2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM)最新文献_第2页

Evaluating Machine Learning Algorithms for Predicting Financial Aid Eligibility: A Comparative Study of Random Forest, Gradient Boosting and Neural Network 评估预测资助资格的机器学习算法：随机森林、梯度提升和神经网络的比较研究

2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM) Pub Date : 2024-01-03 DOI: 10.1109/IMCOM60618.2024.10418450

M. H. Ismail, T. R. Razak, Noorfaizalfarid Mohd Noor, Azlan Abdul Aziz

{"title":"Evaluating Machine Learning Algorithms for Predicting Financial Aid Eligibility: A Comparative Study of Random Forest, Gradient Boosting and Neural Network","authors":"M. H. Ismail, T. R. Razak, Noorfaizalfarid Mohd Noor, Azlan Abdul Aziz","doi":"10.1109/IMCOM60618.2024.10418450","DOIUrl":"https://doi.org/10.1109/IMCOM60618.2024.10418450","url":null,"abstract":"Financial aid ensures equitable access to higher education, irrespective of students' social or economic backgrounds. However, as the financial aid source are limited, the administrators are burdened with the task of determining the student eligibility for financial aid in a fair and unbias manner. Additionally, the process of determining eligibility by human evaluators can benefit from machine learning assisted decision support tools. This study investigates the feasibility of using machine learning algorithms to achieve this goal. Three algorithms were selected for this comparative study with Decision Tree acts as a baseline. The algorithms are trained against a highly imbalanced dataset provided by ZAWAF. The training process incorporates k-fold cross-validation and employs stratified sampling techniques. It was found that all machine learning models outperformed the baseline, with the MLP-ANN model exhibiting the highest accuracy and precision scores. This demonstrates the potential for machine learning models to be integrated as decision support for the distribution of financial aid.","PeriodicalId":518057,"journal":{"name":"2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"296 2-3","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140532822","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

Rib Segmentation and Sequence Labeling via Biaxial Slicing and 3D Reconstruction 通过双轴切片和三维重建进行肋骨分割和序列标记

2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM) Pub Date : 2024-01-03 DOI: 10.1109/IMCOM60618.2024.10418333

Hyunsung Kim, Seonghyun Ko, J. Bum, D. Le, Hyunseung Choo

{"title":"Rib Segmentation and Sequence Labeling via Biaxial Slicing and 3D Reconstruction","authors":"Hyunsung Kim, Seonghyun Ko, J. Bum, D. Le, Hyunseung Choo","doi":"10.1109/IMCOM60618.2024.10418333","DOIUrl":"https://doi.org/10.1109/IMCOM60618.2024.10418333","url":null,"abstract":"The process of diagnosing rib lesions involves radiologists interpreting 2D CT images produced by a CT scanner. To identify the location of the lesion and make an accurate diagnosis, hundreds of 2D CT images are meticulously reviewed and ribs are classified. This study proposes Transverse and Frontal Rib Segmentation (TFRS) to address the issues of labor-intensive process, and performs Sequential labeling based on it. TFRS trains 2D images composed of Transverse and Frontal planes from the chest CT volume in the U-Net model. The combination of segmentation masks produced by the model complements spatial information from different planes, reconstructing a 3D rib volume. The performance of TFRS is evaluated using Dice, Recall, and Precision metrics, showing Dice of 90.29, Recall of 89.74, and Precision of 90.72. Sequential labeling is evaluated using the Successful Labeling rate, determining whether the 12 pairs of ribs within the chest volume have been accurately labeled in sequence. The performance of Sequential labeling based on TFRS demonstrated that out of 460 test sets, 448 were correctly labeled.","PeriodicalId":518057,"journal":{"name":"2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"165 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140532592","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

Efficient Thermal Management Strategies for 3D-SiP Architectures 针对 3D-SiP 架构的高效热管理策略

2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM) Pub Date : 2024-01-03 DOI: 10.1109/IMCOM60618.2024.10418285

Amrou Zyad Benelhaouare, A. Oukaira, Maroua Oumlaz, A. Lakhssassi

{"title":"Efficient Thermal Management Strategies for 3D-SiP Architectures","authors":"Amrou Zyad Benelhaouare, A. Oukaira, Maroua Oumlaz, A. Lakhssassi","doi":"10.1109/IMCOM60618.2024.10418285","DOIUrl":"https://doi.org/10.1109/IMCOM60618.2024.10418285","url":null,"abstract":"The thermal management of three-dimensional System-in-Package (3D-SiP) has garnered significant attention from researchers. Through Silicon Vias (TSVs) have been extensively studied for their role in improving heat dissipation and addressing hot spot issues. Additionally, other techniques like Micro-Channels Heat Sinks (MCHS) and Micro Pin-Fin Heat Sinks (MPFHS) have been explored to enhance 3D-SiP performance. Many thermal management issues stem from uneven temperature distribution on chip surfaces, leading to temperature gradients along the flow path. In a novel approach, this study combines the assessment of both techniques in a single investigation, presenting a distinctive contribution to enhancing thermal management efficiency. Utilizing the Finite Element Method (FEM) with ANSYS software, the study will conduct modeling and simulation to validate heat dissipation pathways, aiming to optimize the thermal performance of 3D-SiP assemblies. The focus will primarily be on how various geometric and thermophysical characteristics affect the heat dissipation capabilities of SiPs. The study's results, which led to an 84% reduction in maximum temperature inside the SiP, could serve as a crucial foundation for developing tailored thermal design guidelines for 3D-SiPs. This would significantly contribute to the ingenious optimization of thermal management strategies.","PeriodicalId":518057,"journal":{"name":"2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"36 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140532578","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

Comprehensive Assessment of Perovskite Solar Cell Efficiency Through Holistic Edge Detection Analysis of Crystallographic Grain Size 通过晶体晶粒尺寸的整体边缘检测分析全面评估 Perovskite 太阳能电池的效率

2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM) Pub Date : 2024-01-03 DOI: 10.1109/IMCOM60618.2024.10418271

Suniya Mansoor, S. M. Mannan

{"title":"Comprehensive Assessment of Perovskite Solar Cell Efficiency Through Holistic Edge Detection Analysis of Crystallographic Grain Size","authors":"Suniya Mansoor, S. M. Mannan","doi":"10.1109/IMCOM60618.2024.10418271","DOIUrl":"https://doi.org/10.1109/IMCOM60618.2024.10418271","url":null,"abstract":"Perovskite solar cells (PSCs) offer substantial potential to achieve remarkable energy conversion efficiency. However, the presence of grain boundaries poses a significant challenge, introducing non-radiative recombination pathways that can reduce overall performance. This manuscript presents a comprehensive investigation into the microstructure of PSCs with a focus on grain boundaries. The analysis involves preprocessing scanning electron microscope images to enhance quality, utilizing Holistic Nested Edge Detection for efficient grain boundary identification, followed by grain segmentation and size measurement. The study ensures data diversity by collecting grain size information from numerous scanning electron microscope images, offering automated analysis for consistency and repeatability. Furthermore, this study employs linear regression analysis to quantitatively assess the relationship between grain size and photovoltaic parameters. This leads to the development of a mathematical model that predicts efficiency based on factors such as the Voltage-Current relationship and others.","PeriodicalId":518057,"journal":{"name":"2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"43 3","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140532974","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

Differential Privacy Based Federated Learning Techniques in IoMT: A Review 物联网技术中基于差异隐私的联合学习技术：综述

2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM) Pub Date : 2024-01-03 DOI: 10.1109/IMCOM60618.2024.10418361

Shaista Ashraf Farooqi, Aedah Abd Rahman, Amna Saad

{"title":"Differential Privacy Based Federated Learning Techniques in IoMT: A Review","authors":"Shaista Ashraf Farooqi, Aedah Abd Rahman, Amna Saad","doi":"10.1109/IMCOM60618.2024.10418361","DOIUrl":"https://doi.org/10.1109/IMCOM60618.2024.10418361","url":null,"abstract":"The ever-expanding landscape of the Internet of Medical Things (IoMT) is increasingly reliant on Federated Learning (FL) to construct cooperative, privacy-centric AI models. By enabling model training on dispersed data sources, FL maintains the security of sensitive healthcare information while promoting the development of global models to augment the realm of medical care. To effectively mitigate privacy apprehensions intrinsic to healthcare data, the integration of differential privacy with FL emerges as a compelling strategy. This amalgamation not only offers robust privacy assurances but also facilitates the customization of model updates, ensuring the safeguarding of individual user data. This review aims to promote knowledge on the synergies between differential privacy and Federated Learning in IoMT. It is intended to benefit healthcare professionals, data scientists, policymakers, and technologists, by providing insights on privacy-preserving AI models, techniques to integrate FL and differential privacy, and designing secure and efficient IoMT solutions.","PeriodicalId":518057,"journal":{"name":"2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"127 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140532735","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

Arduino Based Smart Walking Aid for Rehabilitation 基于 Arduino 的智能康复行走辅助设备

2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM) Pub Date : 2024-01-03 DOI: 10.1109/IMCOM60618.2024.10418448

Mohammed Ibrahim Adam, S. Rahardja

引用次数: 0

Title Copyright Page 标题版权页

2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM) Pub Date : 2024-01-03 DOI: 10.1109/imcom60618.2024.10418273

引用次数: 0

Integrated Empowered AI and IoT Approach for Heart Prediction 用于心脏预测的人工智能和物联网综合赋能方法

2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM) Pub Date : 2024-01-03 DOI: 10.1109/IMCOM60618.2024.10418366

Eiad Yafi, Ritu Chuahan, Anushka Sharma, M. Zuhairi

{"title":"Integrated Empowered AI and IoT Approach for Heart Prediction","authors":"Eiad Yafi, Ritu Chuahan, Anushka Sharma, M. Zuhairi","doi":"10.1109/IMCOM60618.2024.10418366","DOIUrl":"https://doi.org/10.1109/IMCOM60618.2024.10418366","url":null,"abstract":"The application of Internet of Things (IoT) technology has transformed the healthcare sector. Using IoT monitored data with AI, especially ML algorithms and statistical methodologies, we provide a study on the prediction of heart conditions. This study aims to create a precise and trustworthy predictive model that can efficiently analyse and understand the enormous quantity of data gathered from Internet of Things devices for monitoring heart health. The proposed methodology involves collecting real-time physiological data, such as systolic and diastolic blood pressure, heart rate, and BMI readings, from an IOT health monitoring device with different machine learning (ML) algorithms (random forest, decision tree, gradient booster classifier, and logistic regression) and statistical techniques (correlational analysis, data visualisation, ANOVA, and t-test) used to analyse and forecast heart conditions. Further, cross-validation techniques are used to evaluate the generalizability and robustness of the model. The performance of the predictive model is assessed using several criteria, including accuracy, precision, recall, and F1-score. The Gradient Boosting classifier worked well on the dataset for cardiac conditions, with an accuracy of almost 98%. Approximately 88% accuracy was attained. Naive Bayes functioned admirably, although it wasn't as effective as the Gradient Boost. Around 86% accuracy was attained. Overall, among the models, the Gradient Booster demonstrated the best accuracy, demonstrating its superior performance on the heart condition dataset. The outcomes of our tests and model building show good accuracy rates and reliable predictions for the prediction of heart conditions. In conclusion, the suggested method demonstrates the potential for early identification and prevention of cardiac illnesses using IoT-monitored data in conjunction with AI, improving patient outcomes and lowering healthcare expenditures.","PeriodicalId":518057,"journal":{"name":"2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"330 3","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140532986","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

Traffic Jam Detection Using Real-Time Bus Operation Data Considering Timetable Information in Various Conditions 在各种条件下利用考虑了时刻表信息的实时公交运营数据进行交通拥堵检测

2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM) Pub Date : 2024-01-03 DOI: 10.1109/imcom60618.2024.10418376

Nozomi Hatanka, Hiroki Aoyagi, Tomoya Fujita, Hayato Yamana, Masato Oguchi

引用次数: 0

MySIMS: A Hybrid Application of Face Recognition Attendance and Tuition Management System MySIMS：人脸识别考勤和学费管理系统的混合应用

2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM) Pub Date : 2024-01-03 DOI: 10.1109/IMCOM60618.2024.10418293

Muhamad Ashraff Othman, H. S. Husin, Suriana Ismail

{"title":"MySIMS: A Hybrid Application of Face Recognition Attendance and Tuition Management System","authors":"Muhamad Ashraff Othman, H. S. Husin, Suriana Ismail","doi":"10.1109/IMCOM60618.2024.10418293","DOIUrl":"https://doi.org/10.1109/IMCOM60618.2024.10418293","url":null,"abstract":"MySIMS are designed for small educational organizations such as tuition centers or kindergartens. The system itself provides a new solution to the conventional method of attendance taking event at school. The face recognition attendance method is being used in this project because of its reliability that is accurate in terms of determining student faces. Once is not able to trick the system because every student has a unique different face structure. MySIMS is a multi-platform software application that is available on desktop, web, and mobile application. The target user of MySIMS is the educational organization that manages their institution to provide smooth transition of administration. Furthermore, it will also benefit the teacher as the proposed system is meant to reduce the workload of educational staff because the attendance taking can be automated with the use of high-resolution face recognition camera. The system also can be integrated with the school management system that the teacher either able to monitor and update the data regarding the students’ marks, assignment, and performance. While on the other hand, parents can monitor their children's study performance through the mobile application where the data provided is in real-time.","PeriodicalId":518057,"journal":{"name":"2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"7 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140532745","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