• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1392-1398
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• 2008

This paper presents a Petri Net (PN) based disassembly sequence planning model with precedence operations. All feasible disassembly sequences are generated by a disassembly tree and a disassembly sequence is determined using the disassembly precedence and disassembly value matrix, The precedence of disassembly operations is determined through a disassembly tree and the value of disassembly is induced by economic analysis in the end-of-life phase. To solve the disassembly sequence planning model with precedence operations, a heuristic algorithm based on PNs is developed. The developed algorithm generates and searches a partial reachability graph to arrive at an optimal or near-optimal disassembly sequence based on the firing sequence of transitions of the PN model. A refrigerator is shown as an example to demonstrate the effectiveness of proposed model.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1009-1024
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• 2018

With the increased use of LiDAR (Light Detection and Ranging) that can obtain over millions of point dataset, methodologies for efficient search and dimensionality reduction for the point cloud became a crucial technique. The existing octree-based "parametric algorithm" has proved its efficiency and contributed as a part of PCL (Point Cloud Library). However, the implementation of the algorithm on GPU (Graphics Processing Unit) is considered very difficult because of structural constraints of the octree implemented in PCL. In this paper, we present a method for the parametric algorithm on GPU environment and implement a projection of the queried points on four directions with an improved noise reduction.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.17-23
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• 2024

Losses in domestic water supply due to leaks are very large, such as fractures and defects in pipelines. Therefore, preventive measures to prevent water leakage are necessary. We propose the development of a leakage detection sensor utilizing vibration sensors and present an optimal leakage detection algorithm leveraging artificial intelligence. Vibrational sound data acquired from water pipelines undergo a preprocessing stage using FFT (Fast Fourier Transform), followed by leakage classification using an optimized tree-based boosting algorithm. Applying this method to approximately 260,000 experimental data points from various real-world scenarios resulted in a 97% accuracy, a 4% improvement over existing SVM(Support Vector Machine) methods. The processing speed also increased approximately 80 times, confirming its suitability for edge device applications.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.542-543
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• 2008

기존의 지그비 기반의 유비쿼터스 센서 네트워크 기술을 적용한 각종 모니터링 어플리케이션들은 노드 수가 증가함에 따라 라우팅 오버헤드 및 종단간의 지연 등 네트워크 성능에 부정적인 영향을 주는 네트워크 효율성에 대한 문제점을 많이 보이고 있다. 본 논문에서 이런 문제점을 해결하기 위해 지그비 기술을 이용하여 멀티흡을 지원하는 트리 라우팅 알고리듬을 적용한 유비쿼터스 지하철역 공기질 모니터링을 위한 무선 통합 공기질 측정 센서노드를 설계하고 실제 지하철역 현장에서 성능평가를 수행하였다. 본 연구결과는 지하 환경에서 신뢰성있는 센서 네트워크를 구축하고 차후 광대역 통합 네트워크망과 연동을 통해 다양한 서비스 사업의 기반이 될 것으로 판단된다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2169-2177
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• 2015

This paper proposes a new pattern matching module to overcome the increased runtime of previous algorithm using RAM, which was designed to overcome cost limitation of hash-based algorithm using CAM (Content Addressable Memory). By adopting Merge FSM algorithm to reduce the number of state, the proposed module contains state block and entry block to use in RAM. In the proposed module, one input string is compared with multiple entry strings simultaneously using entry block. The effectiveness of the proposed pattern matching unit is verified by executing Snort 2.9 rule set. Experimental results show that the number of memory reads has decreased by 15.8%, throughput has increased by 47.1%, while memory usage has increased by 2.6%, when compared to previous methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.12
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• pp.756-763
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• 2014

In this paper, we introduce a new sparse signal recovery algorithm referred to as the matching pursuit with greedy tree search (GTMP). The tree search in our proposed method is implemented to minimize the cost function to improve the recovery performance of sparse signals. In addition, a pruning strategy is employed to each node of the tree for efficient implementation. In our performance guarantee analysis, we provide the condition that ensures the exact identification of the nonzero locations. Through empirical simulations, we show that GTMP is effective for sparse signal reconstruction and outperforms conventional sparse recovery algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.852-855
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• 2010

Tree type of Rule Case will be processed by the method that provide practical Rule Case to Rule Engine that is made with procedural language beforehand, then the Rule Engine according to the condition of the special Rule Case to return result in current Rule-Based System. There are two disadvantages in the method; the first is according to specific business rule after construct the Rule Engine when the business rule changing the Rule Engine also must be changed. The second is when Rule have many conditions the Rule Engine will become very complex and the speed of processing Rule Case will become very slow. In this paper, we will propose a simplified algorithm that according to the theory of ID Tree to produce Rules which be used in Rule-Based System. The algorithm can not only produce Rules but also make sure of satisfying change of business rule by execute the algorithm. Because it is not necessary to make a Rule Engine, we will anticipate effect of increasing speed and reducing cost from Rule-Based System of applying the algorithm.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.2
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• pp.67-75
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• 2004

This paper presents a buffer insertion method for RLC-class interconnect structured as a sin91e line or a tree. First, a closed form expression for the interconnect delay of a CMOS buffer driving single RLC line is represented. This expression has been derived by the n-th power law for deep submicrometer technology and occurs to be within 9 percentage of maximal relative error in accuracy compared with the results of HSPICE simulation for various RLC loads. This paper proposes a closed form expression based on this for the buffer insertion of single RLC lines and the buffer sizing algorithms for RLC tree interconnects to optimize path delays. The proposed buffer insertion algorithms are applied to insert buffers for several interconnect trees with a 0.25${\mu}{\textrm}{m}$ CMOS technology and the results are compared against those of HSPICE.

• The Journal of the Acoustical Society of Korea
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• v.25 no.7
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• pp.319-324
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• 2006

We Propose two new methods for non-keyword modeling to improve the performance of speaker- and vocabulary-independent keyword spotting system. The first method is decision tree clustering of monophone at the state level instead of monophone clustering method based on K-means algorithm. The second method is multi-state multiple mixture modeling at the syllable level rather than single state multiple mixture model for the non-keyword. To evaluate our method, we used the ETRI speech DB for training and keyword spotting test (closed test) . We also conduct an open test to spot 100 keywords with 400 sentences uttered by 4 speakers in an of fce environment. The experimental results showed that the decision tree-based state clustering method improve 28%/29% (closed/open test) than the monophone clustering method based K-means algorithm in keyword spotting. And multi-state non-keyword modeling at the syllable level improve 22%/2% (closed/open test) than single state model for the non-keyword. These results show that two proposed methods achieve the improvement of keyword spotting performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.7B
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• pp.957-967
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• 2001

본 논문에서는 모델 기반 지각적 그룹핑을 이용한 3차원 다면체의 인식 및 형상 복원에 관한 새로운 기법을 제안한다. 2차원 입력 영상과 여기에서 추출된 특징들의 3차원 특징을 거리 측정기를 이용하여 추출하여 인식 및 복원의 기본 특징으로 이용한다. 이 때, 모델의 3차원 기하학적 정보는 결정 트리 분류기에 의하여 학습되며 지각적 그룹핑은 이와 같은 모델 기반으로 이루어진다. 또한, 1차 그룹핑의 결과로 얻어진 3차원 직선 특징간의 관계는 Gestalt 그래프로 표현되며 이것의 부그래프 분할을 통하여 인식을 위한 후보 그룹이 생성된다. 마지막으로 각각의 후보 그룹은 3차원 모델과 정렬되어 가장 잘 부합되는 그룹을 인식 결과로 생성하게 된다. 그리고 정렬의 결과로서 2차원 텍스춰를 추출하여 3차원 모델에 매핑함으로써 실제적인 3차원 형상을 복원할 수 있다. 제안하는 알고리듬의 성능을 평가하기 위하여 불록 영상과 지형 모델 보드 영상에 대하여 실험을 수행하였다. 실험 결과, 모델 기반의 그룹핑 기법은 결과 그룹의 수를 상당히 감소시켰으며 또한 잡음과 가리워짐에 강건한 인식과 복원 결과가 얻어졌다.