International Journal of Advanced Computer Science and Applications最新文献_第3页

Ensemble Security and Multi-Cloud Load Balancing for Data in Edge-based Computing Applications 边缘计算应用中数据的集成安全与多云负载均衡

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140802

R. Dornala

{"title":"Ensemble Security and Multi-Cloud Load Balancing for Data in Edge-based Computing Applications","authors":"R. Dornala","doi":"10.14569/ijacsa.2023.0140802","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140802","url":null,"abstract":"— Edge computing has gained significant attention in recent years due to its ability to process data closer to the source, resulting in reduced latency and improved performance. However, ensuring data security and efficient data management in edge-based computing applications poses significant challenges. This paper proposes an ensemble security approach and a multi-cloud load-balancing strategy to address these challenges. The ensemble security approach leverages multiple security mechanisms, such as encryption, authentication, and intrusion detection systems, to provide a layered defense against potential threats. By combining these mechanisms, the system can detect and mitigate security breaches at various levels, ensuring the integrity and confidentiality of data in edge-based environments. The multi-cloud load balancing strategy also aims to optimize resource utilization and performance by distributing data processing tasks across multiple cloud service providers. This approach takes advantage of the flexibility and scalability offered by the cloud, allowing for dynamic workload allocation based on factors like network conditions and computational capabilities. To evaluate the effectiveness of the proposed approach, we conducted experiments using a realistic edge-based computing environment. The results demonstrate that the ensemble security approach effectively detects and prevents security threats, while the multi-cloud load balancing strategy with edge computing to improve the overall system performance and resource utilization.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"11 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76622033","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

Personalized Music Recommendation Based on Interest and Emotion: A Comparison of Multiple Algorithms 基于兴趣和情感的个性化音乐推荐:多种算法的比较

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140426

Xiuli Yan

{"title":"Personalized Music Recommendation Based on Interest and Emotion: A Comparison of Multiple Algorithms","authors":"Xiuli Yan","doi":"10.14569/ijacsa.2023.0140426","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140426","url":null,"abstract":"Recommendation algorithms can greatly improve the efficiency of information retrieval for users. This article briefly introduced recommendation algorithms based on association rules and algorithms based on interest and emotion analysis. After crawling music and comment data from the NetEase Cloud platform, a simulation experiment was conducted. Firstly, the performance of the Back-Propagation Neural Network (BPNN) in the interest and emotion-based algorithm for recommending music was tested, and then the impact of the proportion of emotion weight between comments and music on the emotion analysis-based algorithm was tested. Finally, the three recommendation algorithms based on association rules, user ratings, and interest and emotion analysis were compared. The results showed that when the BPNN used the dominant interest and emotion and secondary interest and emotion as judgment criteria, the accuracy of interest and emotion recognition for music and comments was higher. When the proportion of interest and emotion weight between comments and music was 6:4, the interest and emotion analysis-based recommendation algorithm had the highest accuracy. The interest and emotion-based recommendation algorithm had higher recommendation accuracy than the association rule-based and user rating-based algorithms, and could provide users with more personalized and emotional music recommendations. Keywords—Interest and emotion; recommendation algorithm; music; personalization","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"9 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78602295","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

Experimental Evaluation of Genetic Algorithms to Solve the DNA Assembly Optimization Problem 遗传算法解决DNA装配优化问题的实验评价

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140333

Hachemi Bennaceur, Meznah Almutairy, Nora Alqhtani

引用次数: 1

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

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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":"168 1","pages":""},"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

Application of Improved Ant Colony Algorithm Integrating Adaptive Parameter Configuration in Robot Mobile Path Design 集成自适应参数配置的改进蚁群算法在机器人移动路径设计中的应用

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140844

Jin-Il Han

{"title":"Application of Improved Ant Colony Algorithm Integrating Adaptive Parameter Configuration in Robot Mobile Path Design","authors":"Jin-Il Han","doi":"10.14569/ijacsa.2023.0140844","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140844","url":null,"abstract":"—Under the background of the continuous progress of Industry 4.0 reform, the market demand for mobile robots in major world economies is gradually increasing. In order to improve the mobile robot's movement path planning quality and obstacle avoidance ability, this research adjusted the node selection method, pheromone update mechanism, transition probability and volatility coefficient calculation method of the ant colony algorithm, and improved the search direction setting and cost estimation calculation method of the A* algorithm. Thus, a robot movement path planning model can be designed with respect to the improved ant colony algorithm and A* algorithm. The simulation experiment results on grid maps show that the planning model constructed in view of the improved algorithm, the traditional ant colony algorithm, the Tianniu whisker search algorithm, and the particle swarm algorithm designed in this study converged after 8, 37, 23, and 26 iterations, respectively. The minimum path lengths after convergence were 13.24m, 17.82m, 16.24m, and 17.05m, respectively. When the edge length of the grid map is 100m, the minimum planning length and total moving time of the planning model constructed in view of the improved algorithm, the traditional ant colony algorithm, the longicorn whisker search algorithm, and the particle swarm algorithm designed in this study are 49m, 104m, 75m, 93m and 49s, 142s, 93s, and 127s, respectively. This indicates that the model designed in this study can effectively shorten the mobile path and training time while completing mobile tasks. The results of this study have a certain reference value for optimizing the robot's movement mode and obstacle avoidance ability.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"110 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77182836","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

Research on Settlement Prediction of Building Foundation in Smart City Based on BP Network 基于BP网络的智慧城市建筑地基沉降预测研究

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140693

Luyao Wei

{"title":"Research on Settlement Prediction of Building Foundation in Smart City Based on BP Network","authors":"Luyao Wei","doi":"10.14569/ijacsa.2023.0140693","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140693","url":null,"abstract":"In the construction process of high-rise buildings, it is necessary to predict the settlement and deformation of the foundation, and the current prediction methods are mainly based on empirical theoretical calculations and methods and more accurate numerical analysis methods. In the face of the interference of complex and ever-changing terrain and parameter values on prediction methods, in order to accurately determine the settlement of building foundations, this study designed a smart city building foundation settlement prediction method based on BP neural network. Firstly, a real-time dynamic monitoring unit for building foundation settlement was constructed using Wireless Sensor Network (WSN) technology. Then, the monitoring data was used to calculate the relevant parameters of building foundation settlement through layer sum method. Finally, input the monitoring data into the BP network results, adjust the weights of the output layer and hidden layer using settlement related parameters, and output the settlement prediction results of the smart city building foundation through training. The study selected average error and prediction time as evaluation criteria to test the feasibility of the method proposed in this article. This method can effectively predict foundation settlement, with an average prediction error always less than 4% and a prediction process time always less than 49ms. Keyword—Smart city; intelligent architecture; foundation settlement; settlement prediction; BP neural network; parameter","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"28 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79139772","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

Fake News Classification Web Service for Spanish News by using Artificial Neural Networks 基于人工神经网络的西班牙新闻假新闻分类Web服务

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140334

P. Moreno-Vallejo, G. Bastidas-Guacho, Patricio Rene Moreno-Costales, Jefferson Jose Chariguaman-Cuji

{"title":"Fake News Classification Web Service for Spanish News by using Artificial Neural Networks","authors":"P. Moreno-Vallejo, G. Bastidas-Guacho, Patricio Rene Moreno-Costales, Jefferson Jose Chariguaman-Cuji","doi":"10.14569/ijacsa.2023.0140334","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140334","url":null,"abstract":"—The use of digital media, such as social networks, has promoted the spreading of fake news on a large scale. Therefore, several Machine Learning techniques, such as artificial neural networks, have been used for fake news detection and classification. These techniques are widely used due to their learning capabilities. Besides, models based on artificial neural networks can be easily integrated into social media and websites to spot fake news early and avoid their propagation. Nevertheless, most fake news classification models are available only for English news, limiting the possibility of detecting fake news in other languages, such as Spanish. For this reason, this study proposes implementing a web service that integrates a deep learning model for the classification of fake news in Spanish. To determine the best model, the performance of several neural network architectures, including MLP, CNN, and LSTM, was evaluated using the F1 score., and LSTM using the F1 score. The LSTM architecture was the best, with an F1 score of 0.746. Finally, the efficiency of web service was evaluated, applying temporal behavior as a metric, resulting in an average response time of 1.08 seconds.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"11 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76238801","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

Construction of an Ontology-based Document Collection for the IT Job Offer in Morocco 基于本体的摩洛哥IT招聘文档集的构建

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140749

Zineb Elkaimbillah, B. E. Asri, M. Mikram, Maryem Rhanoui

引用次数: 0

Demand Forecasting Models for Food Industry by Utilizing Machine Learning Approaches 基于机器学习方法的食品行业需求预测模型

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.01403101

Nouran Nassibi, Heba A. Fasihuddin, L. Hsairi

{"title":"Demand Forecasting Models for Food Industry by Utilizing Machine Learning Approaches","authors":"Nouran Nassibi, Heba A. Fasihuddin, L. Hsairi","doi":"10.14569/ijacsa.2023.01403101","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.01403101","url":null,"abstract":"—Continued global economic instability and uncertainty is causing difficulties in predicting sales. As a result, many sectors and decision-makers are facing new, pressing challenges. In supply chain management, the food industry is a key sector in which sales movement and the demand forecasting for food products are more difficult to predict. Accurate sales forecasting helps to minimize stored and expired items across individual stores and, thus, reduces the potential loss of these expired products. To help food companies adapt to rapid changes and manage their supply chain more effectively, it is a necessary to utilize machine learning (ML) approaches because of ML’s ability to process and evaluate large amounts of data efficiently. This research compares two forecasting models for confectionery products from one of the largest distribution companies in Saudi Arabia in order to improve the company’s ability to predict demand for their products using machine learning algorithms. To achieve this goal, Support Vectors Machine (SVM) and Long Short-Term Memory (LSTM) algorithms were utilized. In addition, the models were evaluated based on their performance in forecasting quarterly time series. Both algorithms provided strong results when measured against the demand forecasting model, but overall the LSTM outperformed the SVM.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"42 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86537929","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