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2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)最新文献

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Decoupled MultiLoop Control of Switched Inductor Z-Source Inverters for Distributed Generations 分布式世代开关电感z源逆变器的解耦多环控制
Pub Date : 2020-09-05 DOI: 10.1109/ICCE50343.2020.9290730
S. singh, S. Bose, P. Dwivedi
Switched inductor topology is an advanced byproduct of Z-Source inverter which is equipped with enlarged voltage boost factor capability, employing less duty ratio and high modulation index. A well established closed loop power control requires high quality waveform followed by a good current controller which should be precise and should have significant effect on the dynamics of the system. Transient modelling is performed to widen the investigative study of non-minimum phase behaviour caused by right hand plane zeroes exhibited due to the impedance network on the DC side of these inverters. Also the independency of DC side and AC side control has been kept in discussion with separate controller designs. This paper presents an idea of decoupled AC side control in synchronous reference frame to eliminate the cross coupled behaviour of d-q axes during independent control of active and reactive powers. Simulation result shows good reference tracking and disturbance rejection property, which is recognised to be evident and substantial using MATLAB as testing platform.
开关电感拓扑结构是z源逆变器的先进副产品,具有放大电压升压因数的能力,占用更小的占空比和更高的调制指数。一个良好的闭环功率控制需要高质量的波形,然后是一个好的电流控制器,它应该是精确的,应该对系统的动力学有显著的影响。暂态建模是为了扩大对这些逆变器直流侧阻抗网络导致的右平面零引起的非最小相位行为的调查研究。此外,直流侧和交流侧控制的独立性也在单独的控制器设计中进行了讨论。本文提出了同步参考系中交流侧解耦控制的思想,以消除有功和无功独立控制时d-q轴的交叉耦合行为。仿真结果表明,该系统具有良好的参考跟踪和抗干扰性能,并在MATLAB测试平台上得到了验证。
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引用次数: 0
A Novel Design of Reversible Gate using Quantum-Dot Cellular Automata (QCA) 基于量子点元胞自动机(QCA)的可逆门设计
Pub Date : 2020-09-05 DOI: 10.1109/ICCE50343.2020.9290583
Abhimanyu Roy, Akash Singh, A. Saha, Suvranil Saha, V. Gupta, Zhu Qingyi, S. Bhattacharya, Subhankar Bhattacharjee
Quantum computing is one of the emerging technologies which is an alternative for Complementary Metal Oxide Semiconductor (CMOS) based design approaches such as VLSI and ULSI. The advantage of this new domain includes substantially faster processing speed and requirement of very less area for circuit integration as compared to CMOS technology. Quantum-dot Cellular Automata (QCA) is the backbone of quantum computing for integrated circuit designing with the execution of conventional logical operations. Implementation of the reversible gate using QCA is one of the fundamental requirements to design complex logic circuits because such a reversible gate is advantageous not only in terms of power consumption and energy dissipation but also in terms of functional area requirements for the physical integration of digital circuits. There are multiple applications of reversible logic circuits in various fields such as low power CMOS, Nanotechnology, DNA computing, quantum computing, etc. This paper provides modified and efficient designs of several reversible logic gates using QCA in optimum requirements.
量子计算是一种新兴技术,是基于互补金属氧化物半导体(CMOS)的设计方法(如VLSI和ULSI)的替代方案。与CMOS技术相比,这个新领域的优势包括更快的处理速度和对电路集成面积的要求非常小。量子点元胞自动机(quantum -dot Cellular Automata, QCA)是集成电路设计中量子计算的骨干,可执行常规逻辑运算。使用QCA实现可逆门是设计复杂逻辑电路的基本要求之一,因为这种可逆门不仅在功耗和能量消耗方面有利,而且在数字电路物理集成的功能面积要求方面也有利。可逆逻辑电路在低功耗CMOS、纳米技术、DNA计算、量子计算等领域有着广泛的应用。本文提出了几种基于QCA的可逆逻辑门的改进和高效设计。
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引用次数: 0
Modified Genetic Based Algorithm for Load Balancing in Cloud Computing 基于改进遗传算法的云计算负载均衡
Pub Date : 2020-09-05 DOI: 10.1109/ICCE50343.2020.9290563
Soumen Swarnakar, Neeraj Kumar, Amit Kumar, Chandan Banerjee
Cloud-based Computation is one of the important computing technologies where demand-based services and resources from the user's application to cloud data center with the help of internet connection can be achieved as pay on demand. The software, resources, applications are shared among different computing devices in a cloud-based approach. Balancing of Load in cloud computation technology is meant for the distribution of workload to balance loads among different cloud servers connected with different virtual machines. The main idea of load balancing is to optimize resource usage, cost of data center and virtual machines, maximization of throughput, reduction of response time and avoidance of overloading in different virtual machines as well as cloud servers. In cloud load balancing fitness checking of different cloud servers as well as virtual machines are playing an important role in cloud applications. In this proposed research paper genetic-based algorithmic approach has been used to handle the load balancing in the cloud environment. Genetic Algorithm can be used for getting solution of an optimization problem. Here it is used to find the fittest virtual machines connected with different Data Centers. Our proposed work is more appropriate compared to different algorithms discussed in [1][2], as in proposed algorithm cloudlets are taking a smaller amount time for execution and performs the load balancing in cloud environment with more efficient way by using strong fittest function for allocating cloudlets into appropriate virtual machines of a data center in cloud environment.
云计算是一种重要的计算技术,通过互联网连接,用户的应用到云数据中心的按需服务和资源可以按需付费。软件、资源和应用程序以基于云的方式在不同的计算设备之间共享。云计算技术中的负载均衡(Balancing of Load)是指负载的分配,在连接不同虚拟机的不同云服务器之间实现负载均衡。负载平衡的主要思想是优化资源使用,数据中心和虚拟机的成本,最大限度地提高吞吐量,减少响应时间,避免不同虚拟机和云服务器的过载。在云计算负载平衡中,不同云服务器和虚拟机的适应度检查在云应用中起着重要的作用。本文提出了一种基于遗传算法的方法来处理云环境下的负载均衡。遗传算法可用于求解优化问题。这里使用它来查找与不同数据中心连接的最合适的虚拟机。与[1][2]中讨论的不同算法相比,我们提出的工作更合适,因为在我们提出的算法中,cloudlets的执行时间更短,并且通过使用强拟合函数将cloudlets分配到云环境中数据中心的适当虚拟机中,以更有效的方式在云环境中执行负载平衡。
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引用次数: 6
Timing Signal Generator for High Frequency Radar 高频雷达定时信号发生器
Pub Date : 2020-09-05 DOI: 10.1109/ICCE50343.2020.9290680
Jasmin B. Mulla, A. Khandare, R. Patil
In a radar application, Time Signal Generator (TSG) is used to generate timing and control signals which helps radar to operate in different functions. The functions include tracking, detection, and hold mode. Timing Signal Generator is the heart of radar applications. Timing Signal Generator is the main part of radar application, which is responsible for synchronization between Transmitter and receiver for the transmitted signal. In this work, an implementation of timing signal using a Hardware Description Language (HDL) language-based state machine which is responsible for enabling Direct Digital Synthesis and Analog to Digital Converter in the Transmitter and receiver window. Timing Signal Generator implementation on Field Programmable Gate Array is preferred as the entire Timing signal generator unit can be assembled on a single Field programmable gate array chip, and conditional modification can be performed remotely, which is cost-effective. Timing signal generator generation begins by providing an arbitrary frequency and phase signal configuration to DDS-AD9854 from Field programmable gate array. Direct digital synthesis block generates a single-tone signal and Binary Phase Shift Keying signal and a chirp signal based on an input arbitrary signal sent by ZYBO-7010 FPGA.
在雷达应用中,时间信号发生器(Time Signal Generator, TSG)用来产生定时和控制信号,帮助雷达完成不同的功能。功能包括跟踪、检测和保持模式。定时信号发生器是雷达应用的核心。授时信号发生器是雷达应用的主要部分,它负责对发射信号在发射机和接收机之间进行同步。在这项工作中,使用基于硬件描述语言(HDL)语言的状态机实现定时信号,该状态机负责在发送和接收窗口中实现直接数字合成和模数转换。首选在现场可编程门阵列上实现定时信号发生器,因为整个定时信号发生器单元可以组装在单个现场可编程门阵列芯片上,并且可以远程进行有条件的修改,具有成本效益。时序信号发生器的生成首先从现场可编程门阵列向DDS-AD9854提供任意频率和相位信号配置。直接数字合成模块根据ZYBO-7010 FPGA发送的任意输入信号,产生单音信号、二相移键控信号和啁啾信号。
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引用次数: 0
A Simple Approach to Detect and Count Missing Cardiac Pulses and PPG Based Heart Rate Sensing 一种简单的方法检测和计数缺失的心脏脉冲和基于PPG的心率传感
Pub Date : 2020-09-05 DOI: 10.1109/ICCE50343.2020.9290530
Soumyadip Jana, Souradeep Mullick, Sayan Sarkar, P. Pal
In reference to general mathematics, Pulse is mainly a rapid, momentary change in the amplitude of any signal from a value of baseline to a higher or lower value, followed by a swift return to the baseline value. In the context of medical science, pulses (heart-pulse) are very useful for diagnosing a patient suffering from cardiac anomalies such as arrhythmia, in which the patient suffers from irregular heartbeat when some of the pulses in his cardiac pulse chain are failed to occur which have a predefined interval of time. Hence, the prototype is to be designed such that any such skipped beats do not go undetected. Therefore, in this paper, a novel, simple solution technique is proposed, in which a condition is simulated where one or more pulse would go missing, a process named Missing Pulse Generation, after which, detection of the missing pulses and their counting after a certain time, have been executed, and along with an external PPG (Photoplethysmogram) based Pulse sensing mechanism has been used to measure patient’s heart beats per minute (BPM) physically, so that, a specialist can prescribe a suitable solution for the patient’s recovery. In heart rate monitoring system, conventional missing pulse detection technique has been used since long time by which only the presence of unnatural missing pulses can be detected but here our approach is more effective than the conventional one as the detection & counting of missing & extra cardiac pulses have been brought together from human cardiac pulse chain and heart rate sensing mechanism in an automated & accurate way by minimizing the diagnosis time which is very much useful for long continuous heart-rate monitoring.
在一般数学中,脉冲主要是任何信号的幅值从基线值到一个更高或更低的值的快速瞬间变化,然后迅速返回到基线值。在医学领域,脉搏(心脏脉搏)对于诊断患有心律失常等心脏异常的患者非常有用,心律失常是指当患者的心脏脉冲链中的某些脉冲在预定的时间间隔内未能发生时,患者会出现不规则的心跳。因此,原型的设计要确保任何跳过的节拍都不会被检测到。因此,本文提出了一种新颖、简单的解决方法,该方法模拟一个或多个脉冲缺失的情况,将其称为缺失脉冲生成(missing pulse Generation),在此过程中,对缺失脉冲进行检测,并在一定时间后对其计数,并结合基于光电体积描记图(Photoplethysmogram)的外部脉冲传感机制,对患者的每分钟心跳(BPM)进行物理测量。专科医生能为病人的康复开出合适的处方。在心率监测系统中,传统的缺失脉冲检测技术已经使用了很长时间,只有非自然缺失脉冲才能被检测到,但在这里,我们的方法比传统的方法更有效,因为缺失和额外的心脏脉冲的检测和计数已经从人类心脏脉冲链和心率传感机制中以自动化和准确的方式汇集在一起,通过最小化诊断时间,这对于长时间连续心率监测非常有用。
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引用次数: 0
Design of Automatic Key Finder for Search Engine Optimization in Internet of Everything 面向万物互联搜索引擎优化的自动键查找器设计
Pub Date : 2020-09-05 DOI: 10.1109/ICCE50343.2020.9290669
G. Khekare, Pushpneel Verma
Technology is advancing day by day. Automation is playing an important role. Internet of Everything (IoE) has emerged as a key technology that enables everything to be connected through the internet. In every field Internet of everything is generating a vast amount of data like health system, traffic system, smart city monitoring system, education system, social networking sites, government organizations, etc. So to handle this huge amount of data, a system is required through which it becomes easier to track, analyze, handle, and apply that data in a better way. A unique system is proposed in this article through which important keys are identified. From those keys, desired data can be retrieved quickly and efficiently. The proposed system uses the entire new process to get the desired output. The k-means clustering with a modified entire process is used. By using natural language processing the data is accessed by the voice command. Through simulation results, it is proved that the proposed system has given better results and the searching process becomes smoother and efficient.
科技日新月异。自动化正在发挥重要作用。万物互联(Internet of Everything, IoE)已经成为一项通过互联网连接万物的关键技术。在每一个领域,万物互联都在产生大量的数据,比如医疗系统、交通系统、智慧城市监控系统、教育系统、社交网站、政府机构等。因此,为了处理如此庞大的数据,需要一个系统,通过它可以更容易地跟踪、分析、处理和更好地应用这些数据。本文提出了一个唯一的系统,通过它可以识别重要的密钥。从这些键中,可以快速有效地检索所需的数据。提出的系统使用整个新过程来获得期望的输出。采用k-means聚类方法对整个过程进行了改进。通过使用自然语言处理,通过语音命令访问数据。仿真结果表明,该系统具有较好的搜索效果,搜索过程更加流畅、高效。
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引用次数: 1
Smart Cart: A Distributed Framework 智能购物车:一个分布式框架
Pub Date : 2020-09-05 DOI: 10.1109/ICCE50343.2020.9290605
Bipin Kumar Yadav, Akash Burman, Abhoy Mahato, Manish Choudhary, A. Kundu
In retail stores, most of the people spend more time in billing queue than the time he spends choosing the items due to long queue in rush time. The average time that customers of any retail store have to spend in the billing queues has a direct influence on the quality analysis of services. Thus, it is important to think about different ways to reduce the waiting time in a queue in real time scenario. We propose a cart system that distributes the whole billing queue into smaller individual units so that no one has to wait for the billing process at point of sales (PoS) for specific items. This device uses radio-frequency identification (RFID) technology to scan each product. A passive RFID sticker tag is attached with all the products. The sticker tag contains information including name and price of the product. The device includes a 13.56 MHz RFID reader/writer module that reads RFID stickers attached to the products. In this covid-19 alarmed situation, this distributed cart system also helps people to maintain social distance avoiding long queues.
在零售商店中,大多数人花在结账队列上的时间比花在挑选商品上的时间要多,因为高峰期排队时间过长。任何零售商店的顾客在结账队列中花费的平均时间对服务质量分析有直接的影响。因此,在实时场景中,考虑不同的方法来减少队列中的等待时间是很重要的。我们提出了一个购物车系统,它将整个计费队列分配到更小的单独单元中,这样就不必在销售点(PoS)等待特定商品的计费过程。该设备使用射频识别(RFID)技术扫描每个产品。所有产品都附有无源RFID标签。标签包含产品的名称和价格等信息。该设备包括一个13.56 MHz的RFID读写模块,用于读取贴在产品上的RFID标签。在covid-19恐慌的情况下,这种分布式推车系统还有助于人们保持社交距离,避免排长队。
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引用次数: 1
Elephant Herding Optimization (EHO) Based Parameters Estimation of Induction Machine Considering the Nonlinear Core-Loss Model 考虑非线性磁芯损耗模型的基于象群优化的感应电机参数估计
Pub Date : 2020-09-05 DOI: 10.1109/ICCE50343.2020.9290586
S. Choudhary, T. Bera
Estimation of parameters for an induction machine is essential in performance analysis and control scheme design in industrial applications. In this paper, elephant herding optimization (EHO) technique-based parameter estimation technique for an induction motor is studied, and the optimum parameters are obtained using a least mean square technique (LMST). The input impedance is studied at different slip samples and a steady-state model of the squirrel-cage induction machine is developed by incorporating the nonlinear core-loss resistance. The real machine parameters are obtained from the practical experimentation on a squirrel cage induction machine. Real machine parameters are fed to the optimization algorithm as the initial values. By considering the nonlinear core-loss parameter in the equivalent circuit model, the proposed method suggests a more accurate parameter estimation technique. The effectiveness of the proposed EHO-based induction machine parameters optimization techniques is validated by the experimental and simulation results.
在工业应用中,感应电机的参数估计在性能分析和控制方案设计中是必不可少的。本文研究了基于象群优化(EHO)技术的异步电动机参数估计技术,并利用最小均方法(LMST)获得了最优参数。研究了不同滑移情况下的输入阻抗,建立了考虑非线性铁心损耗电阻的鼠笼式感应电机稳态模型。在鼠笼式感应电机上进行了实际实验,得到了实际的电机参数。将实际机器参数作为初始值馈入优化算法。该方法考虑了等效电路模型中的非线性铁芯损耗参数,提出了一种更为精确的参数估计技术。实验和仿真结果验证了基于eho的感应电机参数优化技术的有效性。
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引用次数: 0
Design and Implementation of Trash Collection System for Smart Cities 智慧城市垃圾收集系统的设计与实现
Pub Date : 2020-09-05 DOI: 10.1109/ICCE50343.2020.9290631
S. Garai, Soumyadip Sharma, Biswarup Ganguly
This paper aims to propose the design and implementation of a microcontroller-based autonomous trash collection device for indoor applications in smart cities. The proposed work demonstrates the working of a prototype model: ROBOBIN along with its accessories using Atmega328p. The different ways of implementations are discussed. This model uses a combination of passive infrared (PIR) sensor, ultrasonic sensor, and optical tracker for navigation. The device is specifically designed to be installed inhospitals and food courts. Experimental results reveal that the device is cost-effective and outperforms the state- of- the- art methods.
本文旨在提出一种基于微控制器的智能城市室内自动垃圾收集装置的设计和实现。提出的工作演示了一个原型模型的工作:ROBOBIN及其附件使用Atmega328p。讨论了不同的实现方式。该模型使用被动红外(PIR)传感器、超声波传感器和光学跟踪器的组合进行导航。该设备是专门设计安装在医院和美食广场。实验结果表明,该装置具有较高的成本效益,且性能优于目前最先进的方法。
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引用次数: 1
A Novel Deep CNN Model for Classification of Brain Tumor from MR Images 一种新的深度CNN模型用于从MR图像中分类脑肿瘤
Pub Date : 2020-09-05 DOI: 10.1109/ICCE50343.2020.9290740
H. Rai, K. Chatterjee, Apita Gupta, Alok Dubey
the segmentation of brain tumor and its classification in the early stage is very important for the purpose of diagnosis and treatment. This work introduces a new deep neural network model Lu-Net with less layers, less complexity and very efficient for identifying tumors. The work involves classifying brain magnetic resonance (MR) images from a dataset of 253 images of high pixels into two categories of tumors and non-tumors. MR images are initially resized, cropped, preprocessed, and augmented for accurate and rapid training of deep convolutional neural network (CNN) models. The performance of the Lu-Net model has been evaluated using five types of statistical evaluation matrix accuracy, recall, specificity, F-score and accuracy, and its performance also compared with other two types of model Le-Net and VGG-16. CNN models were trained and evaluated on augmented dataset and tested on untrained datasets. The overall accuracy of Le-Net, VGG-16 and the proposed model is 88%, 90% and 98%, respectively, indicating the superiority of the proposed model.
脑肿瘤的早期分割和分类对诊断和治疗具有重要意义。本文提出了一种新的深度神经网络模型Lu-Net,该模型具有层数少、复杂度低、肿瘤识别效率高的特点。这项工作包括将253张高像素图像数据集中的脑磁共振(MR)图像分为肿瘤和非肿瘤两类。为了准确快速地训练深度卷积神经网络(CNN)模型,MR图像最初被调整大小、裁剪、预处理和增强。采用统计评价矩阵准确率、召回率、特异性、f值和准确率五种类型对Lu-Net模型的性能进行评价,并与其他两种类型的Le-Net模型和VGG-16模型进行比较。CNN模型在增强数据集上进行训练和评估,在未训练的数据集上进行测试。Le-Net、VGG-16和本文模型的总体准确率分别为88%、90%和98%,表明本文模型的优越性。
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引用次数: 4
期刊
2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)
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