2022 8th International Conference on Web Research (ICWR)最新文献

Supervised Machine Learning Models for Covid-19 Diagnosis using a Combination of Clinical and Laboratory Data 结合临床和实验室数据的Covid-19诊断的监督机器学习模型

2022 8th International Conference on Web Research (ICWR) Pub Date : 2022-05-11 DOI: 10.1109/ICWR54782.2022.9786248

Narges Mohebbi, Mehdi Tutunchian, Meysam Alavi, M. Kargari, Amir Behnam Kharazmy

{"title":"Supervised Machine Learning Models for Covid-19 Diagnosis using a Combination of Clinical and Laboratory Data","authors":"Narges Mohebbi, Mehdi Tutunchian, Meysam Alavi, M. Kargari, Amir Behnam Kharazmy","doi":"10.1109/ICWR54782.2022.9786248","DOIUrl":"https://doi.org/10.1109/ICWR54782.2022.9786248","url":null,"abstract":"An epidemic caused by a new type of Coronavirus family, called COVID-19, has created a global crisis involving all countries of the world. In this regard, designing an early detection system using heuristic and noninvasive methods can be a good and decisive factor in detecting the disease early and consequently decreasing the prevalence of the virus. In recent years, to rapidly diagnose diseases, machine learning techniques have increasingly grown to predict and diagnose patients, and researchers have used them in various studies. In this regard, since the outbreak of COVID-19, several researchers have tried to use the machine learning approach as a potential tool for identifying and diagnosing this disease. Due to the importance and role of using clinical and laboratory data in the diagnosis of afflicted people with COVID-19, in this paper, the models of K-NN, SVM, Decision Tree, Random Forest, Naive Bayes, Neural Network, and XGBoost as the most common machine learning models were used on a database with 1354 records consisting of clinical and laboratory data of COVID and non-COVID patients to diagnose COVID-19. Evaluation results based on Accuracy, Precision, Recall, and F-Score criteria showed that a XGBoost and K-NN with accuracy of 97% and 96% could be considered a suitable predictive model to diagnose the COVID-19 disease.","PeriodicalId":355187,"journal":{"name":"2022 8th International Conference on Web Research (ICWR)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115442167","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

Dcomg: Drug Combination Prediction by Applying Gnns on DDI Node2vec Features Dcomg:基于DDI Node2vec特征的Gnns药物联合预测

2022 8th International Conference on Web Research (ICWR) Pub Date : 2022-05-11 DOI: 10.1109/ICWR54782.2022.9786240

Seyyed Sina Ziaee, H. Rahmani, Mina Tabatabaei

引用次数: 0

An Energy-Efficient Compatible Method for Recovering Arterial Blood Pressure and Respiration Signals in WBANs 一种高效兼容的动脉血压和呼吸信号恢复方法

2022 8th International Conference on Web Research (ICWR) Pub Date : 2022-05-11 DOI: 10.1109/ICWR54782.2022.9786254

Mahdieh Hajiloo Vakil, Z. Shirmohammadi

{"title":"An Energy-Efficient Compatible Method for Recovering Arterial Blood Pressure and Respiration Signals in WBANs","authors":"Mahdieh Hajiloo Vakil, Z. Shirmohammadi","doi":"10.1109/ICWR54782.2022.9786254","DOIUrl":"https://doi.org/10.1109/ICWR54782.2022.9786254","url":null,"abstract":"In Wireless Body Area Networks (WBANs), the sensor energy is limited. Due to dynamic and huge data exchange, sending data consumes the most sensor energy. The best solution to solve this problem is to use data compression methods. The Compressed Sensing (CS) method is among the popular methods for compressing data in WBANs. The problem with this method is does not work well when the data set is not sparse. In this paper, to solve this problem, two versions of Block Sparse Bayesian Learning (BSBL) Bound-Optimization (BSBL-BO), and Expectation-Maximization (BSBL-EM) are used to compress and recover the Arterial Blood Pressure systolic (ABPsys) and Respiration signals. These signals are adapted and reshaped to the BSBL environment as an input dataset and then compressed. The phi matrix is created compatible with ABPsys and Respiration signals and obtained 98% similarity with the original signal after restoration. According to the results, the similarity of ABPsys and Respiration signals after recovery by BSBL-BO is higher than the BSBL-EM method. BSBL-BO is faster at signal recovery than BSBL-EM. The amount of residual energy is compared between the two CS methods, DCT, as dictionary matrix in CS using the BSBL versions, and the DCT without the BSBL and DCT with BSBL performs better than alone DCT.","PeriodicalId":355187,"journal":{"name":"2022 8th International Conference on Web Research (ICWR)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117030485","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 Search-Based Method For optimizing Software Architecture Reliability 基于搜索的软件体系结构可靠性优化方法

2022 8th International Conference on Web Research (ICWR) Pub Date : 2022-05-11 DOI: 10.1109/ICWR54782.2022.9786245

Mahsa Einabadi, S. Hasheminejad

{"title":"A Search-Based Method For optimizing Software Architecture Reliability","authors":"Mahsa Einabadi, S. Hasheminejad","doi":"10.1109/ICWR54782.2022.9786245","DOIUrl":"https://doi.org/10.1109/ICWR54782.2022.9786245","url":null,"abstract":"Choosing the optimal software architecture in the search space by considering quality criteria is beyond human capabilities and is very challenging. It is necessary to search the design space automatically to improve the existing architectural features. To do this, we can use search-based software engineering approaches. In this study, we examine the methods of optimizing and evaluating software architecture and provide a search-based method to improve the reliability of software architecture. The proposed method is based on the use of NSGAII algorithm and genetic programming and the use of software architecture reliability tactics in it. In the proposed method, we optimize the software architecture in two steps. First, we use the genetic programming algorithm to extract how to apply the software architecture reliability tactics, and in the next step, we use the NSGA-II algorithm to search for the optimal allocation of components to the hardware servers. To evaluate the proposed method, we use a reporting system case study. The results of applying the proposed optimization steps show that the reliability of the whole system as well as most of its most frequent functionalities is improved.","PeriodicalId":355187,"journal":{"name":"2022 8th International Conference on Web Research (ICWR)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129538707","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

Joint Latency and Energy-aware Data Management Layer for Industrial IoT 面向工业物联网的联合延迟和能量感知数据管理层

2022 8th International Conference on Web Research (ICWR) Pub Date : 2022-05-11 DOI: 10.1109/ICWR54782.2022.9786229

Ali Ghaderi, Z. Movahedi

引用次数: 0

A Trust-Aware Task Allocation Method Based on Blockchain for The Internet of Things 基于区块链的物联网信任感知任务分配方法

2022 8th International Conference on Web Research (ICWR) Pub Date : 2022-05-11 DOI: 10.1109/ICWR54782.2022.9786257

A. Rouzbahani, F. Taghiyareh

{"title":"A Trust-Aware Task Allocation Method Based on Blockchain for The Internet of Things","authors":"A. Rouzbahani, F. Taghiyareh","doi":"10.1109/ICWR54782.2022.9786257","DOIUrl":"https://doi.org/10.1109/ICWR54782.2022.9786257","url":null,"abstract":"In IoT systems, evaluating the trustworthiness of users and devices before relying on their information is a significant problem. Preserving privacy, decentralization, and self-management without the need of a third party is an open problem in trust management in IoT systems. Collecting reputation feedback and shreds of evidence can also be a source of security issues. On the other hand, blockchain is a promising approach for such environments where centralization and trusted third parties can cause security issues. We present a method by extending Contract Net Protocol for task allocation, which can be exploited as a base for trust management in IoT systems. This method allocates tasks to participants through smart contracts, and feedback values are securely collected in the blockchain. After registration of devices, all communications among IoT devices are handled by smart contracts, and reputation values are maintained in blockchain only when a previous task allocation is successfully taken place. The proposed method is evaluated by experiments on Hyperledger Fabric, and results are reported. Our findings indicate that the proposed method enables the IoT environment to collect feedback values robustly. The technique can be applied in a blockchain-based trust management model for security enhancement.","PeriodicalId":355187,"journal":{"name":"2022 8th International Conference on Web Research (ICWR)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129500330","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

Subject Index Page 主题索引页

2022 8th International Conference on Web Research (ICWR) Pub Date : 2022-05-11 DOI: 10.1109/icwr54782.2022.9786236

引用次数: 0

Design and Development of the Rapid Prototyping Techniques Ontology with the Appropriate Technique Selection Approach 基于适当技术选择方法的快速成型技术本体设计与开发

2022 8th International Conference on Web Research (ICWR) Pub Date : 2022-05-11 DOI: 10.1109/ICWR54782.2022.9786249

Nasibeh Pouti

引用次数: 1

Structural Analysis of Iran Railway Network based on Complex Network Theory 基于复杂网络理论的伊朗铁路网结构分析

2022 8th International Conference on Web Research (ICWR) Pub Date : 2022-05-11 DOI: 10.1109/ICWR54782.2022.9786237

Melika Mosayyebi, Hadi Shakibian, R. Azmi

引用次数: 1

Detection of Anomalous Cluster Heads and Nodes in Wireless Sensor Networks 无线传感器网络中异常簇头和节点的检测

2022 8th International Conference on Web Research (ICWR) Pub Date : 2022-05-11 DOI: 10.1109/ICWR54782.2022.9786227

Sare Gorgbandi, Reza Brangi

{"title":"Detection of Anomalous Cluster Heads and Nodes in Wireless Sensor Networks","authors":"Sare Gorgbandi, Reza Brangi","doi":"10.1109/ICWR54782.2022.9786227","DOIUrl":"https://doi.org/10.1109/ICWR54782.2022.9786227","url":null,"abstract":"Almost all security protocols of wireless sensor networks believe that the enemy or attacker can take full control of a sensor node through direct connection. Security is very important in accepting and using sensor networks in many applications. In order to clarify this issue, we focus on detecting anomalies in the nodes and cluster heads of wireless sensor networks, and look for a solution to detect anomalies in the nodes and cluster heads and determine new cluster heads. A group of researchers to detect anomalies have suggested Mobile Data Collectors (MDCs) machines, where some abnormal nodes may be inactive at the time of inspection and not be identified, and due to environmental problems, the machine cannot go to those places, it is also very expensive and cannot work online and cannot quickly overcome attacks. Due to the large number of sensors, it is not scalable. In this article, we first review the methods that have been proposed until now and describe their advantages and disadvantages and then propose a method that detects the anomalies of the nodes in the cluster heads and detects the anomalies of the cluster heads in the sink node, it runs without the need for external circuits and does not impose additional costs, it works online and can quickly overcome attacks. Our proposed method for evaluating performance was simulated by MATLAB software and it uses Intel Research Laboratory Database.","PeriodicalId":355187,"journal":{"name":"2022 8th International Conference on Web Research (ICWR)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125117314","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