• Journal of KIISE:Computing Practices and Letters
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• v.13 no.2
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• pp.100-109
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• 2007

Object recognition of service robots is very important for most of services such as delivery, and errand. Conventional methods are based on the geometric models in static industrial environments, but they have limitations in indoor environments where the condition is changable and the movement of service robots occur because the interesting object can be occluded or small in the image according to their location. For solving these uncertain situations, in this paper, we propose the method that exploits observed objects as context information for predicting interesting one. For this, we propose the method for modeling domain knowledge in probabilistic frame by adopting Bayesian networks and ontology together, and creating knowledge model dynamically to extend reasoning models. We verify the performance of our method through the experiments and show the merit of inductive reasoning in the probabilistic model

• Journal of Korean Society of Steel Construction
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• v.28 no.6
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• pp.395-402
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• 2016

Space frame structures considering the components such as forms, layers, grids, etc. are possible to form a large space without interior columns. Here, steels having the yield strengths of 210 MPa to 450 MPa are generally used. The high strength steel (i.e., yield strength of 690 MPa) having suitable weldability, aseismicity and economics have been recently developed. In this paper, the high strength steel is applied to the space frame structures in order to analytically find out their transient responses considering the material and geometric nonlinearities. For various circular dome types of space frame structures, the modal analysis and nonlinear transient analysis are carried out using nonlinear three dimensional finite element analysis.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.853-862
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• 2003

Many more use e-mail purely on a personal basis and the pool of e-mail users is growing daily. Also, the amount of mails, which are transmitted in electronic commerce, is getting more and more. Because of its convenience, a mass of spam mails is flooding everyday. And yet automated techniques for learning to filter e-mail have yet to significantly affect the e-mail market. This paper suggests Web Mail Filtering Agent for Personalized Classification, which automatically manages mails adjusting to the user. It is based on web mail, which can be logged in any time, any place and has no limitation in any system. In case new mails are received, it first makes some personal rules in use of the result of observation ; and based on the personal rules, it automatically classifies the mails into categories according to the contents of mails and saves the classified mails in the relevant folders or deletes the unnecessary mails and spam mails. And, we applied Bayesian Algorithm using Dynamic Threshold for our system's accuracy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.4
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• pp.73-81
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• 1987

Dynamic analysis of tethers and platforms of tension leg platforms(TLP's) subjected to wave forces is presented in this paper. The efficient platform analysis model which can adequately include the dynamic characteristics of tethers is proposed, and the platform motion analyses are mainly carried out using this model. Also, the tether analyses are performed utilizing the finite element method with geometric stiffnesses due to the pre-tension in tethers. Two different. TLP's located in 1000 ft and 3000 ft waters are chosen as example structures. For the purpose of comparison, analyses are also carried out by two different models. One is the conventional model in which the tethers are idealized as weightless springs. The other is the coupled model of platform and tethers. A comparison has been made between the results obtained by three different models mentioned above. Also, effects of the conventional stiffnesses of tethers and the wave exciting forces acting on tethers for the tether responses are examined.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.1
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• pp.79-87
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• 2013

An isogeometric topological shape optimization method is developed using the level sets and Heaviside enrichments. In the level set method, the initial domain is kept fixed and its boundary is represented by an implicit moving boundary embedded in the level set functions, which facilitates to handle complicated topological shape changes. The Heaviside enrichment improves the isogeometric analysis by adding some enrichment functions to model the internal boundaries. The proposed topological shape optimization method has several benefits: exact geometric models can be obtained using the isogeometric approach and the limitation of tensor-product patches can be overcome using the Heaviside enrichments to represent the internal voids. Even in a single patch, discontinuous displacement fields as well as smooth stress field can be obtained. Since the level sets offer the implicit moving boundary inside the domain, it is easy to represent the topological shape variations in the isogeometric analysis using Heaviside enrichments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1499-1506
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• 2017

The use of smartphones and the launch of various apps have increased exponentially, and malicious apps have also increased. Existing app recommendation systems have been limited to operate based on static information analysis such as ratings, comments, and popularity categories of other users who are online. In this paper, we first propose a robust app recommendation system that realistically uses dynamic information of apps actually used in smartphone and considers static information and dynamic information at the same time. In other words, this paper proposes a robust Android app recommendation system by partially reflecting the time of the app, the frequency of use of the app, the interaction between the app and the app, and the number of contact with the Android kernel. As a result of the performance evaluation, the proposed method proved to be a robust and efficient app recommendation system.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.17-24
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• 2020

The traveling salesman problem is an algorithmic problem tasked with finding the shortest route that a salesman visits, visiting each city and returning to the started city. Due to the exponential time complexity of TSP, it's hard to implement on cases like amusement park or delivery. Also, TSP is hard to meet user's demand that is associated with multi-dimensional attributes like travel time, interests, waiting time because it uses only one attribute - distance between nodes. This paper proposed Top-n Skyline-Multi Dimension TSP to resolve formerly adverted problems. The proposed algorithm finds the shortest route faster than the existing method by decreasing the number of operations, selecting multi-dimensional nodes according to the dominance of skyline. In the simulation, we compared computation time of dynamic programming algorithm to the proposed a TS-MDT algorithm, and it showed that TS-MDT was faster than dynamic programming algorithm.

• The KIPS Transactions:PartA
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• v.9A no.4
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• pp.497-502
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• 2002

Conditional branches can severely limit the performance of instruction level parallelism by causing branch penalties. 2-level adaptive branch predictors were developed to get accurate branch prediction in high performance superscalar processors. Although 2 level adaptive branch predictors achieve very high prediction accuracy, they tend to be very costly. In this paper, set-associative cached correlated 2-level branch predictors are proposed to overcome the cost problem in conventional 2-level adaptive branch predictors. According to simulation results, cached correlated predictors deliver higher prediction accuracy than conventional predictors at a significantly lower cost. The best misprediction rates of global and local cached correlated predictors using set-associative caches are 5.99% and 6.28% respectively. They achieve 54% and 17% improvements over those of the conventional 2-level adaptive branch predictors.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.4
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• pp.191-199
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• 2003

The inelastic response of many structural steel and reinforced concrete structures subject to extreme loadings can be characterized by elastoplastic behaviors. Although excursion beyond the elastic range is usually not permitted under normal conditions of service, the extent of permanent damage a structure may sustain when subjected to extreme conditions, such as severe blast or earthquake loading, is frequently of interest to the engineer. A blast is usually the result of an explosion defined as a "sudden expansion". This paper discusses the basic concept that defines blast loadings on structures and corresponding elastoplastic structural response (displacement, velocity, and acceleration) and try to explain a crack propagation of concrete in sudden expansion. According to nonlinear finite element analysis, the crack forms of static and dynamic states displayed different in RC structural members. This paper also provides useful data for the dynamic fracture analysis of RC frame structures.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.582-584
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• 2014

Conventional Web crawlers are reducing overhead burden on the server to ensure the integrity of data optimization measures have been continuously developed. The amount of data growing exponentially faster among those data, then the data needs to be collected should be used to the modern web crawler is the indispensable presence. In this paper, suggested that the existing Web crawler and Web crawler approach efficiency comparison and analysis. In addition, based on the results, compared to suggest an optimized technique, Web crawlers, data collection cycle dynamically reduces the overhead of the server system was designed for. This is a Web crawler approach will be utilized in the field of the search system.