International Journal of Computing最新文献_第3页

Predicting Life Style of Early Diabetes Mellitus using Machine Learning Technique 利用机器学习技术预测早期糖尿病患者的生活方式

International Journal of Computing Pub Date : 2023-10-01 DOI: 10.47839/ijc.22.3.3230

Salliah Shafi Bhat, Venkatesan Selvam, Gufran Ahmad Ansari

{"title":"Predicting Life Style of Early Diabetes Mellitus using Machine Learning Technique","authors":"Salliah Shafi Bhat, Venkatesan Selvam, Gufran Ahmad Ansari","doi":"10.47839/ijc.22.3.3230","DOIUrl":"https://doi.org/10.47839/ijc.22.3.3230","url":null,"abstract":"A branch of artificial intelligence called Machine Learning (ML) enables machines to learn without having to be emphatically instructed. Machine Learning Techniques (MLT) have been used to forecast a variety of chronic diseases in the healthcare sector. Improvement in clinical approaches is necessary for early diabetes prediction to prevent complications and prolong the diagnosis of diabetes. Diabetes is growing fast in this world. In this paper MLT based Framework is recommended for early prediction of Diabetes Mellitus (DM). In this Paper the authors make use of PIDD data set. Different MLTs are used including Support Vector Classification (SVC), Logistic Regression (LR), K Nearest Neighbor (KNN) and Random Forest (RF). Data analysis is the first step in our method after which the information is transferred for data pre-processing and feature selection methods. RF performed better than other models with a 92.85 % accuracy rate followed by SVC (91.5%), LR (83.11) and KNN (89.6). K-fold cross-validation technique is utilized to verify the outcomes. The contribution of lifestyle characteristics is calculated using a feature engineering process. As a result, comprehensive overall comparative assessments of all the algorithms are performed taking into account variables such as accuracy, precision, sensitivity, recall, F1 score and ROC-AUC. The medical field can use the proposed framework to make early diabetes predictions. Additionally, it can be applied to other datasets that have data in common with diabetes.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135458402","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

Designing an Intelligent System for Predicting Alzheimer’s Disease 阿尔茨海默病智能预测系统的设计

International Journal of Computing Pub Date : 2023-10-01 DOI: 10.47839/ijc.22.3.3238

Wasan Ahmed Ali

引用次数: 0

Image Compression and Protection Systems Based on Atomic Functions 基于原子函数的图像压缩与保护系统

International Journal of Computing Pub Date : 2023-10-01 DOI: 10.47839/ijc.22.3.3222

Viktor O. Makarichev, Vladimir V. Lukin, Vyacheslav S. Kharchenko

引用次数: 0

Approach to Implementation of Configuration Process for Adaptive Software Systems based on Ontologies 基于本体的自适应软件系统配置过程实现方法

International Journal of Computing Pub Date : 2023-10-01 DOI: 10.47839/ijc.22.3.3234

Dmytro Fedasyuk, Illia Lutsyk

{"title":"Approach to Implementation of Configuration Process for Adaptive Software Systems based on Ontologies","authors":"Dmytro Fedasyuk, Illia Lutsyk","doi":"10.47839/ijc.22.3.3234","DOIUrl":"https://doi.org/10.47839/ijc.22.3.3234","url":null,"abstract":"Analysis of scientific research on the development of adaptive and self-adaptive software systems is conducted. It is established that the use of machine learning methods and feedback diagrams is an effective way to design and develop adaptive software. It is determined that the existing methods do not fully provide the possibility of dynamic changes and expansion of functional and graphic characteristics. The software adaptation process is designed based on the ontological model using the semantic decision-making mechanism. The proposed method allows us to dynamically determine the necessary system characteristics and perform software adaptation. Modification process takes into account the information about currently active device based on data about the needs and requirements of the user. Using the results of designing an abstract approach to software configuration modification, an experimental study of the speed of generating optimal system settings is conducted. According to the results of the experiment, it is established that the new method demonstrates 20% better indicators of the speed of generating software settings compared to classical approaches.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135459001","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

Development of an Investment Management Model for Air Carriers 航空承运人投资管理模式的发展

International Journal of Computing Pub Date : 2023-10-01 DOI: 10.47839/ijc.22.3.3226

Kamilla G. Sadvakassova, Azhar Z. Nurmagambetova, Gulmira E. Kassenova, Zhanar S. Kazbekova, Dariyoush Jamshidi

{"title":"Development of an Investment Management Model for Air Carriers","authors":"Kamilla G. Sadvakassova, Azhar Z. Nurmagambetova, Gulmira E. Kassenova, Zhanar S. Kazbekova, Dariyoush Jamshidi","doi":"10.47839/ijc.22.3.3226","DOIUrl":"https://doi.org/10.47839/ijc.22.3.3226","url":null,"abstract":"For Kazakh airlines, the issue of using information technologies (IT) is relevant and complex, since the increased competition and partially identical business practices by companies in the same industry force the accelerated implementation of such technologies in their activities. It is necessary to consider and systematize information technologies and systems used by leading air carriers in order to structure them and determine the formats of their use in airlines. The methodological framework of the study consists of the dialectical, system, and historical approaches, fundamental provisions of economic theory, the theory of information economy and innovative development, and studies conducted by scientists-economists devoted to the development of the information society and the problems of company functioning in the information economy. As a result, the investment project assessment for the implementation of information technologies was calculated, which clearly demonstrated the capabilities of such systems as a tool for improving competitiveness, and proved their fast payback period and positive impact on the company.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135458717","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

Transformation of Mathematical Model for Complex Object in Form of Interval Difference Equations to a Differential Equation 区间差分方程形式的复杂对象数学模型到微分方程的转换

International Journal of Computing Pub Date : 2023-07-01 DOI: 10.47839/ijc.22.2.3091

M. Dyvak, R. Pasichnyk, A. Melnyk, A. Dyvak, Frank Otoo

引用次数: 0

ECG Arrhythmia Classification Using Recurrence Plot and ResNet-18 使用复发图和ResNet-18进行心电心律失常分类

International Journal of Computing Pub Date : 2023-07-01 DOI: 10.47839/ijc.22.2.3083

Joshua Gutierrez-Ojeda, V. Ponomaryov, J. Almaraz-Damian, R. Reyes-Reyes, Clara Cruz-Ramos

{"title":"ECG Arrhythmia Classification Using Recurrence Plot and ResNet-18","authors":"Joshua Gutierrez-Ojeda, V. Ponomaryov, J. Almaraz-Damian, R. Reyes-Reyes, Clara Cruz-Ramos","doi":"10.47839/ijc.22.2.3083","DOIUrl":"https://doi.org/10.47839/ijc.22.2.3083","url":null,"abstract":"Cardiovascular diseases are the leading cause of death worldwide, claiming approximately \u000017.9 million lives each year. In this study, a novel CAD system to detect and classify electrocardiogram (ECG) signals is presented. Designed system employs the recurrence plot (RP) approach that transforms a ECG signal into a 2D representative colour image, finally performing their classifications via employment of Deep Learning architecture (ResNet-18). Novel system includes two steps, where the first step is the preprocessing one, which performs segmentation of the data into two-second intervals, finally forming images via the RP approach; following, in the second step, the RP images are classified by the ResNet- 18 network. The proposed method is evaluated on the MIT-BIH arrhythmia database where 5 principal types of arrhythmias that have medical relevance should be classified. Novel system can classify the before-mentioned quantity of diseases according to the AAMI Standard and appears to demonstrate good performance in terms of criteria: overall accuracy of 97.62%, precision of 95.42%, recall of 95.42%, F1-Score of 95.06%, and AUC of 95.7% that are competitive with better state-of-the-art systems. Additionally. the method demonstrated the ability in mitigating the problem of imbalanced samples.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75068796","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

Real-Time Face Mask Classification with Convolutional Neural Network for Proper and Improper Face Mask Wearing 基于卷积神经网络的口罩正确与不正确佩戴的实时分类

International Journal of Computing Pub Date : 2023-07-01 DOI: 10.47839/ijc.22.2.3087

Fatin Amanina Azis, Hazwani Suhaimi, E. Abas

{"title":"Real-Time Face Mask Classification with Convolutional Neural Network for Proper and Improper Face Mask Wearing","authors":"Fatin Amanina Azis, Hazwani Suhaimi, E. Abas","doi":"10.47839/ijc.22.2.3087","DOIUrl":"https://doi.org/10.47839/ijc.22.2.3087","url":null,"abstract":"Since the discovery of COVID-19, the wearing of a face mask has been recognized as an effective means of curbing the spread of most infectious respiratory diseases. A face mask must completely enclose the lips and nose properly for effective prevention of the disease. Some people still refuse to wear the mask, either out of annoyance or difficulty, or they are just wearing it incorrectly, which diminishes the mask's effectiveness and renders it worthless. The deep learning models described in this research provide a mechanism for assessing whether a face mask is being worn correctly or incorrectly using images. For both training and testing, the suggested method makes use of MaskedFace-Net dataset that contains annotated photos of an individual's face with proper and improper masks. Threshold optimizations are applied to produce significant results of prediction when comparing ResNet50, MobileNetV2 and DenseNet121 models. It is observed that better performance can be achieved with having accuracy as the target evaluation metric and reaching accuracy levels of 97.6%, 99.0%, and 99.8% for ResNet50, DenseNet121, and MobileNetV2, respectively after threshold optimization. As an outcome, DenseNet121 outperformed the other evaluated models when accuracy, recall, and precision metrics were used to assess the testing set. The face mask categorization can be used to automatically monitor face masks in real-time in public locations like hospitals, airports, shopping complexes and congested spaces to verify compliance with the published guidelines by the higher authorities in a country, making the results valuable for future use.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72859905","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

Early Detection of Breast Cancer Using Machine Learning and Ensemble Techniques 使用机器学习和集成技术的乳腺癌早期检测

International Journal of Computing Pub Date : 2023-07-01 DOI: 10.47839/ijc.22.2.3093

Disha H. Parekh, Vishal Dahiya

引用次数: 0

A Study on Internet of Things Devices Vulnerabilities using Shodan 基于Shodan的物联网设备漏洞研究

International Journal of Computing Pub Date : 2023-07-01 DOI: 10.47839/ijc.22.2.3084

V. Rajasekar, S. Rajkumar

{"title":"A Study on Internet of Things Devices Vulnerabilities using Shodan","authors":"V. Rajasekar, S. Rajkumar","doi":"10.47839/ijc.22.2.3084","DOIUrl":"https://doi.org/10.47839/ijc.22.2.3084","url":null,"abstract":"IoT has attracted a diverse range of applications due to its adaptability, flexibility, and scalability. However, the most significant barriers to IoT adoption are security, privacy, interoperability, and a lack of standards. Due to the persistent online connectivity and lack of security measures, adversaries can quickly attack IoT systems for various adversarial operations, financial gain, and access to sensitive data. We conducted a massive vulnerability scan on IoT devices using Shodan, the IoT search engine. The discovered vulnerabilities are analyzed using the Octave Allegro risk assessment method to determine the risk level (Critical, High, Moderate, Low, None), and the results are classified based on the vulnerabilities. The research findings are intriguing, shocking, and alarming, revealing the bitter reality that IoT devices are rapidly increasing while simultaneously eroding users' privacy on a never-before-seen scale. Our search discovered 13,558 webcams with outdated components, 11,090 devices disclosing NAT-PMP information, and 16,356 connected devices responding to remote telnet access. Around 2,456 IoT devices were found with the Heartbleed vulnerability, 674 with the Ticketbleed vulnerability, and 9,241 with expired SSL certificates. Nearly 18,638 IoT consumer devices are configured with insecure default settings; 11,481 devices with default SNMP agent community names; 4,987 devices running on non-standard ports; and 4,425 Cisco devices are configured with generic or default passwords.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73173735","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