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2018 International Conference on Advanced Computation and Telecommunication (ICACAT)最新文献

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Basis & Sensing Matrix as key effecting Parameters for Compressive Sensing 基和感知矩阵是影响压缩感知的关键参数
Pub Date : 2018-12-01 DOI: 10.1109/ICACAT.2018.8933745
Vivek Upadhyaya, M. Salim
Compressive Sensing (CS) is a new approach for compression and reconstruction of compressed signals using very minute observations. These minute observations are also called the number of measurement. The basic benefits of CS are that the number of measurements which are required for proper reconstruction of the compressed signal is very less than the conventional method. If we go through the literature then, we get that for proper reconstruction of signal a theory is given by Shannon. This theory states that the sampling frequency must be higher than twice the highest frequency component in that signal. So the limitation of the conventional method is that it requires so much storage to store and a large bandwidth to transmit the data. So researchers came with a new idea which is termed as Compressive Sensing. Key effecting parameters which are very crucial for the compressive sensing is the Basis and Sensing matrix. The basic fact behind this approach is that the signal which is used for the compression and reconstruction must be Sparse. In the analysis which is done by us in this paper is that the change in these two matrices directly changes the value of SNR which will be obtained after compression and reconstruction using the compressive sensing. The work which is carried out based on three kinds of music signals with different cases of Basis and Sensing matrices.
压缩感知(CS)是一种利用极微小的观测值对压缩信号进行压缩和重构的新方法。这些微小的观察也被称为测量的次数。CS的基本优点是正确重建压缩信号所需的测量次数比传统方法少得多。如果我们回顾一下文献,我们就会发现Shannon给出了一个理论,用来对信号进行适当的重构。该理论指出,采样频率必须高于该信号中最高频率分量的两倍。因此,传统方法的局限性在于需要大量的存储空间和大的带宽来传输数据。因此,研究人员提出了一种新的想法,称为压缩感知。影响压缩感知的关键参数是基和感知矩阵。这种方法背后的基本事实是用于压缩和重构的信号必须是稀疏的。在本文所做的分析中,这两个矩阵的变化直接改变了压缩感知压缩重建后得到的信噪比值。该工作基于三种音乐信号,采用不同的基矩阵和传感矩阵。
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引用次数: 2
Performance comparison of hard and soft fusion Techniques for Energy Efficient CSS in Cognitive Radio 认知无线电节能CSS硬、软融合技术性能比较
Pub Date : 2018-12-01 DOI: 10.1109/ICACAT.2018.8933672
Girraj Sharma, Ritu Sharma
In this paper Comparative analysis of hard and soft fusion techniques for Energy Efficient cooperative spectrum sensing (CSS) is presented. CSS is the efficient way of detecting spectrum holes in cognitive radio (CR) network by combining sensing information of various CR users also known as secondary users (SUs). In CSS, energy resources become precious when the SUs in CR network are battery operated. So it becomes important to use their energy efficiently. In this paper, Hard fusion techniques like AND, OR and Majority and soft fusion techniques like square law selection (SLS) and square law combine (SLC) fusion are explained and fusion rule threshold that maximizes the EE is calculated. Results show that for Energy Efficient CSS, Majority fusion outperforms other fusion techniques. For majority fusion EE is 4.4% more compared to SLS fusion and maximum EE is 3.8 Mbits/Hz/joule at sensing time equals to 2ms.
本文对节能协同频谱传感(CSS)中的硬融合技术和软融合技术进行了对比分析。CSS是将认知无线电(cognitive radio, CR)网络中各种次要用户(secondary users, su)的感知信息结合在一起,有效检测频谱漏洞的一种方法。在CSS中,当CR网络中的单元采用电池供电时,能源变得非常宝贵。因此,有效利用它们的能量变得非常重要。本文阐述了AND、OR、Majority等硬融合技术和平方律选择(SLS)、平方律组合(SLC)等软融合技术,并计算了使EE最大化的融合规则阈值。结果表明,对于节能CSS,多数融合优于其他融合技术。与SLS聚变相比,大多数聚变的EE高4.4%,在传感时间等于2ms时,最大EE为3.8 Mbits/Hz/焦耳。
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引用次数: 7
Performance Estimation of Amorphouss-IGZO Based Thin Film Transistor 非晶igzo薄膜晶体管的性能评估
Pub Date : 2018-12-01 DOI: 10.1109/ICACAT.2018.8933640
S. K. Dargar, V. Srivastava
Among the high field mobility materials, amorphous-InGaZnO (α-IGZO) is very prominent for their application as a channel material in Thin Film Transistors (TFTs). Electrical parameters for α-IGZO TFT are retrieved from the simulation results and the extraction of the switching parameters as threshold voltage, field effect mobility, subthreshold slope, and current ratio (ION/IOFF) have been reported in this paper. The results display large field effect mobility (μFE) 12.27 to 13.3 cm2/Vs ranging threshold voltage (Vth) 1.03 to 1.27 V, Subthreshold Swing (SS) 23.82 to 21.78 mV/decade and significant ON-OFF current ratio (ION/IOFF) 3.8 × 104 to 1.7×105. The reported characteristics from the simulation results demonstrated superior electrical parameters due to α-IGZO channel and shows that it can provide rapid switching, better resolution in flat-panel, and OLED displays.
在高场迁移率材料中,非晶ingazno (α-IGZO)作为通道材料在薄膜晶体管(tft)中的应用非常突出。本文从仿真结果中提取了α-IGZO TFT的电学参数,并报道了阈值电压、场效应迁移率、亚阈值斜率和电流比(ION/IOFF)等开关参数的提取。结果表明:大场效应迁移率(μFE)为12.27 ~ 13.3 cm2/Vs,阈值电压(Vth)为1.03 ~ 1.27 V,亚阈值摆幅(SS)为23.82 ~ 21.78 mV/decade,通断电流比(ION/IOFF)为3.8 × 104 ~ 1.7×105。仿真结果表明,α-IGZO通道具有优越的电学参数,可以在平板和OLED显示器上提供快速切换和更好的分辨率。
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引用次数: 0
An Ontology Development For University 面向大学的本体开发
Pub Date : 2018-12-01 DOI: 10.1109/ICACAT.2018.8933803
Shubhi Shrivastava, Iti Mathur, Nisheeth Joshi
Web is the very fastest resource to search any kind of information. With the development of semantic web, the result of search has become more informed. Ontologies are the integral part of semantic web. Ontology is a knowledge representation system because of its distribution and sharing of information features. With the Ontologies it can focus on the main concepts and its relation rather than information. Protégé is the most popular and widely used tool for developing Ontology. Here it is going to use this tool for constructing university ontology. In this paper it shall discuss the development, verification and validation of ontology in university domain.
网络是搜索任何类型信息的最快的资源。随着语义网的发展,搜索结果的信息量越来越大。本体是语义网的重要组成部分。本体是一种知识表示系统,具有信息分布和共享的特点。有了本体,它可以关注主要概念及其关系,而不是信息。protp是开发本体最流行和最广泛使用的工具。本文将利用该工具构建大学本体。本文将对本体在大学领域的发展、验证和验证进行探讨。
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引用次数: 3
Effect of Sintering on Time Domain Response of CaTiO3 Nano Ceramics 烧结对CaTiO3纳米陶瓷时域响应的影响
Pub Date : 2018-12-01 DOI: 10.1109/ICACAT.2018.8933532
Subhanarayan Sahoo
High-energy ball milling(HEBM) used for synthesize nano crystalline Calcium Titanate, CaTiO3 (CT) ceramic. X-ray diffraction(XRD), impedance and time domain analysis applied for characterization. Effect of grain conduction observed from complex impedance spectrum in the Nyquist plot by the appearance of one semi-circular arc. Various time response parameters have been calculated. Green pellets in disk shaped sintered at 1000°C, 1100°C and 1200°C to study the effect of sintering on time response. Time domain response obtained by MATLAB programming of equivalent circuit parameters got from cole-cole plot of respective samples using partial fraction and inverse Laplace transform method. Potential of nano CaTiO3 as faster sensitive material for electrical and electronic device applications proven by the study.
高能球磨(HEBM)用于合成纳米晶钛酸钙CaTiO3 (CT)陶瓷。采用x射线衍射(XRD)、阻抗和时域分析进行表征。从奈奎斯特图的复杂阻抗谱中观察到一个半圆弧的出现对晶粒传导的影响。计算了各种时间响应参数。在1000℃、1100℃和1200℃下烧结成圆盘状的绿色球团,研究烧结对时间响应的影响。利用部分分式和拉普拉斯逆变换方法对各样本的cole-cole图得到的等效电路参数进行MATLAB编程得到时域响应。该研究证明了纳米CaTiO3作为电气和电子设备应用中更快敏感材料的潜力。
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引用次数: 0
Bumble Bees Mating Optimization Algorithm for Economic Load Dispatch with Pollution 污染条件下经济负荷调度的大黄蜂交配优化算法
Pub Date : 2018-12-01 DOI: 10.1109/ICACAT.2018.8933681
Nagendra Singh, Ritesh Tirole
A new nature inspired algorithm, that simulates the mating behavior of the bumble bees, the Bumble Bees Mating Optimization (BBMO) algorithm, is proposed in this work for optimization of economic load dispatch. Economic dispatch is a method to evaluate the performance of the generating units to fulfill the load demand on minimum fuel cost. The proposed method bumble bees mating optimization (BBMO), work on different three modes namely the queen, the workers and the drones (males). For the evaluation of performance this study consider case study of forty generating unit data. The case study data is tested in various algorithms like Ant colony optimization, particle swarm optimization and genetic algorithm along with BBMO. The performance of all considered algorithm in this work is compared and it is found that minimum operating cost of the forty generating unit system is evaluated by BBMO. Convergence rate of BBMO is also very fast as compared to other considered methods.
本文提出了一种模拟大黄蜂交配行为的自然启发算法——大黄蜂交配优化算法(BBMO),用于经济负荷调度的优化。经济调度是评价发电机组在最小燃料成本下满足负荷需求的性能的一种方法。提出的大黄蜂交配优化(BBMO)方法,适用于蜂王、工蜂和雄蜂三种不同的交配模式。为了进行性能评价,本研究以40个发电机组数据为例进行了研究。案例研究数据在蚁群优化、粒子群优化、遗传算法以及BBMO等多种算法中进行了测试。通过对所考虑算法的性能进行比较,发现BBMO可以对40台发电机组系统的最小运行成本进行评估。与其他考虑的方法相比,BBMO的收敛速度也非常快。
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引用次数: 1
Comparing Physiological Feature Selection Methods for Emotion Recognition 情绪识别的生理特征选择方法比较
Pub Date : 2018-12-01 DOI: 10.1109/ICACAT.2018.8933599
K. Kaushal, Mahesh Pawar, Sachin Goyal, Ratish Agrawal
Human-computer interactions result in psychological effects on human behavior. The analysis of the human behavior can be done using physiological data of a user in intense emotional states. A user may have intense emotions, which could make the user more nervous, sad or aggressive. This paper shows how physiological data can be used to analyze a user’s emotional state and summarizes the findings of using different feature selection and classification techniques to learn the user’s emotional states. The general flow of this approach is to record physiological signals from a person, extract features and feed them to a machine learning algorithm. This algorithm will then predict the user’s emotional state. The outcome will be helpful to analyze and understand how to train the models with the given dataset. Results of this study can be utilized for future research and applications for mitigating the effects of the content on user’s emotions.
人机交互会对人的行为产生心理影响。人类行为的分析可以通过使用用户在强烈情绪状态下的生理数据来完成。用户可能会有强烈的情绪,这可能会使用户更加紧张、悲伤或好斗。本文展示了如何使用生理数据来分析用户的情绪状态,并总结了使用不同的特征选择和分类技术来学习用户情绪状态的结果。这种方法的一般流程是记录一个人的生理信号,提取特征并将其输入机器学习算法。该算法将预测用户的情绪状态。结果将有助于分析和理解如何使用给定的数据集训练模型。本研究的结果可用于未来的研究和应用,以减轻内容对用户情绪的影响。
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引用次数: 0
Cascaded Gradient Sequence for LTE System to Reduce Peak Power LTE系统的级联梯度序列降低峰值功率
Pub Date : 2018-12-01 DOI: 10.1109/ICACAT.2018.8933602
Amit Shivhare, Manish Patidar, Ravi Kumar
This article provides an assessment of combinational technique for maximum power reduction in the transmitter of long-term evolution (LTE). An intelligent combination has been presented using constellation extension and scrambling technique in the Orthogonal Frequency Division Multiplexing (OFDM) structure. The principle of this arrangement approach is to apply approximate gradient project (AGP) and partial transmit sequence (PTS) on the OFDM subcarrier. The simulation results show that the proposed approach reduce the PAPR as compared to traditional techniques and maintain the bit error rate (BER) performance of the system especially at low signal to noise ratio (SNR).
本文对长期演进(LTE)发射机中最大功率降低的组合技术进行了评估。在正交频分复用(OFDM)结构中,利用星座扩展和置乱技术实现了一种智能组合。这种排列方法的原理是在OFDM子载波上应用近似梯度投影(AGP)和部分发射序列(PTS)。仿真结果表明,与传统方法相比,该方法降低了系统的PAPR,并保持了系统在低信噪比下的误码率性能。
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引用次数: 0
Protecting Data Storage on Cloud to Enhance Security Level and Processing of the Data by using Hadoop 利用Hadoop保护云上的数据存储,提高数据的安全级别和处理能力
Pub Date : 2018-12-01 DOI: 10.1109/ICACAT.2018.8933675
S. Saxena, A. Shrivastava, A. Saxena, M. Manoria
Cloud computing is the modern technology, that facilitates to the user various resources, data and files to access from anywhere that a network is available, it is today’s modern computing where we distribute our resources and software from one place to another, but still the security of the data is a major problem in the cloud. However, there is need of processing a huge number of data and maintained the security over cloud. In this research we proposed a software framework (hadoop) with the cloud which helps us to process the huge number of data by using map-reduce model. To add security we use Kerberos authentication protocol which helps us to enhance security level over the cloud and also it is used to provide authentication to the users. We analyze and compare our technique with existing techniques, the results shows that our technique is much more secure and provide user authentication.
云计算是一种现代技术,它方便用户从任何地方访问网络可用的各种资源、数据和文件,这是今天的现代计算,我们将资源和软件从一个地方分发到另一个地方,但数据的安全性仍然是云中的一个主要问题。但是,需要处理大量的数据并维护云上的安全性。在本研究中,我们提出了一个基于云的软件框架(hadoop),利用map-reduce模型帮助我们处理海量数据。为了增加安全性,我们使用Kerberos身份验证协议,它可以帮助我们提高云上的安全级别,并且还用于向用户提供身份验证。通过与现有技术的对比分析,结果表明该技术具有更高的安全性,并提供了用户身份验证。
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引用次数: 1
Feature Reduction and Selection Based Optimization for Hybrid Intrusion Detection System Using PGO followed by SVM 基于特征约简和选择的PGO - SVM混合入侵检测系统优化
Pub Date : 2018-12-01 DOI: 10.1109/ICACAT.2018.8933651
S. Sagar, A. Shrivastava, Chetan Gupta
The requisition or insistence of internet (web) connectivity i.e. wireless network like WSN, MANET, cellular network, broadband increases day by day. So it is obvious that increase demand of connectivity increase the problem also i.e. safety and security. In this paper discusses the security issue or problem on connectivity network generally define as the network intrusion (malicious activity) finding system. This system has to be used for secure or protect the information data from any unwanted activities. In this paper presents the feature reduction and selection based on an optimization mechanism which followed by supervised learning classifier. This paper introduce the hybrid intrusion detection system using supervised classifier i.e. SVM followed by the optimization mechanism i.e. PGO. Every IDS system needs reduce feature data set attributes to perform efficiently and smoothly that has to be major issue for any NIDS. The hybrid optimization mechanism provide the optimal solution, plant growth optimization mechanism inspired the natural tree growth process, here make this an artificial plant growth process and apply for data set attributes and set similar condition. That optimization method provide the best fitness value for branches and leaf for an artificial plant, these branches or leaf fit for artificial plant growth or not. According to these fitness values data set attributes further classified into intruder class. In this paper present mechanism or system use NSL-KDD data set (i.e. basically intruder class attribute data sets contain DOS, PROBE, R2L and U2R intruder class) for evaluation and comparing the mechanism performance in term of accuracy and Kappa. This hybrid mechanism based on optimization decreased the false alarm rate of the system and enhance the performance.
互联网(web)连接的需求或坚持,即无线网络,如WSN, MANET,蜂窝网络,宽带日益增加。因此,很明显,连接需求的增加也增加了安全问题。本文讨论了连接网络的安全问题,一般将其定义为网络入侵(恶意活动)发现系统。该系统必须用于保护或保护信息数据免受任何不必要的活动。本文提出了一种基于优化机制的特征约简和选择,然后采用监督学习分类器。本文介绍了一种基于监督分类器(SVM)和优化机制(PGO)的混合入侵检测系统。每个入侵检测系统都需要减少特征数据集属性,以有效和平稳地执行,这是任何入侵检测系统的主要问题。混合优化机制提供了最优解,植物生长优化机制启发了自然树木的生长过程,这里使这一人工植物生长过程应用于数据集属性和设置相似的条件。该优化方法为人工植物的枝叶提供最佳适应度值,这些枝叶是否适合人工植物生长。根据这些适应度值将数据集属性进一步划分为入侵者类。本文的机制或系统使用NSL-KDD数据集(即入侵者类属性数据集基本上包含DOS、PROBE、R2L和U2R入侵者类)对机制性能的准确性和Kappa进行评估和比较。这种基于优化的混合机制降低了系统的虚警率,提高了系统的性能。
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引用次数: 1
期刊
2018 International Conference on Advanced Computation and Telecommunication (ICACAT)
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