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Energy Efficient Low Latency Routing Design for Target Tracking Applications of Wireless Sensor Network 面向无线传感器网络目标跟踪应用的高能效低延迟路由设计
Q4 Engineering Pub Date : 2022-06-01 DOI: 10.46300/9106.2022.16.124
Deepika Lokesh, N. V. U. Reddy
Target tracking is the greatest important applications in Wireless Sensor Networks (WSNs). The wireless sensor network applications have been increasing since the IoT has been established. Most of the applications have various kind of sensors to transmit the information from one source to another. The basic operation of a wireless sensor network is to sense the data, collect the data and transmit the data from time to time whenever the base station requires the data for evaluation. Improving the reliability, performance for the collection of the data is the main role of the wireless sensor device. Moreover, the objective of the wireless sensor network device is to minimize the latency and improve the energy efficiency in order to provide more reliability is a major performance metric for provisioning WSNs. In this paper, we have presented an Energy Efficient Low Latency Routing (EELLR) design for Target Tracking (TT) Applications of Wireless Sensor Network. This model provides reliability and has a better performance in terms of communication overhead, energy efficiency and packet processing latency reduction when compared with the existing routing-based models.
目标跟踪是无线传感器网络中最重要的应用。自物联网建立以来,无线传感器网络的应用不断增加。大多数应用都有各种各样的传感器来将信息从一个源传输到另一个源。无线传感器网络的基本操作是在基站需要数据进行评估时,对数据进行感知、采集和传输。提高数据采集的可靠性、性能是无线传感器设备的主要作用。此外,无线传感器网络设备的目标是最小化延迟和提高能源效率,以提供更高的可靠性,这是配置wsn的主要性能指标。在本文中,我们提出了一种用于无线传感器网络目标跟踪应用的节能低延迟路由(EELLR)设计。与现有的基于路由的模型相比,该模型在通信开销、能源效率和数据包处理延迟降低方面具有更高的可靠性和性能。
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引用次数: 0
Millimeter-Wave Antenna Circuitry for Inter-Satellite Communications at 60 GHz 60 GHz卫星间通信毫米波天线电路
Q4 Engineering Pub Date : 2022-06-01 DOI: 10.18178/ijsps.10.2.7-13
P. Shrivastava, B. Abe
 Abstract —With the growing complexity of communication systems, there is an increasing scope for antenna arrays with multi-beam capability for ultra-high broadband, inter-satellite links and inter-spacecraft communications. High data rate demands increased bandwidth requirements, the frequency of operation is increasing to the 60/70/80/90 GHz bands. These frequency bands are applicable to last-mile technologies for inter-satellite links and inter-spacecraft communications with data rates as high as 10 Gbit/s and even beyond. For these applications it is of paramount importance to develop planar technologies that can apply to millimeter-wave (MmW) frequencies with highly integrated system approach including smart antennas. This paper lays a robust foundation for MmW based smart antenna designs, its issues related to radio propagation and applications for inter-satellite links and inter-spacecraft communications. The intermediate and long-term objectives will create a unique and systematic understanding of the proposed innovative antenna array technology and its beamforming
摘要随着通信系统的日益复杂,具有多波束能力的天线阵列在超高宽带、卫星间链路和航天器间通信中的应用范围越来越大。高数据速率对带宽的要求越来越高,工作频率逐渐增加到60/70/80/90 GHz频段。这些频段适用于数据速率高达10gbit /s甚至更高的卫星间链路和航天器间通信的最后一英里技术。对于这些应用,开发能够应用于毫米波(MmW)频率的平面技术以及包括智能天线在内的高度集成系统方法至关重要。本文为基于毫米波的智能天线设计、卫星间链路和航天器间通信的无线电传播和应用问题奠定了坚实的基础。中期和长期目标将创建一个独特的和系统的理解所提出的创新天线阵列技术及其波束形成
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引用次数: 1
A Practical Method for Estimating Mutual Inductance in Wireless Power Transmission System 一种实用的无线电力传输系统互感估计方法
Q4 Engineering Pub Date : 2022-06-01 DOI: 10.46300/9106.2022.16.125
Takuto ,, Nakamura, T. Hirata, Eko Setiawan, I. Hodaka
This paper proposes a practical method for estimating mutual inductance in wireless power transmission system based on the principle of electromagnetic induction. Conventional estimation methods utilize a voltage, current, and phase of current in transmitter side, while our method requires only an amplitude of the voltage and current in transmitter side. Our method is designed so that the mutual inductance can be estimated under challenging situation which there is a measurement noise. Numerical simulations show that if the system has a small mutual inductance, a relative error and standard derivation of estimated mutual inductance tend to become larger. However, it will be shown that these factors can be improved to make a voltage of voltage source in the system high.
基于电磁感应原理,提出了一种实用的无线输电系统互感估计方法。传统的估计方法利用发射机侧电流的电压、电流和相位,而我们的方法只需要发射机侧电压和电流的幅值。我们的方法是为了在有测量噪声的困难情况下估计互感而设计的。数值模拟结果表明,当系统互感系数较小时,估计互感系数的相对误差和标准导数趋于增大。然而,将表明,这些因素可以改善,使电压源在系统中的电压高。
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引用次数: 0
Multiple Stuck At Fault Diagnosis System For Digital Circuit On FPGA Using Vedic Multiplier and ANN 基于Vedic乘法器和人工神经网络的FPGA数字电路多卡故障诊断系统
Q4 Engineering Pub Date : 2022-05-30 DOI: 10.46300/9106.2022.16.120
Mangesh Islampurkar, Kishanprasad G. Gunale, Sunil Somani, Nikhil Bagade
In an electronics circuit, the presence of a Fault leads to undesired or unexpected results. The output of many nodes on the circuit is changed due to the presence of the Fault at one node. So, it is necessary to detect the nature of the Fault present in a particular faulty node. To detect the fault present in the digital circuit, it is necessary to understand logical behavior using mathematical modeling. After the successful modeling, parameters are extracted, and the database is generated. The mathematical model uses Hebbian Artificial Neural Network algorithms [1] [2]. The database generated is used by the fault detection system to find the masked and multiple faults. A fault detection system monitors the faults present in the test circuit and finds the origin and nature of the Fault [3] [4]. The database generated for single stuck-at faults is used to find the multiple faults present in the faulty circuit. In this paper, Modified Vedic Multiplication [5] [4] method is used to optimize the utilization of the proposed system. In this proposed design multiplier of {N x N} bit input and {N} bit output is used, due to which device utilization is decreased, which is the expected outcome from the design. This system is designed using ISE Design Suite and implemented on Spartan-6 FPGA [6] [7].
在电子电路中,故障的存在会导致不希望的或意想不到的结果。电路中许多节点的输出由于一个节点的故障而改变。因此,有必要检测特定故障节点中存在的故障的性质。为了检测数字电路中存在的故障,有必要使用数学建模来理解逻辑行为。建模成功后,提取参数,生成数据库。数学模型采用Hebbian人工神经网络算法[1][2]。生成的数据库用于故障检测系统查找被屏蔽故障和多故障。故障检测系统对测试电路中存在的故障进行监测,找出故障的来源和性质[3][4]。单个卡死故障生成的数据库用于查找故障电路中存在的多个故障。本文采用修正吠陀乘法[5][4]方法对所提出的系统进行优化利用。在这个建议的设计中,使用了{N x N}位输入和{N}位输出的乘法器,由于这降低了设备利用率,这是设计的预期结果。本系统采用ISE Design Suite设计,在Spartan-6 FPGA上实现[6][7]。
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引用次数: 0
Connectivity Analysis of WSN Nodes using Neighborhood Search Technique (WSNNST) 基于邻域搜索技术的WSN节点连通性分析
Q4 Engineering Pub Date : 2022-05-30 DOI: 10.46300/9106.2022.16.121
M. Iskandarani
A new approach to wireless sensor network (WSN) communication through multi-hop routing is investigated in this work. The proposed approach utilizes search radius expansion in order to find highest energy nodes within a WSN network and preserves the energy of the lowest energy nodes. This approach which is built on trust in terms of providing good quality communication channels between a source node and a destination node considers energy as one parameter of trust that will enable strong, reliable communication channels and shorter routes to be used in a WSN. This approach enables efficient energy consumption during data communication, but with higher level energy consumption due to expanded search radius, which can be minimized using search time limit. The work also relates through mathematical equations, number of discovered routes, maximum hops, and search time to the considered search radius. The overall objective of this work is to enable faster and efficient channel communication between WSN nodes, through gradual cost effective search in neighborhoods. This is achieved by uncovering shorter and less number of routes within an acceptable time limits. The proposed and simulated approach presented in this work differ in terms of the gradual expansion of search and the equal increments in search radius compared to other used techniques. The presented work also adds a unique feature of allowing re-charging of low energy nodes using the already established routes connecting high energy nodes through the registration of weak nodes locations. A final general expression relates search radius to other WSN variables is also presented.
研究了一种基于多跳路由的无线传感器网络通信新方法。该方法利用搜索半径扩展在WSN网络中寻找能量最高的节点,并保留能量最低的节点的能量。这种方法建立在信任的基础上,在源节点和目标节点之间提供高质量的通信通道,将能量作为信任的一个参数,使WSN能够使用强大、可靠的通信通道和更短的路由。该方法在数据通信过程中实现了高效的能源消耗,但由于扩大了搜索半径,因此能耗更高,可以使用搜索时间限制将其最小化。该工作还通过数学方程、发现的路由数量、最大跳数和搜索时间与考虑的搜索半径相关联。本工作的总体目标是通过在邻域中逐步进行成本有效的搜索,实现WSN节点之间更快、更有效的信道通信。这是通过在可接受的时间限制内发现更短、数量更少的路线来实现的。本文提出的方法和模拟的方法在搜索的逐步扩展和搜索半径的等增量方面与其他使用的技术不同。本文的工作还增加了一个独特的功能,即通过注册弱节点位置,使用已经建立的连接高能量节点的路线,允许低能节点重新充电。最后给出了将搜索半径与其他WSN变量关联起来的通用表达式。
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引用次数: 0
Transmission of Depth Data by Pulse Position Modulation for Underwater Acoustic Positioning Systems 水声定位系统中脉冲位置调制的深度数据传输
Q4 Engineering Pub Date : 2022-05-30 DOI: 10.46300/9106.2022.16.122
Atsushi Wada, S. Yoshizawa
This paper presents a three dimensional localization method for underwater acoustic positioning systems. In typical ultra-short baseline (USBL) acoustic positioning systems, the three dimensional position is localized by using multiple time difference of arrivals (TDOAs). Since the TDOA accuracy is less than the other sensor data, we focus on a localization method with the minimum number of TDOA. We propose a method of transmitting depth data by pulse position modulation (PPM), where the target position is localized by a single TDOA, a distance, and a depth. The proposed method shows a higher positional accuracy than the conventional method with two TDOAs. The effectiveness of the proposed method has been demonstrated in the evaluation of simulation and experiment.
提出了一种用于水声定位系统的三维定位方法。在典型的超短基线(USBL)声定位系统中,利用多个到达时间差(TDOAs)进行三维定位。由于TDOA精度低于其他传感器数据,我们重点研究一种TDOA数最少的定位方法。我们提出了一种通过脉冲位置调制(PPM)传输深度数据的方法,其中目标位置由单个TDOA、距离和深度定位。与传统的双tdoa定位方法相比,该方法具有更高的定位精度。仿真和实验验证了该方法的有效性。
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引用次数: 1
A Robust Illumination and Intensity invariant Face Recognition System 一种鲁棒光照强度不变人脸识别系统
Q4 Engineering Pub Date : 2022-04-14 DOI: 10.46300/9106.2022.16.119
M. Meena, Shreya Pare, Priti Singh, A. Rana, M. Prasad
Face recognition has achieved more attention in computer vision with the focus on modelling the expression variations of human. However, in computer vision system, face recognition is a challenging task, due to variation in expressions, poses, and lighting conditions. This paper proposes a facial recognition technique based on 2D Hybrid Markov Model (2D HMM), Cat Swam Optimization (CSO), Local Directional Pattern (LDP), and Tetrolet Transform. Skin segmentation method is used for pre-processing followed by filtering to extract the region of interest. Resultant image is fed to proposed feature extraction method comprising of Tetrolet Transform and LDP. Extracted features are classified using proposed classifier “CSO trained 2D-HMM classification method”. To prove the superiority of method, four face datasets are used, and comparative results are presented. Quantitively results are measured by False Acceptance Rate (FAR), False Rejection Rate (FRR) and Accuracy and the values are 0.0025, 0.0035 and 99.65% respectively
人脸识别在计算机视觉领域受到越来越多的关注,其重点是对人的表情变化进行建模。然而,在计算机视觉系统中,由于表情、姿势和光照条件的变化,人脸识别是一项具有挑战性的任务。提出了一种基于二维混合马尔可夫模型(2D HMM)、猫游优化(CSO)、局部方向模式(LDP)和Tetrolet变换的人脸识别技术。采用皮肤分割法进行预处理,然后进行滤波提取感兴趣的区域。将生成的图像馈送到由Tetrolet变换和LDP组成的特征提取方法中。提取的特征使用提出的分类器“CSO训练2D-HMM分类方法”进行分类。为了证明该方法的优越性,使用了4个人脸数据集,并给出了对比结果。通过错误接受率(FAR)、错误拒绝率(FRR)和准确性(Accuracy)对结果进行定量测量,其值分别为0.0025、0.0035和99.65%
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引用次数: 0
A New Predictive Machine-learning Approach for Detecting Creditworthiness of Borrowers 一种用于检测借款人信誉的预测机器学习新方法
Q4 Engineering Pub Date : 2022-04-06 DOI: 10.46300/9106.2022.16.118
Zaynab Hjouji, M. M’hamdi
We present in this paper a new approach for predicting creditworthiness of borrowers that we call “Method of splitting the learning set into two region”. The aim of this approach consists on the construction of two regions from a learning set, the first called "Solvency Region" that contains the feature vectors of the elements that have paid their financial obligations on time and the second one called "Non-Solvency Region", which contains the feature vectors of the elements that have defaulted in paying their debts. Therefore, to predict creditworthiness borrowers, it is sufficient to identify which of the two regions includes his feature vectors; if it doesn’t correspond to any region, the credit decision-making requires further analysis. To develop and test our predictive proposed approach, a large set of real and recent credit data obtained from the UCI repository is used, we trained also on a real credit database from a Moroccan bank and the creditworthiness of borrowers are analyzed using two performance measurement indicators such as Classification accuracy and the AUC of the ROC curve as a robustness measurement criteria. The proposed model was compared to three traditional machine-learning algorithms: LR, RBF-NN and the MLP-NN. The experimental results show the improved performance of our proposed predictive method for predicting creditworthiness of borrowers.
本文提出了一种预测借款人信誉的新方法,我们称之为“将学习集分成两个区域的方法”。该方法的目的在于从一个学习集中构建两个区域,第一个称为“偿付能力区域”,其中包含按时支付其财务义务的元素的特征向量,第二个称为“非偿付能力区域”,其中包含违约支付其债务的元素的特征向量。因此,要预测借款人的信誉,只需确定两个区域中哪一个包含他的特征向量;如果不对应任何区域,则需要进一步分析信用决策。为了开发和测试我们提出的预测方法,我们使用了从UCI存储库获得的大量真实和最近的信用数据,我们还在摩洛哥银行的真实信用数据库上进行了训练,并使用两个绩效衡量指标(如分类准确性和ROC曲线的AUC)作为稳健性衡量标准来分析借款人的信誉。将该模型与三种传统的机器学习算法:LR、RBF-NN和MLP-NN进行了比较。实验结果表明,本文提出的预测方法在预测借款人信誉度方面具有较好的效果。
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引用次数: 0
Post-processing Improvement of Lock-in Thermography Study of MCM-L for Better Hidden Defect Localization MCM-L锁相热像成像后处理改进及对隐藏缺陷更好定位的研究
Q4 Engineering Pub Date : 2022-03-30 DOI: 10.46300/9106.2022.16.115
A. Stoynova, B. Bonev
This paper examines the impact of post-processing of lock-in thermographic measurement data on the ability to detect and characterize in terms of geometric dimensions and location of specific types of defects in MCM-L. A thermal 3D model of a test specimen with hidden artificial defects is used and simulated lock-in thermography measurement is performed. Qualitative and quantitative assessment was performed of the correct detection and geometric dimensions characterization of the defects. The Shape Difference (SD) criteria was defined and used for qualitative and quantitative assessment of the confidence detection and characterization of defects in MCM-L. A Window Sliding Offset (WSO) approach is performed as method for improvement of the defects characterization quality. This study revel that providing information on the depth and shape of defects through the combined use of infrared thermography measurement and 3D thermal modeling can be used to determine the desired confidence levels of defects detection.
本文研究了锁定热成像测量数据的后处理对MCM-L中特定类型缺陷的几何尺寸和位置的检测和表征能力的影响。采用了含有隐藏人工缺陷的试样热三维模型,并进行了模拟锁相热成像测量。对缺陷的正确检测和几何尺寸表征进行了定性和定量评估。定义了形状差异(SD)标准,并将其用于MCM-L中缺陷的置信度检测和表征的定性和定量评估。采用窗口滑动偏移(WSO)方法提高缺陷表征质量。该研究表明,通过结合使用红外热成像测量和3D热建模来提供有关缺陷深度和形状的信息,可以用于确定所需的缺陷检测置信度。
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引用次数: 2
Application of Speech Recognition Technology in Chinese English Simultaneous Interpretation of Law 语音识别技术在中英文法律同声传译中的应用
Q4 Engineering Pub Date : 2022-03-30 DOI: 10.46300/9106.2022.16.117
Xiao Yang
Speech recognition is an important research field in natural language processing. In Chinese and English, which have rich data resources, the performance of end-to-end speech recognition model is close to that of Hidden Markov Model—Deep Neural Network (HMM-DNN) model. However, for the low resource speech recognition task of Chinese English hybrid, the end-to-end speech recognition system does not achieve good performance. In the case of limited mixed data between Chinese and English, the modeling method of end-to-end speech recognition is studied. This paper focuses on two end-to-end speech recognition models: connection timing distribution and attention based codec network. In order to improve the performance of Chinese English hybrid speech recognition, this paper studies how to improve the performance of the coder based on connection timing distribution model and attention mechanism, and tries to combine the two models to improve the performance of Chinese English hybrid speech recognition. In low resource Chinese English mixed data, the advantages of different models are used to improve the performance of end-to-end models, so as to improve the recognition accuracy of speech recognition technology in legal Chinese English simultaneous interpretation.
语音识别是自然语言处理中的一个重要研究领域。在数据资源丰富的中文和英文中,端到端语音识别模型的性能接近隐马尔可夫模型-深度神经网络(HMM-DNN)模型。然而,对于中英混合的低资源语音识别任务,端到端语音识别系统并没有取得很好的性能。在有限的中英文混合数据情况下,研究了端到端语音识别的建模方法。本文重点研究了两种端到端语音识别模型:连接时序分布模型和基于注意力的编解码网络模型。为了提高中英混合语音识别的性能,本文研究了如何基于连接时间分布模型和注意机制来提高编码器的性能,并尝试将这两种模型结合起来提高中英混合语音识别的性能。在低资源的中英文混合数据中,利用不同模型的优势,提高端到端模型的性能,从而提高法律中英文同声传译语音识别技术的识别精度。
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引用次数: 1
期刊
International Journal of Circuits, Systems and Signal Processing
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