• Proceedings of the KSPS conference
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• 2003.05a
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• pp.215-218
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• 2003

In this paper we apply PMC (parallel model combination) to speech recognition system online. As a representative of model based noise compensation techniques, PMC compensates environmental mismatch by combining pretrained clean speech models and real-time estimated noise information. This is very effective approach for compensating extreme environmental mismatch but is inadequate to use in on-line system for heavy computational cost. To reduce the computational cost and to apply PMC online, we use a noise masking effect - the energy in a frequency band is dominated either by clean speech energy or by noise energy - in the process of model compensation. Experiments on artificially produced noisy speech data confirm that the proposed technique is fast and effective for the on-line model compensation.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.53-62
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• 2018

As the performance of computer hardware has been increased in recent years, more realistic computer generated objects can be created and presented in personal computers and portable digital devices as well. For this reason, digital contents, including computer graphics, require virtual objects that are more realistic and representable in real-time on various devices, thus it requires more computational costs. In order to support the production of contents including computer graphics, games, and animations on multi-platform, Unity or unreal engines are mainly used. To represent more realistic behavior of virtual objects in a simulation, a virtual object must collide with other virtual objects and present the plausible interaction, as in the real world. However, such dynamic simulation requires a large amount of computational cost, and most portable devices cannot provide these dynamic simulations in real-time. In this paper, we proposed a GPGPU computation based dynamic cloth simulation to represent collision and response with spherical object in real-time. We believe that the proposed method can be useful for readily producing realistic digital contents.

• Information Systems Review
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• v.16 no.1
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• pp.37-50
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• 2014

Conventional case-based reasoning (CBR) does not perform efficiently for high volume dataset because of case-retrieval time. In order to overcome this problem, some previous researches suggest clustering a case-base into several small groups, and retrieve neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performances than the conventional CBR. This paper suggests a new hybrid case-based reasoning method which dynamically composing a searching pool for each target case. This method is applied to diagnose for the heart disease dataset. The results show that the suggested hybrid method produces statistically the same level of predictive performances with using significantly less computational cost than the CBR method and also outperforms the basic clustering-CBR (C-CBR) method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.506-512
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• 2006

In this paper, we propose a lot-sizing and scheduling problem that seeks to minimize the sum of production cost and inventory cost over a given planning horizon while considering idle state of a machine in a batch production system. For this problem, we develop an integer programming model. And, we develop an efficient 2-phase heuristic algorithm to find a high quality feasible solution within reasonable time bounds. In the first phase, we seek to minimize the production cost by assigning batches to machines. Then, in the second phase, we find a production sequence of batches that reduces the inventory cost, while considering adding or deleting idle states between batches. Computational results show that the developed heuristic algorithm finds excellent feasible solutions within reasonable time bounds. Also, we could significantly reduce the total cost consisting of production cost and inventory cost by using the developed heuristic algorithm at a real manufacturing system that produces zinc alloys.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.45-52
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• 2020

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Network(SCN). One of keys issues in the current SCN research area involves minimizing both production and distribution costs. This study deals with finding an optimal solution for minimizing the total cost of production and distribution problems in supply chain network. First, we presented an integrated mathematical model that satisfies the minimum cost in the supply chain. To solve the presented mathematical model, we used a genetic algorithm with an excellent searching ability for complicated solution space. To represent the given model effectively, the matrix based real-number coding schema is used. The difference rate of the objective function value for the termination condition is applied. Computational experimental results show that the real size problems we encountered can be solved within a reasonable time.

• Korean Journal of Computational Design and Engineering
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• v.16 no.5
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• pp.370-379
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• 2011

The increasing complexity of complex buildings, such as high-rise buildings and underground subway stations, presents new challenges to firefighters. In a fire in complex buildings, the importance of the collaboration between firefighters is clear. The increased demand on firefighter training for such environment is now evident. Due to cost, time, and safety issues, it is impossible to experience a real fire in such environments for training. In addition, the use of real fire for training does not enable repeatable training and the evaluation of the training is difficult. We developed a team-based firefighter training simulator for complex buildings using the virtual reality technology. It provides the training and evaluation of firefighting and mission-based team training. To model real fire phenomena in virtual space, a numerical analysis method based on fire dynamics is used. To achieve an immersive virtual environment, an augmented reality technique for the compensation of real world image and a haptic technique for heat experience are adopted. The developed training simulator can help the firefighter to respond to large and complex firefighting scenarios, while maintaining the safety of the trainees.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2439-2442
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• 2000

This paper presents a practical On-The-Fly(OTF) integer ambiguity resolution algorithm for real-time precise positioning with low cost, $L_1$ single frequency, conventional C/A code GPS receiver. A state reconfiguration scheme is adopted in the Kalman filter to deal with the variation of ambiguity states caused by varying sets of visible GPS satellites. The proposed algorithm reduces the ambiguity search space from the coarse m-level C/A code pseudorange measurements of the conventional C/A code reciever, thereby reducing the computational time. Simulation results are presented to show that the algorithm achieves a cm-level accuracy.

• Smart Structures and Systems
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• v.15 no.3
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• pp.913-929
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• 2015

Hybrid simulation is increasingly being recognized as a powerful technique for laboratory testing. It offers the opportunity for global system evaluation of civil infrastructure systems subject to extreme dynamic loading, often with a significant reduction in time and cost. In this approach, a reference structure/system is partitioned into two or more substructures. The portion of the structural system designated as 'physical' or 'experimental' is tested in the laboratory, while other portions are replaced with a computational model. Many researchers have quite effectively used hybrid simulation (HS) and real-time hybrid simulation (RTHS) methods for examination and verification of existing and new design concepts and proposed structural systems or devices. This paper provides a detailed perspective of the enabling role that HS and RTHS methods have played in advancing the practice of earthquake engineering. Herein, our focus is on investigations related to earthquake engineering, those with CURATED data available in their entirety in the NEES Data Repository.

• Korean Journal of Computational Design and Engineering
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• v.12 no.5
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• pp.382-394
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• 2007

Nowadays, manufacturing industries undergo constantly growing pressures for global competitions, and they must shorten time and cost in product development and production to response varied customers' requirements. Digital virtual manufacturing is a technology that can facilitate effective product development and agile production by using digital models representing the physical and logical schema and the behavior of real manufacturing systems including products, processes, manufacturing resources and plants. For successful applications of this technology, a digital virtual factory as a well-designed and integrated environment is essential. In this paper, we developed a new classification and coding system for effective managements of digital virtual factory objects, and implement a supporting application to verify and apply it. Furthermore, a digital virtual factory layout management system based on the classification and coding system has developed using XML, Visual Basic.NET and FactoryCAD. By some case studies for automotive general assembly shops of a Korean automotive company, efficient management of factory objects and reduction of time and cost in digital virtual factory constructions are possible.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.6
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• pp.306-315
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• 2017

This study introduces a software for real-time assessment of combustion stability for utility gas turbines. The software was written with LabView, and implemented the time-domain kurtosis as a parameter to proactively access the instantaneous combustion stability during operation of the industrial gas turbine. The simple time-domain assessment algorithm incorporated in the software is advantageous over conventional frequency-domain signal processing of dynamic pressure signal since it reduces the computational cost, thereby making the algorithm more appropriate for real-time monitoring of combustion stability. Benchmark data obtained from a model gas turbine combustor were used for the reproducibility test of the software. The assessment obtained from the software agreed well with previously published results, indicating that incorporation of the software could enhance the performance of systems monitoring the combustion stability for gas turbines during power generation.