• Journal of Korea Game Society
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• v.11 no.6
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• pp.193-199
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• 2011

Producing high density crowd simulation is time-consuming task as increasing the number of individuals in the crowds. In this paper, we propose a new control technique that can create realistic high density crowd simulation by using Smoothed Particle Hydrodynamics (SPH) method from fluid simulation field. Equations in SPH method are modified for evacuation, distance maintenance, and group maintenance forces for individual behaviors in the crowds. Experimental results showed that the proposed system could enable natural high density crowd simulation efficiently.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.297-298
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• 2007

Repetitive systems stand for a kind of systems that perform a simple task on a fixed pattern repetitively and are widely spread in industrial fields. Hence, those systems have been of much interests by many researchers, especially in the field of iterative learning control (ILC). In this paper, we propose a finite-horizon tracking control scheme for linear time-varying repetitive systems with uncertain initial conditions. The scheme is derived both analytically and numerically for state-feedback systems and only numerically for output-feedback systems. Then, it is extended to stable systems with input constraints. All numerical schemes are developed in the forms of linear matrix inequalities. A distinguished feature of the proposed scheme from the existing iterative learning control is that the scheme guarantees the tracking performance exactly even under uncertain initial conditions. The simulation results demonstrate the good performance of the proposed scheme.

• Convergence Security Journal
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• v.13 no.1
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• pp.31-36
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• 2013

The personal information protection act has been enacted from 2011 for the protection of public and private privacy. Since the application area of the law is so broad, there is a limit to covers everything in the financial field. In this paper, I'll discuss an impact and problem by the personal information protection act. and propose some new task to build an efficient personal information protection governance on financial sector.

• Journal of the Ergonomics Society of Korea
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• v.33 no.1
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• pp.1-14
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• 2014

Objective: The purpose of this study is to select the methodology for SMR HRA which has characteristics that are different from existing nuclear power plants and digital-based plants. Background: We must assure safety to preoccupy export of technology to developing countries or countries interested in nuclear application. And we can be an advanced country in nuclear technology by securing original technology in the field of SMR such as SMART. Method: THERP, which is the most representative HRA methodology among all, and RARA, which is the latest HRA methodology. This study compared and evaluated THERP and RARA. Results: As a result of applying THERP and RARA methodologies which are based on LOCA EOG task analysis result, this research concluded that RARA has higher personal errors than THERP. Conclusion: This study needs validation for LOCA, emergency operations, normal and abnormal scenarios since HRA methodology was only focused on LOCA scenario. Application: The results of this study can apply as base line data when designing MMIS, which is the main control room of SMART, and when building a simulator.

• Journal of the Society of Naval Architects of Korea
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• v.35 no.1
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• pp.80-87
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• 1998

This paper deals with the evaluation of structural safety to fatigue strength of marine propeller blades having high skew angle and operating in irregular wake field. The determination of the optimum skew angle of a propeller blade is one of the important task at the initial design stage especially in the case of high speed vessel such as container ships. A computer program system has been developed to evaluate the structural safety to fatigue strength and has been applied to several propeller blades with varying skew angle within a wide range. In the parametric study the pressure acting on the blade surface is calculated using the non-lineal lifting surface theory and the structural analysis is performed using MSC/NASTRAN. The relationship between skew angle and structural safety to fatigue strength is investigated and this paper ends with describing the optimum skew angle of a propeller blade.

• Current Industrial and Technological Trends in Aerospace
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• v.9 no.1
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• pp.37-42
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• 2011

Korea's space activity is expected more vital in the next decade. 14 Korean government satellites, with 10 satellites more over the last decade, are planned for launch between 2011 and 2020 according to the national space long-term plan. And Korean Space Launch Vehicle 2 has been developing aiming to launch in 2021. Forecasting and supply planning for the Korea Aerospace Research Institute's manpower could be essential to successfully fulfill the Korea's next decadal task in the aerospace field. In this paper, KARI's manpower is forecasted using the relations between KARI's budget and total personnel. KARI is expected to has 1,000~1,400 personnel in 2020 which is at least 400 personnels more than present.

• Hwankyungkyoyuk
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• v.24 no.1
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• pp.102-113
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• 2011

The role of teachers has been explicitly emphasized to implement the vision of sustainable development(SD). Also, it is very important to understand the way student teachers understand SD and how they interpret their own professional task in terms of SD, usually referred to as education for sustainable development(ESD). This study investigated student teachers' perceptions of SD and ESD using group interview. Key findings include, first, that they think SD as development which does not exceed the limits of natural environment, and as wise management of resources/protection of environment for future generations. They also think SD as good thing though they don't understand the contested nature of SD. Second they think ESD as education about SD, but some student teachers say they can't explain ESD. Many student teachers prefer field trip to local examples for both elementary school students and themselves. Also they will teach only what the textbook says about SD and ESD during their school placement and as teachers. So it will be the beginning of ESD in school to include SD in the curriculum for students and student teachers. It is suggested to study student teachers' perception of SD focussing on how they think the relationship between protection of environment and economic growth.

• Journal of Construction Engineering and Project Management
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• v.8 no.1
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• pp.10-21
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• 2018

Many construction projects involve a plethora of safety-related problems that can cause loss of productivity, diminished revenue, time overruns, and legal challenges. Incorporating data collection and analytics methods can help overcome the root causes of many such problems. However, in a dynamic construction workplace collecting data from a large number of resources is not a trivial task and can be costly, while many contractors lack the motivation to incorporate technology in their activities. In this research, an Android-based mobile application, Preemptive Construction Site Safety (PCS2) is developed and tested for real-time location tracking, trajectory prediction, and prevention of potential collisions between workers and site hazards. PCS2 uses ubiquitous mobile technology (smartphones) for positional data collection, and a robust trajectory prediction technique that couples hidden Markov model (HMM) with risk-taking behavior modeling. The effectiveness of PCS2 is evaluated in field experiments where impending collisions are predicted and safety alerts are generated with enough lead time for the user. With further improvement in interface design and underlying mathematical models, PCS2 will have practical benefits in large scale multi-agent construction worksites by significantly reducing the likelihood of proximity-related accidents between workers and equipment.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.123-131
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• 2015

Training neural networks is a complex task with great importance in the field of supervised learning. In the training process, a set of input-output patterns is repeated to an artificial neural network (ANN). From those patterns weights of all the interconnections between neurons are adjusted until the specified input yields the desired output. In this paper, a new hybrid algorithm is proposed for global optimization of connection weights in an ANN. Dynamic swarms are shown to converge rapidly during the initial stages of a global search, but around the global optimum, the search process becomes very slow. In contrast, the gradient descent method can achieve faster convergence speed around the global optimum, and at the same time, the convergence accuracy can be relatively high. Therefore, the proposed hybrid algorithm combines the dynamic particle swarm optimization (DPSO) algorithm with the backpropagation (BP) algorithm, also referred to as the DPSO-BP algorithm, to train the weights of an ANN. In this paper, we intend to show the superiority (time performance and quality of solution) of the proposed hybrid algorithm (DPSO-BP) over other more standard algorithms in neural network training. The algorithms are compared using two different datasets, and the results are simulated.

• Journal of Power Electronics
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• v.8 no.2
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• pp.181-191
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• 2008

The task performed by induction motors grows increasingly complex in modern industry and hence improvements are sought in the field of fault diagnosis. It is essential to diagnose faults at their very inception, as unscheduled machine down time can upset critical dead lines and cause heavy financial losses. Artificial intelligence (AI) techniques have proved their ability in detection of incipient faults in electrical machines. This paper presents an application of AI techniques for the detection of inter-turn insulation and bearing wear faults in single-phase induction motors. The single-phase induction motor is considered a proto type model to create inter-turn insulation and bearing wear faults. The experimental data for motor intake current, rotor speed, stator winding temperature, bearing temperature and noise of the motor under running condition was generated in the laboratory. The different types of fault detectors were developed based upon three different AI techniques. The input parameters for these detectors were varied from two to five sequentially. The comparisons were made and the best fault detector was determined.