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2018 IEEE International Conference on System, Computation, Automation and Networking (ICSCA)最新文献

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Recent Trends in HCI: A survey on Data Glove, LEAP Motion and Microsoft Kinect 关于Data Glove、LEAP Motion和Microsoft Kinect的调查
K. Aditya, Praise Chacko, Deeksha Kumari, D. Kumari, Saurabh Bilgaiyan
The way humans interact with material objects around them has evolved a lot over the ages, with new technologies being added to the lot over the years. Same goes for the human computer interaction, the basic mode comprising of mouse and various buttons and keyboards etc. has become obsolete now. New emerging technologies and ideas from various companies are setting a benchmark for the way this interaction can take place, with utmost ease and precision. From visual based guidance systems to recognition based on retina scan, fingerprints or gesture recognition, the possibilities are virtually endless. Gone are the days of needing a GUI for interacting with a computer application, each replaced by motion tracking softwares and firmwares for the same. This paper deals with three emerging technologies for the same, LEAP motion controller, Microsoft Kinect and Data Glove. Gesture recognition using data glove is an efficient choice for HCI but it has poor interface and it lags as far as computational time is concerned. Microsofts Xbox Kinect uses a high definition camera and an active IR feature to help recognize the body features and skeletal tracking to track movements of multiple users. Leap motion with its state of the art depth sensing camera and ability to render hand gestures using palm and fingers orientation in 3D space is yet another choice for HCI. A detailed description and working principles of each of the devices, along with the applications and advantages of one over the other are discussed in brief in this paper, along with the future prospects discussed at the end.
多年来,随着新技术的不断涌现,人类与周围物质物体互动的方式已经发生了很大的变化。人机交互也是如此,由鼠标、各种按钮和键盘等组成的基本模式现在已经过时了。来自不同公司的新兴技术和想法正在为这种互动的方式设定一个基准,以最大限度地方便和精确。从基于视觉的导航系统到基于视网膜扫描、指纹或手势识别的识别,可能性几乎是无穷无尽的。需要GUI与计算机应用程序交互的日子已经一去不复返了,每个GUI都被运动跟踪软件和固件所取代。本文介绍了这一领域的三种新兴技术:LEAP运动控制器、Microsoft Kinect和Data Glove。使用数据手套进行手势识别是人机交互的一种有效选择,但其界面较差且计算时间滞后。微软Xbox Kinect使用一个高清摄像头和一个主动红外功能来帮助识别身体特征和骨骼跟踪来跟踪多个用户的运动。Leap motion拥有最先进的深度感应摄像头,能够在3D空间中使用手掌和手指方向渲染手势,这是HCI的另一个选择。本文简要介绍了每种器件的详细描述和工作原理,以及每种器件的应用和优点,并对未来的前景进行了展望。
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引用次数: 8
Energy Harvesting Circuit Utilizing MOSFET Based Bridge Rectifier 基于MOSFET的桥式整流器的能量收集电路
S. Dhayabarasivam, K. Jayanthi
Full wave rectifier using diodes are commonly employed in energy harvestor. The conventional harvestor circuit consists of a full wave bridge AC/DC rectifier with significant voltage charges. These diode based rectifier circuit is not suitable for gaining a current. This paper focuses at designing a suitable single and double stage energy harvestor module using n-channel switches in the place of diodes in conventional circuit. In order to obtain an optimum voltage, the existing diode based rectifier circuit is modified with an n channel MOSFET. The proposed MOSFET rectifier circuit is considered to overcome the voltage drop and gaining a current. To double the voltage obtained at the output of the rectifier, boost converter has been used to the energy harvesting circuit. In this paper an energy harvesting circuit is simulated using MATLAB Simulink tool and constructed with an auto parameter from the MATLAB-simulation.
利用二极管的全波整流器通常用于能量收集。传统的收割机电路由一个具有显著电压电荷的全波桥式AC/DC整流器组成。这些基于二极管的整流电路不适合获得电流。本文的重点是设计一种合适的单级和双级能量收集模块,使用n通道开关代替传统电路中的二极管。为了获得最佳电压,用n沟道MOSFET对现有的二极管整流电路进行了改进。所提出的MOSFET整流电路被认为可以克服压降并获得电流。为了使整流器输出电压加倍,能量收集电路采用升压变换器。本文利用MATLAB Simulink工具对能量采集电路进行了仿真,并根据仿真结果构造了一个自动参数。
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引用次数: 3
A Survey Paper on Calcaneus Bone Tumor Detection Using different Improved Canny Edge Detector 不同改进型Canny边缘检测器对跟骨肿瘤检测的综述
Ak Pandey, S. Shrivastava
Malignant and benign tumors of bone in the foot have traditionally been characterized as rare, or at least unusual. When these lesions do appear, mostly used methods, for foot and ankle tumors detection, are Ultrasound, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). There is a lot of image segmentation techniques are available. In this paper we are analyzing Computed Tomography images through Computer Aided Diagnosing (CAD) system. And for edge detection in image, canny edge detector is used. Canny edge detector has some limitations like it is not able to distinguish edges occurring around objects but still it is beneficial than other traditional edge detector methods.But to make the Canny edge detector better at identifying contours in natural images, in this paper some improved canny edge detector are analyzed.
脚骨的恶性和良性肿瘤传统上被认为是罕见的,或者至少是不寻常的。当这些病变确实出现时,用于足部和踝关节肿瘤检测的主要方法是超声、计算机断层扫描(CT)和磁共振成像(MRI)。有很多图像分割技术是可用的。本文采用计算机辅助诊断(CAD)系统对ct图像进行分析。对于图像的边缘检测,采用了精细边缘检测器。Canny边缘检测方法虽然存在一些局限性,如不能区分物体周围的边缘,但与其他传统的边缘检测方法相比,它仍然是有益的。为了使Canny边缘检测器能够更好地识别自然图像中的轮廓,本文分析了几种改进的Canny边缘检测器。
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引用次数: 7
Finite Element Analysis of Composite Shell Structure of Aircraft Wing Using Composite Structure 基于复合材料结构的飞机机翼复合壳结构有限元分析
V. Pugazhenthi, S. Gopalakannan, R. Rajappan
The simplified methods of the wing structures can be performed with enough confidence; as long as the simplified method based designs are analysts. The analysis result shows that the simplified method is applicable to used for performing the wing structure. During the analysis depending on the meshing is used from software package as MSC/PATRAN. Conclusions are also inferred with regard to the deficiency of certain element types in handling the true external load and internal load acting on the wing structure.
机翼结构的简化方法可以有足够的信心进行;只要基于简化方法进行设计分析。分析结果表明,该简化方法适用于机翼结构的计算。在分析过程中,根据网格划分从软件包中使用MSC/PATRAN。在处理作用在机翼结构上的真正外部载荷和内部载荷时,还推断出某些元件类型的不足。
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引用次数: 1
Voltage Stability Using STATCOM During Sudden Increase in Load Demand 负载需求突然增加时使用STATCOM的电压稳定性
Prafulkumar Kamble, S. Kamble
Modern power systems are highly complex and are expected to fulfill the growing demands of power wherever required, with acceptable quality and costs. In the Electrical power system area, an exciting opportunity called Custom Power enables at-the-fence solutions for delivery to industrial and commercial customers, value added reliable electric service distortions, and over-voltages. It is now well known that voltage reductions of greater than 15 or 20% and of duration greater than a few cycles lead to significant losses for the increasingly automated processing and manufacturing industry. Sudden increase in load always creates voltage fluctuation. This paper investigates the effect of sudden increase in load with and without STATCOM.
现代电力系统是高度复杂的,并期望在质量和成本可接受的情况下满足日益增长的电力需求。在电力系统领域,一个令人兴奋的机会被称为定制电源,为工业和商业客户提供围栏解决方案,增值可靠的电力服务扭曲和过电压。现在众所周知,电压降低超过15%或20%,持续时间超过几个周期,对于日益自动化的加工和制造业来说,会导致重大损失。负荷的突然增加总是造成电压波动。本文研究了有STATCOM和无STATCOM时载荷突然增加的影响。
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引用次数: 0
Simulation model for the analysis of Patient Scheduling Process in Radio Diagnosis Department 放射科病人调度过程分析的仿真模型
V. V. Panicker, P. Arun
India accounts for only 2.4 percent of the world surface area and yet it supports and sustains 17.74 percent of the world population. This statistics always seems to be a barrier for successful growth of Healthcare systems in India. Even though ample number of new schemes is launched, still the public health system in the country continues to face formidable challenges. Development of efficient healthcare systems can improve the public health systems. This work aims to develop a simulation model for the Radio diagnosis department of a hospital. The model is developed to study the behavior of the Radio diagnosis department and perform a "what-if" analysis. Thus the simulation model is used as an efficient tool to understand the problem environment and suggesting possible improvements.
印度只占世界表面积的2.4%,却养活了世界17.74%的人口。这些统计数据似乎一直是印度医疗保健系统成功发展的障碍。尽管启动了大量的新计划,但该国的公共卫生系统仍然面临着巨大的挑战。发展高效的卫生保健系统可以改善公共卫生系统。本工作旨在建立一个医院放射诊断科的仿真模型。该模型是为了研究无线电诊断部门的行为并进行“假设”分析而开发的。因此,仿真模型是了解问题环境并提出改进建议的有效工具。
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引用次数: 0
An improved Clustering Based Hierarchical Protocol for extending Wireless Sensor Network Lifetime – EG LEACH 一种改进的基于聚类的扩展无线传感器网络生存期的分层协议——EG LEACH
Remika Ngangbam, A. Hossain, A. Shukla
Wireless sensor networks play a vital role in present day world which are being used in different types of applications and occupy an important part in networking domain. It comprises of number of sensor nodes of limited battery power due to which saving power becomes the main factor to be considered in this finite energy wireless sensor networks to increase its lifetime. It is fact that in clustering protocol energy consumption by cluster head node (CHN) during communication with the BS is much higher than energy depletion by cluster member nodes (CMN) to transmit data to the associated cluster head (ACH). Therefore, energy consumption by cluster head and other member nodes become a crucial factor to be discussed for determining wireless sensor networks (WSNs) lifetime. This proposed protocol organises the cluster head selection efficiently to provide longer network lifetime and to provide balanced cluster head selection. The simulated output shows better performance comparing with traditional LEACH.
无线传感器网络在当今世界中发挥着至关重要的作用,它被应用于不同类型的应用中,在网络领域中占有重要的地位。它由电池电量有限的传感器节点组成,因此在这种有限能量的无线传感器网络中,节省电能成为增加其使用寿命的主要考虑因素。事实上,在集群协议中,簇头节点(CHN)在与BS通信过程中的能量消耗远远高于簇成员节点(CMN)向关联簇头(ACH)传输数据所消耗的能量。因此,簇头和其他成员节点的能量消耗成为决定无线传感器网络(WSNs)生存期的关键因素。该协议有效地组织簇头选择,以提供更长的网络生存期和提供均衡的簇头选择。与传统LEACH相比,仿真输出具有更好的性能。
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引用次数: 4
Heuristic Algorithm based Approach to Classify EEG Signals into Normal and Focal 基于启发式算法的脑电信号正常与病灶分类方法
V. S. Narayanan, R. Elavarasan, C. Gnanaprakasam, N. S. Madhava Raja, R. Kiran Kumar
Condition of brain can be examined using the brain-signals and brain-images. Signal based evaluation is simple and offers essential information compared with the image based methods. This paper proposes an approach to evaluate the benchmark EEG signals. The implemented approach initially implements an amplitude based assessment to compute the peak-to-peak voltage value of the EEG signal. Later, it implements time-frequency conversation procedure to transfer the signal into image based on the wavelet transform. Further, the S-transform approach is considered to extract the essential signal features for the classifier system. Firefly-Algorithm (FA) based approach is also considered to choose leading signal features considered to train and test the classifier unit. In this work, classifiers, such as Support-Vector-Machine (SVM), Random-Forest (RF) and K-Nearest Neighbor (KNN) are implemented and the result of this work offered an average accuracy of 80.39%. The works confirms that, proposed procedure offers better result on the chosen EEG signals.
利用脑信号和脑图像可以检查大脑的状态。与基于图像的评估方法相比,基于信号的评估方法简单且能提供必要的信息。本文提出了一种评估基准脑电信号的方法。所实现的方法首先实现了基于幅度的评估来计算脑电信号的峰间电压值。然后基于小波变换实现时频对话处理,将信号转换成图像。进一步,考虑了s变换方法来提取分类器系统的基本信号特征。本文还考虑了基于萤火虫算法(FA)的方法,选择考虑的主要信号特征来训练和测试分类器单元。在这项工作中,实现了支持向量机(SVM),随机森林(RF)和k近邻(KNN)等分类器,该工作的结果平均准确率为80.39%。实验结果表明,该方法对所选的脑电信号有较好的处理效果。
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引用次数: 8
A NOVEL APPROACH FOR DETECTING DDoS ATTACK IN H-IDS USING ASSOCIATION RULE 一种利用关联规则检测H-IDS中DDoS攻击的新方法
Ragav Venkatesan, D. Devi, R. Keerthana, A. Kumar
Across the globe, all the companies are marching towards data security and data protection. Prevention measures are taken to secure their database from an intruder. As the technology grows rapidly for information/data security, the intruders also use various techniques to exploit data on other side. Distributed Denial of Service (DDoS) attack is used to override the security of targeted system, where the attacker seeks to make a terminal unavailable to its authorized users temporarily by sending "n" number of packets over the network. The triggered DDoS attack interrupts any normal operation in a network and not letting the legitimate users to access the machine. Simply, the DDoS floods the targeted machine not to do any further actions. This examination is conveyed to distinguish DDoS attack in OSSEC HIDS, and successful measures to decrease false positive rate. "OSSEC (HIDS)"[1] has brought together, cross stage design enabling different frameworks to be effortlessly observed, overseen and simple to get the recorded logs. The extracted report was analyzed with "ASSOCIATION RULE" using Weka open source tool.
在全球范围内,所有公司都在朝着数据安全和数据保护的方向迈进。采取了预防措施来保护他们的数据库免受入侵者的攻击。随着信息/数据安全技术的快速发展,入侵者也在使用各种技术来利用另一端的数据。分布式拒绝服务(DDoS)攻击用于覆盖目标系统的安全性,攻击者通过网络发送“n”个数据包,试图使其授权用户暂时无法使用终端。触发的DDoS攻击会中断网络中的任何正常操作,并且不允许合法用户访问计算机。简单地说,DDoS会淹没目标机器,使其不做任何进一步的操作。阐述了在OSSEC HIDS中如何识别DDoS攻击,以及降低误报率的有效措施。“OSSEC (HIDS)”[1]汇集了跨阶段设计,使不同的框架可以毫不费力地观察,监督和简单地获得记录的日志。提取的报告使用Weka开源工具“ASSOCIATION RULE”进行分析。
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引用次数: 3
Cloud Assisted Recovery Scheme for Compressively Sensed Medical Sensor Data 压缩感测医疗传感器数据的云辅助恢复方案
S. Dyaneshwar, K. Monica, G. Jaiyashri, R. Amutha
In recent times health problems like cardiac failure and respiratory issues are on the rise. With the explosion of Internet of Things and development of variety of low cost sensors, monitoring of health parameters remotely has been become a viable alternative to regular hospital visits. This paper proposes a novel remote health parameter monitoring system with compressed sensing mechanism to monitor patients remotely while simultaneously minimizing the amount of information sent over the network. In addition to remote monitoring this system also enables storage of the data on a remote server/cloud solution which can be used for future processing to study health conditions in a retrospective manner.
近年来,心脏衰竭和呼吸系统疾病等健康问题呈上升趋势。随着物联网的蓬勃发展和各种低成本传感器的发展,远程监测健康参数已成为常规医院就诊的可行替代方案。提出了一种新型的基于压缩感知机制的远程健康参数监测系统,在对患者进行远程监测的同时,最大限度地减少了通过网络发送的信息量。除了远程监测外,该系统还可以将数据存储在远程服务器/云解决方案上,以便将来进行处理,以回顾性的方式研究健康状况。
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引用次数: 0
期刊
2018 IEEE International Conference on System, Computation, Automation and Networking (ICSCA)
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