• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.89-99
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• 2011

The payload signature-based traffic classification system has to deal with large amount of traffic data, as the number of internet-based applications and network traffic continue to grow. While a number of pattern-matching algorithms have been proposed to improve processing speedin the literature, the performance of pattern matching algorithms is restrictive and depends on the features of its input data. In this paper, we studied how to optimize the search space in order to improve the processing speed of the payload signature-based traffic classification system. Also, the feasibility of our design choices was proved via experimental evaluation on our campus traffic trace.

• Journal of the Korean Society for information Management
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• v.27 no.3
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• pp.307-323
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• 2010

The amount of online scholarly information rapidly expands in numerous resources, while user behavior demands single search box interface like Google Scholar. Despite scholarly values of e-resources libraries provide, users consider Google Scholar as the most efficient research tool attracted by its speed, simplicity, ease of use, and convenience. Characteristics of Metasearch System compared with Google Scholar are analyzed from perspectives of the interface and e-resource. Based on usage statistics of Metasearch System along with a link resolver in one academic library, e-resource accessibility patterns and information seeking behaviors of subject-specific areas are investigated for electronic information services.

• Journal of the Korea Computer Industry Society
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• v.9 no.4
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• pp.149-156
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• 2008

There is the temporal correlation of a animation sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the scene change detection algorithm for block matching using the temporal correlation of the animation sequence and the center-biased property of motion vectors. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate point on each search region. Simulation results show that the proposed algorithm has better detection performance, such as recall rate, then the existing method. The algorithm has the advantage of speed, simplicity and accuracy. In addition, it requires less amount of storage.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.3
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• pp.155-160
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• 2002

This paper focuses on the problem of local obstacle avoidance of mobile robots. To solve this problem, the safety direction section search algorithm is suggested. This concept is mainly composed with non-collision section and collision section from the detecting area of laser scanning sensor. Then, we will search for the most suitable direction in these sections. The proposed local motion planning method is simple and requires less computation than others. An environment model is developed using the vector space concept to determine robot motion direction taking the target direction, obstacle configuration, and robot trajectory into account. Since the motion command is obtained considering motion dynamics, it results in smooth and fast as well as safe movement. Using the mobile base, the proposed obstacle avoidance method is tested, especially in the environment with pillar, wall and some doors. Also, the proposed autonomous motion planning and control algorithm are tested extensively. The experimental results show the proposed method yields safe and stable robot motion through the motion speed is not so fast.

• ETRI Journal
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• v.29 no.6
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• pp.736-744
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• 2007

We propose a fast macroblock (MB) mode prediction and decision algorithm based on temporal correlation for P-slices in the H.264/AVC video standard. There are eight block types for temporal decorrelation, including SKIP mode based on rate-distortion (RD) optimization. This scheme gives rise to exhaustive computations (search) in the coding procedure. To overcome this problem, a thresholding method for fast inter mode decision using a MB tracking scheme to find the most correlated block and RD cost of the correlated block is suggested for early stop of the inter mode determination. We propose a two-step inter mode candidate selection method using statistical analysis. In the first step, a mode is selected based on the mode information of the co-located MB from the previous frame. Then, an adaptive thresholding scheme is applied using the RD cost of the most correlated MB. Secondly, additional candidate modes are considered to determine the best mode of the initial candidate modes that does not satisfy the designed thresholding rule. Comparative analysis shows that a speed-up factor of up to 70.59% is obtained when compared with the full mode search method with a negligible bit increment and a minimal loss of image quality.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.1
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• pp.27-38
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• 2017

Packet classification is one of the essential functionalities of Internet routers in providing quality of service. Since the arrival rate of input packets can be tens-of-millions per second, wire-speed packet classification has become one of the most challenging tasks. While traditional packet classification only reports a single matching result, new network applications require multiple matching results. Ternary content-addressable memory (TCAM) has been adopted to solve the multi-match classification problem due to its ability to perform fast parallel matching. However, TCAM has a fundamental issue: high power dissipation. Since TCAM is designed for a single match, the applicability of TCAM to multi-match classification is limited. In this paper, we propose a cost- and energy-efficient multi-match classification architecture that combines TCAM with a tuple space search algorithm. The proposed solution uses two small TCAM modules and requires a single-cycle TCAM lookup, two SRAM accesses, and several Bloom filter query cycles for multi-match classifications.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.99-108
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• 2004

In this paper, a new fast detection and clutter rejection method is proposed for CCD-image-based Automatic Target Detection System. For defence application, fast computation is a critical point, thus we concentrated on the ability to detect various targets with simple computation. In training stage, 1D template set is generated by regional vertical projection and K-means clustering, and binary tree structure is adopted to reduce the number of template matching in test stage. We also use adaptive skip-width by Correlation-based Adaptive Predictive Search(CAPS) to further improve the detecting speed. In clutter rejection stage, we obtain Fourier Descriptor coefficients from boundary information, which are useful to rejected clutters.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.49-54
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• 2017

Pathfinding for pedestrians provided by various navigation programs is based on a shortest path search algorithm. There is no big difference in their guide results, which makes the path quality more important. Multiple criteria should be included in the search cost to calculate the path quality, which is called a multi-criteria pathfinding. In this paper we propose a user adaptive pathfinding algorithm in which the cost function for a multi-criteria pathfinding is defined as a weighted sum of multiple criteria and the weights are learned automatically by Perceptron learning. Weight learning is implemented in two ways: short-term weight learning that reflects weight changes in real time as the user moves and long-term weight learning that updates the weights by the average value of the entire path after completing the movement. We use the weight update method with momentum for long-term weight learning, so that learning speed is improved and the learned weight can be stabilized. The proposed method is implemented as an app and is applied to various movement situations. The results show that customized pathfinding based on user preference can be obtained.

• Journal of Sensor Science and Technology
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• v.6 no.2
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• pp.145-154
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• 1997

Based on a new search strategy using circuit simulation and simulated annealing with local search, a technique for design automation of high-performance operational amplifiers is proposed. For arbitrary circuit topology and performance specifications, through discrete optimization of a cost function with discrete design variables the design of operational amplifiers is performed. A special-purpose circuit simulator and some heuristics are used to reduce the design time. Through the design of a low-power high-speed fully differential CMOS operational amplifier usable in smart sensors and 10-b 25-MS/s pipelined A/D converters, it has been demonstrated that a design tool developed using the proposed technique can be used for designing high-performance operational amplifiers with less design knowledge and less design effort.

• Convergence Security Journal
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• v.14 no.4
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• pp.33-40
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• 2014

Since 2006, social networking services such as Facebook, Twitter, and Blog user increasing very rapidly. Furthermore demand of Book Retrieval Service using smartphone on social network service environment are increasing too. This service can to easy and share information for search book and data in several university. However, the current edition of the social services in the country to provide security services do not have the right. Therefore, we suggest a social book Retrieval service in social network environment that can support user authentication and partial filter search method on smartphone. our proposed system can to provide more speed responsiveness, effective display result on smartphone and security service.