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RIT Logo based Slotted PLPCMA Multi-Band Patch Antenna 基于RIT标识的开槽PLPCMA多波段贴片天线
Q4 Engineering Pub Date : 2022-03-08 DOI: 10.46300/9106.2022.16.95
V. Prasad, E. D. Gowda, K. Indira, Ananya Kodikula, Bhavan B. Rao
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.
提出了一种具有缺陷地平面(DGP)的紧凑印刷对数周期曲线单极子阵列(PLPCMA)天线,并对其进行了测试。所提出的曲线单极子阵列被设计在介电常数为4.4的FR-4衬底上。设计的天线在S频段(2GHz至4GHz)、X频段(8GHz至12GHz)和C频段(4GHz至8GHz)范围内进行多频段谐振。设计结果表明,在2.49GHz、3.28GHz、6.84GHz和8.36GHz谐振频率下,电压驻波比(VSWR)均小于1.5,分数带宽分别为4.02、3.66、50.58和41.39 %。该天线呈现单向火末辐射方向图,峰值实现增益为7。1145 dbi。测量结果表明,PLPCMA天线在1.58GHz至15GHz(9.49:1)范围内具有良好的-10dB阻抗带宽,带宽为158%,适用于Wi-Fi/WIMAX超宽带应用。
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引用次数: 0
Design of High-speed Delay-FXLMS Hardware Architecture Based on FPGA 基于FPGA的高速延迟fxlms硬件架构设计
Q4 Engineering Pub Date : 2022-02-28 DOI: 10.46300/9106.2022.16.94
Jun Yuan, X. Meng, Jianhua Ran, Wei Wang, Qiang Zhao, Jun Li, Qin Li
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.
为了提高DFxLMS自适应滤波器的收敛性和时钟速度,提出了一种硬件共享转置形式的细粒度重定时DFxLMS (HS-TF-RDFXLMS)滤波器的硬件架构。首先,该架构采用延迟分解算法,解决了由于延迟和输出滞后增大导致滤波器收敛性降低的问题。其次,在保持算法性能不变的前提下,将自适应滤波模块和副路径模块进行调换,进一步减少关键路径,提高系统时钟速度。通过优化电路子模块,减少了寄存器的数量。最后,在关键路径不变的基础上,通过硬件共享实现TF-RDFXLMS滤波器的面积/速度权衡。实验结果表明,该算法的收敛速度是DFxLMS算法的3.5倍,关键路径缩短了([log2N]+1)TADD。本文设计的自适应滤波器的电路结构是在Xilinx Artix7 FPGA平台上实现的。HS-TF-RDFXLMS滤波器的时钟速度比TF-RDFXLMS滤波器降低了4.386%。而LUT和FF的资源分别节省了10.964%和28.322%。功耗为150.73 mW。这样可以提高系统的性能。
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引用次数: 0
IoT-based Network Attacks Discovery with Combined Classifiers 基于物联网的网络攻击发现与组合分类器
Q4 Engineering Pub Date : 2022-02-28 DOI: 10.46300/9106.2022.16.93
Vanya Ivanova, T. Tashev, I. Draganov
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.
本文遵循基于物联网的网络攻击发现的最新趋势,并进一步推进我们之前的研究,其中我们优化和测试了单个神经网络,支持向量机和随机森林分类器对多个DDoS攻击的检测和识别,我们提出了新开发的组合分类器的结果。前者仅使用神经网络和随机森林分类器,而后者则额外使用支持向量机。两者都通过两种修改实现——作为恶意流量与正常流量的检测器,以及作为10种攻击与非攻击样本的分类器。在流行的Bot-IoT数据集上获得了很高的分类精度,并且比单一分类器的分类精度更高。同时,它也高于其他解决方案,在实践中提出。
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引用次数: 0
A Review of Graph Signal Processing with Neural Networks 神经网络处理图信号的研究进展
Q4 Engineering Pub Date : 2022-02-25 DOI: 10.46300/9106.2022.16.91
Yuzhong Yan, C. Akujuobi
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.
本文综述了传统图信号处理方法的发展,以及将图神经网络应用于图数据的最新研究领域。针对神经网络处理图形数据的热门话题,详细讨论了主要的模型/框架、数据集和应用。提出了一些挑战和有待解决的问题,为今后的研究方向提供了指导。
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引用次数: 0
Research on Data Mining Algorithm Based on BP Neural Network 基于BP神经网络的数据挖掘算法研究
Q4 Engineering Pub Date : 2022-02-25 DOI: 10.46300/10.46300/9106.2022.16.90
Jingyou Zhang, Haiping Zhong
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.
目前的数据挖掘算法存在数据挖掘功能不完善的问题,导致算法耗时过长。设计了一种基于BP神经网络的数据挖掘算法。分析数据挖掘算法的基本结构,获得多目标决策的数据特征,利用分布式计算技术调整收敛速度,保持惯性因子状态不变,构造局部最小离散模型,测量模型的兴趣,利用BP (Back Propagation)神经网络模型计算网络的最优输出值,完成数据挖掘功能的改进设计。实验结果:所设计的数据挖掘算法的平均计算时间为559.827秒,比其他传统算法分别节省145.975秒和174.237秒。实践证明,基于BP神经网络的数据挖掘算法减少了计算时间,提高了数据挖掘的性能,具有较高的应用价值。
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引用次数: 0
Statistical Analysis of Voltage Unbalance Emission Due to Asymmetrical Loads in Three-Phase Power Systems 三相电力系统不对称负荷引起的电压不平衡发射的统计分析
Q4 Engineering Pub Date : 2022-02-25 DOI: 10.46300/9106.2022.16.92
D. Bellan
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.
本文研究了三相不对称负载不确定参数引起的三相系统电压不平衡系数的统计特性。将三相负荷参数作为高斯分布的随机变量处理。三相负载的随机不对称导致电压不平衡系数的随机值。以封闭形式导出了电压不平衡系数的概率密度函数、累积分布函数、平均值和方差,并进行了数值验证。所得结果有助于定量描述三相负载中不对称可能产生的影响,例如大型单相负载的连接。
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引用次数: 1
DWT based Person Re-Identification using GAN 基于小波变换的GAN人再识别
Q4 Engineering Pub Date : 2022-02-18 DOI: 10.46300/9106.2022.16.89
Arun , Kumar D. R, K. A. N., A. A. C.
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.
由于不同的人在姿势、光照、表情以及相似外表上的差异,对人的再识别具有挑战性。本文提出了一种基于离散小波变换(DWT)的基于生成对抗网络(GAN)的人物再识别方法。采用具有多视点和光照的CMU multi-PIE人脸数据库对模型进行测试。利用双向生成对抗网络(TP-GAN)将待测侧面人脸图像转换为正面人脸图像。将正面人脸图像加载到服务器中,创建服务器数据库。对合成的TP-GAN图像和服务器数据库图像进行预处理,将RGB图像转换为灰度图像,并将其转换为均匀的人脸图像尺寸。人的再识别是基于DWT提取特征,产生一个低频LL波段和三个高频LH、HL、HH波段。l波段系数被认为是最终特征,它是无噪声和压缩的特征数。利用归一化欧几里得距离(NED)和阈值对侧面视图图像和服务器数据库图像的特征进行了比较。
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引用次数: 0
Vehicular Communication using Balanced Centralized and Decentralized Cluster Heads 使用平衡的集中式和分散式簇头的车载通信
Q4 Engineering Pub Date : 2022-01-31 DOI: 10.46300/9106.2022.16.88
M. Iskandarani
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).
提出了一种新的车载通信方法,在集中通信和分散通信中采用距离和车速等权重。本文的主要目的是建立优化的平衡车载通信的利用表达式和特性。该技术是基于分析通信过程(集中、分散)对传输效率和故障概率的影响。利用利用函数、簇头选择时间和端到端传输时间进行分析。仿真和分析表明,去中心化方法比集中化方法更有效,因此两者结合是有效的。研究还发现,需要优化车辆相对于传输半径的速度,并利用分区来有效提高传输效率。建立了涵盖传输失败概率、簇头选择时间和端到端延迟之间的关键关系的数学模型。同时,给出了考虑簇头选择时间和端到端延迟及其对连接利用率影响的重要数学表达式。该研究证明了使用平衡权重方法的集中和分散相结合的技术是有效的,使用动态权重选择算法来确定所使用变量(距离,车辆速度)的最佳权重。
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引用次数: 0
Structural Knowledge-Guided Feature Inference Network for Image Inpainting 基于结构知识的图像补绘特征推理网络
Q4 Engineering Pub Date : 2022-01-27 DOI: 10.46300/9106.2022.16.87
Yongqiang Du
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.
图像修复是图像修复领域的一项重要工作。目前,大多数图像修复方法采用编码器-解码器框架来恢复退化区域,由于缺乏有效先验信息的指导,往往导致合成错误的语义结构。在本文中,我们提出了一个结构化的知识引导框架,该框架可以同时预测边缘图和损坏的内容。我们的模型捕获结构估计分支中的结构知识,以指导潜在特征空间中的内容推理。该模型利用自关注机制对已知信息和推断出的结构知识进行聚合,能够为错误区域合成语义上更合理的内容。在三个基准数据集上进行的大量实验表明,我们的方法在视觉质量和定量指标的评估方面优于大多数最先进的图像绘制方法。
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引用次数: 0
Cluster Integration Path Analysis to Model PT Pelindo II's Market Mapping PT Pelindo II市场映射模型的聚类集成路径分析
Q4 Engineering Pub Date : 2022-01-18 DOI: 10.46300/9106.2021.15.198
Solimun Solimun, A. Fernandes, Intan Rahmawati, Riyanti Isaskar, L. Muflikhah, Fathiyatul Laili Nur Rasyidah
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.
本研究旨在估计聚类整合的路径分析函数,以建立PT Pelindo II的市场映射模型。本研究的对象是所有与PT Pelindo II合作的公司或社区。本研究的样本是与PT Pelindo II合作的社区公司的一部分。本研究亦采用问卷调查法。抽样方法为目的抽样。从问卷中获得数据后,下一步是进行聚类分析。在进行聚类分析之后,利用Path分析法进行建模。聚类1和聚类1的通径分析表明,从9个直接效应检验中,发现2个效应产生显著结果,其余效应不产生显著效果。显著效应是顾客敬业度(X3)对公司潜力(Y1)的影响。聚类1的全通径分析决定系数为0.8235或82.35%,聚类2的全通径分析决定系数为0.7421或74.21%。本研究的新颖之处在于基于Path的聚类集成建模。本研究发展了以往许多研究仅使用聚类分析或路径分析而未进行整合的聚类和路径分析。
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引用次数: 0
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International Journal of Circuits, Systems and Signal Processing
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