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Sleep Stage Classification using Laplacian Score Feature Selection Method by Single Channel EEG 基于拉普拉斯评分特征选择的单通道脑电睡眠阶段分类
Q4 Engineering Pub Date : 2020-12-01 DOI: 10.29252/MJEE.14.4.11
Mahtab Vaezi, M. Nasri
Sleep is a normal state in humans and the subconscious level of brain activity increases during sleep. The brain plays a prominent role during sleep, so a variety of mental and brain-related diseases can be identified through sleep analysis. A complete sleep period according to the two world standards R&K and AASM consists of seven and five steps, respectively. To diagnose diseases through sleep, it is necessary to identify different stages of sleep because the disorder at each stage indicates a certain disease. On the other hand, efficient and useful features should be selected to increase the accuracy of sleep stage classification. In this paper, at first, different statistical, entropy, and chaotic features are extracted from sleep data. Afterwards, by introducing and using the Laplacian score selector, the best feature set is selected. At the end, some conventional classification algorithms such as SVM, ANN and KNN are used to classify different sleep stages. Simulation results confirms the superiority of the proposed method based on the classification results. With the proposed algorithm, 2, 3, 4, 5 and 6 stages of sleep were classified by SVM and decision tree with 98.0%, 98.0%, 97.3%, 96.6%, and 95.0% accuracy, which are more superior to previous method’s results.
睡眠是人类的正常状态,大脑的潜意识活动水平在睡眠中增加。大脑在睡眠中起着突出的作用,因此通过睡眠分析可以识别各种精神和大脑相关疾病。根据R&K和AASM两个世界标准,一个完整的睡眠时间分别由七个和五个步骤组成。为了通过睡眠诊断疾病,有必要区分睡眠的不同阶段,因为每个阶段的障碍都代表着某种疾病。另一方面,应选择高效、有用的特征,以提高睡眠阶段分类的准确性。本文首先从睡眠数据中提取不同的统计、熵和混沌特征。然后,通过引入和使用拉普拉斯分数选择器,选择出最优特征集。最后,利用SVM、ANN和KNN等传统分类算法对不同睡眠阶段进行分类。基于分类结果的仿真结果证实了所提方法的优越性。采用该算法对2、3、4、5、6个阶段的睡眠进行SVM和决策树分类,准确率分别为98.0%、98.0%、97.3%、96.6%、95.0%,优于以往方法。
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引用次数: 1
Fast Islanding Detection for Distribution System including PV using Multi-Model Decision Tree Algorithm 基于多模型决策树算法的含光伏配电系统孤岛快速检测
Q4 Engineering Pub Date : 2020-12-01 DOI: 10.29252/MJEE.14.4.29
R. Ebrahimi, G. Shahgholian, B. Fani
Modern distribution system including Distributed Generation (DG) requires reliable and fast islanding detection algorithms in order to determine the grid status. In this paper, a new multi-model classification-based method is proposed, in order to detect islanding condition for photovoltaic units. Decision tree is chosen as the classification algorithm to classify input feature vectors. The final result is based on voting among three decision tree algorithms. First order derivatives of electrical parameters are employed to construct feature vectors. To cover intermittent nature of renewable sources, different generating states for PV unit are assumed. Probable events are simulated under different system operating states to generate classification data set. The pro­po­sed method is tested on typical distribution system including the PV unit, different loads, and synchronous generator. This study sh­o­wed that this method succeeds in highly fast islanding det­ec­tion. This quick response can be used in micro-grid application as well as anti-islanding strategy. The results revealed that the proposed vot­ing-base algorithm could classify instances with very high acc­ur­a­cy which leads to reliable operation of distributed gene­rat­i­on units.
包括分布式发电(DG)在内的现代配电系统需要可靠、快速的孤岛检测算法来确定电网状态。本文提出了一种新的基于多模型分类的光伏发电机组孤岛状态检测方法。选择决策树作为分类算法对输入特征向量进行分类。最终结果基于三种决策树算法的投票。利用电参数的一阶导数构造特征向量。考虑到可再生能源的间歇性,假设光伏发电机组处于不同的发电状态。模拟不同系统运行状态下的可能事件,生成分类数据集。在光伏机组、不同负荷、同步发电机等典型配电系统上进行了试验。实验结果表明,该方法可实现快速孤岛检测。这种快速响应可用于微电网应用以及反孤岛策略。结果表明,所提出的基于投票的算法能够以非常高的准确率对实例进行分类,从而保证分布式基因单元的可靠运行。
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引用次数: 0
A Low-power, CMOS Optical Communication Receiver System for 5Gbps Applications based on RGC Structure 基于RGC结构的5Gbps低功耗CMOS光通信接收系统
Q4 Engineering Pub Date : 2020-12-01 DOI: 10.29252/MJEE.14.4.57
Sima Honarmand, Soorena Zohoori, K. Abbasi
An optical communication receiver system is presented in this research using 65nm CMOS, which consists of three low-power active differential stages as Limiting Amplifier (LA) following an ultra-low-power RGC-Based Transimpedance Amplifier (RB-TIA). The presented active circuit of the RB-TIA is followed by a gain stage that extends the -3dB frequency of the circuit by creating a resonance for the load capacitance. Thus, needless of consuming extra power, a wide-bandwidth circuit has been designed. In addition, employing active-inductor loads within the LA stages enables obtaining a 5Gbps receiver system. The RB-TIA consumes 573µW and provides 3.52GHz frequency, while the complete optical receiver consumes only 4.76mW power to provide -3dB frequency of 3.5GHz and high gain of 80dB (10’000). The circuits have been mathematically presented and discussed, and simulations have justified the presented circuit design.
本文提出了一种基于65nm CMOS的光通信接收系统,该系统由三个低功耗有源差分级作为限幅放大器(LA),然后是一个超低功耗rgc - Transimpedance放大器(RB-TIA)。所提出的RB-TIA有源电路随后是一个增益级,该增益级通过产生负载电容的谐振来扩展电路的-3dB频率。因此,在不消耗额外功率的情况下,设计了一种宽频带电路。此外,在LA级内采用有源电感器负载可以获得5Gbps的接收器系统。RB-TIA功耗573µW,提供3.52GHz的频率,而完整的光接收机功耗仅为4.76mW,可提供3.5GHz的-3dB频率和80dB(10,000)的高增益。对电路进行了数学描述和讨论,仿真验证了所提出的电路设计。
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引用次数: 0
Prediction Analysis for Business To Business (B2B) Sales of Telecommunication Services using Machine Learning Techniques 使用机器学习技术对企业对企业(B2B)电信服务销售进行预测分析
Q4 Engineering Pub Date : 2020-12-01 DOI: 10.29252/MJEE.14.4.145
Oryza Wisesa, A. Andriansyah, Osamah Ibrahim Khalaf
Sales prediction analysis requires intelligent data mining techniques with accurate prediction models and high reliability. In most cases, business highly relies on information as well as demand forecast of the sales trends. This research uses B2B sales data for analysis. The B2B data could provide information on how telecommunication company should manage its sales team, products, and budgeting flows. The accurate estimates enable Telecommunication company to survive the market war and increase with market growth. Comprehensible predictive models were studied and analyzed using a technique of machine learning to improve the prediction of the future sale. It is hard to cope with big data and sale prediction accuracy if the system of traditional forecast is used. In this study, machine learning technique was also used to analyze the reliability of B2B sales. In addition, at the end of this research, other measures and techniques used to predict sales were introduced. The predictive model with best performance evaluation is recommended to forecast the trending B2B sales. The study results are put into an order of reliability and accuracy of the best method to predict and forecast including estimation, evaluation, and transformation. The best performance model found was Gradient Boost Algorithm. The result form graph the data close together from beginning till end of data target MSE and MAPE result are the best result than other method, MSE =24.743.000.000,00 and MAPE =0,18. This model performed maximum accuracy in predicting and forecasting of the future B2B sales.
销售预测分析需要具有准确预测模型和高可靠性的智能数据挖掘技术。在大多数情况下,业务高度依赖于信息以及销售趋势的需求预测。本研究使用B2B销售数据进行分析。B2B数据可以提供有关电信公司应该如何管理其销售团队、产品和预算流程的信息。准确的估值使电信企业能够在市场竞争中生存下来,并随着市场的增长而增长。使用机器学习技术研究和分析了可理解的预测模型,以改进对未来销售的预测。传统的销售预测系统难以应对大数据和销售预测的准确性。在本研究中,机器学习技术也被用于分析B2B销售的可靠性。此外,在本研究的最后,介绍了用于预测销售的其他措施和技术。推荐绩效评价最佳的预测模型用于预测B2B销售趋势。将研究结果按可靠性和准确性排序为最佳预测和预测方法,包括估计、评价和转化。发现性能最好的模型是梯度增强算法。结果形成数据从头到尾紧密相连的图形,目标MSE和MAPE结果是其他方法中效果最好的,MSE =24.743.000.000,00, MAPE =0,18。该模型在预测和预测未来B2B销售方面表现出最大的准确性。
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引用次数: 38
Electroencephalography Artifact Removal using Optimized Radial Basis Function Neural Networks 基于优化径向基函数神经网络的脑电图伪影去除
Q4 Engineering Pub Date : 2020-12-01 DOI: 10.29252/MJEE.14.4.133
S. S. S. Farahani, M. M. Arefi, A. H. Zaeri
Electroencephalography (EEG) is a major clinical tool to diagnose, monitor and manage neurological disorders which is mostly affected by artifacts. Given the importance and the need for an automated method to remove artifacts, in this paper some intelligent automated methods are proposed which are composed of three main parts as extraction of effective input, filtering and filter optimization. Wavelet transform is utilized to extract the effective input, and the wavelet approximation coefficients are used as an effective input signal. In addition, Radial Basis Function Neural Network (RBFNN) has been used for filtering. The appropriate number of RBFs has been selected using extensive simulations, and the optimal value​​ of spread parameter has been achieved by Bees algorithm (BA). Finally, the proposed artifact removal schemes have been evaluated on some real contaminated EEG signals in Mashad Ghaem hospital database. The results show that the proposed artifact removal schemes are able to effectively remove artifacts from EEG signals with little underlying brain signal distortion.
脑电图(EEG)是诊断、监测和管理主要受伪影影响的神经系统疾病的主要临床工具。考虑到自动化方法的重要性和必要性,本文提出了一些智能自动化方法,这些方法由有效输入的提取、滤波和滤波器优化三个主要部分组成。利用小波变换提取有效输入,并利用小波近似系数作为有效输入信号。此外,采用径向基函数神经网络(RBFNN)进行滤波。通过大量的仿真,选择了合适的rbf数量,并通过蜜蜂算法(Bees algorithm, BA)获得了传播参数的最优值。最后,对Mashad Ghaem医院数据库中实际污染的脑电图信号进行了评价。结果表明,所提出的伪影去除方案能够有效地去除脑电信号中的伪影,且底层脑信号失真很小。
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引用次数: 0
Sliding Mode Contact Force Control of n-Dof Robotics by Force Estimation 基于力估计的n自由度机器人滑模接触力控制
Q4 Engineering Pub Date : 2020-12-01 DOI: 10.29252/MJEE.14.4.1
M. Namnabat, A. H. Zaeri, M. Vahedi
Control of the force exerted on an object is important for boosting system performance in robotics manipulators. Any undesired applied force may leave remarkable effects on the system, with the potential to damage the object. In addition, measuring external force is another challenge associated with such cases. Proposing an appropriate force estimation algorithm is a solution to overcome this deficiency. In this research, a control strategy is proposed to control the external force applied on the n-dof robotics. To eliminate force measurement in the controller, a force estimation strategy based on a disturbance observer is employed. Subsequently, a sliding-mode based control is implemented to cope with the force estimation error. The closed-loop stability of the system in the presence of estimated force is analytically considered. The proposed algorithm was implemented on piezoelectric actuators as the experimental setup. The experimental results confirm that by employing the proposed control scheme, precise force control is achievable. The force estimation algorithm can also suitably estimate external force.
在机器人机械臂中,作用在物体上的力的控制是提高系统性能的重要因素。任何不希望施加的力都可能对系统造成显著影响,并有可能损坏物体。此外,测量外力是与这种情况有关的另一个挑战。提出一种合适的力估计算法是克服这一缺陷的方法。在本研究中,提出了一种控制策略来控制施加在n-dof机器人上的外力。为了消除控制器中的力测量,采用了基于扰动观测器的力估计策略。然后,采用基于滑模的控制方法来处理力估计误差。分析了系统在估计力存在下的闭环稳定性。将该算法作为实验装置在压电驱动器上实现。实验结果表明,采用该控制方案可以实现精确的力控制。力估计算法也能较好地估计外力。
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引用次数: 0
Sophisticated Microgrid Communication System Management 复杂微电网通信系统管理
Q4 Engineering Pub Date : 2020-12-01 DOI: 10.29252/MJEE.14.4.123
Maytham Khudhair Abbas, Emad Jadeen Abdualsada Alshebaney, Mohammed Madhi Faraj Janabi
Conversation and assurance issues play a crucial function when talking regarding to the wise grid. This particular paper presents opportunities of testing power framework assurance transfers and correspondence standards for smart supply. A depiction in the Smart Grid lab hardware and the key protection devices is usually presented in the paper. Further employ cases and uses offered by the Labrador equipment are referred to and the possibilities by dynamically setting up devices and program interaction are demonstrated. Ideas for the mix of checked and controllable decentralized vitality sources are demonstrated the network capacity and Quality of Services (QoS) are tested and evaluated.  By implementing adaptive modulation scheme, the served users were increased by 10% at heavy Traffic Load (TL).
在讨论智能电网时,对话和保证问题起着至关重要的作用。本文介绍了测试智能供电的电力框架、保证传输和通信标准的机会。本文通常对智能电网实验室的硬件和关键保护装置进行描述。进一步的使用案例和使用拉布拉多设备提供了参考,并通过动态设置设备和程序交互的可能性进行了演示。提出了可检查和可控分散活力源混合的思想,并对网络容量和服务质量(QoS)进行了测试和评估。通过实施自适应调制方案,在大流量负载下服务用户增加了10%。
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引用次数: 0
Design, Optimization and Prototype of a Multi-Phase Fractional Slot Concentrated Windings Surface Mounted on Permanent Magnet Machine 永磁电机表面安装多相分数槽集中绕组的设计、优化及样机
Q4 Engineering Pub Date : 2020-12-01 DOI: 10.29252/MJEE.14.4.75
Amir Nekoubin, J. Soltani, M. Dowlatshahi
The multi-phase permanent-magnet motors are suitable choices for certain purposes like aircrafts, marine, and electric vehicles due to the fault tolerance and high-power density capabilities. The paper aims to design and prototype an optimized five-phase fractional slot concentrated windings surface mounted permanent magnet motor. To optimize the designed multi-phase motor, a multi-objective optimization technique based on the genetic algorithm method has been applied. The machine design objectives are to minimize mass and loss, subsequently, to determine the best choice of the designed machine parameters. Afterwards, 2-Dimensional Finite Element Method (2D-FEM) has been used to verify the performance of the optimized machine. Finally, the optimized machine has been prototyped. The results of the prototyped machine have validated the results of the theatrical analyses of the machine, and accurate consideration of the parameters improved the performance of the machine.
多相永磁电机具有容错性和高功率密度能力,适用于飞机、船舶和电动汽车等特定用途。本文旨在设计和原型一个优化的五相分数槽集中绕组表面安装永磁电机。为了优化设计的多相电机,采用了基于遗传算法的多目标优化技术。机器设计的目标是最大限度地减少质量和损失,然后确定设计机器参数的最佳选择。然后,采用二维有限元法对优化后的机床性能进行了验证。最后,对优化后的机器进行了原型设计。原型机器的结果验证了机器的剧场分析结果,准确考虑参数提高了机器的性能。
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引用次数: 0
Haptic Interface Controller Design using Intelligent Techniques 基于智能技术的触觉界面控制器设计
Q4 Engineering Pub Date : 2020-12-01 DOI: 10.29252/MJEE.14.4.67
N. Kumar, J. Ohri
Haptic technology has enormous applications in several fields from medical, military, and in our day-to-day life’s products including video games, smartphones, and smart cities. The Haptic Interface Controller (HIC), a key circuitry for interaction between the user and the virtual world, has two main control issues: stability and transparency. These two issues are complementary to each other i.e. emphasis on one will degrade the other and vice-versa. To address this, intelligent control techniques including Genetic Algorithm (GA), Feed-Forward Neural Network (FFNN), and Fuzzy Logic Control (FLC) have been used in design of the HIC. To ensure the performance in real-time, in system parametric uncertainty and delay have been added while designing the HIC so that a balance could be maintained between the two issues.
触觉技术在医疗、军事以及我们日常生活中的产品(包括视频游戏、智能手机和智能城市)等多个领域都有广泛的应用。触觉接口控制器(HIC)是用户与虚拟世界交互的关键电路,它有两个主要的控制问题:稳定性和透明性。这两个问题是相辅相成的,即强调一个会贬低另一个,反之亦然。为了解决这个问题,智能控制技术包括遗传算法(GA)、前馈神经网络(FFNN)和模糊逻辑控制(FLC)被用于HIC的设计。为了保证系统的实时性,在设计HIC时加入了系统参数的不确定性和延迟,使两者保持平衡。
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引用次数: 0
Development of a Neutron Radiography System based on a 10 MeV Electron Linac 基于10MeV电子直线加速器的中子照相系统的研制
Q4 Engineering Pub Date : 2020-12-01 DOI: 10.29252/MJEE.14.4.21
J. Fantidis, G. Nicolaou
A thermal neutron radiography unit using the neutrons which emits a 10 MeV electron linac compact has been designed and simulated via MCNPX Monte Carlo code. The facility was carried out for an extensive range of values for the collimator ratio L/D, the main parameter which describes the quality of the produced radiographic images. The results show that the presented facility provides high thermal neutron flux; while with the use of single sapphire filter fulfills all the suggested values which characterize a high quality thermal neutron radiography system. A comparison with other similar facilities indicates that the use of a photoneutron source using a 10 MeV electrons beam is a useful substitutional for radiographic purposes.
用MCNPX蒙特卡罗程序设计并模拟了一种利用中子发射10MeV电子直线加速器的热中子照相装置。该设施针对准直器比率L/D的广泛值范围进行,该比率是描述所产生的射线照相图像质量的主要参数。结果表明,该装置具有较高的热中子通量;而使用单个蓝宝石滤光片满足了表征高质量热中子射线照相系统的所有建议值。与其他类似设施的比较表明,使用10MeV电子束的光中子源是射线照相目的的有用替代品。
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引用次数: 2
期刊
Majlesi Journal of Electrical Engineering
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