Journal of Intelligent Systems最新文献_第7页

Replay attack detection based on deformable convolutional neural network and temporal-frequency attention model 基于可变形卷积神经网络和时频注意模型的重放攻击检测

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Journal of Intelligent Systems Pub Date : 2023-01-01 DOI: 10.1515/jisys-2022-0265

Dang-en Xie, Hai Hu, Qiang Xu

引用次数: 0

A novel distance vector hop localization method for wireless sensor networks 一种新的无线传感器网络距离矢量跳定位方法

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Journal of Intelligent Systems Pub Date : 2023-01-01 DOI: 10.1515/jisys-2023-0031

Y. A. A. S. Aldeen, S. Kadhim, N. N. Kadhim, Syed Hamid Hussain Madni

引用次数: 1

RES-KELM fusion model based on non-iterative deterministic learning classifier for classification of Covid19 chest X-ray images 基于非迭代确定性学习分类器的RES-KELM融合模型用于新冠肺炎胸片图像分类

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Journal of Intelligent Systems Pub Date : 2023-01-01 DOI: 10.1515/jisys-2022-0235

Arshi Husain, Virendra P. Vishvakarma

引用次数: 1

Efficient mutual authentication using Kerberos for resource constraint smart meter in advanced metering infrastructure 在高级计量基础设施中使用Kerberos实现资源约束智能电表的高效相互认证

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Journal of Intelligent Systems Pub Date : 2023-01-01 DOI: 10.1515/jisys-2021-0095

Md. Mehedi Hasan, Noor Afiza Mohd Ariffin, N. F. M. Sani

{"title":"Efficient mutual authentication using Kerberos for resource constraint smart meter in advanced metering infrastructure","authors":"Md. Mehedi Hasan, Noor Afiza Mohd Ariffin, N. F. M. Sani","doi":"10.1515/jisys-2021-0095","DOIUrl":"https://doi.org/10.1515/jisys-2021-0095","url":null,"abstract":"Abstract The continuous development of information communication technology facilitates the conventional grid in transforming into an automated modern system. Internet-of-Things solutions are used along with the evolving services of end-users to the electricity service provider for smart grid applications. In terms of various devices and machine integration, adequate authentication is the key to an accurate source and destination in advanced metering infrastructure (AMI). Various protocols are deployed to lead the identification between two parties, which require high computation time and communicational bit operations for system development. Therefore, Kerberos-based authentication protocols were designed in this study with the assistance of elliptic curve cryptography to manage the mutual authentication between two parties and reduce the time and bit operations. The protocols were evaluated in a widely adopted tool, AVISPA, which builds an understanding of the proposed protocol and ensures mutual authentication without unauthorized knowledge. In addition, upon comparing security and performance assessments to the current schemes, it was found that the protocol in this study required less time and bits to transmit information. Consequently, it effectively provides multiple security features making it suitable for resource constraint smart meters in AMI.","PeriodicalId":46139,"journal":{"name":"Journal of Intelligent Systems","volume":"15 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89426552","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

PUC: parallel mining of high-utility itemsets with load balancing on spark PUC:基于spark负载均衡的高效用项集并行挖掘

IF 3

Journal of Intelligent Systems Pub Date : 2022-01-01 DOI: 10.1515/jisys-2022-0044

Anup Brahmavar, H. Venkatarama, Geetha Maiya

{"title":"PUC: parallel mining of high-utility itemsets with load balancing on spark","authors":"Anup Brahmavar, H. Venkatarama, Geetha Maiya","doi":"10.1515/jisys-2022-0044","DOIUrl":"https://doi.org/10.1515/jisys-2022-0044","url":null,"abstract":"Abstract Distributed programming paradigms such as MapReduce and Spark have alleviated sequential bottleneck while mining of massive transaction databases. Of significant importance is mining High Utility Itemset (HUI) that incorporates the revenue of the items purchased in a transaction. Although a few algorithms to mine HUIs in the distributed environment exist, workload skew and data transfer overhead due to shuffling operations remain major issues. In the current study, Parallel Utility Computation (PUC) algorithm has been proposed with novel grouping and load balancing strategies for an efficient mining of HUIs in a distributed environment. To group the items, Transaction Weighted Utility (TWU) values as a degree of transaction similarity is employed. Subsequently, these groups are assigned to the nodes across the cluster by taking into account the mining load due to the items in the group. Experimental evaluation on real and synthetic datasets demonstrate that PUC with TWU grouping in conjunction with load balancing converges mining faster. Due to reduced data transfer, and load balancing-based assignment strategy, PUC outperforms different grouping strategies and random assignment of groups across the cluster. Also, PUC is shown to be faster than PHUI-Growth algorithm with a promising speedup.","PeriodicalId":46139,"journal":{"name":"Journal of Intelligent Systems","volume":"18 1","pages":"568 - 588"},"PeriodicalIF":3.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88493013","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

Masking and noise reduction processing of music signals in reverberant music 混响音乐中音乐信号的掩蔽与降噪处理

IF 3

Journal of Intelligent Systems Pub Date : 2022-01-01 DOI: 10.1515/jisys-2022-0024

Shenghuan Zhang, Ye Cheng

引用次数: 0

Face recognition algorithm based on stack denoising and self-encoding LBP 基于堆栈去噪和自编码LBP的人脸识别算法

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Journal of Intelligent Systems Pub Date : 2022-01-01 DOI: 10.1515/jisys-2022-0011

Yan-sheng Lu, Mudassir Khan, Mohd Dilshad Ansari

{"title":"Face recognition algorithm based on stack denoising and self-encoding LBP","authors":"Yan-sheng Lu, Mudassir Khan, Mohd Dilshad Ansari","doi":"10.1515/jisys-2022-0011","DOIUrl":"https://doi.org/10.1515/jisys-2022-0011","url":null,"abstract":"Abstract To optimize the weak robustness of traditional face recognition algorithms, the classification accuracy rate is not high, the operation speed is slower, so a face recognition algorithm based on local binary pattern (LBP) and stacked autoencoder (AE) is proposed. The advantage of LBP texture structure feature of the face image as the initial feature of sparse autoencoder (SAE) learning, use the unified mode LBP operator to extract the histogram of the blocked face image, connect to form the LBP features of the entire image. It is used as input of the stacked AE, feature extraction is done, realize the recognition and classification of face images. Experimental results show that the recognition rate of the algorithm LBP-SAE on the Yale database has achieved 99.05%, and it further shows that the algorithm has a higher recognition rate than the classic face recognition algorithm; it has strong robustness to light changes. Experimental results on the Olivetti Research Laboratory library shows that the developed method is more robust to light changes and has better recognition effects compared to traditional face recognition algorithms and standard stack AEs.","PeriodicalId":46139,"journal":{"name":"Journal of Intelligent Systems","volume":"10 1","pages":"501 - 510"},"PeriodicalIF":3.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73321286","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: 8

Eurasian oystercatcher optimiser: New meta-heuristic algorithm 欧亚捕牡蛎优化器:新的元启发式算法

IF 3

Journal of Intelligent Systems Pub Date : 2022-01-01 DOI: 10.1515/jisys-2022-0017

A. Salim, Wisam K. Jummar, Farah Maath Jasim, Mohammed S. Yousif

引用次数: 6

Interactive 3D reconstruction method of fuzzy static images in social media 社交媒体中模糊静态图像的交互式三维重建方法

IF 3

Journal of Intelligent Systems Pub Date : 2022-01-01 DOI: 10.1515/jisys-2022-0049

Xiaomei Niu

{"title":"Interactive 3D reconstruction method of fuzzy static images in social media","authors":"Xiaomei Niu","doi":"10.1515/jisys-2022-0049","DOIUrl":"https://doi.org/10.1515/jisys-2022-0049","url":null,"abstract":"Abstract Because the traditional social media fuzzy static image interactive three-dimensional (3D) reconstruction method has the problem of poor reconstruction completeness and long reconstruction time, the social media fuzzy static image interactive 3D reconstruction method is proposed. For preprocessing the fuzzy static image of social media, the Harris corner detection method is used to extract the feature points of the preprocessed fuzzy static image of social media. According to the extraction results, the parameter estimation algorithm of contrast divergence is used to learn the restricted Boltzmann machine (RBM) network model, and the RBM network model is divided into input, output, and hidden layers. By combining the RBM-based joint dictionary learning method and a sparse representation model, an interactive 3D reconstruction of fuzzy static images in social media is achieved. Experimental results based on the CAD software show that the proposed method has a reconstruction completeness of above 95% and the reconstruction time is less than 15 s, improving the completeness and efficiency of the reconstruction, effectively reconstructing the fuzzy static images in social media, and increasing the sense of reality of social media images.","PeriodicalId":46139,"journal":{"name":"Journal of Intelligent Systems","volume":"94 1","pages":"806 - 816"},"PeriodicalIF":3.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83909130","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

Iot-based power detection equipment management and control system 基于物联网的电力检测设备管理与控制系统

IF 3

Journal of Intelligent Systems Pub Date : 2022-01-01 DOI: 10.1515/jisys-2022-0127

Jintao Chen, Jianfeng Jiang, Binruo Zhu

{"title":"Iot-based power detection equipment management and control system","authors":"Jintao Chen, Jianfeng Jiang, Binruo Zhu","doi":"10.1515/jisys-2022-0127","DOIUrl":"https://doi.org/10.1515/jisys-2022-0127","url":null,"abstract":"Abstract The development and application scope of the Internet of Things is also becoming more and more extensive. Especially in the application of power testing improved systems, great progress has been made. This article aims to study how to analyze the system detection equipment based on the Internet of Things. This article describes the basic theoretical knowledge of the Internet of Things and power detection improved systems. A clustering analysis algorithm and a support vector machine algorithm based on the Internet of Things are proposed. In the experiment of this article, the scoring items of the expert’s traditional detection system include complex technology, inconvenient use, and incomplete intelligence. Among them, the highest score for complex technology is 8.6 points, the lowest score is 7 points; the highest score for inconvenience is 8.6 points, and the lowest is 8.3 points. It can be seen that related experts believe that the traditional power detection improved system is not only very complicated in technology, very inconvenient to use but also incompletely intelligent. Therefore, it is very necessary to study the system detection equipment based on the Internet of Things.","PeriodicalId":46139,"journal":{"name":"Journal of Intelligent Systems","volume":"281 1","pages":"1229 - 1245"},"PeriodicalIF":3.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74979709","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