• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.6
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• pp.286-304
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• 2017

In this study, we proposed a new-type of circular perforated caisson breakwater consisting of a bundle of latticed blocks that can be applied to a small port such as a fishing port, and numerically investigated the hydraulic characteristics of the breakwater. The numerical method used in this study is OLAFOAM which newly added wave generation module, porous media analysis module and reflected wave control module based on OpenFOAM that is open source CFD software published under the GPL license. To investigate the applicability of OLAFOAM, the variations of wave pressure acting on the three-dimensional slit caisson were compared to the previous experimental results under the regular wave conditions, and then the performance for irregular waves was examined from the reproducibility of the target irregular waves and frequency spectrum analysis. As a result, a series of numerical simulations for the new-type of circular perforated caisson breakwaters, which is similar to slit caisson breakwater, was carried out under the irregular wave actions. The hydraulic characteristics of the breakwater such as wave overtopping, reflection, and wave pressure distribution were carefully investigated respect to the significant wave height and period, the wave chamber width, and the interconnectivity between them. The numerical results revealed that the wave pressure acting on the new-type of circular perforated caisson breakwaters was considerably smaller than the result of the impermeable vertical wall computed by the Goda equation. Also, the reflection of the new-type caisson breakwater was similar to the variation range of the reflection coefficient of the existing slit caisson breakwater.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.180-186
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• 2020

ICT convergence using smart livestock is that in the first-generation dairy smart farm model, each device made by several manufacturers uses its own communication method, limiting the mutual operation of each device. This study uses a model based on open control technology to secure interoperability of existing ICT devices and to manage data efficiently. The open integrated control derived from this process is the software interface structure of Open API. It is an observer that serves as real-time data collection according to the communication method of ICT devices and sensors located at each end. It consists of a broker that connects and transmits to the upper integrated management server. As a result of the performance analysis through verification of two first-generation dairy smart farm model sites, the average daily milk production increased compared to the previous year (farm A 5.13%, farm B 1.33%, p<0.05). Cow days open (DO) was reduced by 17.5% on farm A and 13.3% for farm B(p<0.05). Cows require an adaptation period after the introduction of the ICT device, but if continuous effects are observed, the effect of production can be expected to increase gradually.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3353-3359
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• 2011

The co-generation system consisted of gas a turbine, a steam turbine, heat recovery steam generator and a heat exchangers for district heating was investigated in the present study. A back-pressure steam turbine (non-condensing type) was used. A partial load analysis according to the outdoor temperature in winter was conducted and optimal thermal load and power conditions was examined using the commercial computing software Thermoflex. As a result, under a constant thermal load, the power outputs of gas turbine and overall system increased as an outdoor temperature decreased. On the other hand, the reduction in exhaust gas temperature led to the decrease in output of steam turbine. Considering the portion of gas turbine in overall system in terms of the power output, it can be known that the tendency in power output of overall system was similar to that of the gas turbine.

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1045-1055
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• 2007

Latent topic models are statistical models which automatically captures salient patterns or correlation among features underlying a data collection in a probabilistic way. They are gaining an increased popularity as an effective tool in the application of automatic semantic feature extraction from text corpus, multimedia data analysis including image data, and bioinformatics. Among the important issues for the effectiveness in the application of latent topic models to the massive data set is the efficient learning of the model. The paper proposes an accelerated learning technique for PLSA model, one of the popular latent topic models, by an incremental EM algorithm instead of conventional EM algorithm. The incremental EM algorithm can be characterized by the employment of a series of partial E-steps that are performed on the corresponding subsets of the entire data collection, unlike in the conventional EM algorithm where one batch E-step is done for the whole data set. By the replacement of a single batch E-M step with a series of partial E-steps and M-steps, the inference result for the previous data subset can be directly reflected to the next inference process, which can enhance the learning speed for the entire data set. The algorithm is advantageous also in that it is guaranteed to converge to a local maximum solution and can be easily implemented just with slight modification of the existing algorithm based on the conventional EM. We present the basic application of the incremental EM algorithm to the learning of PLSA and empirically evaluate the acceleration performance with several possible data partitioning methods for the practical application. The experimental results on a real-world news data set show that the proposed approach can accomplish a meaningful enhancement of the convergence rate in the learning of latent topic model. Additionally, we present an interesting result which supports a possible synergistic effect of the combination of incremental EM algorithm with parallel computing.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.104-109
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• 2010

The lighting reflection is a common problem in image analysis and causes the many difficulties to extract distinct features in related fields. Furthermore, the problem grows in the rainy night. In this paper, we aim to remove light reflection effects and reconstruct a road surface without lighting reflections in order to extract distinct features. The proposed method utilizes a 3D analysis based on a multiple geometry using captured images, with which we can combine each reflected areas; that is, we can remove lighting reflection effects and reconstruct the surface. At first, the regions of lighting sources and reflected surfaces are extracted by local maxima based on vertically projected intensity-histograms. After that, a fundamental matrix and homography matrix among multiple images are calculated by corresponding points in each image. Finally, we combine each surface by selecting minimum value among multiple images and replace it on a target image. The proposed method can reduces lighting reflection effects and the property on the surface is not lost. While the experimental results with collected data shows plausible performance comparing to the speed, reflection-overlapping areas which can not be reconstructed remain in the result. In order to solve this problem, a new reflection model needs to be constructed.

• Journal of KIISE:Software and Applications
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• v.33 no.5
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• pp.481-488
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• 2006

The performance of face recognition methods using subspace projection is directly related to the characteristics of their basis images, especially in the cases of local distortion or partial occlusion. In order for a subspace projection method to be robust to local distortion and partial occlusion, the basis images generated by the method should exhibit a part-based local representation. We propose an effective part-based local representation method named locally salient ICA (LS-ICA) method for face recognition that is robust to local distortion and partial occlusion. The LS-ICA method only employs locally salient information from important facial parts in order to maximize the benefit of applying the idea of 'recognition by parts.' It creates part-based local basis images by imposing additional localization constraint in the process of computing ICA architecture I basis images. We have contrasted the LS-ICA method with other part-based representations such as LNMF (Localized Non-negative Matrix Factorization) and LFA (Local Feature Analysis). Experimental results show that the LS-ICA method performs better than PCA, ICA architecture I, ICA architectureII, LFA, and LNMF methods, especially in the cases of partial occlusions and local distortions.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.8
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• pp.385-392
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• 2016

Market analysis for a business plain is required for the success in the modern world. Most important part in this analysis is pedestrian traffic counting. A traditional way for this is counting it in person. However, it causes high labor costs and mistakes. This paper proposes an automatic algorithm to measure the pedestrian traffic count using images with webcam. The proposed algorithm is composed of two parts: pedestrian area detection and movement tracking. In pedestrian area detection, moving blobs are extracted and pedestrian areas are detected using HoG features and Adaboost algorithm. In movement tracking, multi-level matching and false positive removal are applied to track pedestrian areas and count the pedestrian traffic. Multi-level matching is composed of 3 steps: (1) the similarity calculation between HoG area, (2) the similarity calculation of the estimated position with Kalman filtering, and (3) the similarity calculation of moving blobs in the pedestrian area detection. False positive removal is to remove invalid pedestrian area. To analyze the performance of the proposed algorithm, a comparison is performed with the previous human area detection and tracking algorithm. The proposed algorithm achieves 83.6% accuracy in the pedestrian traffic counting, which is better than the previous algorithm over 11%.

• Journal of Distribution Science
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• v.14 no.7
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• pp.71-81
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• 2016

Purpose - Because creativity, which is an intangible resource embedded within the company, can offer a competitive advantage, most companies have an interest in promoting creativity among their employees and division(e.g., marketing organization). Creativity renders a sustainable competitive advantage to a firm because it is a strategic resource that is valuable, flexible, rare, and imperfectly imitable or substitutable. Although most companies broadly recognize the importance of creativity, the methods for developing creativity remain elusive. Therefore, the present study investigates how to structure incentives to motivate employees to be more creative and how to develop tools to facilitate creativity. In detail, the present study aimed to examine the relationship between the regulatory focus of marketing organizations(e.g., promotion focus vs prevention focus) and creativity of marketing organizations. In addition, the present study set out to examine the moderating role of interaction of financial reward and creative training in addition to investigating the direct relationship between creativity and regulatory focus in New Product Development(NPD) context. Research design, data, and methodology - The data used to test the hypotheses are drawn from a survey of full time NPD project members(including project manager, designer, engineer, and marketer). The present study utilized data obtained mainly from a database compiled by the Korea Investors Service-Financial Analysis System which provides comprehensive corporate and financial information on firms listed on the Korea Stock Exchange. A study population comprising 1,000 South Korean firms was obtained from this database. We selected 864 firms from the database, and the firms have experiences of new product development project. We collected a total of 162 responses, for a 18.8% response rate. After we excluded 14 questionnaire because of incomplete responses, a total of 148 questionnaire remained(final response rate: 17.1%). Working with a sample of 148 responses in South Korea, hierarchical moderated regression is employed to test research hypotheses(

The relationship between promotion focus and creativity of marketing organization,

The relationship between prevention focus and creativity of marketing organization,

The moderating effect of joint influences(interaction between financial rewards and creativity training) on the relationship between promotion focus creativity of marketing organization,

The moderating effect of joint influences(interaction between financial rewards and creativity training) on the relationship between prevention focus creativity of marketing organization). SPSS 18.0 and AMOS software were used in the data analysis. Results - The empirical study confirmed that promotion focus of marketing organization is positively related to creativity of marketing organization. Also, prevention focus of marketing organization is positively affected to creativity of marketing organization. In addition, the interaction between financial rewards and creativity training moderated the relationship between regularity focus(e.g.), promotion focus vs prevention focus) and creativity of marketing organization. These results suggest that managers can improve the performances of their creative efforts by providing the use of financial rewards and creativity training in combination. Conclusion - Based on results of this study that examine the effects of regulatory focused creative efforts on creativity of marketing organization, promotion focus is helpful with marketing organizations to enhance their service innovation and performance. Prevention focused organization should allow monetary rewards and creativity training to increase their creativity for innovation of new products.

• Investigative Magnetic Resonance Imaging
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• v.4 no.2
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• pp.128-135
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• 2000

Purpose : The aim of this study is to develope the Magnetic Resonance Spectroscopy(MRS) data processing S/W which plays an important role as a diagnostic tool in clinical field. Materials and methods : Post-processing software of MRS based on graphical user interface(GUI) under windows operating system of personal computer(PC) was developed using MATLAB(Mathwork, U.S.A.). This tool contains many functions to increase the quality of spectrum data such as DC correction, zero filling, line broadening, Gauss-Lorentzian filtering, phase correction, etc. And we obtained the normal human brain $^1H$ MRS data from parietal white matter, basal ganglia and occipital grey matter region using 1.5T Gyroscan ACS-NT R6 (philips, Amsterdam, Netherland) MRS package. The analysis of the MRS peaks were performed by obtaining the ratio of peak area. Results : The peak ratios of NAA/Cr, Cho/Cr, MI/Cr for the different MRS machines have a little different values. But these peak ratios were not significantly different between different echo time MRS peak ratios in the same machine (p<0.05). Conclusion : MRS post-processing S/W based on GUI using PC was developed and applied to the analysis of normal human brain $^1H$ MRS. This independent MRS processing job increases the performance and throughput of patient scan of main console. Finally, we suggest that the database for normal in-yivo human MRS data should be obtained before clinical applications.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.608-613
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• 2019

NOx (Nitrogen oxide) in the exhaust gas from vehicle engines is considered one of the most harmful substances in air pollution problems. NOx is made when combustion occurs under high temperature conditions and EGR (exhaust gas recirculation) is normally used to lower the combustion temperature. As the EGR ratio increases, the NOx level becomes low, but a high EGR ratio makes the combustion unstable and causes further air pollution problems, such as CO and unburned hydrocarbon level increase. This study showed that fuel droplets could move more freely by the radiation of sonic wave for the stable combustion. In addition, the engine performance improved with increasing EGR ratio. As a basic study, the effect of sonic wave radiation on the velocity of fuel droplets was studied using CFD software. The results showed that the velocity of small droplets increased more under high frequency sonic wave conditions and the velocity of the large droplets increased at low frequency sonic wave conditions. In addition, an engine analysis model was used to study the effects of the increased combustion stability. These results showed that a 15% increase in EGR ratio in combustion resulted in a 45% decrease in NOx and a 10% increase in thermal efficiency.