• East Asian Journal of Business Economics (EAJBE)
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• v.6 no.4
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• pp.13-24
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• 2018

Purpose - This study investigates the moderation effect of internal factor, a firms size, on the external knowledge sourcing strategy and its effectiveness in generating radical innovation. We incorporate concepts of breadth and depth as two measures to gauge the degree of openness in firms external search Research design and methodology - The dependent variable in the regression model is the percentage of innovative sales and therefore, Tobit regression is employed for estimating significant factors affecting on the ratio of first-to-market by breadth and depth in external knowledge, internationalization, and size. Results - The results show that the external knowledge, in terms of both breadth and depth, has a positive relationship with radical innovation. However internationalization as external knowledge resources is not statistically accepted. Firm size has moderating effect on innovation negatively only in case of using external knowledge resources to a high degree. Conclusions - Firms obtain external information mostly from customers, competitors, and suppliers etc. empirical knowledge in terms of scope and intensity is an important contributor to innovation. And intensity use of external knowledge and information resources can work in favor of smaller firms rather than larger ones. Internationalization seems to have little effect on innovation but it requires further researches with clear criteria and more data.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.63-71
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• 2013

Developing future weapons systems has become increasingly complicated and costly. There, modeling and simulation techniques have been highly interested in developing the defense systems. Modeling and simulation techniques provide a means to simulate military training, strategies, military doctrines, and weapons acquisition. In this paper, we proposed a small scale engagement scenario generation method for engagement M&S model. Generated scenario is one of critical factors in the field of commander training, operational analysis, and tactical evaluation. The objective of this paper is to develop a scenario generation method for small scale engagement using the FSA(Finite State Automata) and DFS(Depth First Search) algorithm. The proposed method is verified using a one-on-one combat engagement scenario between assault ship and reconnaissance ship. Also, we are visualized using Delta3D$^{TM}$.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.141-147
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• 1992

This article evaluates the efficiency of three branch-and-bound heuristics for a job scheduling problem that minimizes the sum of absolute deviations of completion times from a common due date. To improve the performance of the branch-and-bound procedure, Algorithm SA is presented for the initial feasible schedule and three heuristics : breadth-first, depth-first and best-first search are investigated depending on the candidate selection procedure. For the three heuristics the CPU time, memory space, and the number of nodes generated are computed and tested with nine small examples (6 ${\leq}$ n ${\leq}$ 4). Medium sized random problems (10 ${\leq}$ n ${\leq}$ 30) are also generated and examined. The computational results are compared and discussed for the three heuristics.

• KIISE Transactions on Computing Practices
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• v.23 no.8
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• pp.492-497
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• 2017

A hypergraph consists of a set of nodes and hyperedges that connect an arbitrary number of nodes. We employ graph traversal algorithms such as BFS and DFS to analyze or explore hypergraph data. However, the conventional BFS and DFS do not consider the structural characteristics of hyperedges. In this paper, we propose a method to record visited edges and nodes during the traversal algorithm for data stored in hypergraphDB. In the experiments, we conduct various hypergraph analyses that utilize traversal algorithms and show that our method achieves a fewer number of database accesses and faster processing time than the conventional one.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.233-236
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• 1989

This paper deals with the expert system using network configuration and input information composed of protective relays and tripped circuit breakers. This system has knowlegebase independent on network dimension because network representation consists of the type of the matrix. Therefore, the knowlege of network representation is simplified, the space of knowlege is reduced, the addition of facts to the knowlege is easy and the expansion of facts is possible. In this paper, the network representation is defined to system matrix. This expert system based on the system matrix diagnoses normal, abnormal operations of protective devices as well as possible fault sections. The brach and bound search technique is used: breadth first technique mixed with depth first technique of primitive PROLOG search technique. This system will be used for real time operations. This expert system obtaines the solution using the pattern matching in working memory without no listing approach for rule control. This paper is written in PROLOG, the A.I. language.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.958-964
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• 2015

In this paper, an object recognition method based on the depth information from the RGB-D camera, Xtion, is proposed for an indoor mobile robot. First, the RANdom SAmple Consensus (RANSAC) algorithm is applied to the point cloud obtained from the RGB-D camera to detect and remove the floor points. Next, the removed point cloud is classified by the k-means clustering method as each object's point cloud, and the normal vector of each point is obtained by using the k-d tree search. The obtained normal vectors are classified by the trained multi-layer perceptron as 18 classes and used as features for object recognition. To distinguish an object from another object, the similarity between them is measured by using Levenshtein distance. To verify the effectiveness and feasibility of the proposed object recognition method, the experiments are carried out with several similar boxes.

• Journal of Technology Innovation
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• v.21 no.1
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• pp.199-228
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• 2013

Globalization has been accelerated in today's business environment. In this situation, the opening of economies can be either an opportunity or a treat for small and medium sized enterprises (SMEs) who have limited resources. Especially, managerial perception to the opening of economies carries on significant meaning because managerial perception determines future responses and strategies. Therefore, this study examined which innovation activities are related with SMEs' positive perception to the opening of economies. The activities of innovation are classified by types of generic strategy. Also, this study scrutinized the moderating effects of external search strategy and market entry strategy. In order to test hypotheses, this study analyzed data on Korean manufacturing firms collected in the Korean Innovation Survey (KIS). As a result, SMEs conducting innovation for differentiation strategy perceived the opening of economies positively. Search breadth and search depth moderated this relationship negatively and the first entry strategy moderated this relationship positively.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.58-61
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• 2002

In this paper, we present a new generalized k-Tree-based (CU/PE) allocation model to perform dynamic resource (CU/PE) allocation/deallocation decision for the reconfigurable MSIMD/MIMD multi-dimensional (k-D) mesh-connected architectures. Those reconfigurable multi-SIMD/MIMD systems allow dynamic modes of executing tasks, which are SIMD and MIMD. The MIMD task requires only the free sub-system; however the SIMD task needs not only the free sub-system but also the corresponding free CU. In our new k-Tree-based (CU/PE) allocation model, we introduce two best-fit heuristics for the CU allocation decision: 1) the CU depth first search (CU-DFS) in O(kN$_{f}$ ) time and 2) the CU adjacent search (CU-AS) in O(k2$^{k}$ ) time. By the simulation study, the system performance of these two CU allocation strategies was also investigated. Our simulation results showed that the CU-AS and CU-DFS strategies performed the same system performance when applied for the reconfigurable MSIMD/MIMD 2-D and 3-D mesh-connected architectures.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.127-135
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• 2011

Efficient ordering of decision variables is one of the methods that find solutions quickly in the depth first search using backtracking. At this time, development of variables ordering algorithms considering dynamic and static properties of the problems is very important. However, to exploit optimal variable ordering algorithms appropriate to the problems. In this paper, we propose a problem classifying rule which provides problem type based on variables' properties, and use this rule to predict optimal type of variable ordering algorithms. We choose frequency allocation problem as a DS-type whose decision variables have dynamic and static properties, and estimate optimal variable ordering algorithm. We also show the usefulness of problem classifying rule by applying base station problem as a special case whose problem type is not generated from the presented rule.

• Journal of KIISE
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• v.44 no.10
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• pp.1045-1061
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• 2017

This paper suggests a method to expand linkages in a Linked Open Data(LOD) cloud that is a practical consequence of a semantic web. LOD cloud, contrary to the first expectation, has not been used actively because of the lack of linkages. Current method for establishing links by applying to explicit links and attaching the links to LODs have restrictions on reflecting target LODs' changes in a timely manner and maintaining them periodically. Instead of attaching them, this paper suggests that each LOD should prepare a link policy and publish it together with the LOD. The link policy specifies target LODs, predicate pairs, and similarity degrees to decide on the establishment of links. We have implemented a system that performs in-depth searching through LODs using their link policies. We have published APIs of the system to Github. Results of the experiment on the in-depth searching system with similarity degrees of 1.0 ~ 0.8 and depth level of 4 provides searching results that include 91% ~ 98% of the trustworthy links and about 170% of triples expanded.