• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.213-220
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• 2008

The object of this paper is to propose a method to deal with the problem of modeling user specifications in approaches based on supervisory control and Petri nets. However, most of Petri Net approaches are based on forbidden states specifications, and these specifications are suitable the use of tool such as the reachability graph. But these methods were not able to show the user specification easily and these formalisms are generally limited by the combinatorial explosion that occurs when attempting to model complex systems. Herein, we propose a new efficient method using FSSTP (Forbidden Sequences of State-Transitions Problem) and theory of region. Also, to detect and avoid the deadlock problem in control process, we use DAPN method (Deadlock Avoidance Petri nets) for solving this problem in control model.

• Genomics & Informatics
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• v.7 no.1
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• pp.1-12
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• 2009

An alternative way of constructing ancestral graphs, which is different from the coalescent-based approach, is proposed using population linkage disequilibrium (LD) data. The main difference from the existing method is the construction of the ancestral graphs based on variants instead of individual sequences. Therefore, the key of the proposed method is to use the order of allele ages in the graphs. Distinct from the previous age-estimation methods, allele ages are estimated from full haplotype information by examining the number of generations from the initial complete LD to the current decayed state for each two variants depending on the direction of LD decay between variants. Using a simple algorithmic procedure, an ancestral graph can be derived from the expected allele ages and current LD decay status. This method is different in many ways from previous methods, and, with further improvement, it might be a good replacement for the current approaches.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.132-139
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• 2008

This paper proposes a scatternet topology formation, self-healing, and self-routing path optimization algorithm based on Relative Neighborhood Graph. The performance of the algorithm using ns-2 and extensible Bluetooth simulator called blueware shows that even though RNG-FHR does not have superior performance, it is simpler and easier to implement in deploying the Ad-Hoc network in the distributed dynamic environments due to the exchange of fewer messages and the only dependency on local information. We realize that our proposed algorithm is more practicable in a reasonable size network than in a large scale.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2659-2669
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• 1999

This paper a heuristic, clustering based task allocation scheme applicable to non-directed task graph on a distributed system. This scheme firstly builds a task-machine graph, and then applies a clustering process where in a pair of tasks that are connected to the highest cost edge is merged into a big one or a task is allocated to a machine. During the process, the proposed scheme figure out a machine onto which the task allocation may cause deduction of large communication overhead that has incurred between the task and tasks that are already allocated to the machine while the computation costs is slightly increased in the machine. Simulation for the various task graphs shows that the scheduling using the proposed scheme result far better than ones by using the traditional schemes. A comparison with optimal task scheduling also promises that our scheme derives optimal results more occasionally than the traditional schemes do.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.697-699
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• 2004

Despite many successful spectral clustering algorithm (based on the spectral decomposition of Laplacian(1) or stochastic matrix(2) ) there are several unsolved problems. Most spectral clustering Problems are based on the normalized of algorithm(3) . are close to the classical graph paritioning problem which is NP-hard problem. To get good solution in polynomial time. it needs to establish its convex form by using relaxation. In this paper, we apply a novel optimization technique. semidefinite programming(SDP). to the unsupervised clustering Problem. and present a new multiple Partitioning method. Experimental results confirm that the Proposed method improves the clustering performance. especially in the Problem of being mixed with non-compact clusters compared to the previous multiple spectral clustering methods.

• International Journal of High-Rise Buildings
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• v.12 no.1
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• pp.83-91
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• 2023

Under the dual pressure of population growth and land shortage, threedimensional development is the inevitable choice for cities in China. In such a scenario, a mixed-use complex has considerable potential in its realization and research. Based on space syntax and the three-dimensional visibility graph analysis, this paper describes the spatial and functional layout of the Shanghai Super Brand Mall and studies the relationship between spatial visibility and user behaviour through linear regression analysis and correlation analysis. This paper studies three different types of user behaviour, namely, path selection, staying selection, and store selection, and finds that spatial visibility and accessibility have different effects on user behaviour depending on the type and purpose of the activity. This paper reveals the influence of spatial and functional layout on user behaviour and puts forward the corresponding design strategy under the three-dimensional environment.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.399-401
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• 2022

POI (Point-of-Interest) 추천은 다양한 위치 기반 서비스에서 중요한 역할을 있다. 기존 연구에서는 사용자의 모바일 선호도를 모델링하기 위해 과거의 체크인의 공간-시간적 관계를 추출한다. 그러나 사용자 궤적에 숨겨진 개인 방문 경향을 반영할 수 있는 structured feature 는 잘 활용되지 않는다. 이 논문에서는 궤적 그래프를 결합한 시공간 인식 attention 네트워크를 제안한다. 개인의 선호도가 시간이 지남에 따라 변할 수 있다는 점을 고려하면 Dynamic GCN (Graph Convolution Network) 모듈은 POI 들의 공간적 상관관계를 동적으로 집계할 수 있다. LBSN (Location-Based Social Networks) 데이터 세트에서 검증된 새 모델은 기존 모델보다 약 9.0% 성능이 뛰어나다.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.1-10
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• 2017

Open data has received a lot of attention from around the world. The Korean government is also making efforts to open government data. However, despite the quantitative increase in public data, the lack of data is still pointed out. This paper proposes a method to improve data sharing and utilization by semantically linking public data. First, we propose a knowledge model for expressing administrative districts and their semantic relationships in Korea. An administrative district is an administrative unit that divides the territory of a nation, which is a unit of politics, according to the purpose of the state administration. The knowledge model of the administrative district defines the structure of the administrative district system and the relationship between administrative units based on the Local Autonomy Act. Second, a knowledge graph of the administrative districts is introduced. As a reference information to link public open data at a semantic level, some characteristics of a knowledge graph of administrative districts and methods for linking heterogeneous public open data and improving data quality are addressed. Finally, some use cases are addressed for interlinking between the knowledge graph of the administrative districts and public open data. In particular, national administrative organisations are interlinked with the knowledge graph, and it demonstrates how the knowledge graph can be utilised for improving data identification and data quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.364-380
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• 2016

The most popular approach in object classification is based on the bag of visual-words model, which has several fundamental problems that restricting the performance of this method, such as low time efficiency, the synonym and polysemy of visual words, and the lack of spatial information between visual words. In view of this, an object classification based on weakly supervised E2LSH and saliency map weighting is proposed. Firstly, E2LSH (Exact Euclidean Locality Sensitive Hashing) is employed to generate a group of weakly randomized visual dictionary by clustering SIFT features of the training dataset, and the selecting process of hash functions is effectively supervised inspired by the random forest ideas to reduce the randomcity of E2LSH. Secondly, graph-based visual saliency (GBVS) algorithm is applied to detect the saliency map of different images and weight the visual words according to the saliency prior. Finally, saliency map weighted visual language model is carried out to accomplish object classification. Experimental results datasets of Pascal 2007 and Caltech-256 indicate that the distinguishability of objects is effectively improved and our method is superior to the state-of-the-art object classification methods.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.143-149
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• 2024

The production and procurement of shipbuilding and offshore equipment is an important competitive factor in the shipbuilding and offshore industry. Recently, ICT-based digital technology has been rapidly applied to the manufacturing industry following the Fourth Industrial Revolution. Under the digital transformation, real-time data interface technology based on SCM (Supply Chain Management) is emerging as an important tool to improve the efficiency of the equipment manufacturing process. In this study, the characteristics and advantages and disadvantages of interface technologies of web-based data interface technologies were compared and analyzed. The performance was compared between theoretical evaluation based on technical features and practical application cases. As a result, it was confirmed that GraphQL is useful for selective data processing, but there is a problem with optimization, and REST API has a problem with receiving data due to a fixed data structure. Therefore, this study aims to suggest ways to utilize and optimize these data interface technologies.