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Head Motion Controlled Wheelchair for Physically Disabled People 残疾人士头部运动控制轮椅
Farah Binte Haque, Tawhid Hossain Shuvo, R. Khan
Physically disabled people face difficulties in daily life because of their body impairment from their birth or due to an accident or illness. The project’s goal is to design a wheelchair that could function for a disable-person who cannot move other parts of the body correctly, keeping their words in mind with the help of head movements. Medical equipment manufactured to assist disabled peoples are very complicated, limited, and costly. A head motion controlled wheelchair is an intelligent wheelchair with facilities for navigating, recognizing obstacles, and moving automatically by managing detectors and motions. The prototype of the wheelchair performs head motion through a microcontroller. Furthermore, data processing is performed with the help of an accelerometer. The controller filters the indication and allows the action of the wheelchair for its navigation. The ultrasound detector helps to resist impediments. Usually, it is expensive, but we have designed it at an inadequate cost so that ordinary people from underdeveloped or developing countries can use it. The system memorizes the head gesture for further referencing it as the stable gesture or “neutral position” after identifying the start signal. The dc motors will drive the wheelchair during the gesture of control mode. The motors will not work, and consequently, the wheelchair will not run when the head is neutral.
身体残疾人士在日常生活中面临困难,因为他们的身体从出生起就有缺陷,或由于事故或疾病。该项目的目标是设计一种轮椅,可以为残疾人服务,他们不能正常移动身体的其他部位,通过头部运动来记住他们的话。为帮助残疾人而制造的医疗设备非常复杂、有限且昂贵。头部运动控制轮椅是一种智能轮椅,具有导航、识别障碍物、通过管理探测器和运动自动移动的功能。轮椅的原型通过微控制器执行头部运动。此外,数据处理是在加速度计的帮助下进行的。控制器过滤指示并允许轮椅的导航动作。超声波探测仪有助于抵抗障碍物。通常,它是昂贵的,但我们设计了一个不适当的成本,使不发达国家或发展中国家的普通人可以使用它。系统会记住头部手势,以便在识别启动信号后将其作为稳定手势或“中立位置”进行参考。在手势控制模式下,由直流电机驱动轮椅。马达将不工作,因此,轮椅将不会运行时,头部是中性的。
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引用次数: 9
14nm FinFET based 0.8V Supply 25Gbps Subsampler and Phase Detector Circuits for All Digital CDR 基于14nm FinFET的全数字CDR 0.8V电源25Gbps下采样器和鉴相电路
Sai Bhargav Sriramoju, Subhakumar Reddy Ankireddypalli
In this paper, the design of subsampler and phase detector circuits at 14nm technology node (FinFET) is presented. The design is carried out on cadence virtuoso with a supply voltage of 0.8V and across process corners (ss, sf, tt, fs, ff). The designed subsampler and phase detector circuits are in compliance with the All-digital clock and data recovery (ADCDR) circuit and which is applicable to passive optical networks of 4 channels with a speed of 25Gbps per channel by consuming a power dissipation of 0.9728 mW.
本文介绍了14nm技术节点(FinFET)下采样器和鉴相器电路的设计。设计是在cadence virtuoso上进行的,电源电压为0.8V,跨工艺角(ss, sf, tt, fs, ff)。所设计的下采样器和鉴相器电路符合全数字时钟和数据恢复(ADCDR)电路,适用于每通道速度为25Gbps的4通道无源光网络,功耗为0.9728 mW。
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引用次数: 0
Implementation of Peanut Leaf Disease Detection System Using Faster RCNN 基于快速RCNN的花生叶病检测系统的实现
P. Panda, Sake Vinay, Modepalli Surendra, Kure Venugopal
Leaf diseases are a common disease in many plants. It has been normally controlled by fungicides bactericides and resistant varieties. Leaves are important for the fast-growing of plants and to extend the production of crops. But in this paper, predominantly engrossed in peanut plant leaves. Nowadays, India is the largest producer of groundnut in the world but when it comes to production, the average yields at 745kg/ha. Whereas disease attack is the foremost reason for the low yield. However, identifying diseases in plant leaves is profound challenging for farmers in day-to-day life. To address the respective challenge, a leaf disease detection system based on Machine Learning (ML) and viable Faster Region-Based Convolutional Neural Networks (RCNN) algorithms has been proposed. This result reveals that the RCNN provides a solution to whether the leaf is in a fine or infirmity position. Moreover, the proposed model has been analyzed concerning the accuracy, time complexity, and computational complexity.
叶片病害是许多植物的常见病。它通常由杀菌剂和抗性品种控制。叶片对植物的快速生长和延长作物产量很重要。但在本文中,主要集中于花生植株叶片。如今,印度是世界上最大的花生生产国,但就产量而言,平均产量为745公斤/公顷。而病害是造成产量低的首要原因。然而,在日常生活中,识别植物叶片的疾病对农民来说是一个巨大的挑战。为了解决相应的挑战,提出了一种基于机器学习(ML)和可行的更快的基于区域的卷积神经网络(RCNN)算法的叶片病害检测系统。这一结果表明,RCNN提供了一种解决方案,以确定叶片是处于良好还是虚弱的位置。并从精度、时间复杂度和计算复杂度等方面对该模型进行了分析。
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引用次数: 2
Integrated Voltage and Generator Stability Analysis of a Three Bus System Combining SMIB and SMLB Systems SMIB系统和SMLB系统相结合的三母线系统的电压和发电机稳定性分析
Venu Yarlagadda, J. Rao, Giriprasad Ambati, S. K. Karthik Kumar, K. Rajesh
The Power System stability plays an extraordinary role in system security and reliability of power grid, and is broadly classified into Generator Stability and Voltage Stability. These two stability issues are can’t be separated with each other and one is interdepends on the other. The main objective of the article is to analyze both of these problems simultaneously with the development of a Three Bus System by integrating both these stability problems. The three bus test system is formed with Single Machine Infinite Bus (SMIB) System with that of the Single Machine Load Bus (SMLB) systems. The SMLB system used to study the absolute voltage stability alone whereas SMIB System is resembles the Generator Stability problem. The Simulink Model is developed for the three bus test system to evaluate the integrated angle and voltage stability analysis. The voltage stability can be assessed using pv and qv curves and angle stability is analyzed with power angle curves. Static Var Compensator (SVC) is used to improve the power system stability. The test system performance is evaluated and compared without and with Static Shunt Compensator.
电力系统稳定对电网系统的安全可靠起着举足轻重的作用,大致分为发电机稳定和电压稳定两大类。这两个稳定性问题是不可分割的,是相互依存的。本文的主要目的是通过整合这两个稳定性问题来同时分析这两个问题以及三总线系统的发展。三母线测试系统由单机无限母线(SMIB)系统和单机负载母线(SMLB)系统组成。SMLB系统用于单独研究绝对电压稳定性,而SMIB系统则类似于发电机稳定性问题。开发了三母线测试系统的Simulink模型,对综合角度和电压稳定性分析进行了评估。用pv和qv曲线评价电压稳定性,用功率角曲线分析角度稳定性。采用静态无功补偿器(SVC)来提高电力系统的稳定性。对无静态并联补偿器和有静态并联补偿器的测试系统性能进行了评价和比较。
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引用次数: 1
VLSI Implementation of a High Speed and Area efficient N-bit Digital CMOS Comparator 高速高效n位数字CMOS比较器的VLSI实现
S. Karunakaran, K. Pavan, P. Reddy
This paper deals with a comparator with N bits which is efficient in terms of area and operates at high speed with power dissipation as low as possible. Area and power necessities can be scaled down by this proposed digital comparator. Among all the arithmetic operations comparison is the most basic. This operation directs if one number is less than, greater than, or equals to the other number. In our proposed model comparison is carried out bit wise up to least significant from most significant bit , when bits are equal only then comparison forgoes ,which is called as parallel prefix tree structure is exercised. This proposed methodology of comparator structure comprises of two independent modules .Comparison evaluation unit (CEU) and final unit (FU) named first and second units respectively. For implementing tree structure results obtained from systematic structure of repeated logic cells is validated. By depending on the outcomes of CEU, FU module authenticates the result. The presence of structured VLSI methodology in the mooted architecture grants the area derivation through analytical method relating transistors count and entire total delay can be seen in terms of operand bit width. By making use of 0.18 micron CMOS technology at 1 GHz spectre simulations have been performed. Using this proposed design, power consumption reduced by 77.76% and operating speed had increased by 31.92% when compared with existing model.
本文研究了一种N位比较器,该比较器在面积上是高效的,在高速度下运行,功耗尽可能低。该数字比较器可以减小面积和功率需求。在所有的算术运算中,比较运算是最基本的。该操作指示一个数字是否小于、大于或等于另一个数字。在我们提出的模型中,比较是从最高有效位到最低有效位进行的,当位相等时才放弃比较,这被称为并行前缀树结构。该比较物结构方法包括两个独立的模块:比较评价单元(CEU)和最终单元(FU),分别命名为第一单元和第二单元。为实现树形结构,验证了由重复逻辑单元系统结构得到的结果。通过依赖CEU的结果,FU模块对结果进行验证。在讨论的体系结构中存在结构化VLSI方法,通过分析方法将晶体管数量和整个总延迟与操作数位宽度相关,从而获得面积推导。利用0.18微米CMOS技术在1ghz波段进行了光谱模拟。采用该设计,与现有机型相比,功耗降低77.76%,运行速度提高31.92%。
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引用次数: 0
Design Speech Recognition Systems in the nosily Environment by Utilizing intelligent Devices 利用智能设备设计嘈杂环境下的语音识别系统
Ali Nasret Najdet Coran, Ardm Haseeb Mohammaed Ali, Zuhair Shakor Mahhmood, Sameen F Mohammed
Many individuals have always found the ability to recognize human speech interesting because of the diversity of applications in virtually every industry. Improvements in human voice/speech recognition capacity and quality have been made possible via advancements in science and technology, particularly when using equipment known as a terminal. Speech recognition enables devices to alter speech data in a manner that is understandable, and this means that information has been completely identified and comprehended. The main aim of recognizing human voice is to be able to tailor information (for humans) for device use. The main goal of voice recognition systems is to allow the device to interact with the user and provide new possibilities. The growing use of intelligent terminals, as well as their substantial scientific and technological potential, calls into question the capabilities of human voice recognition in the workplace. The aim of this article is to demonstrate human speech recognition capabilities utilizing intelligent terminal devices. Also, this will primarily be investigated in the transportation (vehicle) context, where the advantages and disadvantages of these devices and concepts will be assessed.
许多人总是发现识别人类语言的能力很有趣,因为几乎每个行业的应用都很多样化。通过科学技术的进步,特别是在使用终端设备时,人类语音/语音识别能力和质量的提高成为可能。语音识别使设备能够以可理解的方式改变语音数据,这意味着信息已被完全识别和理解。识别人类声音的主要目的是能够(为人类)为设备使用量身定制信息。语音识别系统的主要目标是允许设备与用户交互,并提供新的可能性。越来越多的智能终端的使用,以及它们巨大的科学和技术潜力,使人们对人类语音识别在工作场所的能力产生了质疑。本文的目的是演示利用智能终端设备的人类语音识别能力。此外,这将主要在运输(车辆)背景下进行调查,其中将评估这些设备和概念的优点和缺点。
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引用次数: 1
Distributed DoS Detection in IoT Networks Using Intelligent Machine Learning Algorithms 物联网网络中使用智能机器学习算法的分布式DoS检测
S. Binny, Shamili Srimani Pendyala, S. J. Pimo, Sagaya Aurelia, P. Reddy, D. Satyanarayana
The threat of a Distributed Denial of Service (DDoS) attack on web-based services and applications is grave. It only takes a few minutes for one of these attacks to cripple these services, making them unavailable to anyone. The problem has further persisted with the widespread adoption of insecure Internet of Things (IoT) devices across the Internet. In addition, many currently used rule-based detection systems are weak points for attackers. We conducted a comparative analysis of ML algorithms to detect and classify DDoS attacks in this paper. These classifiers compare Nave Bayes with J48 and Random Forest with ZeroR ML as well as other machine learning algorithms. It was found that using the PCA method, the optimal number of features could be found. ML has been implemented with the help of the WEKA tool.
分布式拒绝服务(DDoS)攻击对基于web的服务和应用程序的威胁是严重的。这些攻击只需几分钟就能使这些服务瘫痪,使任何人都无法使用它们。随着不安全的物联网(IoT)设备在互联网上的广泛采用,这个问题进一步持续存在。此外,许多目前使用的基于规则的检测系统是攻击者的弱点。本文对ML算法检测和分类DDoS攻击进行了对比分析。这些分类器比较了Nave Bayes与J48和Random Forest与ZeroR ML以及其他机器学习算法。结果表明,采用主成分分析方法可以找到最优的特征数量。ML是在WEKA工具的帮助下实现的。
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引用次数: 1
Computerization in Home: Change in Way of Life 家庭电脑化:生活方式的改变
Tanay Reshamwala, Charmil Shah, Swapna Naik
The giant network and applications offered by a device tiny enough to be called “Dust”, has revolutionized the way we live our lives. IoT has gained rapid access and application in a wide spectrum of applications ranging from a heart monitoring device to a sensor in hazardous factory locations saving lives further leaping on to home automation & managing vehicles on roads. Home automation has seen an increased usage in developed countries as most homes are equipped and controlled through IoT. The Internet of Things is a huge network of associated things and individuals all of which gather and share data about the manner in which they are utilized and about the environment around them. In today’s modern technological era IOT has gained much admiration and is evolving at a very high pace. This paper lays out an idea of creating an IOT based Home Automation system. It illustrates the use of various hardware devices such as Arduino Uno, ESP8266 NodeMCU and some sensors along with software applications like the google firebase which is a realtime database to create a completely functional smart home. This project proposes a system where the home appliances can be controlled from the user’s mobile application via the internet from any part of the world while other minor devices and their tasks are fully automated by the system. It even integrates voice commands to the system using Google’s Voice Assistant system. The paper presents a very simple and cost effective system that can be easily implemented in any household.
一个小到被称为“尘埃”的设备提供了巨大的网络和应用程序,它彻底改变了我们的生活方式。物联网已经在广泛的应用中获得了快速的访问和应用,从心脏监测设备到危险工厂场所的传感器,从而进一步跨越到家庭自动化和管理道路上的车辆。家庭自动化在发达国家的使用越来越多,因为大多数家庭都是通过物联网装备和控制的。物联网是一个由相互关联的事物和个人组成的庞大网络,所有这些事物和个人都收集并共享有关它们被利用的方式和周围环境的数据。在当今的现代技术时代,物联网已经获得了很多的赞赏,并且正在以非常高的速度发展。本文提出了创建基于物联网的家庭自动化系统的想法。它说明了使用各种硬件设备,如Arduino Uno, ESP8266 NodeMCU和一些传感器以及软件应用程序,如谷歌firebase,这是一个实时数据库,以创建一个功能齐全的智能家居。这个项目提出了一个系统,在这个系统中,家用电器可以从用户的移动应用程序中通过互联网从世界的任何地方进行控制,而其他小型设备及其任务则由系统完全自动化。它甚至使用谷歌的语音助手系统将语音命令集成到系统中。本文介绍了一个非常简单和经济有效的系统,可以很容易地在任何家庭实施。
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引用次数: 2
期刊
2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)
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