• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.89-104
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• 2007

This research attempts to give a personalized recommendation framework in large-sized music contents environment. Despite of existing studios and commercial contents for recommendation systems, large online shopping malls are still looking for a recommendation system that can serve personalized recommendation and handle large data in real-time. This research utilizes data mining technologies and new pattern matching algorithm. A clustering technique is used to get dynamic user segmentations using user preference to contents categories. Then a sequential pattern mining technique is used to extract contents access patterns in the user segmentations. And the recommendation is given by our recommendation algorithm using user contents preference history and contents access patterns of the segment. In the framework, preprocessing and data transformation and transition are implemented on DBMS. The proposed system is implemented to show that the framework is feasible. In the experiment using real-world large data, personalized recommendation is given in almost real-time and shows acceptable correctness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.510-518
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• 2014

In this study, in order to improve and optimize the performance of the turning mechanism for a fish robot in the fluid, we propose the tail joint trajectories using neural networks to mimic the CST(C-shape Sharp Turn) patterns of a real fish which is optimized in the natural environment. In order to mimic the CST patterns of a fish, we convert the sequential recording CST patterns into the coordinate data, and change the numerical coordinate data into a functions. We change the motion functions to the relative joint angles which is adapted to suit robot's shape and data. However, these relative joint trajectories obtained by the sequential recording of the carp have low-precision. It is difficult to apply to the control of a fish robot. Therefore, the relative joint trajectories are interpolated using neural networks with superior generalization ability and applied to the fish robot. we have found that the proposed method using neural networks is superior to ones using high-order polynomial equation through the computer simulations.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1017-1024
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• 2004

Ubiquitous system requires intelligent environment and system that perceives context in a proactive manner. This paper describes proactive retrieval method using context patterns in ubiquitous computing. And as the user's contexts change, new information is delivered proactively based on user's context patterns. For proactive retrieval, we extract context patterns based on sequential pattern discovery and association rule in data mining. By storing only information to be needed in near future using the context patterns, we solved the problem of speed and storage capacity of mobile devices in ubiquitous computing. We explain algorithms and an example. Several experiments are performed and the experimental results show that our method has a good information retrieval.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.85-92
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• 2019

In this paper, we extract the quantitative relation data of activities from the workflow event log file recorded in the XES standard format and connect them to rediscover the workflow process model. Extract the workflow process patterns and proportions with the rediscovered model. There are four types of control-flow elements that should be used to extract workflow process patterns and portions with log files: linear (sequential) routing, disjunctive (selective) routing, conjunctive (parallel) routing, and iterative routing patterns. In this paper, we focus on four of the factors, disjunctive routing, and conjunctive path. A framework implemented by the authors' research group extracts and arranges the activity data from the log and converts the iteration of duplicate relationships into a quantitative value. Also, for accurate analysis, a parallel process is recorded in the log file based on execution time, and algorithms for finding and eliminating information distortion are designed and implemented. With these refined data, we rediscover the workflow process model following the relationship between the activities. This series of experiments are conducted using the Large Bank Transaction Process Model provided by 4TU and visualizes the experiment process and results.

• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.272-278
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• 1994

The paper proposes a test pattern generator and a signature analyzer for pseudoexhaustive testing of the combinational circuit part within a sequential circuit when performing built-in self test of the circuit. The test pattern generator can scan in the seed test pattern and generate exhaustive test patterns. The signature analyzer can perform the analysis of the circuit response and scan out the result. Such test pattern generator and signature analyzer have been developed using SRL(shift register latch) and LFSR(linear feedback shift register).

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.4
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• pp.30-37
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• 1998

In this paper, we propose a test generation method for large scale sequential circuits based on circuit partitioning to increase the size of circuits that the implicit product machine traversal (IPMT) method can handle. Our method paratitions a circuit under test into subset circuits with only single output, and performs a partial scan design using the state transtition cost that represents a degree of the connectivity of the subset circuit. The IPMT method is applied to the partitioned partial scan circuits in test generation. Experimental results for ISCAS89 benchmark circuits with more thatn 50 flip-flops show that our method has generated test patterns with almost 100% fault coverage at high speed by use of 34%-73% scanned flip-flops.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.87-94
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• 2020

Recently, computer hardware is evolving toward increasing the number of computing cores, not increasing the clock speed. In order to use the performance of parallelized hardware to the maximum, the running program must also be parallelized. However, software developers are accustomed to sequential programs, and in most cases, write programs that operate sequentially. They also have a lot of difficulty designing and developing software in parallel. We propose a method to automatically convert a sequential C/C++ program into a parallelized program, and develop a parallelization tool that supports it. It supports open multiprocessing (OpenMP) and parallel patterns library (PPL) as a parallel framework. Perfect automatic parallelization is difficult due to dynamic features such as pointer operation and polymorphism in C/C++ language. This study focuses on verifying the conditions of parallelization rather than focusing on fully automatic parallelization, and providing advice to developers in detail if parallelization is not possible.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1471-1475
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• 1987

This paper proposes testable design of sequential NMOS PLAs. The extra bit lines and devices are added to the conventional PLAs. The time is taken to assigning devices in the extra bit lines, which is excessive in the conventional method, is reduced by using the symmetrical distance matrix of the PLA and the regular assigning method. As a result, the test patterns can be easily generated. Also, the silicon area overhead of extra hardware is low.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.143-145
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• 2005

In this paper, an empirical study result on pattern estimation method is devoted to reveal underlying data patterns with a relatively reduced computational cost. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). Conventional SAHN based clustering requires large computation time in the initial step of algorithm. To deal with this concern, we modified overall process with a partial approach. In the beginning of this method, we divide given data set to several sub groups with uniform sampling and then each divided sub data group is applied to SAHN based method. The advantage of this method reduces computation time of original process and gives similar results. Proposed is applied to several test data set and simulation result with conceptual analysis is presented.

• Structural Engineering and Mechanics
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• v.3 no.6
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• pp.529-539
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• 1995

The rigid-plastic yield-line analysis of isotropically reinforced concrete slabs acting in conjunction with torsionally weak supporting beams is developed as the lower-bound form of a linear programming formulation. The analysis is extended to consider geometric variation of chosen yield-line patterns by the technique of sequential linear programming. A strategy is followed of using a fine potential yield-line mesh to identify possible collapse modes, followed by analysis using a coarser, simplified mesh to refine the investigation and for use in conjunction with geometric optimization of the yield-line system. The method is shown to be effective for the analysis of three slabs of varying complexity. The modes detected by the fine and simplified analyses are not always similar but close agreement in load factors has been consistently obtained.