V. Prasad, E. D. Gowda, K. Indira, Ananya Kodikula, Bhavan B. Rao
{"title":"RIT Logo based Slotted PLPCMA Multi-Band Patch Antenna","authors":"V. Prasad, E. D. Gowda, K. Indira, Ananya Kodikula, Bhavan B. Rao","doi":"10.46300/9106.2022.16.95","DOIUrl":"https://doi.org/10.46300/9106.2022.16.95","url":null,"abstract":"A compact Printed Log-Periodic Curvilinear Monopole Array (PLPCMA) antenna having a Defected Ground Plane (DGP) is proposed and examined. The proposed array of curvilinear monopoles is designed on a FR-4 substrate having a dielectric constant of 4.4. The designed antenna is multi-band operated having its resonance in the regions of S band (2GHz to 4GHz), X band (8GHz to 12GHz) and C band (4GHz to 8GHz). The design reveals Voltage Standing Wave Ratio (VSWR) lesser than 1.5 has been achieved at resonating frequencies 2.49GHz, 3.28GHz, 6.84GHz and 8.36GHz with fractional bandwidth of 4.02, 3.66, 50.58 and 41.39 percentages respectively. The presented antenna exhibits unidirectional end-fire radiation pattern with peak realized gain of 7. 1145dBi.The measured results depicts that PLPCMA antenna has good -10dB impedance bandwidth of 158% from 1.58GHz to 15GHz (9.49:1) and suits for Wi-Fi/WIMAX UWB applications.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74323019","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}
Jun Yuan, X. Meng, Jianhua Ran, Wei Wang, Qiang Zhao, Jun Li, Qin Li
{"title":"Design of High-speed Delay-FXLMS Hardware Architecture Based on FPGA","authors":"Jun Yuan, X. Meng, Jianhua Ran, Wei Wang, Qiang Zhao, Jun Li, Qin Li","doi":"10.46300/9106.2022.16.94","DOIUrl":"https://doi.org/10.46300/9106.2022.16.94","url":null,"abstract":"In order to improve the convergence and clock speed of DFxLMS adaptive filter, a hardware architecture of fine-grained retiming DFxLMS (HS-TF-RDFXLMS) filter in the form of hardware sharing transpose is proposed. Firstly, the architecture adopts delay decomposition algorithm to solve the problem that the convergence of filter decreases due to the increase of delay and output lag. Secondly, on the premise that the algorithm performance remains unchanged, the adaptive filter module and the secondary path module are transposed to further reduce the critical path to improve the clock speed of the system. The number of registers is reduced by optimizing circuit sub-module. Finally, the area/speed tradeoff of TF-RDFXLMS filter is realized by hardware sharing on the basis of constant critical path. Experimental results show that the convergence speed of the algorithm is 3.5 times that of DFxLMS algorithm, and the critical path is shortened by ([log2N]+1)TADD. The circuit structure of adaptive filter designed in this paper is realized by Xilinx Artix7 FPGA platform. The clock speed of HS-TF-RDFXLMS filter is reduced by 4.386% compared with TF-RDFXLMS filter. However, the resources of LUT and FF are saved by 10.964% and 28.322% respectively. The power consumption is 150.73 mW. This improves the performance of the system.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86106594","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}
{"title":"IoT-based Network Attacks Discovery with Combined Classifiers","authors":"Vanya Ivanova, T. Tashev, I. Draganov","doi":"10.46300/9106.2022.16.93","DOIUrl":"https://doi.org/10.46300/9106.2022.16.93","url":null,"abstract":"In this paper following the recent trends in IoT-based network attacks discovery and advancing further our previous research, in which we optimize and test single neural network, support vector machine and random forest classifiers for both the detection and recognition of multiple DDoS attacks, we propose results from newly developed combined classifiers. The first of them employs only a neural network and a random forest classifier, while the second use additionally a support vector machine. Both are implemented in two modifications – as detectors of malicious vs. normal traffic, and as classifiers of 10 types of attacks vs. non-attack samples. High classification accuracy is being obtained over the popular Bot-IoT dataset and it prove higher than that of the single classifiers. At the same time, it is also higher than other solutions, proposed in the practice.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77512328","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}
{"title":"A Review of Graph Signal Processing with Neural Networks","authors":"Yuzhong Yan, C. Akujuobi","doi":"10.46300/9106.2022.16.91","DOIUrl":"https://doi.org/10.46300/9106.2022.16.91","url":null,"abstract":"In this paper, we review the development of the traditional graph signal processing methodology, and the recent research areas that are applying graph neural networks on graph data. For the popular topics on processing the graph data with neural networks, the main models/frameworks, dataset and applications are discussed in details. Some challenges and open problems are provided, which serve as the guidance for future research directions.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87168120","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}
{"title":"Research on Data Mining Algorithm Based on BP Neural Network","authors":"Jingyou Zhang, Haiping Zhong","doi":"10.46300/10.46300/9106.2022.16.90","DOIUrl":"https://doi.org/10.46300/10.46300/9106.2022.16.90","url":null,"abstract":"The current data mining algorithm has the problem of imperfect data mining function, which leads to the algorithm taking too long time. This paper designs a data mining algorithm based on BP neural network. Analyze the basic structure of the data mining algorithm, obtain the data characteristics of the multi-objective decision-making, adjust the convergence speed with the distributed computing technology to keep the inertia factor state unchanged, construct the local minimal discrete model, measure the interest of the model, calculate the optimal output value of the network using the BP (Back Propagation) neural network model, and complete the improved design of the data mining function. Experimental results: The average computational time consumption of the designed data mining algorithm is 559.827 seconds, which saves 145.975 seconds and 174.237 seconds respectively than other traditional algorithms. It is proved that the data mining algorithm based on BP neural network reduces the computational time consumption, improves the performance of data mining, and has high application value.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86433289","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}
{"title":"Statistical Analysis of Voltage Unbalance Emission Due to Asymmetrical Loads in Three-Phase Power Systems","authors":"D. Bellan","doi":"10.46300/9106.2022.16.92","DOIUrl":"https://doi.org/10.46300/9106.2022.16.92","url":null,"abstract":"This paper investigates the statistical properties of the voltage unbalance factor in a three-phase system due to an asymmetrical three-phase load with uncertain parameters. The parameters of the three-phase load are treated as random variables with Gaussian distribution. Random asymmetry in the three-phase load results in random values of the voltage unbalance factor. The probability density function, the cumulative distribution function, the mean value and the variance of the voltage unbalance factor are derived in closed form and numerically validated. The obtained results are useful to provide a quantitative description of possible effects of asymmetry in a three-phase load such as the connection of a large single-phase load.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87070482","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}
{"title":"DWT based Person Re-Identification using GAN","authors":"Arun , Kumar D. R, K. A. N., A. A. C.","doi":"10.46300/9106.2022.16.89","DOIUrl":"https://doi.org/10.46300/9106.2022.16.89","url":null,"abstract":"The recent development in person re-identification has challenging task for variations in pose, illumination, expression, and also similar appearance between two different persons. In this paper, we propose Discrete Wavelet Transform (DWT) based person re-identification using Generative Adversarial Network (GAN). The CMU multi-PIE face database with multiple viewpoints and illuminations is considered to test the model. The profile side view face images to be tested are converted into frontal face images using Two-pathway generator adversarial network (TP-GAN). The frontal face images are loaded into the server to create server database. The synthesized TP-GAN images and server database images are pre-processed to convert RGB into grayscale images and also to convert into uniform face image dimensions. The person re-identification is based on feature extraction through DWT, which generates one low frequency LL band and three high frequency bands LH, HL and HH. The LL band coefficients are considered as final features, which are noise-free and compressed number of features. The features of profile side view images and server database images are compared using Normalized Euclidean Distance (NED) and threshold values for person re-identification.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85634121","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}
{"title":"Vehicular Communication using Balanced Centralized and Decentralized Cluster Heads","authors":"M. Iskandarani","doi":"10.46300/9106.2022.16.88","DOIUrl":"https://doi.org/10.46300/9106.2022.16.88","url":null,"abstract":"A new approach to vehicular communication employing equal weights for distance and vehicular speed for centralized and decentralized communication is presented. The main objective of this work, which is to establish utilization expression and characteristics for an optimized balanced vehicular communication is achieved. The technique is based on analyzing effect of communication process (centralized, decentralized) on transmission efficiency and probability of failure. The analysis using utilization function, cluster head selection time, and end to end transmission time. The simulation and analysis concluded that the decentralization approach is more efficient compared to the centralized approach, so combination of both is proved to be effective. The work also uncovered the need for optimization of vehicular speed relative to transmission radius and use of zoning to effectively improve transmission efficiency. Mathematical models are presented that covers a critical relationship between probability of transmission failure, cluster head selection time and end to end delay. Also, an important mathematical expression that considers cluster head selection time and end to end delay and their effect on connection utilization is presented. The work proves that combined centralized and decentralized techniques using balanced weights approach is effective using dynamic weights selection algorithm that determines optimum weights for both used variables (distance, Vehicular speed).","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81045720","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}
{"title":"Structural Knowledge-Guided Feature Inference Network for Image Inpainting","authors":"Yongqiang Du","doi":"10.46300/9106.2022.16.87","DOIUrl":"https://doi.org/10.46300/9106.2022.16.87","url":null,"abstract":"Image inpainting is an essential task in image restoration field. Currently, most meth- ods for image inpainting employ the encoder- decoder framework to restore degraded areas, and this often results in synthesizing wrong se- mantic structure due to the lack of guiding from effective prior information. In this paper, we pro- pose a structural knowledge-guided framework for image inpainting, which predicts both the edge map and corrupted content at the same time. Our model captures structural knowledge in the structure estimation branch to guide the content inference in the latent feature space. By employing self-attention mechanism to aggre- gate known information and inferred structural knowledge, our model is able to synthesize more semantically reasonable content for the corrupted areas. Extensive experiments on three bench- mark datasets demonstrate that our method out- performs most state-of-the-art methods for image inpainting in terms of the evaluation of both vi- sual quality and quantitative metrics.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":"71 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77327286","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}
Solimun Solimun, A. Fernandes, Intan Rahmawati, Riyanti Isaskar, L. Muflikhah, Fathiyatul Laili Nur Rasyidah
{"title":"Cluster Integration Path Analysis to Model PT Pelindo II's Market Mapping","authors":"Solimun Solimun, A. Fernandes, Intan Rahmawati, Riyanti Isaskar, L. Muflikhah, Fathiyatul Laili Nur Rasyidah","doi":"10.46300/9106.2021.15.198","DOIUrl":"https://doi.org/10.46300/9106.2021.15.198","url":null,"abstract":"This research aims to estimate the path analysis function of cluster integration to model the market mapping of PT Pelindo II. The population of this research is all companies or communities that cooperate with PT Pelindo II. The sample in this study is part of the community companies that cooperate with PT Pelindo II. This study also uses a survey method with a questionnaire. The sampling method used is purposive sampling. After getting data from the questionnaire, the next step is to perform cluster analysis. After performing cluster analysis, modeling is carried out using Path analysis. Path analysis in Cluster 1 and Cluster 1 shows that from nine direct effect tests, it was found that 2 effects gave significant results and the rest did not give significant effects. The significant effect is the influence of Customer Engagement (X3) on Company Potential (Y1). The coefficient of determination for the total path analysis in Cluster 1 is 0.8235 or 82.35%, while in Cluster 2 it is 0.7421 or 74.21%. Novelty in this research is Cluster integration modeling with Path. This study develops Cluster and Path analysis, where many previous studies only use Cluster analysis or Path analysis but are not integrated.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86871622","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}