International Journal of Advanced Computer Science and Applications最新文献_第4页

SSEC: Semantic Segmentation and Ensemble Classification Framework for Static Hand Gesture Recognition using RGB-D Data 基于RGB-D数据的静态手势识别语义分割和集成分类框架

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.01403104

D. Nc, K. Suresh, Chandrasekhar V, D. R

引用次数: 0

A Novel Framework for Detecting Network Intrusions Based on Machine Learning Methods 基于机器学习方法的网络入侵检测新框架

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140755

B. Omarov, Nazgul Abdinurova, Zhamshidbek Abdulkhamidov

{"title":"A Novel Framework for Detecting Network Intrusions Based on Machine Learning Methods","authors":"B. Omarov, Nazgul Abdinurova, Zhamshidbek Abdulkhamidov","doi":"10.14569/ijacsa.2023.0140755","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140755","url":null,"abstract":"—In the rapidly evolving landscape of cyber threats, the efficacy of traditional rule-based network intrusion detection systems has become increasingly questionable. This paper introduces a novel framework for identifying network intrusions, leveraging the power of advanced machine learning techniques. The proposed methodology steps away from the rigidity of conventional systems, bringing a flexible, adaptive, and intuitive approach to the forefront of network security. This study employs a diverse blend of machine learning models including but not limited to, Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), and Random Forests. This research explores an innovative feature extraction and selection technique that enables the model to focus on high-priority potential threats, minimizing noise and improving detection accuracy. The framework's performance has been rigorously evaluated through a series of experiments on benchmark datasets. The results consistently surpass traditional methods, demonstrating a remarkable increase in detection rates and a significant reduction in false positives. Further, the machine learning-based model demonstrated its ability to adapt to new threat landscapes, indicating its suitability in real-world scenarios. By marrying the agility of machine learning with the concreteness of network intrusion detection, this research opens up new avenues for dynamic and resilient cybersecurity. The framework offers an innovative solution that can identify, learn, and adapt to evolving network intrusions, shaping the future of cyber defense strategies.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84894582","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

Developing a Computer Simulation to Study the Behavior of Factors Affecting the Flooding of the Gash River 建立影响裂谷河洪水因素行为的计算机模拟研究

IF 0.9

International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140110

Abdalilah. G. I. Alhalangy

{"title":"Developing a Computer Simulation to Study the Behavior of Factors Affecting the Flooding of the Gash River","authors":"Abdalilah. G. I. Alhalangy","doi":"10.14569/ijacsa.2023.0140110","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140110","url":null,"abstract":"—In recent years, the city of Kassala has suffered from frequent flooding disasters in the Gash River, which is the city's lifeblood. But the problem of frequent flooding of the river has made it a life-threatening nightmare. The importance of research lies in the fact that it is one of the few attempts to discuss and study the causes and effects of the Gash River floods. It aims to identify the factors affecting river floods. It proposes an algorithm to simulate flooding by randomly generating different factors that effectively affect river flooding. The descriptive analytical approach, the analytical, inductive approach, and the analytical deductive approach to desk research were used, taking advantage of the primary statistical method in its observation and evaluation, which relies on primary and secondary information to help make scientific, practical, and objective. The research came out with significant results related to the problems that threaten the town of Kassala from the frequent floods of the Gash River. The study's results proved that there is a deviation and discrepancy between the floods rate during the year, which gives a negative indication, and that deposited quantities vary in different proportions from one period to another, which causes a significant threat in the future. The research suggests other solutions that help reduce the problems and their effects. In addition to the above, the study proposes various recommendations that will be the basis for future studies to reach the required solutions and goals.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76892042","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 Survey on Attention-Based Models for Image Captioning 基于注意力的图像字幕模型研究综述

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140249

Asmaa A. E. Osman, Mohamed A. Wahby Shalaby, Mona M. Soliman, K. Elsayed

引用次数: 2

A Machine Learning Enabled Hall-Effect IoT-System for Monitoring Building Vibrations 用于监测建筑物振动的机器学习霍尔效应物联网系统

IF 0.9

International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140205

E. Lattanzi, Paolo Capellacci, Valerio Freschi

{"title":"A Machine Learning Enabled Hall-Effect IoT-System for Monitoring Building Vibrations","authors":"E. Lattanzi, Paolo Capellacci, Valerio Freschi","doi":"10.14569/ijacsa.2023.0140205","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140205","url":null,"abstract":"—Vibration monitoring of civil infrastructures is a fundamental task to assess their structural health, which can be nowadays carried on at reduced costs thanks to new sensing devices and embedded hardware platforms. In this work, we present a system for monitoring vibrations in buildings based on a novel, cheap, Hall-effect vibration sensor that is interfaced with a commercially available embedded hardware platform, in order to support communication toward cloud based services by means of IoT communication protocols. Two deep learning neural networks have been implemented and tested to demonstrate the capability of performing nontrivial prediction tasks directly on board of the embedded platform, an important feature to conceive dynamical policies for deciding whether to perform a recognition task on the final (resource constrained) device, or delegate it to the cloud according to specific energy, latency, accuracy requirements. Experimental evaluation on two use cases, namely the detection of a seismic event and the count of steps made by people transiting in a public building highlight the potential of the adopted solution; for instance, recognition of walking-induced vibrations can be achieved with an accuracy of 96% in real-time within time windows of 500ms. Overall, the results of the empirical investigation show the flexibility of the proposed solution as a promising alternative for the design of vibration monitoring systems in built environments.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85378288","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

Innovating Art with Augmented Reality: A New Dimension in Body Painting 用增强现实创新艺术:人体彩绘的新维度

IF 0.9

International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140787

Dou Lei, W. S. A. W. M. Daud

{"title":"Innovating Art with Augmented Reality: A New Dimension in Body Painting","authors":"Dou Lei, W. S. A. W. M. Daud","doi":"10.14569/ijacsa.2023.0140787","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140787","url":null,"abstract":"—This study investigates the fusion of augmented reality (AR) and body painting as a novel concept for artistic expression. By combining the immersive capabilities of AR with the creative potential of body painting, this research explores individuals' perceptions and attitudes towards this innovative artistic approach from an HCI perspective. Drawing upon the Technology Acceptance Model (TAM) and the Diffusion of Innovation Theory (DIT), the study examines the factors influencing individuals' acceptance and intention to engage in AR-integrated body painting. Additionally, the research explores the mediating role of artistic expression in understanding the impact of these factors on the actual outcomes of this merged concept. A sample of 212 respondents participated in an online survey to accomplish the research objectives. The survey comprehensively measured participants' perceptions of innovativeness, social system support, perceived usefulness, perceived ease of use, artistic expression, and behavioral intention towards AR-integrated body painting. Rigorous data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the intricate relationships between the variables. The findings underscore the significant impact of factors such as Innovativeness, social system support, perceived usefulness, and perceived ease of use on individuals' acceptance and intention to engage in AR-integrated body painting from an HCI perspective. Moreover, the study reveals the mediating role of artistic expression in connecting these influential factors with the actual outcomes of this merged concept. These empirical insights substantially contribute to our understanding of the fundamental mechanisms driving the adoption and utilization of AR in artistic practices, particularly within the domain of body painting, from both an artistic and HCI standpoint.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84552468","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

Adaptive Learner-CBT with Secured Fault-Tolerant and Resumption Capability for Nigerian Universities 尼日利亚大学具有安全容错和恢复能力的自适应学习者cbt

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140816

B.O. Malasowe, M. Akazue, Ejaita Abugor Okpako, Fidelis Obukowho Aghware, A. Ojugo, Dr. Ojie

引用次数: 3

Implementing a Blockchain, Smart Contract, and NFT Framework for Waste Management Systems in Emerging Economies: An Investigation in Vietnam 在新兴经济体中实施区块链、智能合约和NFT框架的废物管理系统:在越南的一项调查

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.01408107

Khiem H. G, K. V, Huong H. L, Quy T. L, P. N., N. K, T. N., B. K, Trong D. P. N., Hieu M. D., Bao Q. T., Khoa D. T.

引用次数: 0

Advances in Machine Learning and Explainable Artificial Intelligence for Depression Prediction 机器学习和可解释的人工智能在抑郁症预测中的进展

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140656

H. Byeon

{"title":"Advances in Machine Learning and Explainable Artificial Intelligence for Depression Prediction","authors":"H. Byeon","doi":"10.14569/ijacsa.2023.0140656","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140656","url":null,"abstract":"There is a growing interest in applying AI technology in the field of mental health, particularly as an alternative to complement the limitations of human analysis, judgment, and accessibility in mental health assessments and treatments. The current mental health treatment service faces a gap in which individuals who need help are not receiving it due to negative perceptions of mental health treatment, lack of professional manpower, and physical accessibility limitations. To overcome these difficulties, there is a growing need for a new approach, and AI technology is being explored as a potential solution. Explainable artificial intelligence (X-AI) with both accuracy and interpretability technology can help improve the accuracy of expert decision-making, increase the accessibility of mental health services, and solve the psychological problems of high-risk groups of depression. In this review, we examine the current use of X-AI technology in mental health assessments for depression. As a result of reviewing 6 studies that used X-AI to discriminate high-risk groups of depression, various algorithms such as SHAP (SHapley Additive exPlanations) and Local Interpretable Model-Agnostic Explanation (LIME) were used for predicting depression. In the field of psychiatry, such as predicting depression, it is crucial to ensure AI prediction justifications are clear and transparent. Therefore, ensuring interpretability of AI models will be important in future research. Keywords—Depression; LIME; Explainable artificial intelligence; Machine learning; SHAP","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78071905","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

Machine Learning Techniques in Keratoconus Classification: A Systematic Review 圆锥角膜分类中的机器学习技术:系统综述

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140569

Aatila Mustapha, Lachgar Mohamed, Hrimech Hamid, Kartit Ali

引用次数: 1