• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1334-1337
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• 2004

This paper presents a novel method to speed up neural network (NN) based face detection systems. NN-based face detection can be viewed as a classification and search problem. The proposed method formulates the search problem as an integer nonlinear optimization problem (INLP) and expands the basic particle swarm optimization (PSO) to solve it. PSO works with a population of particles, each representing a subwindow in an input image. The subwindows are evaluated by how well they match a NN-based face filter. A face is indicated when the filter response of the best particle is above a given threshold. To achieve better performance, the influence of PSO parameter settings on the search performance was investigated. Experiments show that with fine-adjusted parameters, the proposed method leads to a speedup of 94 on 320${\times}$240 images compared to the traditional exhaustive search method.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.48-57
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• 2017

In the last few years, banks have experienced more challenging market than any other times. They need to find new ways to reconnect with their customers and rebuild their trust. But in the race to the future some banks are taking clear lead. Research works show that while high perform leading banks are different, they also share some common characteristics and principles that have allowed them to move ahead to profitable growth. Cost cutting is no longer enough to succeed in tomorrow's world. Instead, the IT function needs to work shoulder-to-shoulder with the business to support the growth agenda. Therefore "C" level's attention is moving from cost reduction towards customer experience, speeding to market for new offerings, analytics and distribution channel enhancements, taking advantage of several levers that will shape the technology agenda for the high performing organization. Next generation of digital core-banking solutions will improve pre-existing capabilities, introduce new innovations and drive qualities such as flexibility and scalability to support time to market.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.42
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• pp.193-200
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• 1997

For the industrialized nations, the manufacturing industries have becomes increasingly difficult to meet customers' demands and complete on the international market. Thus, manufacturing industries must be able tn react quickly to prevailing market conditions and to maximize the utilization of resources. Within recent years, computer technology, in conjunction with software technology, has made available to the manufacturer tools which can greatly improve their reaction to a new market situation, speeding up the design of products, improving process planning, maximizing resource scheduling, and streamling production flow through factories. This paper investigate "CALS" systems for motor's companies. The purpose of this study is to give some ideas of finding a better way of constructing "CALS" system in Korea motor's companies.a motor's companies.

• Journal of the Korean Society of Safety
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• v.28 no.5
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• pp.66-70
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• 2013

This study examined the relative effects of education and eco-IVIS(in-vehicle information system) to reduce fuel consumption and greenhouse gas emissions. Also the study investigated the increasing of driving workload when drivers interact with intervention technique. Thirty participants randomly assigned into two groups(training and eco-IVIS) and conducted driving before and after the each intervention technique. While driving, we observed three driving behaviors: Frequency of excessive RPM, percent of speeding, and mean fuel efficiency. Also the Driver Activity Load Index was used to rate participants' subjective ratings of driving workload. Although the results showed positive impact of both education and eco-IVIS to increasing the eco-driving behaviors, eco-IVIS was more effective than education. However, we found comparable level of driving workload in the education and eco-IVIS.

• International Journal of Highway Engineering
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• v.16 no.5
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• pp.83-90
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• 2014

PURPOSES : The purpose of this study is to identify the factors affecting the effectiveness of speed limit change that is defined as the amount of increased travel speed. METHODS : A ordered logit model was adopted to analyze the relationship between the change in travel speed and contributing factors. A stretch of Kyungbu freeway was selected for the analysis because the Korea expressway corporation has raised speed limit from 100km/h to 110km/h since September 1st in 2010. RESULTS : The results showed that geometric design elements, speeding cameras, and section length were identified as factors contributing the effectiveness. Contributing geometric design elements include the number of horizontal curves and vertical curves that do not meet the design requirement with 110km/h speed limit. CONCLUSIONS : The outcome of this study will be used for establishing various traffic operations and control strategies for freeway speed management.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1327-1335
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• 2002

The shock wave process represents an abrupt change in fluid properties, in which finite variations in pressure, temperature, and density occur over the shock thickness which is comparable to the mean free path of the gas molecules involved. This shock wave fluid phenomenon is simulated by using the finite difference lattice Boltzmann method (FDLBM). In this paper, a new model is proposed using the lattice BGK compressible fluid model in FDLBM for the purpose of speeding up the calculation as well as stabilizing the numerical scheme. The numerical results of the proposed model show good agreement with the theoretical predictions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3520-3537
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• 2014

Video copy detection methods have emerged in recent years for a variety of applications. However, the lack of efficiency in the usual retrieval systems restricts their use. In this paper, we propose a parallel implementation strategy for content based video copy detection (CBCD) by using a multi-core processor. This strategy can support video copy detection effectively, and the processing time tends to decrease linearly as the number of processors increases. Experiments have shown that our approach is successful in speeding up computation and as well as in keeping the performance.

• Computers and Concrete
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• v.18 no.5
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• pp.1019-1039
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• 2016

In this paper, a parallel algorithm of nonlinear dynamic analysis of three-dimensional (3D) reinforced concrete (RC) frame structures based on the platform of graphics processing unit (GPU) is proposed. Time integration is performed using Newmark method for nonlinear implicit dynamic analysis and parallelization strategies are presented. Correspondingly, a parallel Preconditioned Conjugate Gradients (PCG) solver on GPU is introduced for repeating solution of the equilibrium equations for each time step. The RC frames were simulated using fiber beam model to capture nonlinear behaviors of concrete and reinforcing bars. The parallel finite element program is developed utilizing Compute Unified Device Architecture (CUDA). The accuracy of the GPU-based parallel program including single precision and double precision was verified in comparison with ABAQUS. The numerical results demonstrated that the proposed algorithm can take full advantage of the parallel architecture of the GPU, and achieve the goal of speeding up the computation compared with CPU.

• Annual Conference on Human and Language Technology
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• 2012.10a
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• pp.113-116
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• 2012

UTagger는 한국어 의미 처리를 위해 개발된 형태소분석기이며 의미 분열 기능도 가지고 있다. 정확률이 매우 높고 다앙한 기능을 갖추고 있으나 이전에 개발된 다른 형태소 분석기에 비하여 속도가 느리다는 단점을 가지고 있었다. 형태소 분석기의 빠른 속도는 많은 분야에서 요구되고 있기 때문에 본 논문에서는 UTagger의 정확률을 유지하면서 속도를 향상시키는 캐시(Cache) 방법과, 정확률을 조금 낮추면서 향상시키는 다앙한 방법들을 제시한다. 또한 상황에 따라 적합한 방법을 선택할 때 참조가 되도록 하기 위해 각 방법들 실험 결과를 정리한다.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.853-858
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• 1993

The error back-propagation(BP) algorithm is widely used for finding optimum weights of multi-layer neural networks. However, the critical drawback of the BP algorithm is its slow convergence of error. The major reason for this slow convergence is the premature saturation which is a phenomenon that the error of a neural network stays almost constant for some period time during learning. An inappropriate selections of initial weights cause each neuron to be trapped in the premature saturation state, which brings in slow convergence speed of the multi-layer neural network. In this paper, to overcome the above problem, Micro-Genetic algorithms(.mu.-GAs) which can allow to find the near-optimal values, are used to select the proper weights and slopes of activation function of neurons. The effectiveness of the proposed algorithms will be demonstrated by some computer simulations of two d.o.f planar robot manipulator.