• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.4
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• pp.745-750
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• 2009

The goal of this study is to examine on reasoning and search for construction of diagnosis ontology as a knowledge base of diagnosis expert system in oriental medicine. Expert system is a field of artificial intelligence. It is a system to acquire information with diverse reasoning methods after putting expert's knowledge in computer systematically. A typical model of expert system consists of knowledge base and reasoning & explanatory structure offering conclusion with the knowledge. To apply ontology as knowledge base to expert system practically, consideration on reasoning and search should be together. Therefore, this study compared and examined reasoning, search with diagnosis process in oriental medicine. Reasoning is divided into Rule-based reasoning and Case-based reasoning. The former is divided into Forward chaining and Backward chaining. Because of characteristics of diagnosis, sometimes Forward chaining or backward chaining are required. Therefore, there are a lot of cases that Hybrid chaining is effective. Case-based reasoning is a method to settle a problem in the present by comparing with the past cases. Therefore, it is suitable to diagnosis fields with abundant cases. Search is sorted into Breadth-first search, Depth-first search and Best-first search, which have respectively merits and demerits. To construct diagnosis ontology to be applied to practical expert system, reasoning and search to reflect diagnosis process and characteristics should be considered.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.45-69
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• 2024

Purpose - To examine the influence of mobile visual search as a strategic technology service on consumer perceived economic value and customer commitments, which in turn affect consumer's usage intention of mobile visual search. This study also explores the moderating effect of different levels of consumer online shopping orientation. Design/methodology/approach - One-by-one open-ended in-depth interview was first undertaken to 15 Korean consumers to figure the features of mobile visual search. Then a conceptual model was built to verify the hypotheses that indicate the impact of mobile visual search on consumer perceived economic value and customer commitment, which further influence consumer's usage intention. Findings - The results show Convenience, Information quality, Personalization, Text-free search interface design and Visual communication of mobile visual search positively influence consumer perceived economic value and customer commitment and in turn positively affect consumer's usage intention. Moreover, the different levels of consumer online shopping orientation also found to have different effects on consumers' perception and behavior of using mobile visual search in online fashion shopping. Research implications or Originality - The present study verified that mobile visual search is a service tool that consumers want to use in the online fashion shopping journey since it provides economic benefits.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.1 s.173
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• pp.190-195
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• 2000

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure. Nikolakopoulos et. al. used the intersection point of the superposed contours that correspond to the eigenfrequency caused by the crack presence. However the intersecting point of the superposed contours is not only difficult to find but also incorrect to calculate. A method is presented in this paper which uses optimization technique for the location and depth of the crack. The basic idea is to find parameters which use the structural eigenfrequencies on crack depth and location and optimization algorithm. With finite element model of the structure to calculate eigenfrequencies, it is possible to formulate the inverse problem in optimization format. Method of optimization is augmented lagrange multiplier method and search direction method is BFGS variable metric method and one dimensional search method is polynomial interpolation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2525-2532
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• 2009

In this paper, a fast sphere decoder is proposed for the joint detection of phase-shift keying (PSK) signals in uncoded Vertical Bell Laboratories Layered Space Time (V-BLAST) systems. The proposed decoder, PSD, consists of preprocessing stage and search stage. The search stage of PSD relies on the depth-first branch-and-bound (BB) algorithm with "best-first" orders stored in lookup tables. Simulation results show that the PSD is able to provide the system with the maximum likelihood (ML) performance at low complexity.

• Knowledge Management Research
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• v.17 no.1
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• pp.49-72
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• 2016

Extant research on firm innovation productivity is limited in measuring the innovation productivity, in which they measured firm innovation productivity by using either inputs or outputs of innovation. The present study complemented the extant research by employing Data Envelopment Analysis (DEA) approach to measure firm innovation productivity. Furthermore, this paper examined the effects of firms' external knowledge search, as one of open innovation practices, on firm innovation productivity, for open innovation activities are regarded as an influencing factor on firm innovation productivity in the previous literatures. Using the data of the Korean Innovation Survey (KIS) of manufacturing industries conducted in 2008, this study developed hypotheses in which we considered not only two dimensions of external knowledge search (breadth and depth) but also two subtypes of external knowledge search (market-driven and science-driven). The results found that searching deeply and market-driven search are positively related to firm innovation productivity, but science-driven search is somewhat negatively related to firm innovation productivity. Furthermore, market-driven search can mitigate the negative effect of science-driven search on innovation productivity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.292-302
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• 2003

We propose a new method to reduce the complexity of excitation codebook search. The preselected excitation pulses by the coarse search method can be updated to pulses with higher quality performance measure. The excitation pulses can arbitrarily be deleted and inserted among the searched pulses until the overall performance achieves. If we use this excitation pulse search method in AMR-WB, the complexity required for excitation codebook search can be reduced to half the original method while the output speech maintains equal speech quality to a conventional method.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.707-720
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• 2014

This paper proposes a face tracking scheme that is a combination of a face detection algorithm and a face tracking algorithm. The proposed face detection algorithm basically uses the Adaboost algorithm, but the amount of search area is dramatically reduced, by using skin color and motion information in the depth map. Also, we propose a face tracking algorithm that uses a template matching method with depth information only. It also includes an early termination scheme, by a spiral search for template matching, which reduces the operation time with small loss in accuracy. It also incorporates an additional simple refinement process to make the loss in accuracy smaller. When the face tracking scheme fails to track the face, it automatically goes back to the face detection scheme, to find a new face to track. The two schemes are experimented with some home-made test sequences, and some in public. The experimental results are compared to show that they outperform the existing methods in accuracy and speed. Also we show some trade-offs between the tracking accuracy and the execution time for broader application.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.239-246
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• 2009

This paper deals with the makespan minimization problem of job shops. The problem is known as one of hard problems to optimize, and therefore, many heuristic methods have been proposed by many researchers. The aim of this study is also to propose a heuristic scheduling method for the problem. However, the difference between the proposed method and many other heuristics is that the proposed method is based on depth-first branch and bound, and thus it is possible to find an optimal solution at least in principle. To accelerate the search, when a node is judged hopeless in the search tree, the proposed flexible branch and bound method can indicate a higher backtracking node. The unexplored nodes are stored and may be explored later to realize the strict optimization. Two methods are proposed to generate the backtracking point based on the critical path of the current best feasible schedule, and the minimum lower bound for the makespan in the unexplored sub-problems. Schedules are generated based on Giffler and Thompson's active schedule generation algorithm. Acceleration of the search by the flexible branch and bound is confirmed by numerical experiment.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.171-174
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• 2003

In this paper, we propose the method of stereo images composition using adaptive dense disparity estimation. For the correct composition of stereo image and 3D virtual object, we need correct marker position and depth information. The existing algorithms use position information of markers in stereo images for calculating depth of calibration object. But this depth information may be wrong in case of inaccurate marker tracking. Moreover in occlusion region, we can't know depth of 3D object, so we can't composite stereo images and 3D virtual object. In these reasons, the proposed algorithm uses adaptive dense disparity estimation for calculation of depth. The adaptive dense disparity estimation is the algorithm that use pixel-based disparity estimation and the search range is limited around calibration object.

• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.340-347
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• 2015

HEVC (High Efficiency Video Coding) achieves high coding efficiency by employing a quadtree-based coding unit (CU) block partitioning structure and various prediction units (PUs), and the determination of the best CU partition structure and the best PU mode based on rate-distortion (R-D) cost. However, the computation complexity of encoding also dramatically increases. In this paper, to reduce such encoding computational complexity, we propose three fast PU mode decision methods based on encoding information of upper depth as follows. In the first method, the search of PU mode of the current CU is early terminated based on the sub-CBF (Coded Block Flag) of upper depth. In the second method, the search of intra prediction modes of PU in the current CU is skipped based on the sub-Intra R-D cost of upper depth. In the last method, the search of intra prediction modes of PU in the lower depth's CUs is skipped based on the sub-CBF of the current depth's CU. Experimental results show that the three proposed methods reduce the computational complexity of HM 14.0 to 31.4%, 2.5%, and 23.4% with BD-rate increase of 1.2%, 0.11%, and 0.9%, respectively. The three methods can be applied in a combined way to be applied to both of inter prediction and intra prediction, which results in the complexity reduction of 34.2% with 1.9% BD-rate increase.