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1.
Yoon-Sik Tak Seungmin Rho Eenjun Hwang Hanku Lee 《Multimedia Tools and Applications》2012,61(1):51-68
Dominant features for the content-based image retrieval usually have high-dimensionality. So far, many researches have been done to index such values to support fast retrieval. Still, many existing indexing schemes are suffering from performance degradation due to the curse of dimensionality problem. As an alternative, heuristic algorithms have been proposed to calculate the answer with ??high probability?? at the cost of accuracy. In this paper, we propose a new hash tree-based indexing structure called tertiary hash tree for indexing high-dimensional feature data. Tertiary hash tree provides several advantages compared to the traditional extendible hash structure in terms of resource usage and search performance. Through extensive experiments, we show that our proposed index structure achieves outstanding performance. 相似文献
2.
Seungmin Ahn Hoyoung Jung Prof. Dr. Jung-Min Kee 《Chembiochem : a European journal of chemical biology》2021,22(2):319-325
Protein phosphorylation is one of the most studied post-translational modifications (PTMs). Despite the remarkable advances in phosphoproteomics, a chemically less-stable subset of the phosphosites, which we call the crypto-phosphoproteome, has remained underexplored due to technological challenges. In this Viewpoint, we briefly summarize the current understanding of these elusive protein phosphorylations and identify the missing pieces for future studies. 相似文献
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Chao Chen Wen Ji Seungmin Rho Bo-Wei Chen Yiqiang Chen 《Multimedia Tools and Applications》2016,75(22):14507-14524
Mobile video quality assessment plays an essential role in multimedia systems and services. In the case of scalable video coding, which enables dynamic adaptation based on terminal capabilities and heterogeneous network, variable resolution is one of the most prominent types of video distortions. In this paper, we propose a new hybrid spatial and temporal distortion metric for evaluating video streaming quality with variable spatio-temporal resolution. The key idea is to project video sequence into feature domain and calculate the distortion of content information from the projected principal component matrix and its eigenvectors. This metric can measures the degree of content information degradation especially in spatio-temporal resolution scalable video. The performance of the proposed metric is evaluated and compared to some state-of-the-art quality evaluation metrics in the literature. Our results show that the proposed metric achieves good correlations with the subjective evaluations of the EPFL scale video database. 相似文献
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Meiyu Huang Yiqiang Chen Bo-Wei Chen Junfa Liu Seungmin Rho Wen Ji 《Peer-to-Peer Networking and Applications》2016,9(5):864-875
With the proliferation of healthcare data, the cloud mining technology for E-health services and applications has become a hot research topic. While on the other hand, these rapidly evolving cloud mining technologies and their deployment in healthcare systems also pose potential threats to patient’s data privacy. In order to solve the privacy problem in the cloud mining technique, this paper proposes a semi-supervised privacy-preserving clustering algorithm. By employing a small amount of supervised information, the method first learns a Large Margin Nearest Cluster metric using convex optimization. Then according to the trained metric, the method imposes multiplicative perturbation on the original data, which can change the distribution shape of the original data and thus protect the privacy information as well as ensuring high data usability. The experimental results on the brain fiber dataset provided by the 2009 PBC demonstrated that the proposed method could not only protect data privacy towards secure attacks, but improve the clustering purity. 相似文献
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Seungmin Rho Naveen Chilamkurti Karim El Defrawy 《Personal and Ubiquitous Computing》2013,17(8):1667-1669
In ubiquitous computing environments, providing appropriate services and information to users at the right place in the right way is challenging for many reasons: different user interests, heterogeneous devices and services, dynamic networks, information overload, or differing privacy levels, for example. Agent technology is a paradigm expected to play an increasing role in complex computing environments, and due to the increasing popularity of social networking services, we expect to see the convergence of agent and social web technologies. The goal of this theme issue is to bring together state-of-the-art research contributions that examine the convergence of agent technologies and social networks for ubiquitous computing. 相似文献
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As recent Internet threats are evolving more rapidly than ever before, one of the major challenges in designing an intrusion detection system is to provide early and accurate detection of emerging threats. In this study, a novel framework is developed for fully unsupervised training and online anomaly detection. The framework is designed so that an initial model is constructed and then it gradually evolves according to the current state of online data without any human intervention. In the framework, a self-organizing map (SOM) that is seamlessly combined with K-means clustering is transformed into an adaptive and dynamic algorithm suitable for real-time processing. The performance of the proposed approach is evaluated through experiments using the well-known KDD Cup 1999 data set and further experiments using the honeypot data recently collected from Kyoto University. It is shown that the proposed approach can significantly increase the detection rate while the false alarm rate remains low. In particular, it is capable of detecting new types of attacks at the earliest possible time. 相似文献
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