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Research in Adaptive and Convergent Systems最新文献

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Concurrency control scheme for key-value stores based on InfiniBand 基于ib的键值存储并发控制方案
Research in Adaptive and Convergent Systems Pub Date : 2014-10-05 DOI: 10.1145/2663761.2664239
Joonhyouk Jang, Yookun Cho, Jinman Jung, Sanghee Yoon
{"title":"Concurrency control scheme for key-value stores based on InfiniBand","authors":"Joonhyouk Jang, Yookun Cho, Jinman Jung, Sanghee Yoon","doi":"10.1145/2663761.2664239","DOIUrl":"https://doi.org/10.1145/2663761.2664239","url":null,"abstract":"Using InfiniBand technologies, the performance of key-value stores can be greatly improved because of RDMA features and the ultra-low latency of InfiniBand. However, maximizing the benefits of InfiniBand for key-value stores is still challenging because of the data consistency problem between RDMAs and CPU-aware memory accesses. In this paper, we propose a concurrency control scheme to utilize the RDMA features of InfiniBand in key-value stores. The proposed scheme efficiently handles the race conditions among GET and PUT operations on the key-value store.","PeriodicalId":120340,"journal":{"name":"Research in Adaptive and Convergent Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121128183","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}
引用次数: 1
Shape based medical image retrieval method using irregularity chain code similarity 基于形状的不规则链码相似性医学图像检索方法
Research in Adaptive and Convergent Systems Pub Date : 2014-10-05 DOI: 10.1145/2663761.2664203
Byung K. Jung, Sung Y. Shin, Seong‐Ho Son, J. Pack
{"title":"Shape based medical image retrieval method using irregularity chain code similarity","authors":"Byung K. Jung, Sung Y. Shin, Seong‐Ho Son, J. Pack","doi":"10.1145/2663761.2664203","DOIUrl":"https://doi.org/10.1145/2663761.2664203","url":null,"abstract":"In this paper, we present a shape based image retrieval method based on chain code representing irregularity of an object. A distinctive chain code is introduced as a main extracted feature of the object. All objects used in this paper are binary object images extracted by well-known classification algorithm, Support Vector Machine (SVM). From these classified binary images, we propose a modified shape based image retrieval method with the unique chain code interpreting irregularity of object. Proposed method is experimented along with known shape based image retrieval method using characteristic point features. The experimental result shows that proposed method exceed matching rate that of conventional contour to centroid triangulation (CTCT) method showing proposed method has higher matching rate.","PeriodicalId":120340,"journal":{"name":"Research in Adaptive and Convergent Systems","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116000390","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}
引用次数: 1
A robust and efficient birthmark-based android application filtering system 一种鲁棒高效的基于胎记的android应用过滤系统
Research in Adaptive and Convergent Systems Pub Date : 2014-10-05 DOI: 10.1145/2663761.2664231
SeongWook Kang, Hyungjoon Shim, Seong-je Cho, Minkyu Park, Sangchul Han
{"title":"A robust and efficient birthmark-based android application filtering system","authors":"SeongWook Kang, Hyungjoon Shim, Seong-je Cho, Minkyu Park, Sangchul Han","doi":"10.1145/2663761.2664231","DOIUrl":"https://doi.org/10.1145/2663761.2664231","url":null,"abstract":"Since it is very easy to decompile and repackage Android applications (or apps), many paid apps in the official Android Market are exposed to software piracy such as illegal copy, license cracking, and illegal distribution. To address this problem, we can employ app filtering systems that can prevent OSP servers from distributing illegally copied or tampered apps. In this paper, we propose a birthmark-based Android app filtering system. The system extracts birthmarks from APK files, and compares the birthmarks to examine if a given APK file is actually identical to one of (paid) original apps, that is, the APK file is a duplicated or tampered one. The experimental results show that the system is efficient and robust in the sense that the birthmark size is very small and the tampered apps can be identified effectively.","PeriodicalId":120340,"journal":{"name":"Research in Adaptive and Convergent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129667981","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}
引用次数: 6
GPU-based matrix multiplication methods for social networks analysis 基于gpu的社会网络矩阵乘法分析方法
Research in Adaptive and Convergent Systems Pub Date : 2014-10-05 DOI: 10.1145/2663761.2664192
Yong-Yeon Jo, Sang-Wook Kim, Duck-Ho Bae
{"title":"GPU-based matrix multiplication methods for social networks analysis","authors":"Yong-Yeon Jo, Sang-Wook Kim, Duck-Ho Bae","doi":"10.1145/2663761.2664192","DOIUrl":"https://doi.org/10.1145/2663761.2664192","url":null,"abstract":"A matrix multiplication is a building block for social networks analysis. Recently, there have been various methods proposed for GPU-based matrix multiplications. NVIDIA, one of major manufacturers of GPUs, has also proposed various matrix multiplication methods based on GPUs. In this paper, we introduce the methods, and evaluate their performance via extensive experiments using synthetic and real-world datasets. Our results would help practitioners choose the best one for analyzing real-world social networks.","PeriodicalId":120340,"journal":{"name":"Research in Adaptive and Convergent Systems","volume":"51 2-4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120918039","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}
引用次数: 2
Visual tracking with multiple representative models based on sparse prototypes 基于稀疏原型的多代表性模型视觉跟踪
Research in Adaptive and Convergent Systems Pub Date : 2014-10-05 DOI: 10.1145/2663761.2663766
Deqian Fu, S. Jhang
{"title":"Visual tracking with multiple representative models based on sparse prototypes","authors":"Deqian Fu, S. Jhang","doi":"10.1145/2663761.2663766","DOIUrl":"https://doi.org/10.1145/2663761.2663766","url":null,"abstract":"Online visual tracking plays a critical role in research and application of computer vision, and it is still a challenging task to alleviate the possibility of drift. In this paper, a robust visual tracker is proposed with multiple representative appearance models based on sparse prototypes. Benefitting from the representation with sparse prototypes, the multiple representative appearance models maintain representative and discriminative features of the target appearance. The multiple models are triggered to recognize the target in challenging cases with an effective strategy, which is demonstrated by the extensive experiments.","PeriodicalId":120340,"journal":{"name":"Research in Adaptive and Convergent Systems","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114101112","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}
引用次数: 0
Implicit graphical password mutual authentication using mirror-image encryption 使用镜像加密的隐式图形密码相互认证
Research in Adaptive and Convergent Systems Pub Date : 2014-10-05 DOI: 10.1145/2663761.2664194
R. Goutham, Dae-Soo Kim, K. Yoo
{"title":"Implicit graphical password mutual authentication using mirror-image encryption","authors":"R. Goutham, Dae-Soo Kim, K. Yoo","doi":"10.1145/2663761.2664194","DOIUrl":"https://doi.org/10.1145/2663761.2664194","url":null,"abstract":"User authentication is the most fundamental decision in designing secure systems and to organize majority of the attacks. Though alpha-numeric password and biometric based authentication methods are the most popular methods till date, they have been exposed to numerous attacks. As an alternative solution, various graphical-based password authentication schemes have been proposed. The efficiency of a graphical password is evaluated by its intensity of security and usability. Regardless of being many existing methods most were unsuccessful to accomplish both features concurrently. In this paper, we propose recognition based mutual authentication method with mirror-image encryption technique, based on images and text. The goal of this paper is to emphasize the enhancements on security and usability of existing graphical password schemes. The proposed method is resistant to most of existing attacks such as shoulder-surfing, secret camera etc.","PeriodicalId":120340,"journal":{"name":"Research in Adaptive and Convergent Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124157216","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}
引用次数: 2
Metadata based combined approach for effective collaborative recommendation 基于元数据的有效协同推荐组合方法
Research in Adaptive and Convergent Systems Pub Date : 2014-10-05 DOI: 10.1145/2663761.2664189
K. Kim, Jun Yeop Lee, Y. Choi
{"title":"Metadata based combined approach for effective collaborative recommendation","authors":"K. Kim, Jun Yeop Lee, Y. Choi","doi":"10.1145/2663761.2664189","DOIUrl":"https://doi.org/10.1145/2663761.2664189","url":null,"abstract":"In this paper, we propose content-metadata based combined approach to effective collaborative recommendation. Our approach combines user-item rating scores and/or trust network information with content-metadata compensatively for boosting collaborative recommendation. In experiment, we identified that our approach could considerably improve recommendation performance when compared to existing collaborative recommendation methods.","PeriodicalId":120340,"journal":{"name":"Research in Adaptive and Convergent Systems","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134159428","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}
引用次数: 1
HILF: hybrid indoor locating framework HILF:混合室内定位框架
Research in Adaptive and Convergent Systems Pub Date : 2014-10-05 DOI: 10.1145/2663761.2664196
Daeho Kim, Taegyu Hwang, Sanghoon Choi, Ikhyun Cho, Jiman Hong
{"title":"HILF: hybrid indoor locating framework","authors":"Daeho Kim, Taegyu Hwang, Sanghoon Choi, Ikhyun Cho, Jiman Hong","doi":"10.1145/2663761.2664196","DOIUrl":"https://doi.org/10.1145/2663761.2664196","url":null,"abstract":"As smart devices with sensors have become increasingly common, several studies on indoor location tracking techniques used with smart devices have been conducted. However, current studies of indoor locating techniques possess weaknesses based on the type of resources these techniques employ. In this paper, we propose a hybrid indoor locating framework for tracking a device's current location by using step detection and Wi-Fi fingerprinting. The framework thus introduces a technique that combines the use of two resources.","PeriodicalId":120340,"journal":{"name":"Research in Adaptive and Convergent Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132756509","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}
引用次数: 0
Robust background subtraction via online robust PCA using image decomposition 基于图像分解的在线鲁棒PCA鲁棒背景减法
Research in Adaptive and Convergent Systems Pub Date : 2014-10-05 DOI: 10.1145/2663761.2664195
S. Javed, S. Oh, JunHyeok Heo, Soon Ki Jung
{"title":"Robust background subtraction via online robust PCA using image decomposition","authors":"S. Javed, S. Oh, JunHyeok Heo, Soon Ki Jung","doi":"10.1145/2663761.2664195","DOIUrl":"https://doi.org/10.1145/2663761.2664195","url":null,"abstract":"Accurate and efficient background subtraction is an important task in video surveillance system. The task becomes more critical when the background scene shows more variations, such as water surface, waving trees and lighting conditions, etc. Recently, Robust Principal Components Analysis (RPCA) shows a nice framework for moving object detection. The background sequence is modeled by a low-dimensional subspace called low-rank matrix and sparse error constitutes the foreground objects. But RPCA presents the limitations of computational complexity and memory storage due to batch optimization methods, as a result it is hard to apply for real-time system. To handle these challenges, this paper presents a robust background subtraction algorithm via Online Robust PCA (OR-PCA) using image decomposition. OR-PCA with image decomposition approach improves the accuracy of foreground detection and the computation time as well. Comprehensive simulations on challenging datasets such as Wallflower, I2R and Change Detection 2014 demonstrate that our proposed scheme significantly outperforms the state-of-the-art approaches and works effectively on a wide range of complex background scenes.","PeriodicalId":120340,"journal":{"name":"Research in Adaptive and Convergent Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123530903","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}
引用次数: 18
Comparative study of microwave tomography segmentation techniques based on GMM and KNN in breast cancer detection 基于GMM和KNN的微波断层分割技术在乳腺癌检测中的比较研究
Research in Adaptive and Convergent Systems Pub Date : 2014-10-05 DOI: 10.1145/2663761.2663769
Chunqiu Wang, Wei Wang, Sung Y. Shin, S. Jeon
{"title":"Comparative study of microwave tomography segmentation techniques based on GMM and KNN in breast cancer detection","authors":"Chunqiu Wang, Wei Wang, Sung Y. Shin, S. Jeon","doi":"10.1145/2663761.2663769","DOIUrl":"https://doi.org/10.1145/2663761.2663769","url":null,"abstract":"Microwave Tomography Imaging (MTI) is a new technology for early breast cancer detection. Compared to other methods such as X-ray, Magnetic Resonance Imaging (MRI) and ultrasound, the MTI technology is almost radiation-free, and low cost. However, the analysis and method to utilize new MTI method still remains unclear. In this paper, we study two segmentation techniques, Gaussian Mixture Model (GMM) and k-Nearest Neighbor (KNN), using the Artificial Neural Network (ANN) tool based on the microwave tomography data, which differentiates normal tissues and suspicious tissues in the breast tissue. Comparing different statistical models in the MTI segmentation process on breast cancer detection, our extensive study contributes to the feature extraction and classification processes on breast cancer detection. The results show that in terms of specificity and Mathew Correlation Coefficient (MCC), the KNN model outperforms the GMM method in segmenting the Region of Interest (ROI) from raw MTI data.","PeriodicalId":120340,"journal":{"name":"Research in Adaptive and Convergent Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121974060","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}
引用次数: 5
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