Pub Date : 2023-12-01DOI: 10.3844/jcssp.2023.1505.1519
Apoorva Muppidi, Ahmad Sobri Hashim, Mohd Hilmi Hasan, Aminu Aminu Muazu
: Interactive dashboards are becoming increasingly popular for aiding users with data discovery and BI analysis. As UX is an important factor in developing Business Intelligence (BI) dashboards, the majority of current research centers around the evaluation of the User Experience (UX) in Business Intelligence (BI) dashboards, but there are only a few studies that focus on the UX aspect of designing and developing such dashboards and most of the dashboards were developed without considering the human aspects. Therefore, the absence of UX in dashboard development can make it difficult for users to understand and fully utilize the dashboard, which leads to a lack of effectiveness. Therefore, there is a need to consider UX factors while designing and developing BI dashboards. The main aim of this study is to develop a UX Model by including both user experience and business intelligence dashboard elements for designing and developing the BI dashboards. In this research, we proposed a user experience by considering the elements of UX and BI dashboards from the existing literature, validated the model by conducting FGD, and analyzed FGD comments by applying the thematic analysis method. Based on the result after conducting analysis we updated the proposed model. The developed model can guide the developer while designing and developing the BI dashboard.
{"title":"A Conceptual UX Model for Designing and Developing the Business Intelligence Dashboards","authors":"Apoorva Muppidi, Ahmad Sobri Hashim, Mohd Hilmi Hasan, Aminu Aminu Muazu","doi":"10.3844/jcssp.2023.1505.1519","DOIUrl":"https://doi.org/10.3844/jcssp.2023.1505.1519","url":null,"abstract":": Interactive dashboards are becoming increasingly popular for aiding users with data discovery and BI analysis. As UX is an important factor in developing Business Intelligence (BI) dashboards, the majority of current research centers around the evaluation of the User Experience (UX) in Business Intelligence (BI) dashboards, but there are only a few studies that focus on the UX aspect of designing and developing such dashboards and most of the dashboards were developed without considering the human aspects. Therefore, the absence of UX in dashboard development can make it difficult for users to understand and fully utilize the dashboard, which leads to a lack of effectiveness. Therefore, there is a need to consider UX factors while designing and developing BI dashboards. The main aim of this study is to develop a UX Model by including both user experience and business intelligence dashboard elements for designing and developing the BI dashboards. In this research, we proposed a user experience by considering the elements of UX and BI dashboards from the existing literature, validated the model by conducting FGD, and analyzed FGD comments by applying the thematic analysis method. Based on the result after conducting analysis we updated the proposed model. The developed model can guide the developer while designing and developing the BI dashboard.","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138612589","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 : 2023-12-01DOI: 10.3844/jcssp.2023.1580.1593
Boris Tunjić, A. Bernik, Andrej Cep
: One of the main challenges in aerial photogrammetry is the lack of standardization in the process of data integration, which is the first step in 3D reconstruction. This study analyses the influence of the distance from the camera to the subject of the recording, the influence of different overlap percentages in photography as well as the difference between the three methods of re-cording in programming flight plans. DJI Phantom 3 unmanned aerial vehicle and PIX4Dmapper software for 3D reconstruction were used in this research. The old town of Medvedgrad near Zagreb, Croatia was the subject of recording. The purpose of this study is to design a standardized image recording protocol that would contribute to a faster and more optimal workflow while maintaining a quantitatively measured quality according to the total number of 2D key points per image and the total number of 3D key points in a point cloud. Based on research and the obtained results, the possibility of data recording at a distance of up to 30 m without a significant loss (3.6%) of the number of 2D key points per photograph was proven. A larger horizontal distance allows recording from one viewing altitude if the height of the subject does not exceed 30 m. This study determines that 85% image overlap results in an almost identical number of 3D key points (0.7% difference) as well as 90% image overlap. The authors proposed a new flight plan, which would implement optimized parameters obtained in this research.
{"title":"Analysis and Design of Protocol for the Reconstruction of Computer Field Model Using Dron and Photogrammetry","authors":"Boris Tunjić, A. Bernik, Andrej Cep","doi":"10.3844/jcssp.2023.1580.1593","DOIUrl":"https://doi.org/10.3844/jcssp.2023.1580.1593","url":null,"abstract":": One of the main challenges in aerial photogrammetry is the lack of standardization in the process of data integration, which is the first step in 3D reconstruction. This study analyses the influence of the distance from the camera to the subject of the recording, the influence of different overlap percentages in photography as well as the difference between the three methods of re-cording in programming flight plans. DJI Phantom 3 unmanned aerial vehicle and PIX4Dmapper software for 3D reconstruction were used in this research. The old town of Medvedgrad near Zagreb, Croatia was the subject of recording. The purpose of this study is to design a standardized image recording protocol that would contribute to a faster and more optimal workflow while maintaining a quantitatively measured quality according to the total number of 2D key points per image and the total number of 3D key points in a point cloud. Based on research and the obtained results, the possibility of data recording at a distance of up to 30 m without a significant loss (3.6%) of the number of 2D key points per photograph was proven. A larger horizontal distance allows recording from one viewing altitude if the height of the subject does not exceed 30 m. This study determines that 85% image overlap results in an almost identical number of 3D key points (0.7% difference) as well as 90% image overlap. The authors proposed a new flight plan, which would implement optimized parameters obtained in this research.","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138621380","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}
Since several active pharmaceutical ingredients are sourced from medicinal plants, identifying and classifying these plants are generally a valuable and essential task during the drug manufacturing process. For many years, identifying and classifying those plants have been exclusively done by experts in the domain, such as botanists and herbarium curators. Recently, powerful computer vision technologies, using deep learning or deep artificial neural networks, have been developed for classifying or identifying objects using images. A convolutional neural network is a deep learning architecture that outperforms previous state-of-the-art approaches in image classification and object detection based on its efficient feature extraction of images. This study investigated several pre-trained convolutional neural networks for identifying and classifying leaves of three species of the genus Brachylaena. The three species considered were Brachylaena discolor, Brachylaena ilicifolia, and Brachylaena elliptica. All three species are used medicinally by people in South Africa. We trained and evaluated different deep convolutional neural networks from 1259 labeled images of those plant species (at least 400 for each species) split into training, evaluation, and test sets. The best model provided a 98.26% accuracy using cross-validation with a confidence interval of ±2.16%.
{"title":"Dataset of Selected Medicinal Plant Species of the Genus Brachylaena: A Comparative Application of Deep Learning Models for Plant Leaf Recognition","authors":"Avuya Deyi, Arnaud Nguembang Fadja, Eleonora Deborah Goosen, Xavier Siwe Noundou","doi":"10.3844/jcssp.2023.1387.1397","DOIUrl":"https://doi.org/10.3844/jcssp.2023.1387.1397","url":null,"abstract":"Since several active pharmaceutical ingredients are sourced from medicinal plants, identifying and classifying these plants are generally a valuable and essential task during the drug manufacturing process. For many years, identifying and classifying those plants have been exclusively done by experts in the domain, such as botanists and herbarium curators. Recently, powerful computer vision technologies, using deep learning or deep artificial neural networks, have been developed for classifying or identifying objects using images. A convolutional neural network is a deep learning architecture that outperforms previous state-of-the-art approaches in image classification and object detection based on its efficient feature extraction of images. This study investigated several pre-trained convolutional neural networks for identifying and classifying leaves of three species of the genus Brachylaena. The three species considered were Brachylaena discolor, Brachylaena ilicifolia, and Brachylaena elliptica. All three species are used medicinally by people in South Africa. We trained and evaluated different deep convolutional neural networks from 1259 labeled images of those plant species (at least 400 for each species) split into training, evaluation, and test sets. The best model provided a 98.26% accuracy using cross-validation with a confidence interval of ±2.16%.","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135111392","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 : 2023-11-01DOI: 10.3844/jcssp.2023.1359.1368
Heersh Azeez Khorsheed, Sadegh Aminifar
Nowadays, due to the high volume of choices for customers which causes confusion, the use of recommender systems is strongly growing. Of course, existing systems have two problems, one is complexity and the other is failure to consider uncertainty. In this article, we have reduced the complexity of the system by using a fuzzy innovative system and solved the problem of the uncertainty of users' ratings regarding goods. For that purpose, this research attempts to extract fuzzy membership functions from the Yahoo movie dataset for recommendation applications. In the proposed method, a type I fuzzy system with low numbers of membership functions is designed. The uncertainty in users' ratings is handled by clustering users and movies. Moreover, repeated user evaluations of the same movies are used to determine the uncertainty in improved type 1 membership functions. To evaluate the proposed strategy, MAE, confusion matrix, and Classification-report are used. The result demonstrates the superiority of the introduced strategy.
{"title":"Measuring Uncertainty to Extract Fuzzy Membership Functions in Recommender Systems","authors":"Heersh Azeez Khorsheed, Sadegh Aminifar","doi":"10.3844/jcssp.2023.1359.1368","DOIUrl":"https://doi.org/10.3844/jcssp.2023.1359.1368","url":null,"abstract":"Nowadays, due to the high volume of choices for customers which causes confusion, the use of recommender systems is strongly growing. Of course, existing systems have two problems, one is complexity and the other is failure to consider uncertainty. In this article, we have reduced the complexity of the system by using a fuzzy innovative system and solved the problem of the uncertainty of users' ratings regarding goods. For that purpose, this research attempts to extract fuzzy membership functions from the Yahoo movie dataset for recommendation applications. In the proposed method, a type I fuzzy system with low numbers of membership functions is designed. The uncertainty in users' ratings is handled by clustering users and movies. Moreover, repeated user evaluations of the same movies are used to determine the uncertainty in improved type 1 membership functions. To evaluate the proposed strategy, MAE, confusion matrix, and Classification-report are used. The result demonstrates the superiority of the introduced strategy.","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135111396","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 : 2023-11-01DOI: 10.3844/jcssp.2023.1305.1317
Islam Alexandrovich Alexandrov, Andrey Victorovich Kirichek, Vladimir Zhanovich Kuklin, Alexander Nikolaevich Muranov, Leonid Mikhajlovich Chervyakov
The Information Protection System (IPS) is an integral part of any Information System (IS). To develop an optimal IPS model at the earliest stages of the IS lifecycle, it is necessary to develop IS resource and threat models. This study is devoted to developing a specific model of IS resources, allowing a detailed description of the relationship between resources and business processes and developing an IS threat model to describe in detail the relationships between threat implementations, various IS vulnerabilities, and the relationships between them. To solve these problems, this study used the methods of set theory, graph theory, probability theory, game theory, random processes theory, mathematical logic, and object-oriented approach. This study simulated different variants of the IPS and found that only a balanced IPS project met the Pareto demands. The projects where the emphasis is on countering only external or internal threats do not meet these demands.
{"title":"Developing the Concept of Methodological Support for Designing and Assessing the Efficiency of Information Protection Systems of Standard Information Systems Considering Their Vulnerabilities","authors":"Islam Alexandrovich Alexandrov, Andrey Victorovich Kirichek, Vladimir Zhanovich Kuklin, Alexander Nikolaevich Muranov, Leonid Mikhajlovich Chervyakov","doi":"10.3844/jcssp.2023.1305.1317","DOIUrl":"https://doi.org/10.3844/jcssp.2023.1305.1317","url":null,"abstract":"The Information Protection System (IPS) is an integral part of any Information System (IS). To develop an optimal IPS model at the earliest stages of the IS lifecycle, it is necessary to develop IS resource and threat models. This study is devoted to developing a specific model of IS resources, allowing a detailed description of the relationship between resources and business processes and developing an IS threat model to describe in detail the relationships between threat implementations, various IS vulnerabilities, and the relationships between them. To solve these problems, this study used the methods of set theory, graph theory, probability theory, game theory, random processes theory, mathematical logic, and object-oriented approach. This study simulated different variants of the IPS and found that only a balanced IPS project met the Pareto demands. The projects where the emphasis is on countering only external or internal threats do not meet these demands.","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135111399","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}
Nowadays, companies are immersed in disruptive environments. To thrive in the ‘new normal’, they drive strategic initiatives resulting in changes with unpredictable frequencies and extents. These changes impact different elements of the company, which makes them a crucial matter for enterprise architecture. However, the traditional management operating models have become overstrained, which leads to existential threats. Therefore, the adaptation of enterprise architecture has emerged. It is an agile approach that continuously senses and responds to change without compromising the alignment in the enterprise. The management of the impact of strategic initiatives is pivotal to the success of companies. Overall, in the context of adaptation, contributions to the proactive assessment and monitoring of the impact of strategic initiatives on enterprise architecture are lacking. Therefore, this study aims to model this impact and evaluate it while focusing on the enterprise architecture structural components and their relationships. It proposes tools to support the analysis. Thereafter, it indicates the applicability of the suggested approach via a case study in a state urban planning agency.
{"title":"Impact of Strategic Initiatives on the Adaptation of Enterprise Architecture","authors":"Wissal Daoudi, Kawtar Imgharene, Karim Doumi, Laila Kjiri","doi":"10.3844/jcssp.2023.1318.1332","DOIUrl":"https://doi.org/10.3844/jcssp.2023.1318.1332","url":null,"abstract":"Nowadays, companies are immersed in disruptive environments. To thrive in the ‘new normal’, they drive strategic initiatives resulting in changes with unpredictable frequencies and extents. These changes impact different elements of the company, which makes them a crucial matter for enterprise architecture. However, the traditional management operating models have become overstrained, which leads to existential threats. Therefore, the adaptation of enterprise architecture has emerged. It is an agile approach that continuously senses and responds to change without compromising the alignment in the enterprise. The management of the impact of strategic initiatives is pivotal to the success of companies. Overall, in the context of adaptation, contributions to the proactive assessment and monitoring of the impact of strategic initiatives on enterprise architecture are lacking. Therefore, this study aims to model this impact and evaluate it while focusing on the enterprise architecture structural components and their relationships. It proposes tools to support the analysis. Thereafter, it indicates the applicability of the suggested approach via a case study in a state urban planning agency.","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135111400","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 : 2023-11-01DOI: 10.3844/jcssp.2023.1345.1358
Pavithra S, B. Muruganantham
Artificial Intelligence (AI) is a technique that incorporates human intelligence into mundane activities. And there is no question that AI is significantly affecting security and surveillance. Although relying on numerous resources, finding answers, and implementing technology for decades, our security and surveillance systems still have flaws. In every country around the globe, the use of video security and surveillance is becoming more widespread. Nonetheless, a wide range of businesses has made use of it, including hospitals, universities, and warehouses. Yet, as people are limited in their ability to vigilantly monitor live video streams, deep learning was developed to better fill the position. Unfortunately, there are other problems with images in the real world, including jitter or blurring caused by rotating objects, noise, and sharpness concerns. As a result, deep learning technology for surveillance has considerably improved in recent years. The main objective of this study is to detect burglars using deep learning technology. This system aims to take video surveillance of the residential environment as input and pass it into the Yolo model to increase the speed and accuracy of the system to detect burglars in the residential. This system mainly concentrates on object detection.
{"title":"Panoramic Video Surveillance: An Analysis of Burglary Detection Based on YOLO Framework in Residential Areas","authors":"Pavithra S, B. Muruganantham","doi":"10.3844/jcssp.2023.1345.1358","DOIUrl":"https://doi.org/10.3844/jcssp.2023.1345.1358","url":null,"abstract":"Artificial Intelligence (AI) is a technique that incorporates human intelligence into mundane activities. And there is no question that AI is significantly affecting security and surveillance. Although relying on numerous resources, finding answers, and implementing technology for decades, our security and surveillance systems still have flaws. In every country around the globe, the use of video security and surveillance is becoming more widespread. Nonetheless, a wide range of businesses has made use of it, including hospitals, universities, and warehouses. Yet, as people are limited in their ability to vigilantly monitor live video streams, deep learning was developed to better fill the position. Unfortunately, there are other problems with images in the real world, including jitter or blurring caused by rotating objects, noise, and sharpness concerns. As a result, deep learning technology for surveillance has considerably improved in recent years. The main objective of this study is to detect burglars using deep learning technology. This system aims to take video surveillance of the residential environment as input and pass it into the Yolo model to increase the speed and accuracy of the system to detect burglars in the residential. This system mainly concentrates on object detection.","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135111394","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 : 2023-11-01DOI: 10.3844/jcssp.2023.1380.1386
Foziah Gazzawe
: Covid-19 is one of the pandemics that has shocked the world. Having originated from China, the virus rapidly spread across many countries of the world. There was a need to come up with mechanisms to manage the spread of the virus. The traditional methods of temperature capture through thermal handheld gun thermometers were tedious and exposed the officers to the same virus. Therefore, due to technological advancement, the Internet of Things has been widely used with smart devices being developed. This study proposes an IoT-enabled smart helmet that scans individuals for high temperatures using a thermal camera, identifies individuals by capturing their images using an optical camera, and sends alerts and information to authorized officers’ decision-making and further action. For instance, they would notify the identified individual and give guidelines on how to self-manage based on the COVID-19 management guidelines such as quarantine, exercise, self-distance, handwashing, sanitizing, and dietary needs. The integration of technologies in the smart helmet application is beneficial in addressing safety measures and enhanced healthcare and monitoring of patients. For instance, in crowded areas, manual testing can be challenging hence the need for a contactless screening. The implications in real-time data analysis, concurrency, Human-Computer Interaction, remote monitoring, data security, and interdisciplinary collaboration have enhanced operation and decision-making. The knowledge, once tested, will form the basis for advanced research and implementations in various domains such as manufacturing industries. The methodology involved data capture (input), processing, and output. Materials used include thermal and optical cameras for data input, GSM and Google location applications, Arduino IDE, and mobile phone applications. The study used simulation at a mall's entry point and captured the temperature of 8 individuals. Out of the 8 individuals, 3 had high temperatures whereas the rest registered normal temperatures. Temperature measurements were verified by healthcare personnel through a second measure of temperature.
{"title":"IOT-Based Smart Helmet for COVID-19 Detection and Management","authors":"Foziah Gazzawe","doi":"10.3844/jcssp.2023.1380.1386","DOIUrl":"https://doi.org/10.3844/jcssp.2023.1380.1386","url":null,"abstract":": Covid-19 is one of the pandemics that has shocked the world. Having originated from China, the virus rapidly spread across many countries of the world. There was a need to come up with mechanisms to manage the spread of the virus. The traditional methods of temperature capture through thermal handheld gun thermometers were tedious and exposed the officers to the same virus. Therefore, due to technological advancement, the Internet of Things has been widely used with smart devices being developed. This study proposes an IoT-enabled smart helmet that scans individuals for high temperatures using a thermal camera, identifies individuals by capturing their images using an optical camera, and sends alerts and information to authorized officers’ decision-making and further action. For instance, they would notify the identified individual and give guidelines on how to self-manage based on the COVID-19 management guidelines such as quarantine, exercise, self-distance, handwashing, sanitizing, and dietary needs. The integration of technologies in the smart helmet application is beneficial in addressing safety measures and enhanced healthcare and monitoring of patients. For instance, in crowded areas, manual testing can be challenging hence the need for a contactless screening. The implications in real-time data analysis, concurrency, Human-Computer Interaction, remote monitoring, data security, and interdisciplinary collaboration have enhanced operation and decision-making. The knowledge, once tested, will form the basis for advanced research and implementations in various domains such as manufacturing industries. The methodology involved data capture (input), processing, and output. Materials used include thermal and optical cameras for data input, GSM and Google location applications, Arduino IDE, and mobile phone applications. The study used simulation at a mall's entry point and captured the temperature of 8 individuals. Out of the 8 individuals, 3 had high temperatures whereas the rest registered normal temperatures. Temperature measurements were verified by healthcare personnel through a second measure of temperature.","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139293115","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 : 2023-11-01DOI: 10.3844/jcssp.2023.1292.1304
Vidhi Thakkar, Vrushank Manharlal Shah
The Blockchain boom began with the debut of Bitcoin. The application of blockchain technology is expanding rapidly. Various sectors such as supply chain, logistics, research, healthcare, government, banking, media, and entertainment have already embraced this ground-breaking, decentralized technology. The healthcare industry is at the top of the list with significant blockchain potential. This article discusses the permissioned blockchain powered by Hyperledger Fabric and its privacy-preserving features like identity mixer, multichannel, private data collections, and transient field. This study considers the EHR systems scenario and proves how these privacy protection techniques of Fabric could protect the privacy of healthcare organizations' sensitive data. We evaluate existing studies on the use of the Hyperledger Fabric framework for EHR systems. We discovered that their implementation has data privacy and user privacy concerns that can be addressed in our future studies.
{"title":"Empowering Privacy: Harnessing Hyperledger Fabric to Safeguard EHR Systems","authors":"Vidhi Thakkar, Vrushank Manharlal Shah","doi":"10.3844/jcssp.2023.1292.1304","DOIUrl":"https://doi.org/10.3844/jcssp.2023.1292.1304","url":null,"abstract":"The Blockchain boom began with the debut of Bitcoin. The application of blockchain technology is expanding rapidly. Various sectors such as supply chain, logistics, research, healthcare, government, banking, media, and entertainment have already embraced this ground-breaking, decentralized technology. The healthcare industry is at the top of the list with significant blockchain potential. This article discusses the permissioned blockchain powered by Hyperledger Fabric and its privacy-preserving features like identity mixer, multichannel, private data collections, and transient field. This study considers the EHR systems scenario and proves how these privacy protection techniques of Fabric could protect the privacy of healthcare organizations' sensitive data. We evaluate existing studies on the use of the Hyperledger Fabric framework for EHR systems. We discovered that their implementation has data privacy and user privacy concerns that can be addressed in our future studies.","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135111393","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 : 2023-11-01DOI: 10.3844/jcssp.2023.1333.1344
Evaristus Didik Madyatmadja, None Aldi, Fiona Fheren, Helen Angelica, Hanny Juwitasary, David Jumpa Malem Sembiring
This research aims to classify Short Message Service (SMS) data by applying classification models that have studied SMS data to classify SMS data into SMS spam and SMS ham. The classification model is made from data mining algorithms: Naive Bayes and support vector machine. Before implementing the two algorithms, the SMS data will go through a text preprocessing stage, including data cleaning (whitespace removal, removal of punctuation, and removal of numbers), case folding, stemming, tokenizing, and stop word removal. In this research, a comparison of the accuracy of the two data mining methods will be carried out to see and get the best classification algorithm. Researchers also implemented several experiments by comparing the use of testing data by 20 and 30% and comparing the application of preprocessing stemming and without stemming. This study found that the support vector machine algorithm using testing data of 20% by applying the stemming stage had the highest accuracy rate, 97.5%.
{"title":"Comparative Study: Algorithms for Short Message Service Classification","authors":"Evaristus Didik Madyatmadja, None Aldi, Fiona Fheren, Helen Angelica, Hanny Juwitasary, David Jumpa Malem Sembiring","doi":"10.3844/jcssp.2023.1333.1344","DOIUrl":"https://doi.org/10.3844/jcssp.2023.1333.1344","url":null,"abstract":"This research aims to classify Short Message Service (SMS) data by applying classification models that have studied SMS data to classify SMS data into SMS spam and SMS ham. The classification model is made from data mining algorithms: Naive Bayes and support vector machine. Before implementing the two algorithms, the SMS data will go through a text preprocessing stage, including data cleaning (whitespace removal, removal of punctuation, and removal of numbers), case folding, stemming, tokenizing, and stop word removal. In this research, a comparison of the accuracy of the two data mining methods will be carried out to see and get the best classification algorithm. Researchers also implemented several experiments by comparing the use of testing data by 20 and 30% and comparing the application of preprocessing stemming and without stemming. This study found that the support vector machine algorithm using testing data of 20% by applying the stemming stage had the highest accuracy rate, 97.5%.","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135111397","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}
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