRS reservation. Thus, it is both important and challenging to reserve computing services and the cost of the services in an efficient manner. In the ORRS reservation system, the fuzzy rough set feature selection decreases the dimensional structure and problems of a large database in the computing world. The researcher is now going at a rapid speed in the field of maintaining cost based on decision making like on-demand, reserved, the spot to increase resources utilization and profit. The implementation had done in our research work by the use of cloud simulator.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117020640","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}
引用次数: 11
E-Monitoring System: Analyzing the Benefits and Effects of an E-Monitoring System in the Banks of Kerala 电子监控系统:喀拉拉邦银行电子监控系统的效益和效果分析
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.311507
V. Bharathiveena, Janardhanan Pillai
{"title":"E-Monitoring System: Analyzing the Benefits and Effects of an E-Monitoring System in the Banks of Kerala","authors":"V. Bharathiveena, Janardhanan Pillai","doi":"10.4018/ijsi.311507","DOIUrl":"https://doi.org/10.4018/ijsi.311507","url":null,"abstract":"The purpose of this study is to examine the benefits and effects of electronic monitoring system and measures the performance of employees and satisfaction of customers. The following topics are essential to the study: the benefits and effects of e-monitoring to the customers and employees are self-control, self-realization, job stability, confidence, enhanced productivity, lazy employee removal, increased creativity, and negativism elimination. The recommended task is broken into two stages: The first step is to collect the data using the prepared questionnaire from the customers and employees of Kerala banks. 125 data were collected using the prepared questionnaire from the employees and customers of Kerala banking service and the format of the questionnaire is based on the proposed hypothesis. In the second step, ANOVA and SEM are used to evaluate the collected data.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117294982","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}
引用次数: 1
Traffic Data Collection and Visualization Tool for Knowledge Discovery Using Google Maps 交通数据收集和可视化工具的知识发现使用谷歌地图
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.293270
Iftekhar Hossain, Naushin Nower
{"title":"Traffic Data Collection and Visualization Tool for Knowledge Discovery Using Google Maps","authors":"Iftekhar Hossain, Naushin Nower","doi":"10.4018/ijsi.293270","DOIUrl":"https://doi.org/10.4018/ijsi.293270","url":null,"abstract":"Traffic jam is increasingly aggravating in almost every urban area. Traffic forecast, traffic modeling, visualization can help to provide appropriate route and time for traveling and thus provides a significant impact on traffic jam reduction. For traffic forecasting, modeling and visualization, city-wide traffic data collection and analysis are needed, which is still challenging in many aspects. This paper aims to develop a tool for acquiring and processing traffic data from Google Maps that can be used for forecasting, modeling, and visualization. Dhaka city is used as a case study since there is no infrastructure available for traffic data collection. The traffic flow intensity of the road is analyzed to determine the congestion of the road. The flow intensity is used for traffic modeling, visualization, traffic prediction and many more.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115182130","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}
引用次数: 2
Scene Categorization From Indoor-Outdoor Images Using Hybrid MAMF-Based Deep Convolutional Neural Networks 基于混合mamf的深度卷积神经网络对室内外图像进行场景分类
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.301229
J. D. Pakhare, M. Uplane
{"title":"Scene Categorization From Indoor-Outdoor Images Using Hybrid MAMF-Based Deep Convolutional Neural Networks","authors":"J. D. Pakhare, M. Uplane","doi":"10.4018/ijsi.301229","DOIUrl":"https://doi.org/10.4018/ijsi.301229","url":null,"abstract":"Image scene categorization is the dominant research area, where the localization of the objects along with the background is performed. At the current scenario, existing classifiers fail to provide the accuracy for the classification. Therefore, a novel approach for image scene categorization is performed using the hybrid features and the Hybrid technique named Mayfly Moth Flame (MAMF) optimization algorithm dependent Deep Convolutional Neural Network (MAMF-based Deep CNN) classifier, which positively impacts on the classification accuracy. This algorithm tunes the classifier towards acquiring the optimal classification performance from the classifier and is developed through interbreeding the characteristic features of the vermins and the caddisflies. The significance of the hybrid features for the classification is implemented and analyzed using the MAMF-based deep CNN classifier. The experimental analysis reveals that the proposed Hybrid features with MAMF-based Deep CNN classifier attains highest accuracy of 96.7215 % and 94.8684 % using SCID2 and SUN-397 datasets, respectively.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"363 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122843411","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}
引用次数: 0
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