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International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)最新文献

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Characterization of skin lesions 皮肤病变的特征
K. Madhankumar, P. Kumar
Malignant melanoma is the deadliest form among all skin cancers. Fortunately, if detected early, even malignant melanoma may be treated successfully. In this paper, a new intelligent method of classifying benign and malignant melanoma lesions is used. As the first step of the image analysis, preprocessing techniques are used to remove noise and undesired structures from the images using filter such as median filtering. Segmentation is one of the important steps in cancer automatic detection, because it can greatly affect on the results of detection. In the second step, a simple thresholding method is used to segment and localize the lesion, a boundary tracing algorithm is also implemented to validate the segmentation. In the third step, the different features are extracted from a segmented image and classified by using Stolz algorithm.
恶性黑色素瘤是所有皮肤癌中最致命的一种。幸运的是,如果及早发现,即使是恶性黑色素瘤也可能成功治疗。本文提出了一种新的黑色素瘤良恶性病变智能分类方法。作为图像分析的第一步,使用预处理技术,通过中值滤波等滤波器去除图像中的噪声和不需要的结构。分割是肿瘤自动检测的重要步骤之一,对检测结果有很大的影响。第二步,采用简单的阈值分割方法对病灶进行分割和定位,并采用边界跟踪算法对分割结果进行验证。第三步,从分割后的图像中提取不同的特征,并使用Stolz算法进行分类。
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引用次数: 17
A high throughput sort free VLSI architecture for wireless applications 用于无线应用的高吞吐量免排序VLSI架构
S. Soundharya, G. Prakash
For high data rate Multiple Input Multiple Output technology is used in wireless communications. The use of multiple antennas at both transmitter and receiver (MIMO) significantly increases the capacity and spectral efficiency of wireless systems. This paper presents a Field Programmable Gate Array (FPGA) implementation for a 4 × 4 breadth first K-best MIMO decoder using a 64 Quadrature Amplitude Modulation (QAM) scheme. A novel sort free approach to path extension, as well as, quantized metrics result in a high throughput, low power and area. Finally, VLSI architectural tradeoffs are explored for a synthesized using synopsys the power analysis, throughput analysis in 120 nm technology. The power needed is 20.0025 μW.
多输入多输出技术在无线通信中应用于高数据速率。在发送端和接收端同时使用多天线(MIMO)显著提高了无线系统的容量和频谱效率。本文提出了一种采用64正交调幅(QAM)方案实现4 × 4宽度优先k -最佳MIMO解码器的现场可编程门阵列(FPGA)。一种新的无排序的路径扩展方法,以及量化的指标,导致高吞吐量,低功耗和面积。最后,探讨了VLSI架构的权衡,以综合使用synopsys的功率分析,吞吐量分析在120纳米技术。所需功率为20.0025 μW。
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引用次数: 0
An analysis on the impact of fluoride in human health (dental) using clustering data mining technique 利用聚类数据挖掘技术分析氟化物对人体健康(牙齿)的影响
T. Balasubramanian, R. Umarani
Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Traditional data analysis methods often involve manual work and interpretation of data which is slow, expensive and highly subjective Data Mining, popularly called as knowledge discovery in large data, enables firms and organizations to make calculated decisions by assembling, accumulating, analyzing and accessing corporate data. It uses variety of tools like query and reporting tools, analytical processing tools, and Decision Support System. [1][2] This article explores data mining techniques in health care. In particular, it discusses data mining and its application in areas where people are affected severely by using the under-ground drinking water which consist of high levels of fluoride in Krishnagiri District, Tamil Nadu State, India. This paper identifies the risk factors associated with the high level of fluoride content in water, using clustering algorithms and finds meaningful hidden patterns which give meaningful decision making to this socio-economic real world health hazard.
数据挖掘是通过使用统计学、机器学习和数据库管理系统领域的算法和技术从大型数据集中提取信息的过程。传统的数据分析方法通常涉及人工工作和对数据的解释,这是缓慢、昂贵和高度主观的。数据挖掘通常被称为大数据中的知识发现,它使公司和组织能够通过收集、积累、分析和访问企业数据来做出计算决策。它使用各种工具,如查询和报告工具、分析处理工具和决策支持系统。[1][2]本文探讨了医疗保健中的数据挖掘技术。报告特别讨论了数据挖掘及其在印度泰米尔纳德邦克里希纳吉里地区因使用含高氟化物的地下饮用水而受到严重影响的地区的应用。本文使用聚类算法确定了与水中高氟化物含量相关的风险因素,并找到了有意义的隐藏模式,为这一社会经济现实世界的健康危害提供了有意义的决策。
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引用次数: 27
An improved security mechanism for high-throughput multicast routing in wireless mesh networks against Sybil attack 一种改进的无线网状网络高吞吐量多播路由抗Sybil攻击的安全机制
P. Anitha, G. Pavithra, P. S. Periasamy
Wireless Mesh Networks (WMNs) have become one of the important domains in wireless communications. They comprise of a number of static wireless routers which form an access network for end users to IP-based services. Unlike conventional WLAN deployments, wireless mesh networks offer multihop routing, facilitating an easy and cost-effective deployment. In this paper, an efficient and secure multicast routing on such wireless mesh networks is concentrated. This paper identifies novel attacks against high throughput multicast protocols in wireless mesh networks through S-ODMRP protocol. Recently, Sybil attack is observed to be the most harmful attack in WMNs, where a node illegitimately claims multiple identities. This paper systematically analyzes the threat posed by the Sybil attack to WMN. The Sybil attack is encountered by the defense mechanism called Random Key Predistribution technique (RKP). The performance of the proposed approach which integrates the S-ODMRP and RKP is evaluated using the throughput performance metric. It is observed from the experimental results that the proposed approach provides good security against Sybil attack with very high throughput.
无线网状网络(WMNs)已成为无线通信的重要领域之一。它们由许多静态无线路由器组成,这些路由器形成一个接入网,供最终用户使用基于ip的服务。与传统的WLAN部署不同,无线网状网络提供多跳路由,促进了简单且经济高效的部署。本文主要研究在这种无线网状网络中高效、安全的组播路由。本文通过S-ODMRP协议识别了针对无线网状网络中高吞吐量多播协议的新型攻击。近年来,Sybil攻击被认为是wmn中危害最大的攻击,即一个节点非法声明多个身份。本文系统地分析了Sybil攻击对WMN构成的威胁。Sybil攻击的防御机制被称为随机密钥预分发技术(RKP)。采用吞吐量性能指标对集成了S-ODMRP和RKP的方法的性能进行了评估。实验结果表明,该方法对Sybil攻击具有良好的安全性和较高的吞吐量。
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引用次数: 5
Implementation of VLSI-oriented FELICS algorithm using Pseudo Dual-Port RAM 伪双端口RAM实现面向vlsi的FELICS算法
M. Rejusha, K. Jayanthi
This paper presents a fast, efficient, lossless image compression algorithm named FELICS. This consists of two techniques named simplified adjusted binary code and GOLOMB-Rice code which provide lossless compression for high throughput applications. Two-level parallelism with four-stage pipelining is adopted. Pseudo Dual-Port RAM is used which improves the processing speed and decreases area and power consumption. The proposed architecture can be used for high definition display applications.
本文提出了一种快速、高效、无损的图像压缩算法FELICS。这包括简化调整二进制码和GOLOMB-Rice码两种技术,它们为高吞吐量应用提供无损压缩。采用两级并行和四级流水线。采用伪双端口RAM,提高了处理速度,减少了面积和功耗。所提出的架构可用于高清晰度显示应用。
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引用次数: 1
An augmented prerequisite concept relation map design to improve adaptivity in e-learning 一种增强前提概念关系图设计以提高电子学习的适应性
R. Kavitha, A. Vijaya, D. Saraswathi
Due to the advancement in information and communication technology and vast varied learner group, e-learning has become popular. For achieving the adaptivity in learning, predefined concept map is used to provide proper guidance. In most of the researches, weight of concepts in each learning item is not properly considered. In this study, a three phase prerequisite concept map formulation for adaptivity is proposed. This approach is a most efficient one, since the first phase discards all the unrelated items which may distract the further analysis. Here, Norm-referencing in Item Analysis approach is used to find the item discrimination for elimination of irrelevant items. The second phase, computes all the grade association rules. The weight of concept in each learning item is considered and prerequisite concept sets are found which is not having any redundancy and cyclic in its map, thereby facilitating the next step of procedure. The final phase constructs the concept map with maximum confidence in a capable manner. Finally, the Prerequisite concept map can be used in tutoring system, thereby enhancing the adaptivity in e-learning.
由于信息通信技术的进步和学习者群体的多样化,电子学习已经成为流行。为了实现学习的适应性,使用预定义的概念图来提供适当的指导。在大多数研究中,没有考虑到每个学习项目中概念的权重。在本研究中,提出了一个三个阶段的自适应前提概念图公式。这是一种最有效的方法,因为第一阶段抛弃了所有不相关的项目,这些项目可能会分散进一步的分析。本文采用项目分析中的规范引用方法来寻找项目歧视,以消除不相关的项目。第二阶段,计算所有等级关联规则。考虑每个学习项中概念的权重,找到在其映射中没有任何冗余和循环的前提概念集,从而便于下一步的过程。最后阶段以最大的信心和能力构建概念图。最后,将前提概念图应用到辅导系统中,从而增强网络学习的适应性。
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引用次数: 12
Intelligence technique to solve combined economic and emission dispatch 智能技术解决经济与排放相结合的调度
R. Gopalakrishnan, A. Krishnan
A power system operation at minimum cost is no longer the only measure for electrical power dispatch. Combined Economic Emission Dispatch (CEED) problem is attained by considering both the economy and emission objectives with necessary constraints. The stability of the power system is also considered as an important factor in the performance of the power system. Several optimization techniques are slow for such complex optimization tasks and are not suitable for on-line use. This paper presents an effective optimization algorithm, for solving security constrained combined economic emission dispatch problem. Also, the power system stability plays an important role in power system. Power system stability criteria are also considered in this paper for better performance of the entire power system. In this paper, an efficient optimization technique called Modified Artificial Bee Colony Optimization is used to solve the CEED problem. The performance of the proposed approach is compared with the other optimization techniques. The experimental result shows that the proposed system results in better solution for CEED problem with the maintenance of system stability.
以最低成本运行电力系统已不再是电力调度的唯一标准。综合考虑经济目标和排放目标,并设置必要的约束条件,实现了经济排放调度问题。电力系统的稳定性也被认为是影响电力系统性能的重要因素。对于这种复杂的优化任务,一些优化技术是缓慢的,不适合在线使用。针对安全约束下的联合经济排放调度问题,提出了一种有效的优化算法。同时,电力系统的稳定性在电力系统中也起着重要的作用。为了提高整个电力系统的性能,本文还考虑了电力系统的稳定性准则。本文采用一种高效的优化技术——改进人工蜂群优化技术来解决CEED问题。将该方法的性能与其他优化技术进行了比较。实验结果表明,该系统在保证系统稳定性的前提下,较好地解决了CEED问题。
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引用次数: 10
A new enhanced technique for link farm detection 一种新的链路场检测增强技术
D. Saraswathi, A. V. Kathiravan, R. Kavitha
Search engine spam is a webpage that has been designed to artificially inflating its search engine ranking. Recently this search engine spam has been increased dramatically and creates problem to the search engine and the web surfer. It degrades the search engine's results, occupies more memory and consumes more time for creating indexes, and frustrates the user by giving irrelevant results. Search engines have tried many techniques to filter out these spam pages before they can appear on the query results page. Spammers intend to increase the PageRank of certain spam pages by creating a large number of links pointing to them. We have designed and develop a system, spamcity score that detects spam hosts or pages on the Web. The UK Web Spam UK 2007 data set has been used for experimentation. It is a public web spam dataset annotated at the level of hosts, for all results reported here. System uses the key features of popular link based algorithms to detect spam in improved manner. In this paper, various ways of creating spam pages, a collection of current methods that are being used to detect spam and a new approach to build a tool for improving link spam detection using spamcity score of term spam. This new approach uses SVMLight tool to detect the link spam which considers the link structure of Web and page contents. These statistical features are used to build a classifier that is tested over a large collection of Web link spam. The link farm can be identifying based on Web Graph, classification by using SVMLight Tool, Degree based measure, page Rank, Trust Rank, and Truncated PageRank. The spam classifier makes use of the Wordnet word database and SVMLight tool to classify web links as either spam or not spam. These features are not only related to quantitative data extracted from the Web pages, but also to qualitative properties, mainly of the page links.
搜索引擎垃圾邮件是一个网页,已被人为地夸大其搜索引擎排名。最近,这种搜索引擎垃圾邮件急剧增加,给搜索引擎和网络冲浪者带来了问题。它降低了搜索引擎的结果,占用了更多的内存,花费了更多的时间来创建索引,并且由于给出了不相关的结果而使用户感到沮丧。搜索引擎已经尝试了许多技术来过滤掉这些垃圾页面,以便它们能够出现在查询结果页面上。垃圾邮件发送者打算通过创建大量指向垃圾邮件页面的链接来提高某些垃圾邮件页面的PageRank。我们已经设计和开发了一个系统,垃圾邮件得分,检测垃圾主机或网页在网络上。英国网络垃圾邮件英国2007数据集已被用于实验。对于这里报告的所有结果,它是一个在主机级别标注的公共web垃圾邮件数据集。系统利用当前流行的基于链接的算法的主要特点,对垃圾邮件进行改进检测。本文介绍了创建垃圾邮件页面的各种方法,收集了当前用于检测垃圾邮件的方法,并提出了一种新的方法来构建一个工具,用于使用垃圾邮件术语的垃圾邮件得分来改进链接垃圾邮件检测。该方法使用SVMLight工具检测垃圾链接,该工具考虑了Web和页面内容的链接结构。这些统计特征用于构建一个分类器,该分类器将在大量的Web垃圾链接集合上进行测试。链接场可以基于Web Graph进行识别,使用SVMLight工具进行分类,基于程度的度量,页面排名,信任排名和截断的PageRank。垃圾邮件分类器使用Wordnet word数据库和SVMLight工具将web链接分类为垃圾邮件或非垃圾邮件。这些特性不仅与从Web页面中提取的定量数据有关,而且与定性属性有关,主要是页面链接。
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引用次数: 1
Double encryption based secure fuzzy vault construction using fingerprint biometric features 基于指纹生物特征的双重加密安全模糊保险库构建
R. Narayanan, S. Karthikeyan
Security has become one of the major concerns in the present scenario because of the increase in quantity of data and theft. Due to these reasons, an efficient security system is very much necessary for protecting the authorized properties. This leads to the usage of password, key, etc., for securing the system. This security system can be easily broken because the password and key can be easily lost by the user. Also, the users have to memorize the password and key for access to the system and sometimes the user may forget the password and key. This has forced the researchers for developing a better security system. Then, the usage of biometrics evolved to be better technique for security purpose as biometrics is unique for every individual. Mostly used biometrics features for security purpose are fingerprint, iris, retina, palm, face, etc. This paper focuses on using the fingerprint as biometrics for developing a security system. The security is enhanced in this paper by using double encryption technique by means of combining symmetric key and a symmetric key generation. Also, Reed and Solomon codes are used to provide tolerance for decryption. The experimental result shows that the proposed Fuzzy Vault construction results in proving better security.
由于数据量和盗窃数量的增加,安全性已成为当前场景中主要关注的问题之一。由于这些原因,一个有效的保安系统是非常必要的,以保护授权财产。这导致使用密码、密钥等来保护系统。这种安全系统很容易被破坏,因为密码和密钥很容易被用户丢失。此外,用户必须记住访问系统的密码和密钥,有时用户可能会忘记密码和密钥。这迫使研究人员开发更好的安全系统。然后,生物识别技术的使用演变为更好的安全技术,因为生物识别技术对每个人都是独一无二的。用于安全目的的生物特征主要有指纹、虹膜、视网膜、手掌、面部等。本文主要研究利用指纹作为生物识别技术来开发一种安全系统。本文采用对称密钥和对称密钥生成相结合的双重加密技术,提高了系统的安全性。此外,Reed和Solomon代码用于提供解密的容忍度。实验结果表明,所提出的模糊保险库结构具有较好的安全性。
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引用次数: 4
Performance evaluation of employees of an organization using formal concept analysis 运用形式化概念分析对组织员工进行绩效评估
C. Aswani Kumar, K. Sumangali
FCA is a mathematical framework that depicts knowledge derived from the data represented as formal context. The objective of this paper is to apply Formal Concept Analysis (FCA) to analyze the key performance areas (KPA) of faculty of an institute. While constructing the formal context we have considered the faculties as objects and their KPA as attributes. This context is processed using FCA and the knowledge derived is analyzed to measure the performance of the faculty.
FCA是一个数学框架,它描述了从表示为正式上下文的数据中获得的知识。本文的目的是应用形式概念分析(FCA)来分析学院教师的关键绩效领域(KPA)。在构建正式环境时,我们将院系视为对象,将其KPA视为属性。使用FCA对这一背景进行处理,并对所获得的知识进行分析,以衡量教师的绩效。
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引用次数: 18
期刊
International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)
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