Acta Informatica Pragensia最新文献_第4页

Blood Pressure Estimation Using Emotion-Based Optimization Clustering Model 基于情绪优化聚类模型的血压估计

Acta Informatica Pragensia Pub Date : 2023-03-01 DOI: 10.18267/j.aip.209

Vaishali Rajput, Preeti Mulay, Sharnil Pandya, Chandrashekhar Mahajan, Rupali Deshpande

引用次数: 0

Longitudinal Investigation of Work Stressors Using Human Voice Features 利用人声特征对工作压力源的纵向调查

Acta Informatica Pragensia Pub Date : 2023-03-01 DOI: 10.18267/j.aip.208

Indhumathi Natarajan, M. Shanmugam, S. Dhanalakshmi, Santhosh Easwaramoorthy, Sethuraja Kuppusamy, S. Balu

引用次数: 5

Emotion-Based Sentiment Analysis Using Conv-BiLSTM With Frog Leap Algorithms 使用Conv BiLSTM和Frog Leap算法进行基于情绪的情绪分析

Acta Informatica Pragensia Pub Date : 2023-01-17 DOI: 10.18267/j.aip.206

S. Yelisetti, Nellore Geethanjali

引用次数: 0

Deep Learning Convolutional Neural Network for SARS-CoV-2 Detection Using Chest X-Ray Images 基于胸部x线图像的深度学习卷积神经网络检测新冠肺炎

Acta Informatica Pragensia Pub Date : 2023-01-17 DOI: 10.18267/j.aip.205

A. Ahmed, Inteasar Yaseen Khudhair, Salam Abdulkhaleq Noaman

{"title":"Deep Learning Convolutional Neural Network for SARS-CoV-2 Detection Using Chest X-Ray Images","authors":"A. Ahmed, Inteasar Yaseen Khudhair, Salam Abdulkhaleq Noaman","doi":"10.18267/j.aip.205","DOIUrl":"https://doi.org/10.18267/j.aip.205","url":null,"abstract":"The COVID-19 coronavirus illness is caused by a newly discovered species of coronavirus known as SARS-CoV-2. Since COVID-19 has now expanded across many nations, the World Health Organization (WHO) has designated it a pandemic. Reverse transcription-polymerase chain reaction (RT-PCR) is often used to screen samples of patients showing signs of COVID-19;however, this method is more expensive and takes at least 24 hours to get a positive or negative response. Thus, an immediate and precise method of diagnosis is needed. In this paper, chest X-rays will be utilized through a deep neural network (DNN), based on a convolutional neural network (CNN), to detect COVID-19 infection. Based on their X-rays, those with COVID-19 indications may be categorized as clean, infected with COVID-19 or suffering from pneumonia, according to the suggested CNN network. Sample pieces from every group are used in experiments, and categorization is performed by a CNN. While experimenting, the CNN-derived features were able to generate the maximum training accuracy of 94.82% and validation accuracy of 94.87%. The F1-scores were 97%, 90% and 96%, in clearly categorizing patients afflicted by COVID-19, normal and having pneumonia, respectively. Meanwhile, the recalls are 95%, 91% and 96% for COVID-19, normal and pneumonia, respectively. © 2023 by the author(s). Licensee Prague University of Economics and Business, Czech Republic.","PeriodicalId":36592,"journal":{"name":"Acta Informatica Pragensia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41390604","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

AnnoJOB: Semantic Annotation-Based System for Job Recommendation AnnoJOB:基于语义标注的职位推荐系统

Acta Informatica Pragensia Pub Date : 2023-01-17 DOI: 10.18267/j.aip.204

Assia Brek, Z. Boufaida

引用次数: 0

Artificial Intelligence and Blockchain Technology Enabling Sustainable and Smart Infrastructure 人工智能和区块链技术实现可持续智能基础设施

Acta Informatica Pragensia Pub Date : 2022-12-26 DOI: 10.18267/j.aip.203

Venkatachalam Kandasamy, M. Abouhawwash, N. Bačanin

引用次数: 0

Evaluation of Community Detection by Improving Influence Nodes in Complex Networks Using InfoMap with Sigmoid Fish Swarm Optimization Algorithm 基于Sigmoid鱼群优化算法的InfoMap改进复杂网络中影响节点的社区检测评价

Acta Informatica Pragensia Pub Date : 2022-12-26 DOI: 10.18267/j.aip.201

Devi Selvaraj, Rajalakshmi Murugasamy

引用次数: 0

Comprehensive Review of Multimodal Medical Data Analysis: Open Issues and Future Research Directions 多模式医学数据分析综述：有待解决的问题和未来的研究方向

Acta Informatica Pragensia Pub Date : 2022-12-26 DOI: 10.18267/j.aip.202

S. Shetty, A. S, A. Mahale

引用次数: 2

Blockchain Design and Implementation Techniques, Considerations and Challenges in the Banking Sector: A Systematic Literature Review 银行业的设计和实施技术、考虑和挑战:系统的文献综述

Acta Informatica Pragensia Pub Date : 2022-11-28 DOI: 10.18267/j.aip.200

S. Mafike, Tendani Mawela

{"title":"Blockchain Design and Implementation Techniques, Considerations and Challenges in the Banking Sector: A Systematic Literature Review","authors":"S. Mafike, Tendani Mawela","doi":"10.18267/j.aip.200","DOIUrl":"https://doi.org/10.18267/j.aip.200","url":null,"abstract":"Blockchain is transforming the banking sector and offering opportunities for significant cost reduction and efficient banking services. However, implementing blockchain is a challenge due to lack of adequate knowledge and skills on how to implement the technology. As a result, there are very few market-ready blockchain banking products and organisations are unable to realise the promised value. This paper presents an overview of the banking sector’s blockchain use cases, design and implementation considerations and techniques. The aim is to offer an evidence-based primer to guide researchers and practitioners. The study relies on the systematic literature review method and reviews a total of 45 papers comprising 26 peer-reviewed scholarly articles and 19 technical reports from the banking industry. Leximancer software is used to support the thematic data analysis. The results show for the banking sector an increase in experimentation efforts geared towards the development of payment systems. The results also indicate key considerations from a technological, organisational and environmental perspective. The study highlights that platform selection, scalability and resilience are some of the critical technical considerations for implementing blockchain banking systems. Organisational considerations include collaboration and governance-related challenges. From an environmental perspective, the study notes several legal and regulatory considerations. This study contributes to the existing literature on blockchain adoption in banking, which is still in the nascent stage. The study also offers a research agenda for further understanding of blockchain implementation in the banking sector. Opportunities for further research are noted in the areas of interoperability, governance, security and privacy .","PeriodicalId":36592,"journal":{"name":"Acta Informatica Pragensia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42051535","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: 1

Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction 基于降维的DDoS检测系统高效机器学习模型

Acta Informatica Pragensia Pub Date : 2022-11-15 DOI: 10.18267/j.aip.199

Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, S. Mostafa

{"title":"Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction","authors":"Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, S. Mostafa","doi":"10.18267/j.aip.199","DOIUrl":"https://doi.org/10.18267/j.aip.199","url":null,"abstract":"Distributed denial of service (DDoS) attacks are one of the most common global challenges faced by service providers on the web. It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. The present study proposes an efficient DDoS attack detection model. This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. The model is implemented and tested on the CICDDoS2019 dataset using different data dimensionality reduction test scenarios. The results show that using dimensionality reduction techniques along with the ML algorithms with a dataset containing high-dimensional data significantly improves the classification results. The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40","PeriodicalId":36592,"journal":{"name":"Acta Informatica Pragensia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46609382","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