International Journal of Advanced Computer Science and Applications最新文献_第9页

Optimal Land-cover Classification Feature Selection in Arid Areas based on Sentinel-2 Imagery and Spectral Indices 基于Sentinel-2影像和光谱指数的干旱区土地覆盖分类特征优选

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140312

Mohammed Saeed, Asmala Ahmad, O. Mohd

引用次数: 0

A Single-valued Pentagonal Neutrosophic Geometric Programming Approach to Optimize Decision Maker’s Satisfaction Level 一种优化决策者满意度的单值五边形中性几何规划方法

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140439

Satyabrata Nath, P. Das, P. Debnath

{"title":"A Single-valued Pentagonal Neutrosophic Geometric Programming Approach to Optimize Decision Maker’s Satisfaction Level","authors":"Satyabrata Nath, P. Das, P. Debnath","doi":"10.14569/ijacsa.2023.0140439","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140439","url":null,"abstract":"Achieving the desired level of satisfaction for a decision-maker in any decision-making scenario is considered a challenging endeavor because minor modifications in the process might lead to incorrect findings and inaccurate decisions. In order to maximize the decision-maker’s satisfaction, this paper proposes a Single-valued Neutrosophic Geometric Programming model based on pentagonal fuzzy numbers. The decision-maker is typically assumed to be certain of the parameters, but in reality, this is not the case, hence the parameters are presented as neutrosophic fuzzy values. The decision-maker, with this strategy, is able to achieve varying levels of satisfaction and dissatisfaction for each constraint and even complete satisfaction for certain constraints. Here the decision maker aims to achieve the maximum level of satisfaction while maintaining the level of hesitation and minimizing dissatisfaction in order to retain an optimum solution. Furthermore, transforming the objective function into a constraint adds one more layer to the Ndimensional multi-parametrizes and . The advantages of this multi-parametrized proposed method over the existing ones are proven using numerical examples. Keywords—Decision making; pentagonal neutrosophic numbers; single-valued neutrosophic geometric programming; multi-parametric programming","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":"80664918","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 Fuzzy Reward and Punishment Scheme for Vehicular Ad Hoc Networks 一种车载自组网模糊奖惩方案

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140601

Rezvi Shahariar, C. Phillips

{"title":"A Fuzzy Reward and Punishment Scheme for Vehicular Ad Hoc Networks","authors":"Rezvi Shahariar, C. Phillips","doi":"10.14569/ijacsa.2023.0140601","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140601","url":null,"abstract":"—Trust management is an important security approach for the successful implementation of Vehicular Ad Hoc Networks (VANETs). Trust models evaluate messages to assign reward or punishment. This can be used to influence a driver’s future behaviour. In the author’s previous work, a sender-side based trust management framework is developed which avoids the receiver evaluation of messages. However, this does not guarantee that a trusted driver will not lie. These “untrue attacks” are resolved by the RSUs using collaboration to rule on a dispute, providing a fixed amount of reward and punishment. The lack of sophistication is addressed in this paper with a novel fuzzy RSU controller considering the severity of incident, driver past behaviour, and RSU confidence to determine the reward or punishment for the conflicted drivers. Although any driver can lie in any situation, it is expected that trustworthy drivers are more likely to remain so, and vice versa. This behaviour is captured in a Markov chain model for sender and reporter drivers where their lying characteristics depend on trust score and trust state. Each trust state defines the driver’s likelihood of lying using different probability distribution. An extensive simulation is performed to evaluate the performance of the fuzzy assessment and examine the Markov chain driver behaviour model with changing the initial trust score of all or some drivers in Veins simulator. The fuzzy and the fixed RSU assessment schemes are compared, and the result shows that the fuzzy scheme can encourage drivers to improve their behaviour.","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":"86952175","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

IoT Technology for Intelligent Management of Energy, Equipment and Security in Smart House 智能家居中能源、设备和安全智能管理的物联网技术

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140108

Fang Yuan, Yan Zhang, Junchao Zhang

{"title":"IoT Technology for Intelligent Management of Energy, Equipment and Security in Smart House","authors":"Fang Yuan, Yan Zhang, Junchao Zhang","doi":"10.14569/ijacsa.2023.0140108","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140108","url":null,"abstract":"—The Internet of Things means that many of the daily devices used by humans will share their functions and information with each other or with humans by connecting to the Internet. The most important factor of the Internet of Things is the integration of several technologies and communication solutions. Identification and tracking technologies, wired and wireless sensors and active networks, protocols for increasing communication and intelligence of objects are the most important parts of the Internet of Things. In this article, an attempt has been made to determine the parts that can be used to make a house smart among the concepts and technologies related to web-based programs based on Internet of Things technology. Since it is very time-consuming to investigate the effect of all the Internet of Things technologies in smart homes, by studying and examining various types of research, the web-based program based on the Internet of Things is selected as an independent variable, and its effect on smart home management is investigated. For this purpose, a web-based program based on the Internet of Things for intelligent building energy management, intelligent equipment management, and intelligent security has been designed and implemented. As experimental results shown the proposed method the proposed method achieves better results compared to other existing methods in energy consumption by 33.8% reducing energy usage.","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":"87080553","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

Customer Sentiment Analysis in Hotel Reviews Through Natural Language Processing Techniques 利用自然语言处理技术分析酒店评论中的顾客情感

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140162

S. Ounacer, Driss Mhamdi, S. Ardchir, A. Daif, M. Azzouazi

{"title":"Customer Sentiment Analysis in Hotel Reviews Through Natural Language Processing Techniques","authors":"S. Ounacer, Driss Mhamdi, S. Ardchir, A. Daif, M. Azzouazi","doi":"10.14569/ijacsa.2023.0140162","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140162","url":null,"abstract":"—Customer reviews of products and services play a key role in the customers' decision to buy a product or use a service. Customers' preferences and choices are influenced by the opinions of others online; on blogs or social networks. New customers are faced with many views on the web, but they can't make the right decision. Hence, the need for sentiment analysis is to clarify whether opinions are positive, negative or neutral. This paper suggests using the Aspect-Based Sentiment Analysis approach on reviews extracted from tourism websites such as TripAdvisor and Booking. This approach is based on two main steps namely aspect extraction and sentiment classification related to each aspect. For aspect extraction, an approach based on topic modeling is proposed using the semi-supervised CorEx (Correlation Explanation) method for labeling word sequences into entities. As for sentiment classification, various supervised machine learning techniques are used to associate a sentiment (positive, negative or neutral) to a given aspect expression. Experiments on opinion corpora have shown very encouraging performances.","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":"81957990","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

Implementation of CNN for Plant Identification using UAV Imagery 利用无人机图像实现CNN植物识别

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140441

M. A. Haq, Ahsan Ahmed, J. Gyani

{"title":"Implementation of CNN for Plant Identification using UAV Imagery","authors":"M. A. Haq, Ahsan Ahmed, J. Gyani","doi":"10.14569/ijacsa.2023.0140441","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140441","url":null,"abstract":"Plants are the world's most significant resource since they are the only natural source of oxygen. Additionally, plants are considered crucial since they are the major source of energy for humanity and have nutritional, therapeutic, and other benefits. Image identification has become more prominent in this technology-driven world, where many innovations are happening in this sphere. Image processing techniques are increasingly being used by researchers to identify plants. The capacity of Convolutional Neural Networks (CNN) to transfer weights learned with huge standard datasets to tasks with smaller collections or more particular data has improved over time. Several applications are made for image identification using deep learning, and Machine Learning (ML) algorithms. Plant image identification is a prominent part of such. The plant image dataset of about 300 images collected by mobile phone and camera from different places in the natural scenes with nine species of different plants are deployed for training. A fivelayered convolution neural network (CNN) is applied for largescale plant classification in a natural environment. The proposed work claims a higher accuracy in plant identification based on experimental data. The model achieves the utmost recognition rate of 96% NU108 dataset and UAV images of NU101 have achieved an accuracy of 97.8%. Keywords—Convolutional Neural Networks (CNN); Machine Learning (ML) algorithms; plant image identification; plant image dataset","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":"82027985","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

Iris Recognition Through Edge Detection Methods: Application in Flight Simulator User Identification 基于边缘检测的虹膜识别方法在飞行模拟器用户识别中的应用

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140425

Sundas Khan, Samra Urooj Khan, Onyeka J. Nwobodo, K. Cyran

{"title":"Iris Recognition Through Edge Detection Methods: Application in Flight Simulator User Identification","authors":"Sundas Khan, Samra Urooj Khan, Onyeka J. Nwobodo, K. Cyran","doi":"10.14569/ijacsa.2023.0140425","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140425","url":null,"abstract":"— To meet the increasing security requirement of authorized users of flight simulators, personal identification is becoming more and more important. Iris recognition stands out as one of the most accurate biometric methods in use today. Iris recognition is done through different edge detection methods. Therefore, it is important to have an understanding of the different edge detection methods that are in use these days. Specifically, the biomedical research shows that irises are as different as fingerprints or the other patterns of the recognition. Furthermore, because the iris is a visible organism, its exterior look can be examined remotely using a machine vision system. The main part of this paper delves into concerns concerning the selection of the best results giving method of the recognition. In this paper, three edge detection methods, namely Canny, Sobel and Prewitt, are applied to the image of eye (iris) and their comparative analysis is discussed. These methods are applied using the Software MATLAB. The datasets used for this purpose are CASIA and MMU. The results indicate that the performance of Canny edge detection method is best as compared to Sobel and Prewitt. Image quality is a key requirement in image-based object recognition. This paper provides the quality evaluation of the images using different metrics like PSNR, SNR, MSE and SSIM. However, SSIM is considered best image quality metric as compared to PSNR, SNR and MSE.","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":"83613365","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

Optimal Scheduling using Advanced Cat Swarm Optimization Algorithm to Improve Performance in Fog Computing 利用先进的Cat群算法提高雾计算性能的最优调度

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.01407114

Xiaoyan Huo, Xue-ming Wang

{"title":"Optimal Scheduling using Advanced Cat Swarm Optimization Algorithm to Improve Performance in Fog Computing","authors":"Xiaoyan Huo, Xue-ming Wang","doi":"10.14569/ijacsa.2023.01407114","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.01407114","url":null,"abstract":"—Fog computing can be considered a decentralized computing approach that essentially extends the capabilities offered by cloud computing to the periphery of the network. In addition, due to its proximity to the user, fog computing proves to be highly efficient in minimizing the volume of data that needs to be transmitted, reducing overall network traffic, and shortening the distance that data must travel. But this technology, like other new technologies, has challenges, and scheduling and optimal allocation of resources is one of the most important of these challenges. Accordingly, this research aims to propose an optimal solution for efficient scheduling within the fog computing environment through the application of the advanced cat swarm optimization algorithm. In this solution, the two main behaviors of cats are implemented in the form of seek and tracking states. Accordingly, processing nodes are periodically examined and categorized based on the number of available resources; servers with highly available resources are prioritized in the scheduling process for efficient scheduling. Subsequently, the congested servers, which may be experiencing various issues, are migrated to alternative servers with ample resources using the virtual machine live migration technique. Ultimately, the effectiveness of the proposed solution is assessed using the iFogSim simulator, demonstrating notable reductions in execution time and energy consumption. So, the proposed solution has led to a 20% reduction in execution time while also improving energy efficiency by more than 15% on average. This optimization represents a trade-off between improving performance and reducing resource consumption.","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":"85316991","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

Apache Spark in Riot Games: A Case Study on Data Processing and Analytics Apache Spark在Riot游戏中的应用:数据处理和分析的案例研究

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140704

K. Sharma, Firdous Hussain Mohammad, Deepak Parashar

引用次数: 0

Design and Implementation of an IoT Control and Monitoring System for the Optimization of Shrimp Pools using LoRa Technology 利用LoRa技术优化对虾池的物联网控制与监控系统的设计与实现

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International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI: 10.14569/ijacsa.2023.0140829

J. Pontón, Verónica Ojeda, Víctor Asanza, L. L. Lorente-Leyva, D. H. Peluffo-Ordóñez

{"title":"Design and Implementation of an IoT Control and Monitoring System for the Optimization of Shrimp Pools using LoRa Technology","authors":"J. Pontón, Verónica Ojeda, Víctor Asanza, L. L. Lorente-Leyva, D. H. Peluffo-Ordóñez","doi":"10.14569/ijacsa.2023.0140829","DOIUrl":"https://doi.org/10.14569/ijacsa.2023.0140829","url":null,"abstract":"—The shrimp farming industry in Ecuador, renowned for its shrimp breeding and exportation, faces challenges due to diseases related to variations in abiotic factors during the maturation stage. This is partly attributed to the traditional methods employed in shrimp farms. Consequently, a prototype has been developed for monitoring and controlling abiotic factors using IoT technology. The proposed system consists of three nodes communicating through the LoRa interface. For control purposes, a fuzzy logic system has been implemented that evaluates temperature and dissolved oxygen abiotic factors to determine the state of the aerator, updating the information in the ThingSpeak application. A detailed analysis of equipment energy consumption and the maximum communication range for message transmission and reception was conducted. Subsequently, the monitoring and control system underwent comprehensive testing, including communication with the visualization platform. The results demonstrated significant improvements in system performance. By modifying parameters in the microcontroller, a 2.55-fold increase in battery durability was achieved. The implemented fuzzy logic system enabled effective on/off control of the aerators, showing a corrective trend in response to variations in the analyzed abiotic parameters. The robustness of the LoRa communication interface was evident in urban environments, achieving a distance of up to 1 km without line of sight.","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":"90538665","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