Proceedings of the 2023 6th International Conference on Software Engineering and Information Management最新文献_第3页

WEBUSSD CARE: A MULTI-TENANT USSD BASED APPLICATION FOR IMPROVING PROTECTED HEALTH INFORMATION EXCHANGE webbussd care:一个基于ussd的多租户应用程序，用于改进受保护的健康信息交换

Proceedings of the 2023 6th International Conference on Software Engineering and Information Management Pub Date : 2023-01-31 DOI: 10.1145/3584871.3584888

M. S. Julius, Sylvanus Olufemi Ige, Guzorochi Chimdire Abanobi, U. Alo, F. U. Onu, Kingsley M Okorie

{"title":"WEBUSSD CARE: A MULTI-TENANT USSD BASED APPLICATION FOR IMPROVING PROTECTED HEALTH INFORMATION EXCHANGE","authors":"M. S. Julius, Sylvanus Olufemi Ige, Guzorochi Chimdire Abanobi, U. Alo, F. U. Onu, Kingsley M Okorie","doi":"10.1145/3584871.3584888","DOIUrl":"https://doi.org/10.1145/3584871.3584888","url":null,"abstract":"Quick access to patient's protected health information avails clinicians the insight to understand patient's health conditions and to make an informed treatment decisions. However, the outbreak of the Covid-19 pandemic placed serious access restriction not only to the healthcare facilities and services but also to patient's protected health information. Unstructured Supplementary Service Data (USSD) technology is an efficient tool that can easily be used to create, store, access, and share personal health data whenever the needs arise. In this study, an integrated multi-tenant USSD based application to improve patient's protected health information exchange is presented as a complementary tool for improving healthcare outcomes. Object oriented methodology with integration of USSD Application Programming Interface (API) was adopted for the system development. The prototype of multi-tenant USSD based application for improving protected health Information exchange has been developed named “WEBUSSD Care”. By dialing a selected code on the mobile phone, the system displays an interactive menu for accessing patient's protected information such as medical appointments, diagnoses, medication prescription, medical test results, report drug reactions and treatment information and so on. The adoption of the WEBUSSD Care could greatly reduce delay in accessing patient's protected health information and enhance timely and informed treatment decisions.","PeriodicalId":173315,"journal":{"name":"Proceedings of the 2023 6th International Conference on Software Engineering and Information Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133672788","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

Sentiment Analysis of Social Media: Techniques, Applications, and Reliability 社交媒体的情感分析:技术、应用和可靠性

Proceedings of the 2023 6th International Conference on Software Engineering and Information Management Pub Date : 2023-01-31 DOI: 10.1145/3584871.3584911

P. J. Ryan, R. B. Watson

引用次数: 0

Robust low rank tensor multi-view clustering 鲁棒低秩张量多视图聚类

Proceedings of the 2023 6th International Conference on Software Engineering and Information Management Pub Date : 2023-01-31 DOI: 10.1145/3584871.3584897

Xintong Zou, Yun-jin Zhang, Yanrong Yang

引用次数: 0

CREDERE: A Modular Blockchain Implementation for the Issuance, Sharing, and Verification of Digital Credentials CREDERE:用于发布、共享和验证数字凭证的模块化区块链实现

Proceedings of the 2023 6th International Conference on Software Engineering and Information Management Pub Date : 2023-01-31 DOI: 10.1145/3584871.3584904

Christian E. Pulmano, M. R. Estuar, M. D. De Leon, L. P. Tamayo, Abraham Magpantay, Hans Calvin L. Tan, Nicole Allison S. Co

{"title":"CREDERE: A Modular Blockchain Implementation for the Issuance, Sharing, and Verification of Digital Credentials","authors":"Christian E. Pulmano, M. R. Estuar, M. D. De Leon, L. P. Tamayo, Abraham Magpantay, Hans Calvin L. Tan, Nicole Allison S. Co","doi":"10.1145/3584871.3584904","DOIUrl":"https://doi.org/10.1145/3584871.3584904","url":null,"abstract":"Shared loosely online through multiple unsecured platforms necessitates priority in the development of more secured tracking of issuance, sharing, access, and usage of digital credentials. This paper presents the design and development of CREDERE, a Blockchain-enabled platform for storage, processing, and sharing of digital credentials within the context of academic credentials and national identification. Blockchain technology is considered a potential solution to addressing gaps in existing credentials management systems. To set up the platform, a Hyperledger Fabric network was first deployed. A permissioned Blockchain model was selected because identity management is needed in maintaining the privacy of personal information and preventing unauthorized access to digital credentials. Chaincode was developed and deployed in specific Channels in the network. A web interface was also developed to allow users to interact with the Blockchain network and initiate transactions. The initial implementation shows that the development of a modular Blockchain-based web application for digital credentials is feasible. Two types of digital credentials were initially implemented in order to test the modularity of the Blockchain design. Future work includes the full deployment of a decentralized Hyperledger network, issuance of actual digital credentials, testing and validation on new types of digital credentials, and user validation and satisfaction studies.","PeriodicalId":173315,"journal":{"name":"Proceedings of the 2023 6th International Conference on Software Engineering and Information Management","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130019131","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

Research on the symbiosis of traditional and new energy vehicles manufacturing industries——Based on the symbiotic game model 传统与新能源汽车制造业的共生研究——基于共生博弈模型

Proceedings of the 2023 6th International Conference on Software Engineering and Information Management Pub Date : 2023-01-31 DOI: 10.1145/3584871.3584909

Xiaoying Cui, Hai Shen, Xiaogang Zhao, Jiawei Liu

{"title":"Research on the symbiosis of traditional and new energy vehicles manufacturing industries——Based on the symbiotic game model","authors":"Xiaoying Cui, Hai Shen, Xiaogang Zhao, Jiawei Liu","doi":"10.1145/3584871.3584909","DOIUrl":"https://doi.org/10.1145/3584871.3584909","url":null,"abstract":"Abstract: Using the symbiotic evolution theory to construct a game model between new energy vehicles and traditional vehicles, for the decision-making of automakers and the establishment of government subsidy mechanisms. Introduce the Lotka-Volterra equation in the symbiosis theory into the game model, analyze the interaction of relevant factors, build a symbiotic evolutionary game model between new energy vehicles and traditional vehicles, and analyze the stability points of the model and the stability of each stable point. Then analyze different numerical simulation of different variables to predict decision-making results. Simulation experiments show that, for new energy decisions under limited market capacity, this method effectively provides support for manufacturers' production decisions and government subsidies. The game model based on symbiotic evolution theory has good applicability, and provides an effective way for manufacturers and governments to make reasonable and scientific decisions on new energy vehicle projects.","PeriodicalId":173315,"journal":{"name":"Proceedings of the 2023 6th International Conference on Software Engineering and Information Management","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116974941","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

Method for monitoring stress and vital signs in teachers when conducting online classes, using wearable devices 使用可穿戴设备监测教师在线授课时的压力和生命体征的方法

Proceedings of the 2023 6th International Conference on Software Engineering and Information Management Pub Date : 2023-01-31 DOI: 10.1145/3584871.3584902

Yoni Nicolas-Rojas, W. Auccahuasi, Sandra Meza, Tamara Pando-Eszurra, Oscar Linares, K. Urbano

引用次数: 0

The Effect of System Quality, Information Quality, and Service Quality on the Continued Usage of Mobile Payment Application in Thailand 系统质量、信息质量和服务质量对泰国移动支付应用持续使用的影响

Proceedings of the 2023 6th International Conference on Software Engineering and Information Management Pub Date : 2023-01-31 DOI: 10.1145/3584871.3584886

Montipat Nilapun, Tanapon Jensuttiwetchakul

引用次数: 0

Analyzing critical success factors for a successful implementation of artificial intelligence in agile industry 4.0 分析在敏捷工业4.0中成功实施人工智能的关键成功因素

Proceedings of the 2023 6th International Conference on Software Engineering and Information Management Pub Date : 2023-01-31 DOI: 10.1145/3584871.3584910

F. Tamtam, Larbi Yacoubi, Amina Tourabi

引用次数: 0

Diagnosing Prostate Cancer: An Implementation of Deep Machine Learning Fusion Network in MRI Using a Transfer Learning Approach 前列腺癌诊断:利用迁移学习方法在MRI中实现深度机器学习融合网络

Proceedings of the 2023 6th International Conference on Software Engineering and Information Management Pub Date : 2023-01-31 DOI: 10.1145/3584871.3584876

Ariful Islam Mahmud Badhon, Md Sadman Hasan, Md. Samiul Haque, Md. Shafayat Hossain Pranto, Saurav Ghosh, Md. Golam Rabiul Alam

{"title":"Diagnosing Prostate Cancer: An Implementation of Deep Machine Learning Fusion Network in MRI Using a Transfer Learning Approach","authors":"Ariful Islam Mahmud Badhon, Md Sadman Hasan, Md. Samiul Haque, Md. Shafayat Hossain Pranto, Saurav Ghosh, Md. Golam Rabiul Alam","doi":"10.1145/3584871.3584876","DOIUrl":"https://doi.org/10.1145/3584871.3584876","url":null,"abstract":"Of all the terminal cancers that plague men, prostate cancer remains one of the most prevalent and ubiquitous. Data shows prostate cancer is the second leading cause of cancer death worldwide among men. About 11% of men have prostate cancer at some time during their lives. As it happens, we have dedicated our entire research to developing an approach that can improve the existing precision of prostate cancer diagnosis. In our research, we have dedicated a Transfer Learning approach for the Deep Learning model to compare the accuracy in results using Machine Learning classifiers. In addition, we evaluated individual performance in classifications with different evaluation measures using a Deep Learning pre-trained network, VGG16. During our evaluation, we assessed several performance metrics such as Precision, Recall, F1 Score, and Loss Vs. Accuracy for performance analysis. Upon implementing the Transfer Learning approach, we recorded the optimum performance using the VGG16 architecture compared to other popular Deep learning models such as MobileNet and ResNet. It is important to note that we have used the convolutional block and dense layers of VGG16 architecture to extract features from our image dataset. Afterward, we forwarded those features to Machine Learning classifiers to tabulate the final classification result. Upon successful tabulation, we have secured significant accuracy in prognostication using the Deep Machine Learning method in our research.","PeriodicalId":173315,"journal":{"name":"Proceedings of the 2023 6th International Conference on Software Engineering and Information Management","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124419636","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

Artificial Intelligence of Things (AIoT) for Disaster Monitoring using Wireless Mesh Network 利用无线网状网络进行灾害监测的物联网人工智能(AIoT)

Proceedings of the 2023 6th International Conference on Software Engineering and Information Management Pub Date : 2023-01-31 DOI: 10.1145/3584871.3584905

Mau-Luen Tham, Y. Wong, Ban-Hoe Kwan, Xin Hao Ng, Y. Owada

{"title":"Artificial Intelligence of Things (AIoT) for Disaster Monitoring using Wireless Mesh Network","authors":"Mau-Luen Tham, Y. Wong, Ban-Hoe Kwan, Xin Hao Ng, Y. Owada","doi":"10.1145/3584871.3584905","DOIUrl":"https://doi.org/10.1145/3584871.3584905","url":null,"abstract":"The inherent characteristics of Internet of things (IoT) such as low computation power of IoT nodes and transmission reliability of IoT links demand a new paradigm for efficient data processing and dissemination. This is especially true for disaster situations with high possibility of communication breakdowns. On one hand, the concept of artificial intelligence of things (AIoT) has been introduced as a technology to push data storage and computing closer to the network edge. On the other hand, wireless mesh network offers a strong self-healing capability and network robustness against disaster damages. To enable smart disaster monitoring applications, we first implement a lightweight multi-task model that performs joint disaster classification and victim detection. These AI outputs are then wirelessly synchronized via a mesh network solution called NerveNet. All the experiments are conducted in a real urban environment, including static and mobile nodes. Experimental results validate the effectiveness of the proposed solution, where text and images can be synchronized within two minutes across a multi-hop Wi-Fi network. Furthermore, the optimized AI model has ultra-low power consumption around 1.23 W with frames per second (FPS) of 2.01.","PeriodicalId":173315,"journal":{"name":"Proceedings of the 2023 6th International Conference on Software Engineering and Information Management","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134284284","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