International Journal of Computing最新文献_第10页

Prevent and Reduce the Risk of Implementing the Main Cybersecurity Threats 预防和降低实施主要网络安全威胁的风险

International Journal of Computing Pub Date : 2022-03-30 DOI: 10.47839/ijc.21.1.2515

Y. Danyk, S. Vdovenko, S. Voloshko

引用次数: 0

Stretch-Contract Operator in the Ellipsoidal Approximation of the Minkowski Sum of Convex Sets 凸集Minkowski和的椭球逼近中的拉伸-收缩算子

International Journal of Computing Pub Date : 2022-03-30 DOI: 10.47839/ijc.21.1.2517

O. V. Sholokhov

{"title":"Stretch-Contract Operator in the Ellipsoidal Approximation of the Minkowski Sum of Convex Sets","authors":"O. V. Sholokhov","doi":"10.47839/ijc.21.1.2517","DOIUrl":"https://doi.org/10.47839/ijc.21.1.2517","url":null,"abstract":"The space expansion-contraction operator was originally developed to solve mathematical programming problems. However, it can be successfully applied to solve the problem of ellipsoidal approximation of the information set in the state space analytically specified. In this case, a main property of the operator - space compression is used to minimize the approximating ellipsoid by a multidimensional volume. The paper shows the use of the specified expansion-contraction operator to approximate a set of attainability of the linear control system as an example. The main goal of the paper is to give analytical and geometric representations of the specified operator in order to show its action in the approximation problem. For this purpose, the paper shows an analytical derivation of the operator and a geometric illustration of each parameter of the operator. The results of minimum approximation modeling by this operator compared with other known solutions have been also presented. The simulation results are given both numerically and graphically. Based on the results of comparison, conclusions are made and recommendations are given in the use of ellipsoidal approximation of information sets according to different criteria for minimizing the approximating ellipsoid. Typical examples of ellipsoidal approximation, which show when it is expedient to use the proposed of expansion-contraction operator, have been given.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84999385","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

On Strange Memory Effects in Long–term Forecasts using Regularised Recurrent Neural Networks 正则化递归神经网络在长期预测中的奇异记忆效应

International Journal of Computing Pub Date : 2022-03-30 DOI: 10.47839/ijc.21.1.2513

Arthur Lerke, H. Hessling

引用次数: 0

Implementation of Chatbot in Online Classes using Google Classroom 基于Google课堂的在线课堂聊天机器人的实现

International Journal of Computing Pub Date : 2022-03-30 DOI: 10.47839/ijc.21.1.2516

M. Sarosa, Mokhamad Hadi Wijaya, H. Tolle, A. E. Rakhmania

引用次数: 2

Wireless Sensor Network based Forest Fire Early Detection Systems: Development and Implementation 基于无线传感器网络的森林火灾早期探测系统:开发与实现

International Journal of Computing Pub Date : 2022-03-30 DOI: 10.47839/ijc.21.1.2522

Bohdan Chernetskyi, V. Kharchenko, Alexandr Orehov

{"title":"Wireless Sensor Network based Forest Fire Early Detection Systems: Development and Implementation","authors":"Bohdan Chernetskyi, V. Kharchenko, Alexandr Orehov","doi":"10.47839/ijc.21.1.2522","DOIUrl":"https://doi.org/10.47839/ijc.21.1.2522","url":null,"abstract":"The article is devoted to the development of a monitoring system based on wireless sensor networks. The purpose of the article is to implement a system for environmental monitoring using wireless sensor networks, as well as to solve the problem of covering the area with this network. Wireless sensor networks and their involvement in environmental monitoring are investigated and interactions between wireless networks and data communication protocols are described. The monitoring system is considered and analyzed. An experiment is conducted in which it has been checked at what maximum distance the temperature parameters can be transmitted, the experiment is conducted with and without interference. Routing algorithms for how they work and how parameters (temperature) are transmitted from sensors to the server are considered. A terrestrial monitoring system layout for environmental monitoring is investigated and developed based on Zigbee wireless sensor network construction technology, given that it can be added to this network new units or their replacement. The Mesh topology is selected and the separate physical devices that are the nodes of this network are identified. Nodes are also designed, using modules from Digi called XBee as a base station for Arduino sensors and as a ZigBee data base. These nodes are investigated for noise immunity and stability using flame, smoke and temperature sensors. The study found that XBee nodes are very unstable working near Wi-Fi routers and interfering in the form of forest. The conclusion about the result of the experiment is formulated, as well as how the system can be further upgraded, which can be added and what parameters can be observed. The proposed method for the location of the ground forest fire monitoring system’s equipment ensures full control and the flame detection preciseness.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88582450","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

Cervical Cancer Diagnosis System using Convolutional Neural Network ResidualNet 基于卷积神经网络残差网的宫颈癌诊断系统

International Journal of Computing Pub Date : 2022-03-30 DOI: 10.47839/ijc.21.1.2518

D. C. R. Novitasari, Putri Wulandari, Dina Zatusiva Haq

{"title":"Cervical Cancer Diagnosis System using Convolutional Neural Network ResidualNet","authors":"D. C. R. Novitasari, Putri Wulandari, Dina Zatusiva Haq","doi":"10.47839/ijc.21.1.2518","DOIUrl":"https://doi.org/10.47839/ijc.21.1.2518","url":null,"abstract":"Cervical cancer is a deadly disease attacking women. It represents 6.6% of all female cancers. The stadium of cervical cancer is determined based on the presence of carcinoma. The cervical cancer classification system can be used to help medical workers to analyze the stadium of cervical cancer. In this study, cervical cancer stages were divided into five classes, namely, normal cervix, stadium I, stadium II, stadium III, and stadium IV based on colposcopy images. The proposed method is one of deep learning methods, that is convolutional neural network (CNN) using deep residual network (ResidualNet) architecture. This study compared ResidualNet-18, ResidualNet-50, and ResidualNet-101 models and some conventional methods. The comparison results show that ResidualNet is more accurate than conventional methods. From the experiment, based on the accuracy value and elapsed time, ResidualNet-50 is worth using for cervical cancer classification. The result of this evaluation is higher than the maximum achievement of the ResidualNet-18 architecture. In addition, the elapsed time of the classification process using the ResidualNet-50 architecture with the accuracy, sensitivity, and specificity values reaching 100% is shorter than ResidualNet-101, which is 4397 s.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84572637","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

A Real-Value Parameter Function Optimization Algorithm using Repeated Adaptive Local Search 基于重复自适应局部搜索的实值参数函数优化算法

International Journal of Computing Pub Date : 2022-03-30 DOI: 10.47839/ijc.21.1.2519

S. Auwatanamongkol

{"title":"A Real-Value Parameter Function Optimization Algorithm using Repeated Adaptive Local Search","authors":"S. Auwatanamongkol","doi":"10.47839/ijc.21.1.2519","DOIUrl":"https://doi.org/10.47839/ijc.21.1.2519","url":null,"abstract":"A simple and easy to implement but very effective algorithm for solving real-value parameter optimization problems is introduced in this paper. The main idea of the algorithm is to perform a local search repeatedly on a prospective subregion where the optimal solution may be located. The local search randomly samples a number of solutions in a given subregion. If a new best-so- far solution has been found, the center of the search subregion is moved based on the new best-so-far solution and the size of the search subregion is gradually reduced by a predefined shrinking rate. Otherwise, the center of the search is not moved and the size of the search subregion is reduced using a predefined shrinking rate. This process is repeated for a number of instances so that the search is focused on a gradually smaller and smaller prospective subregion. To enhance the likelihood of achieving an optimal solution, many rounds of this repeated local search are performed. Each round starts with a smaller and smaller initial search space. According to the experiment results, the proposed algorithm, though very simple, can outperform some well-known optimization algorithms on some testing functions.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85094685","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

Utilizing Genetic Algorithm and Artificial Bee Colony Algorithm to Extend the WSN Lifetime 利用遗传算法和人工蜂群算法延长无线传感器网络的寿命

International Journal of Computing Pub Date : 2022-03-30 DOI: 10.47839/ijc.21.1.2514

Sawsan Alshattnawi, Lubna Afifi, Amani Shatnawi, Malek Barhoush

{"title":"Utilizing Genetic Algorithm and Artificial Bee Colony Algorithm to Extend the WSN Lifetime","authors":"Sawsan Alshattnawi, Lubna Afifi, Amani Shatnawi, Malek Barhoush","doi":"10.47839/ijc.21.1.2514","DOIUrl":"https://doi.org/10.47839/ijc.21.1.2514","url":null,"abstract":"Extending the lifetime of Wireless Sensor Networks (WSN) is an important issue due to the mission assigned to these networks. The sensors collect data relevant to a specific field. Then, the sensors send the collected data to a base station where it is analyzed, and a suitable reaction can be taken. Sensors in WSN depend on a battery with limited energy to do their work. Data transmission and receiving consume energy, which may lead to the loss of the whole network or some of the essential nodes. For this reason, energy must be preserved as long as possible to prolong the network lifetime. Several types of research were presented with different approaches to minimize power consumption. In this paper, we present a hybrid technique that includes two population-based algorithms: genetic algorithm (GA) and artificial bee colony (ABC) with clustering approaches. This proposed novel technique aims to reduce the dissipation of power consumption per sensor node in the WSN, and as a consequence, the lifetime of the WSN is extended. The ABC algorithm was used to improve an initial population, which was used in the GA. Also, we used two approaches of clustering; clustering based on genetic algorithm and K-means clustering beside LEACH protocol. The experimental results show that the proposed approach approved its efficiency in lifetime extending through an increasing number of the operational nodes per round and transmission.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81413374","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: 7

Time Series Forecasting Based on Support Vector Machine Using Particle Swarm Optimization 基于粒子群优化的支持向量机时间序列预测

International Journal of Computing Pub Date : 2022-03-30 DOI: 10.47839/ijc.21.1.2520

Zana Azeez Kakarash, Hawkar Saeed Ezat, Shokhan Ali Omar, Nawroz Fadhil Ahmed

{"title":"Time Series Forecasting Based on Support Vector Machine Using Particle Swarm Optimization","authors":"Zana Azeez Kakarash, Hawkar Saeed Ezat, Shokhan Ali Omar, Nawroz Fadhil Ahmed","doi":"10.47839/ijc.21.1.2520","DOIUrl":"https://doi.org/10.47839/ijc.21.1.2520","url":null,"abstract":"In recent years, due to the non-linear nature, complexity, and irregularity of time series, especially in energy consumption and climate, studying this field has become very important. Therefore, this study aims to provide a high accuracy and efficiency hybrid approach to time series forecasting. The proposed model is called EDFPSO-SVR (Empirical Mode Decomposition- Discrete Wavelet Transform- Feature selection with Particle Swarm Optimization-Support Vector Regression). In the proposed hybrid approach, the first step is to decompose the signal into the Intrinsic Mode Functions (IMF) component using the Empirical Mode Decomposition (EMD) algorithm. In the second step, each component is transformed into subsequences of approximation properties and details by converting the Wavelets. In the third step, the best feature is extracted by the PSO algorithm. The purpose of using the PSO algorithm is feature extraction and error minimization of the proposed approach. The fourth step, using time vector regression, has dealt with time series forecasting. Four data sets in two different fields have been used to evaluate the proposed method. The two datasets are electric load of England and Poland, and the other two datasets are related to the temperature of Australia and Belgium. Evaluation criteria include MSE, RMSE, MAPE, and MAE. The evaluation results of the proposed method with other Principal component analysis (PCA) feature extraction algorithms, and comparisons with methods and studies in this field, indicate the proper performance of the proposed approach.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72736472","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: 3

Software Requirements Profile Quality Model 软件需求概要质量模型

International Journal of Computing Pub Date : 2022-03-30 DOI: 10.47839/ijc.21.1.2524

O. Gordieiev, V. Kharchenko, D. Gordieieva

{"title":"Software Requirements Profile Quality Model","authors":"O. Gordieiev, V. Kharchenko, D. Gordieieva","doi":"10.47839/ijc.21.1.2524","DOIUrl":"https://doi.org/10.47839/ijc.21.1.2524","url":null,"abstract":"Article opens series of works devoted to profile-oriented software quality assessment. In this article the concept of software requirements profiling for subsequent software requirements profile quality assessment is analyzed and developed. The main result of the article is the development of the software requirements profile quality model. The model describes the following: characteristics and attributes of software requirements and their classification features; characteristics and attributes of software requirements profile and their classification features; semantics and syntax of software requirements. The article is based on analysis and use of the following standards: ISO/IEC 25012:2008, ISO/IEC/IEEE 29148:2018, ISO/IEC/IEEE 29148:2011. Examples of software requirements profile quality model are introduced. The suggested approach is used for the development of terms of reference or draft of a new standard. For example, the model is used for an assessment draft of the new standard “Requirements to computer security of NPP Instrumentation and Control Systems (NPP I&C)” developed by the Ukrainian state regulatory body. As a result of the development of the software requirements profile quality model, a set of propositions for improving the quality of the standard as a branch of the profile for NPP I&C cybersecurity are implemented.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88194485","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