Segmentation of anatomical regions is the fundamental problem in medical image analysis. The watershed algorithm is used for the segmentation of anatomical regions and it is computationally simple. The active contour algorithm is used to extract the tumor region in the segmented image, but it suffers from computational complexity and it is insensitive to noise. The proposed method combines watershed algorithm with active contour algorithm to reduce the computational complexity and to improve the insensitiveness to noise. The real brain MR image is first segmented using watershed segmentation and then edges produced will be the initial contour of active contour algorithm. The proposed method is superior in terms of capture range, concave tumor region extraction, segmentation accuracy and sensitivity to noise.
{"title":"A Mixed Model Based on Watershed and Active Contour Algorithms for Brain Tumor Segmentation","authors":"S. Bhat, Sanjeev Kunte R.","doi":"10.1109/ARTCOM.2010.13","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.13","url":null,"abstract":"Segmentation of anatomical regions is the fundamental problem in medical image analysis. The watershed algorithm is used for the segmentation of anatomical regions and it is computationally simple. The active contour algorithm is used to extract the tumor region in the segmented image, but it suffers from computational complexity and it is insensitive to noise. The proposed method combines watershed algorithm with active contour algorithm to reduce the computational complexity and to improve the insensitiveness to noise. The real brain MR image is first segmented using watershed segmentation and then edges produced will be the initial contour of active contour algorithm. The proposed method is superior in terms of capture range, concave tumor region extraction, segmentation accuracy and sensitivity to noise.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"38 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132810823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The sign language recognition is the most popular research area involving computer vision, pattern recognition and image processing. It enhances communication capabilities of the mute person. In this paper, we present an object based key frame selection., Hausdorff distance, Forward Algorithm and Euclidean distance are used for shape similarity for hand gesture recognition. We proposed use to the hidden markov model and nonlinear time alignment model with key frame selection facility and gesture trajectory features for hand gesture recognition. Experimental results demonstrate the effectiveness of our proposed scheme for recognizing American Sign Language.
{"title":"Object Based Key Frame Selection for Hand Gesture Recognition","authors":"Ketki P. Kshirsagar, D. Doye","doi":"10.1109/ARTCOM.2010.80","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.80","url":null,"abstract":"The sign language recognition is the most popular research area involving computer vision, pattern recognition and image processing. It enhances communication capabilities of the mute person. In this paper, we present an object based key frame selection., Hausdorff distance, Forward Algorithm and Euclidean distance are used for shape similarity for hand gesture recognition. We proposed use to the hidden markov model and nonlinear time alignment model with key frame selection facility and gesture trajectory features for hand gesture recognition. Experimental results demonstrate the effectiveness of our proposed scheme for recognizing American Sign Language.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130141922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stock market prediction is of great interest to stock traders and applied researchers. Main issues in developing a fully automated stock market prediction system are: feature extraction from the stock market data, feature selection for highest prediction accuracy, the dimensionality reduction of the selected feature set and the accuracy and robustness of the prediction system. In this paper, an automated decision tree-adaptive neuro-fuzzy hybrid automated stock market trend prediction system is proposed. The proposed system uses technical analysis (traditionally used by stock traders) for feature extraction and decision tree for feature selection. Selected features are then subjected to dimensionality reduction and the reduced dataset is then applied to the adaptive neuro-fuzzy system for the next-day stock market trend prediction. The proposed system is tested on four major international stock markets. The results show that the proposed hybrid system produces much higher accuracy when compared to stand-alone decision tree based system and ANFIS based system without feature selection and dimensionality reduction.
{"title":"A Stock Market Trend Prediction System Using a Hybrid Decision Tree-Neuro-Fuzzy System","authors":"B. Nair, N. M. Dharini, V. Mohandas","doi":"10.1109/ARTCOM.2010.75","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.75","url":null,"abstract":"Stock market prediction is of great interest to stock traders and applied researchers. Main issues in developing a fully automated stock market prediction system are: feature extraction from the stock market data, feature selection for highest prediction accuracy, the dimensionality reduction of the selected feature set and the accuracy and robustness of the prediction system. In this paper, an automated decision tree-adaptive neuro-fuzzy hybrid automated stock market trend prediction system is proposed. The proposed system uses technical analysis (traditionally used by stock traders) for feature extraction and decision tree for feature selection. Selected features are then subjected to dimensionality reduction and the reduced dataset is then applied to the adaptive neuro-fuzzy system for the next-day stock market trend prediction. The proposed system is tested on four major international stock markets. The results show that the proposed hybrid system produces much higher accuracy when compared to stand-alone decision tree based system and ANFIS based system without feature selection and dimensionality reduction.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133661853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The wide scale deployment of Internet combined with several advancements in hardware and software technologies created opportunities for several Internet based applications such as Voice Over IP (VoIP) that involves the delivery of voice, video and data to the end user. SIP, the Session Initiation Protocol, is a signaling protocol for Internet conferencing, telephony, presence, events notification and instant messaging. The SIP Proxy Server is a call control software package that enables service providers to build scalable, reliable Voice over IP networks today and it provides a full array of call routing capabilities to maximize network performance in both small and large packet voice networks. The SIP Proxy Server can perform a digest authentication of SIP Register, invite requests, and can encrypt SIP requests and responses using Transport Layer Security (TLS). For secure communication, user authentication, confidentiality and integrity of signaling message and SIP session establishment are essential. TLS is used for the secured SIP signaling and Secure Real Time Protocol (SRTP) for secured SIP session establishment. This paper is focused on evaluating the performance impacts of SIP proxy servers when secured (TLS) over non-secured transport protocols (TCP/UDP) are used to transport SIP messages. Several experiments were conducted in a lab environment to evaluate key performance parameters such as Call setup time, Mean number of calls, Memory utilization, CPU utilization and queue size.
互联网的大规模部署与硬件和软件技术的一些进步相结合，为几种基于互联网的应用创造了机会，例如IP语音(VoIP)，它涉及向最终用户传输语音、视频和数据。SIP，即会话发起协议，是一种用于互联网会议、电话、到场、事件通知和即时消息传递的信令协议。SIP代理服务器是一个呼叫控制软件包，使服务提供商能够构建可扩展的、可靠的IP语音网络，它提供了完整的呼叫路由功能，以最大限度地提高小型和大型分组语音网络的网络性能。SIP代理服务器可以执行SIP注册的摘要身份验证，邀请请求，并可以使用传输层安全(TLS)加密SIP请求和响应。为了实现安全通信，用户认证、信令消息的保密性和完整性以及SIP会话的建立是必不可少的。安全的SIP信令采用TLS，建立安全的SIP会话采用SRTP (Secure Real Time Protocol)。本文的重点是评估当使用安全(TLS)而不是非安全传输协议(TCP/UDP)来传输SIP消息时SIP代理服务器的性能影响。在实验室环境中进行了几个实验，以评估关键性能参数，如呼叫建立时间，平均呼叫数，内存利用率，CPU利用率和队列大小。
{"title":"Comparative Study of Secure vs. Non-secure Transport Protocols on the SIP Proxy Server Performance: An Experimental Approach","authors":"Sureshkumar V. Subramanian, R. Dutta","doi":"10.1109/ARTCOM.2010.90","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.90","url":null,"abstract":"The wide scale deployment of Internet combined with several advancements in hardware and software technologies created opportunities for several Internet based applications such as Voice Over IP (VoIP) that involves the delivery of voice, video and data to the end user. SIP, the Session Initiation Protocol, is a signaling protocol for Internet conferencing, telephony, presence, events notification and instant messaging. The SIP Proxy Server is a call control software package that enables service providers to build scalable, reliable Voice over IP networks today and it provides a full array of call routing capabilities to maximize network performance in both small and large packet voice networks. The SIP Proxy Server can perform a digest authentication of SIP Register, invite requests, and can encrypt SIP requests and responses using Transport Layer Security (TLS). For secure communication, user authentication, confidentiality and integrity of signaling message and SIP session establishment are essential. TLS is used for the secured SIP signaling and Secure Real Time Protocol (SRTP) for secured SIP session establishment. This paper is focused on evaluating the performance impacts of SIP proxy servers when secured (TLS) over non-secured transport protocols (TCP/UDP) are used to transport SIP messages. Several experiments were conducted in a lab environment to evaluate key performance parameters such as Call setup time, Mean number of calls, Memory utilization, CPU utilization and queue size.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116261057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years ECG signal plays an important role in the primary diagnosis and survival analysis of heart diseases. The presence of parasite interference signals could cause serious problems in the registration of the ECG signals. In recent years wavelet thresholding becomes most preferred technique for the removal of these noises. However, the critical problem is computation of proper threshold value. A number of threshold estimators are proposed in the literature. In this paper, we have evaluated the performance of some of the most promising threshold estimators for the denoising of ECG signal.
{"title":"Performance Comparision of Wavelet Threshold Estimators for ECG Signal Denoising","authors":"Z. Jaffery, K. Ahmad, A. Afroz","doi":"10.1109/ARTCOM.2010.86","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.86","url":null,"abstract":"In recent years ECG signal plays an important role in the primary diagnosis and survival analysis of heart diseases. The presence of parasite interference signals could cause serious problems in the registration of the ECG signals. In recent years wavelet thresholding becomes most preferred technique for the removal of these noises. However, the critical problem is computation of proper threshold value. A number of threshold estimators are proposed in the literature. In this paper, we have evaluated the performance of some of the most promising threshold estimators for the denoising of ECG signal.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126313197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Privacy preservation is an important area of research in recent years. Due to the advancement of technology, enormous digital data is being generated at various locations. There are many applications such as market basket analysis, medical research etc where the global results computation places a significant role. The collaborating parties are generally interested in finding the global results for their integrated data without revealing the personal details to the other party. There are few proposals which talk about privacy preservation of vertical partitioned distributed database. Our proposed novel approach preserves the privacy of the distributed databases, using Naïve Bayes Classification along with the trusted third party and secure multiparty computation.
{"title":"Privacy Preservation Naïve Bayes Classification for a Vertically Distribution Scenario Using Trusted Third Party","authors":"Keshavamurthy B.N., Mitesh Sharma, Durga Toshniwal","doi":"10.1109/ARTCOM.2010.36","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.36","url":null,"abstract":"Privacy preservation is an important area of research in recent years. Due to the advancement of technology, enormous digital data is being generated at various locations. There are many applications such as market basket analysis, medical research etc where the global results computation places a significant role. The collaborating parties are generally interested in finding the global results for their integrated data without revealing the personal details to the other party. There are few proposals which talk about privacy preservation of vertical partitioned distributed database. Our proposed novel approach preserves the privacy of the distributed databases, using Naïve Bayes Classification along with the trusted third party and secure multiparty computation.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115445643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates the steady state performance of STATCOM based on 6 pulse voltage sourced converter by which the stator flux oriented vector control of terminal voltage for SEIG is obtained. To increase the transient stability conditions of the generator a STATCOM is introduced as the active VAR supporter. The paper qualifies and quantifies the improved short term voltage and rotor stability performance obtained when a STATCOM is introduced during different types of failure events in the connected power system.
{"title":"Dynamic Response of Wind Power Genarators Using Statcom","authors":"M. Hussaini, R. Anita","doi":"10.1109/ARTCOM.2010.69","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.69","url":null,"abstract":"This paper investigates the steady state performance of STATCOM based on 6 pulse voltage sourced converter by which the stator flux oriented vector control of terminal voltage for SEIG is obtained. To increase the transient stability conditions of the generator a STATCOM is introduced as the active VAR supporter. The paper qualifies and quantifies the improved short term voltage and rotor stability performance obtained when a STATCOM is introduced during different types of failure events in the connected power system.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132230578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：