International Journal of Computing and Digital Systems最新文献_第2页

Evolution in Children Fingerprint Recognition Approaches: A Review 儿童指纹识别方法的演变：综述

International Journal of Computing and Digital Systems Pub Date : 2024-08-10 DOI: 10.12785/ijcds/160173

Vaishali H. Kamble, Manisha P. Dale, Pravin B. Chopade, Priyanka S. Tondewad

引用次数: 0

AES 32: An FPGA implementation of Lightweight-AES for IoT Devices AES 32：面向物联网设备的轻量级 AES FPGA 实现

International Journal of Computing and Digital Systems Pub Date : 2024-08-10 DOI: 10.12785/ijcds/160167

Sumit Singh Dhanda, Brahmjit Singh, P. Jindal

引用次数: 1

Microservices for Asset Tracking Based on Indoor Positioning System 基于室内定位系统的资产追踪微服务

International Journal of Computing and Digital Systems Pub Date : 2024-08-10 DOI: 10.12785/ijcds/160162

Dondi Sasmita, Gede Putra Kusuma

引用次数: 0

A Review on NLP Techniques and Associated Challenges in Extracting Features from Education Data 从教育数据中提取特征的 NLP 技术及相关挑战综述

International Journal of Computing and Digital Systems Pub Date : 2024-08-10 DOI: 10.12785/ijcds/160170

Elia Ahidi Elisante Lukwaro, K. Kalegele, Devotha G. Nyambo

引用次数: 0

Classification of Tuberculosis Based on Chest X-Ray Images for Imbalance Data using SMOTE 利用 SMOTE 对基于胸部 X 光图像的不平衡数据进行肺结核分类

International Journal of Computing and Digital Systems Pub Date : 2024-08-10 DOI: 10.12785/ijcds/160171

Muhammad Fadhlullah Kh.TQ, W. Wahyono

引用次数: 1

IoT-based AI Methods for Indoor Air Quality Monitoring Systems: A Systematic Review 基于物联网的室内空气质量监测系统人工智能方法：系统综述

International Journal of Computing and Digital Systems Pub Date : 2024-08-10 DOI: 10.12785/ijcds/160159

Hayder Qasim Flayyih, Jumana Waleed, Amer M. Ibrahim

引用次数: 0

QR Shield: A Dual Machine Learning Approach Towards Securing QR Codes QR 盾牌：实现 QR 代码安全的双重机器学习方法

International Journal of Computing and Digital Systems Pub Date : 2024-08-10 DOI: 10.12785/ijcds/160164

Hissah Almousa, Arwa Almarzoqi, Alaa Alassaf, Ghady Alrasheed, Suliman A. Alsuhibany

引用次数: 0

Exploring Research Challenges of Blockchain and Supporting Technology with Potential Solution in Healthcare 探讨区块链的研究挑战和支持技术在医疗保健领域的潜在解决方案

International Journal of Computing and Digital Systems Pub Date : 2024-07-01 DOI: 10.12785/ijcds/160138

Shilpi Garg, Rajesh Kumar Kaushal, Naveen Kumar, E. Boonchieng

引用次数: 0

Efficient Early Detection of Patient Diagnosis and Cardiovascular Disease using an IoT System with Machine Learning and Fuzzy Logic 利用机器学习和模糊逻辑的物联网系统高效早期检测患者诊断和心血管疾病

International Journal of Computing and Digital Systems Pub Date : 2024-07-01 DOI: 10.12785/ijcds/160115

Rafly Arief Kanza, M. Udin, Harun Al Rasyid, S. Sukaridhoto

{"title":"Efficient Early Detection of Patient Diagnosis and Cardiovascular Disease using an IoT System with Machine Learning and Fuzzy Logic","authors":"Rafly Arief Kanza, M. Udin, Harun Al Rasyid, S. Sukaridhoto","doi":"10.12785/ijcds/160115","DOIUrl":"https://doi.org/10.12785/ijcds/160115","url":null,"abstract":": Rising healthcare challenges, particularly undiagnosed heart disease due to subtle symptoms and limited access to diagnostics, necessitate innovative solutions. This study introduces an innovative Internet of Things (IoT)-based system for early detection, leveraging the strengths of both fuzzy logic and machine learning. By analyzing patient-specific data such as heart rate, oxygen saturation, galvanic skin response, and body temperature, our system utilizes fuzzy logic to evaluate potential disease symptoms, enabling self-diagnosis under medical supervision. This personalized approach enables individuals to monitor their health and seek prompt medical attention as needed. Additionally, we train multiple machine learning algorithms (Decision Tree, KNN, SVM, Random Forest, Logistic Regression) on the well-established Cleveland heart disease dataset. Among these, Random Forest achieved the highest accuracy (82.6%), precision (81.5%), recall (83.7%), and F1-Score (82.5%), showcasing its e ff ectiveness in predicting cardiovascular disease. This unique blend of fuzzy logic for personalized symptom assessment and machine learning for CVD prediction presents a new method for early diagnosis. While promising, further validation through large-scale clinical trials is essential. Ultimately, this system underscores the significance of integrating AI with medical expertise for optimal patient care, providing a potential pathway to improved health outcomes and enhanced accessibility to early detection of cardiovascular disease.","PeriodicalId":37180,"journal":{"name":"International Journal of Computing and Digital Systems","volume":"56 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141710842","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

A Novel Framework for Mobile Forensics Investigation Process 移动取证调查流程的新框架

International Journal of Computing and Digital Systems Pub Date : 2024-07-01 DOI: 10.12785/ijcds/160110

Mohammed Moreb, Saeed Salah, Belal Amro

{"title":"A Novel Framework for Mobile Forensics Investigation Process","authors":"Mohammed Moreb, Saeed Salah, Belal Amro","doi":"10.12785/ijcds/160110","DOIUrl":"https://doi.org/10.12785/ijcds/160110","url":null,"abstract":": Investigating digital evidence by gathering, examining, and maintaining evidence that was stored in smartphones has attracted tremendous attention and become a key part of digital forensics. The mobile forensics process aims to recover digital evidence from a mobile device in a way that will preserve the evidence in a forensically sound condition. This evidence might be used to prove being a cybercriminal or a cybercrime victim. To do this, the mobile forensics process lifecycle must establish clear guidelines for safely capturing, isolating, transporting, storing, and proving digital evidence originating from mobile devices. There are unique aspects of the mobile forensics procedure that must be considered. It is imperative to adhere to proper techniques and norms for the testing of mobile devices to produce reliable results. In this paper, we develop a novel methodology for the mobile forensics process model lifecycle named Mobile Forensics Investigation Process Framework (MFIPF) which encompasses all the necessary stages and data sources used to construct the crime case. The developed framework contributes to identifying common concepts of mobile forensics through the development of the mobile forensics model that simplifies the examination process and enables forensics teams to capture and reuse specialized forensic knowledge. Furthermore, the paper provides a list of the most commonly used forensics tools and where we can use them in our proposed mobile forensic process model.","PeriodicalId":37180,"journal":{"name":"International Journal of Computing and Digital Systems","volume":"230 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141692612","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