• Journal of Korea Game Society
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• 제11권6호
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• pp.61-70
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• 2011

In this paper, we propose a defense NPC control model in the soccer game by applying the Decision Tree learning algorithm. The proposed model extracts the direction patterns and the action patterns generated by many soccer game users, and applies these patterns to the Decision Tree learning algorithm. Then, the proposed model decides the direction and the action according to the learned Decision Tree. Experimental results show that the proposed model takes some time to learn the Decision Tree while the proposed model takes 0.001-0.003 milliseconds to decide the direction and the action based on the learned Decision Tree. Therefore, the proposed model can control NPC in the soccer game system in real time. Also, the proposed model achieves higher accuracy than a previous model (Letia98); because the proposed model can utilize current state information, its analyzed information, and previous state information.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1521-1524
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• 2003

In this paper, we propose a "Distance Correlation Selection operator (DCS)" as a new selection operator. For Genetic Algorithm (GA), many improvements have been proposed. The MGG (Minimal Generation Gap) model proposed by Satoh et.al. shows good performance. The MGG model has all advantages of conventional models and the ability of avoiding the premature convergence and suppressing the evolutionary stagnation. The proposed method is an extension of selection operator in the original MGG model. Generally, GA has two types of selection operators, one is "selection for reproduction", and the other is "selection for survival"; the former is for crossover and the latter is the individuals which survive to the next generation. The proposed method is an extension of the former. The proposed method utilizes distance information between individuals. From this extension, the proposed method aims to expand a search area and improve ability to search solution. The performance of the proposed method is examined with several standard test functions. The experimental results show good performance better than the original MGG model.

• Proceedings of the KIPE Conference
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• 전력전자학회 2001년도 Proceedings ICPE 01 2001 International Conference on Power Electronics
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• pp.184-188
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• 2001

In this paper, a new fully digital control method for single-phase UPS inverter, which is based on the double control loop such as the outer voltage control loop and inner current control loop, is proposed. The inner current control loop is designed and implemented in the form of internal model control and takes the presence of computational time-delay into account. Therefore, this method provides an overshoot-free reference-to-output response. In the proposed scheme, the outer voltage control loop employing P controller with resonance model implemented by a DSP is introduced. The proposed resonance model has an infinite gain at resonant frequency, and it exhibits a function similar to an integrator for AC component. Thus the outer voltage control loop causes no steady state error as regard to both magnitude and phase. The effectiveness of the proposed control system has been demonstrated by the simulation and experimental results respectively.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제35권4호
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• pp.186-193
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• 2012

Assessing service quality and satisfaction is the essential part of service science. In this study, for G2B electronic commerce service composed of information systems and human resources, a composite research model for exploring factors of service quality satisfaction is proposed. The proposed model uses SERVQUAL's five quality dimensions as independent antecedent factors and usefulness and ease-of-use of the technology acceptance model as mediating factors. A case of a G2B purchase service is empirically studied using the proposed model. The result shows that the proposed composite model is good and appropriate for explaining the characteristics of G2B services.

• Journal of Information Technology Applications and Management
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• 제27권6호
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• pp.141-151
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• 2020

The job mismatch between job seekers and SMEs is becoming more and more intensifying with the serious difficulties in youth employment. In this study, a bi-directional content-based metric learning model is proposed to recommend suitable jobs for job seekers and suitable job seekers for SMEs, respectively. The proposed model not only enables bi-directional recommendation, but also enables HR matching without relearning for new job seekers and new job offers. As a result of the experiment, the proposed model showed superior performance in terms of precision, recall, and f1 than the existing collaborative filtering model named NCF+GMF. The proposed model is also confirmed that it is an evolutionary model that improves performance as training data increases.

• Journal of the Semiconductor & Display Technology
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• 제20권2호
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• pp.103-108
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• 2021

The TCD is used as one of the indicators for determining whether TSV Hole is defective. If the TCD is not normal size, it can lead to contamination of the CMP equipment or failure to connect the upper and lower chips. We propose a deep learning model for measuring the TCD. To verify the performance of the proposed model, we compared the prediction results of the proposed model for 2461 via holes with the CD-SEM measurement data and the prediction results of the existing model. Although the number of trainable parameters in the proposed model was about one two-thousandth of the existing model, the results were comparable. The experiment showed that the correlation between CD-SEM and the prediction results of the proposed model measured 98%, the mean absolute difference was 0.051um, the standard deviation of the absolute difference was 0.045um, and the maximum absolute difference was 0.299um on average.

• Journal of Korea Society of Industrial Information Systems
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• 제15권3호
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• pp.59-65
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• 2010

This paper proposes a modified heuristic mixed model assembly line (MMAL) balancing algorithm that provides consistent station assignments on a model by model basis as well as on a station by station. Basically, some of single model line balancing techniques are modified and incorporated to be fit into the MMAL. The proposed algorithm is based on N.T. Thomopoulos' [8] method and supplemented with several well proven single model line balancing techniques proposed in the literature until recently. Hoffman's precedence matrix [2] is used to indicate the ordering relations among tasks. Arcus' Rule IX [1] is applied to generate rapidly a fairly large number of feasible solutions. Consequently, this proposed algorithm reduces the fluctuations in operation times among the models as well as the stations and the balance delays. A numerical example shows that the proposed algorithm can provide a good feasible solution in a relatively short time and generate relatively better solutions comparing to other three existing methods.

• Geomechanics and Engineering
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• 제35권2호
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• pp.165-179
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• 2023

This study investigates the uplift capacity of a single vertical belled pile buried at shallow depth in dry sand. The laboratory model experiments are conducted with different pile-tip angles and relative densities. In addition, image and FEM analyses are performed to observe the failure surface of the belled pile for different pile-tip angles and relative densities. Accordingly, the uplift capacity and failure angle in the failure surface of the belled pile were found to depend on the belled pile-tip angle and relative density. A predictive model for the uplift capacity of the belled pile was proposed considering the relative density and belled pile-tip angle based on a previous limit equilibrium equation. To validate the applicability of the proposed model, the values calculated using the proposed and previous models were compared to those obtained through a laboratory model experiment. The proposed model had the best agreement with the laboratory model experiment.

• Proceedings of the Korean Information Science Society Conference
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• 한국정보과학회 2002년도 봄 학술발표논문집 Vol.29 No.1 (B)
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• pp.244-246
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• 2002

The rapid increase of E-commerce market requires a solution to assist the buyer to find his or her interested items. The intelligent agent model is one of the approaches to help the buyers in purchasing items in outline market. In this paper, the user query processing model in the item recommendation agent is proposed. In the proposed model, the retrieval result is affected by the automatically generated queries from user preference information as well as the queries explicitly given by user. Therefore, the proposed model can provide the customized search results to each user.

• Journal of Institute of Control, Robotics and Systems
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• 제10권5호
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• pp.450-457
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• 2004

In this research, the automatic synthesis of knowledge models is proposed. which are the basis of the methods using qualitative models adapted widely in fault diagnosis and hazard evaluation of chemical processes. To provide an easy and fast way to construct accurate causal model of the target process, the Role-Behavior modeling method is developed to represent the knowledge of modularized process units. In this modeling method, Fault-Behavior model and Structure-Role model present the relationship of the internal behaviors and faults in the process units and the relationship between process units respectively. Through the multiple modeling techniques, the knowledge is separated into what is independent of process and dependent on process to provide the extensibility and portability in model building, and possibility in the automatic synthesis. By taking advantage of the Role-Behavior Model, an algorithm is proposed to synthesize the plant-wide causal model, Fault-Causality Graph (FCG) from specific Fault-Behavior models of the each unit process, which are derived from generic Fault-Behavior models and Structure-Role model. To validate the proposed modeling method and algorithm, a system for building FCG model is developed on G2, an expert system development tool. Case study such as CSTR with recycle using the developed system showed that the proposed method and algorithm were remarkably effective in synthesizing the causal knowledge models for diagnosis of chemical processes.