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2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)最新文献

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MAQ system development in mobile ad-hoc networks using mobile agents 基于移动代理的移动自组网MAQ系统开发
Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7918791
Mamata Rath, M. R. Panda
To furnish protected and efficient routine activities in cluster based Mobile Adhoc Networks (MANETs), a Mobile Agent based QoS (MAQ) scheme using clustering algorithm for real time data communication has been designed in this paper. A Mobile agent architecture is projected in a way that it remains associated with the cluster head of every cluster and when real time application gets notified in these clusters then the proposed system gets activated to hold up prioritized service to these applications including checking and monitoring the flow qualities for real time applications. JADE (Java Agent Development Environment) based prioritized proposal at the mobile agent has been implemented in the proposed system. As this is an application oriented approach, so the overall network performance significantly improves resulting better throughput and packet delivery ratio. Prioritized functionalities relating to end-to-end delay, jitter in video streaming and power saving policies during real-time data transmission are controlled by operational modules defined in the mobile agent.
为了在基于集群的移动自组网(manet)中提供受保护的、高效的日常活动,本文设计了一种基于移动代理的、采用聚类算法的实时数据通信QoS (MAQ)方案。移动代理架构以一种与每个集群的集群头保持关联的方式进行规划,当实时应用程序在这些集群中得到通知时,提议的系统被激活,以保持对这些应用程序的优先级服务,包括检查和监控实时应用程序的流质量。在被提议的系统中实现了基于JADE (Java Agent Development Environment)的移动代理优先提议。由于这是一种面向应用程序的方法,因此整体网络性能显著提高,从而获得更好的吞吐量和数据包传递率。与端到端延迟、视频流中的抖动和实时数据传输中的节能策略相关的优先功能由移动代理中定义的操作模块控制。
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引用次数: 18
Cut detection and secure routing in wireless sensor networks 无线传感器网络中的割伤检测和安全路由
Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7917949
Pradnya Wagh, Pratik Mahamuni, Kaustubh Rajeshirke
Wireless sensor network will become isolated in various associated segments because of the disappointment of some of its hubs, which is known as a “cut”. In this paper, authors acknowledge the issue of distinguishing cuts by the remaining hubs of a wireless sensor network. System proposes an estimation which grants every hub to identify at the time of accessibility to an extremely assigned hub has been lost, and one or more hubs (that are connected with the unique hub after the cut) to recognize the cut's event. The calculation is passed on and strange: every hub needs to relate with simply those hubs that are within its correspondence range. The estimation relies on upon the iterative calculation of an invented “electrical potential” of the hubs. The combining rate of the concealed iterative arrangement is self-governing of the size as well as network structure. Also this system implements a lightweight encryption algorithm to rout data securely in the network and enhance the system performance.
由于一些集线器的故障,无线传感器网络将在各种相关的细分市场中变得孤立,这被称为“切断”。在本文中,作者承认通过无线传感器网络的剩余集线器来区分切割的问题。系统提出了一种估计方法,该方法允许每个集线器在可访问性被极度分配的集线器丢失时识别,并允许一个或多个集线器(在切割后与唯一的集线器连接)识别切割事件。计算被传递并且奇怪:每个集线器只需要与在其通信范围内的那些集线器相关联。这种估计依赖于对一个虚构的轮毂“电位”的迭代计算。隐式迭代排列的组合速率受网络大小和网络结构的影响。该系统还实现了一种轻量级的加密算法,使数据在网络中安全路由,提高了系统的性能。
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引用次数: 1
Named entity recognition model for Punjabi language: A survey 旁遮普语命名实体识别模型综述
Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7919047
Pawandeep Kaur, Amandeep Kaur
Information extraction is the sub topic of Artificial Intelligence method. Recognition of named entity tags for computer using NLP (Natural language processing) is very important. It is very first step in recognition of unstructured content. For classification and identification of given number of tasks for any data, named entity recognition can be used as a subtask for extraction of information. There are numerous methods that help in applying NE process. In this paper various methods of NER have been presented and various issues related to Punjabi language has been discussed.
信息抽取是人工智能方法的子课题。使用自然语言处理技术对计算机进行命名实体标签的识别是非常重要的。这是识别非结构化内容的第一步。为了对任意数据的给定数量的任务进行分类和识别,可以将命名实体识别用作提取信息的子任务。有许多方法可以帮助应用NE流程。在本文中,提出了各种NER方法,并讨论了与旁遮普语相关的各种问题。
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引用次数: 0
Rough-set and artificial neural networks based image classification 基于粗糙集和人工神经网络的图像分类
Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7917931
D. Vasundhara, M. Seetha
Spatial image classification meant to the mechanism of extracting meaningful knowledge information classes from spatial images dataset. Many traditional pixel based image classification techniques such as Support Vector Machines (SVM), ANN, Fuzzy methods, Decision Trees (DT) etc. exist. The performance and accuracy of these image classification methods depends upon the network structure and number of inputs. Here, in this paper, we have proposed an step-wise mechanism to significantly improve the classification performance of neural network, that uses rough sets approach for purpose of features/attributes selection of image pixels. The complexity analysis of the proposed algorithm and the comparison of mechanism, presented here, with existing classification techniques based on features over the interest area is carried out.
空间图像分类是指从空间图像数据集中提取有意义的知识信息类的机制。传统的基于像素的图像分类技术有支持向量机(SVM)、人工神经网络(ANN)、模糊方法、决策树(DT)等。这些图像分类方法的性能和准确性取决于网络结构和输入的数量。在本文中,我们提出了一种逐步提高神经网络分类性能的机制,即使用粗糙集方法来选择图像像素的特征/属性。对本文提出的算法进行了复杂性分析,并与现有的基于感兴趣区域特征的分类技术进行了机制比较。
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引用次数: 3
Integration of PLC based offline impedance matching system for ICRH experiments 基于PLC的ICRH实验离线阻抗匹配系统集成
Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7918027
R. Joshi, H. M. Jadav, A. Mali, S. Kulkarni
Ion Cyclotron Resonance Heating (ICRH) system has two different impedance matching systems for RF transmission. One is offline matching which has been used before applying the experimental shots. Another is online impedance matching which has been used during experimental shot. Offline matching network consists of two coarse tuner, static stubs and coarse phase shifter which are identical in both the transmission lines. There are motorized arrangement installed in each stubs and phase shifters. Both static and coarse stubs are used to vary length in order to match the source impedance with load impedance. Phase shifter is used for matching impedance via varying the phase of the power. Programmable Logic Controller (PLC) based instrumentation has been implemented for the system. Offline matching should be operated below 1 kHz frequency in order to move stepper motors using square pulses employed to motor controller. In existing system this operation has been carried out by VME instrumentation and control. In order to reduce load on VME, PLC based system has been designed and integrated with VME based DAC. SIMATIC Windows Control Center (WinCC) software has been used as SCADA i.e. front end user interface. WinCC SCADA can communicate with OPC (Open Process Control) server using different PLC signals. This paper describes technical details, design and development of PLC based offline impedance matching system using WinCC as SCADA. The developed system has proved accurate and reliable in use of application as per system requirement. The SCADA system also shows motor frequency and motor speed profile with upper and lower limits. It logs data at the end of operation by which it retrieve the last run status of each motor when it starts again.
离子回旋共振加热(ICRH)系统具有两种不同的射频传输阻抗匹配系统。一种是在应用实验镜头之前使用的离线匹配。另一种方法是在线阻抗匹配,该方法已在实验射击中得到应用。离线匹配网络由两个粗调谐器、静态存根和粗移相器组成,它们在两根传输线上相同。在每个存根和移相器上安装有电动装置。为了使源阻抗与负载阻抗相匹配,静态桩和粗桩都用来改变长度。移相器通过改变电源的相位来匹配阻抗。系统实现了基于可编程逻辑控制器(PLC)的仪器仪表。离线匹配应低于1khz频率操作,以便使用电机控制器使用的方波脉冲移动步进电机。在现有的系统中,该操作是由VME仪表和控制来完成的。为了减少VME的负载,设计了基于PLC的系统,并将其与基于VME的DAC集成在一起。SIMATIC Windows控制中心(WinCC)软件被用作SCADA,即前端用户界面。WinCC SCADA可以使用不同的PLC信号与OPC (Open Process Control)服务器通信。本文介绍了以WinCC作为SCADA的基于PLC的离线阻抗匹配系统的技术细节、设计与开发。经实际应用证明,所开发的系统准确可靠,符合系统要求。SCADA系统还显示了电机频率和电机速度的上下限。它在操作结束时记录数据,通过它检索每个电机再次启动时的最后运行状态。
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引用次数: 1
Routing in WSN network using neural Network (NN) and SPEED protocol 基于神经网络和SPEED协议的WSN网络路由
Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7917952
Manpreet Kaur, Anjana Sharma
Routing stands for the sending the required data to the destination in such a manner that it reaches efficiently with high throughput and accuracy. The data is transferring over the network each sensor use some energy in receiving data, sending data. The life of the network depend how much energy used up in each transmission. The problem occurs when the transmission path meets with some sort of failure like path failure or node goes to sleep mode. The focus, however, has been given to the routing protocols which might differ depending on the application and network architecture. In this paper, we have proposed the state-of-the-art routing technique using SPEED protocol and NN technique to choose an alternative path in WSNs.
路由是指将所需的数据以这样一种方式发送到目的地,从而高效地达到高吞吐量和准确性。数据在网络上传输,每个传感器在接收数据、发送数据时使用一定的能量。网络的寿命取决于每次传输消耗了多少能量。当传输路径遇到某种故障,如路径故障或节点进入休眠模式时,就会出现问题。然而,重点是路由协议,它可能因应用程序和网络体系结构而有所不同。在本文中,我们提出了最先进的路由技术,使用SPEED协议和神经网络技术来选择WSNs中的替代路径。
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引用次数: 3
The performance of multi-layer neural network on face recognition system 多层神经网络在人脸识别系统中的性能
Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7918000
M. J. Yashaswini, V. S. Vishnu, B N Annapuma, Tanik R Prasad
Biometrics and Pattern Recognition have various applications that are found and brought into real-time application use. Face recognition consist mainly of three stages namely: Pre-processing, Feature Extraction and Classification. Neural Networks basically deals with adaptation, classification and rendering noisy values to optimal solution. In this work we illustrate performance and accuracy of the above approaches. Subspace is a plane embedded in a higher dimensional vector space, PCA is a standout amongst the best systems that have been utilized in image recognition and compression while KPCA is utilized in ascertaining PCA conversion in a mapping space by a nonlinear mapping function. FFNN is used for pattern recognition, FNN frequently have at least one hidden layers of sigmoid neurons followed by a yield layer of linear neurons. Multiple layers of neurons with nonlinear transfer function permits the system to learn connections amongst information and yield vectors. LVQ learn to characterize input vectors into target classes picked by the user.
生物识别和模式识别有各种各样的应用,被发现并引入实时应用。人脸识别主要包括预处理、特征提取和分类三个阶段。神经网络主要处理自适应、分类和呈现噪声值的最优解。在这项工作中,我们说明了上述方法的性能和准确性。子空间是嵌入在高维向量空间中的一个平面,PCA是在图像识别和压缩中使用的最好的系统之一,而KPCA用于通过非线性映射函数确定映射空间中的PCA转换。FFNN用于模式识别,FNN通常至少有一个隐藏层的s形神经元,后面是一个屈服层的线性神经元。具有非线性传递函数的多层神经元允许系统学习信息和屈服向量之间的联系。LVQ学习将输入向量特征化为用户选择的目标类。
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引用次数: 1
An IoT based soil moisture monitoring on Losant platform 基于物联网的Losant平台土壤湿度监测
Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7918063
R. Kodali, A. Sahu
The Internet of Things (IoT) is converting the agriculture industry and solving the immense problems or the major challenges faced by the farmers todays in the field. India is one of the 13th countries in the world having scarcity of water resources. Due to ever increasing of world population, we are facing difficulties in the shortage of water resources, limited availability of land, difficult to manage the costs while meeting the demands of increasing consumption needs of a global population that is expected to grow by 70% by the year 2050. The influence of population growth on agriculture leads to a miserable impact on the farmers livelihood. To overcome the problems we design a low cost system for monitoring the agriculture farm which continuously measure the level of soil moisture of the plants and alert the farmers if the moisture content of particular plants is low via sms or an email. This system uses an esp8266 microcontroller and a moisture sensor using Losant platform. Losant is a simple and most powerful IoT cloud platform for the development of coming generation. It offers the real time data visualization of sensors data which can be operate from any part of the world irrespective of the position of field.
物联网(IoT)正在改变农业产业,并解决当今农民在田间面临的巨大问题或主要挑战。印度是世界上水资源短缺的第13个国家之一。由于世界人口的不断增加,我们面临着水资源短缺、土地有限、难以管理成本的困难,同时满足全球人口日益增长的消费需求,预计到2050年将增长70%。人口增长对农业的影响给农民的生计带来了悲惨的影响。为了克服这些问题,我们设计了一个低成本的农业监测系统,该系统可以持续测量植物的土壤水分水平,并通过短信或电子邮件提醒农民特定植物的水分含量低。本系统采用esp8266单片机和Losant平台的湿度传感器。Losant是一个简单而强大的物联网云平台,用于下一代的开发。它提供了传感器数据的实时数据可视化,可以从世界任何地方操作,而不管现场的位置。
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引用次数: 66
Low cost ambient monitoring using ESP8266 采用ESP8266的低成本环境监测
Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7918788
R. Kodali, K. S. Mahesh
A different language is different vision of life. Micropython is the open source scripting language and an interpreter that expresses the concepts in fewer lines of codes. This high level language possesses clear and expressive codes which is designed to respond to the actions. It is a lean and efficient implementation of python 3 programming language that comes with the quick language feedback and is optimized for interactive input to run on microcontroller or embedded systems. This functional and dynamic programming language is ported to ESP8266 board. The DHT11 sensor is interfaced with ESP8266 board to sense the ambient conditions like temperature and humidity. The dht module which is confined to DHT sensor is being imported to perform its programming task. The OLED display used here have dimensions of 128×64, it has an I2C interface and can be driven by SSD1306 driver. Firstly, the library for the SSD1306 driver of the chip needs to be imported. The ESP8266 board have two connections, one with the DHT11 sensor to sense the temperature and humidity, and the second with OLED display to show the collected information of temperature and humidity from DHT11 sensor on to the screen. These all are implemented using lean and efficient Micropython language and thus it is easy to control hardware and connected devices using Micropython.
不同的语言是不同的人生观。Micropython是一种开源脚本语言和解释器,可以用更少的代码行来表达概念。这种高级语言具有清晰而富有表现力的代码,旨在对行为做出反应。它是python 3编程语言的精简和高效实现,具有快速的语言反馈,并针对在微控制器或嵌入式系统上运行的交互式输入进行了优化。该函数式动态编程语言可移植到ESP8266板上。DHT11传感器与ESP8266板接口,用于感知环境条件,如温度和湿度。导入dht模块,完成dht传感器的编程任务。这里使用的OLED显示屏尺寸为128×64,它有一个I2C接口,可以由SSD1306驱动。首先,需要导入芯片的SSD1306驱动程序库。ESP8266板有两个连接,一个是与DHT11传感器连接,用于感知温湿度,另一个是与OLED显示器连接,用于将DHT11传感器采集到的温湿度信息显示在屏幕上。这些都是使用精简高效的Micropython语言实现的,因此使用Micropython很容易控制硬件和连接的设备。
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引用次数: 41
Implementation of neural network for channel estimation in OFDM network OFDM网络中信道估计的神经网络实现
Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7918004
Ravinder Kaur, Rinkesh Mittal
Channel estimation is an important field of interest in wireless OFDM networks. Lot of work has been done in this field, but only few techniques has presented good efficiency in channel estimation in OFDM network. This paper has presented the neural network based channel estimation for OFDM network using Raleigh channel. From result simulation, it has been concluded that obtained values of Mean Square Error (MSE) and Bit Error Rate (BER) are satisfactory using neural network in MATLAB environment.
信道估计是无线OFDM网络研究的一个重要领域。在这方面已经做了大量的工作,但只有少数技术在OFDM网络中表现出较好的信道估计效率。提出了一种基于神经网络的基于罗利信道的OFDM网络信道估计方法。仿真结果表明,在MATLAB环境下利用神经网络得到的均方误差(MSE)和误码率(BER)是令人满意的。
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引用次数: 1
期刊
2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)
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