• Journal of the Korea Society for Simulation
• /
• v.24 no.4
• /
• pp.163-170
• /
• 2015

This research is to focus on the method of moving line optimization in Agricultural Industry, especially Garak Wholesale Market Modernization Project, by using simulation tool. As everybody knew, it's very difficult to apply the SCM operation rules in Agricultural Industry, because the standardization system in Agricultural Industry was not completed. The five flow management factors, vehicle moving line management, customer moving line Management, Logistics Device Moving Line Management, Working Person Moving Line Management, Product display moving line management, are needed to be optimized on the basis of standardization rules, and to achieve this will be the good infrastructure to make the Agricultural SCM system. It's very different between the SCM structure of manufacturing industry and logistics industry and the SCM structure of Agricultural Industry, because the SCM in manufacturing is occur in the basis of flow management, on the contrary, the SCM of Agricultural Industry is on the basis of activity management. For these reason, this study is the first approach to apply the simulation method in the part of moving line optimization in Agricultural SCM, and in near future, This study will help all designers and operators to apply the simulation work in the part of agricultural SCM, and we hope that next advanced study will continue by using this study.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.7 no.1
• /
• pp.10-21
• /
• 2008

User travel behavior is based on the existence of complete traffic information in deterministic user optimal principle by Wardrop(1952). According to deterministic user optimal principle, users choose the optimal route from origin to destination and they change their routes arbitrarily in order to minimize travel cost. In this principle, users only consider travel time as a factor to take their routes. However, user behavior is not determined by only travel time in actuality. Namely, the models that reflect only travel time as a route choice factor could give irrational travel behavior results. Therefore, the model is necessary that considers various factors including travel time, transportation networks structure and traffic information. In this research, more realistic deterministic optimal traffic assignment model is proposed in the way of route recognizance behavior. This model assumes that when users decide their routes, they consider many factors such as travel time, road condition and traffic information. In addition, route recognizance attributes is reflected in this suggested model by forward searching method and backward searching method with numerical formulas and algorithms.

• Tunnel and Underground Space
• /
• v.17 no.2 s.67
• /
• pp.109-118
• /
• 2007

The excavation damaged zone (EDZ) is an area around an excavation where in situ rock mass properties, stress condition. displacement. groundwater flow conditions have been altered due to the excavation. Various studies have been carried out on EDZ, but most studies have been focused on the mechanical bahavior of EDZ by in situ experiment. Even though the EDZ could potentially form a high permeable pathway of groundwater flow, only a few studies were performed on the analysis of groundwater flow in EDZ. In this study, the' hydraulic EDZ' was defined as the rock Lone adjacent to the excavation where the hydraulic aperture has been changed due to the excavation. And hydraulic EDZ (hydraulic aperture changed zone) estimated by two-dimensional DEM program was considered in three-dimensional DFN model. From this approach the groundwater flow characteristics corresponding to hydraulic aperture change were examined. Together. a parametric study was performed to examine the boundary conditions that frequently used in DFN analysis such as constant head or constant flux condition. According to the numerical analysis, hydraulic aperture change induced by the hydraulic-mechanical interaction becomes one of the most important factors Influencing the hydraulic behavior of jointed rock masses. And also from this study, we suggest the proper boundary condition in three-dimensional DFN model.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2024.01a
• /
• pp.55-58
• /
• 2024

최근 각 기업의 AI 면접시스템 도입이 증가하고 있으며, AI 면접에 대한 실효성 논란 또한 많은 상황이다. 본 논문에서는 AI 면접 과정에서 지원자를 평가하는 방식을 시각, 음성, 자연어처리 3영역에서 구현함으로써, 면접 지원자를 다방면으로 분석 방법론의 적절성에 대해 평가하고자 한다. 첫째, 시각적 측면에서, 면접 지원자의 감정을 인식하기 위해, 합성곱 신경망(CNN) 기법을 활용해, 지원자 얼굴에서 6가지 감정을 인식했으며, 지원자가 카메라를 응시하고 있는지를 시계열로 도출하였다. 이를 통해 지원자가 면접에 임하는 태도와 특히 얼굴에서 드러나는 감정을 분석하는 데 주력했다. 둘째, 시각적 효과만으로 면접자의 태도를 파악하는 데 한계가 있기 때문에, 지원자 음성을 주파수로 환산해 특성을 추출하고, Bidirectional LSTM을 활용해 훈련해 지원자 음성에 따른 6가지 감정을 추출했다. 셋째, 지원자의 발언 내용과 관련해 맥락적 의미를 파악해 지원자의 상태를 파악하기 위해, 음성을 STT(Speech-to-Text) 기법을 이용하여 텍스트로 변환하고, 사용 단어의 빈도를 분석하여 지원자의 언어 습관을 파악했다. 이와 함께, 지원자의 발언 내용에 대한 감정 분석을 위해 KoBERT 모델을 적용했으며, 지원자의 성격, 태도, 직무에 대한 이해도를 파악하기 위해 객관적인 평가지표를 제작하여 적용했다. 논문의 분석 결과 AI 면접의 다면적 평가시스템의 적절성과 관련해, 시각화 부분에서는 상당 부분 정확도가 객관적으로 입증되었다고 판단된다. 음성에서 감정분석 분야는 면접자가 제한된 시간에 모든 유형의 감정을 드러내지 않고, 또 유사한 톤의 말이 진행되다 보니 특정 감정을 나타내는 주파수가 다소 집중되는 현상이 나타났다. 마지막으로 자연어처리 영역은 면접자의 발언에서 나오는 말투, 특정 단어의 빈도수를 넘어, 전체적인 맥락과 느낌을 이해할 수 있는 자연어처리 분석모델의 필요성이 더욱 커졌음을 판단했다.

• Journal of Korean Society of Transportation
• /
• v.22 no.7 s.78
• /
• pp.155-159
• /
• 2004

Recently, there are many trials about Artificial neural networks : ANNs structure and studying method of researches for forecasting traffic volume. ANNs have a powerful capabilities of recognizing pattern with a flexible non-linear model. However, ANNs have some overfitting problems in dealing with a lot of parameters because of its non-linear problems. This research deals with the application of a variety of model selection criterion for cancellation of the overfitting problems. Especially, this aims at analyzing which the selecting model cancels the overfitting problems and guarantees the transferability from time measure. Results in this study are as follow. First, the model which is selecting in sample does not guarantees the best capabilities of out-of-sample. So to speak, the best model in sample is no relationship with the capabilities of out-of-sample like many existing researches. Second, in stability of model selecting criterion, AIC3, AICC, BIC are available but AIC4 has a large variation comparing with the best model. In time-series analysis and forecasting, we need more quantitable data analysis and another time-series analysis because uncertainty of a model can have an effect on correlation between in-sample and out-of-sample.

• Korean Journal of Ichthyology
• /
• v.18 no.3
• /
• pp.223-233
• /
• 2006

The annual and spatial changes in the species composition of catch off Yeosu were analyzed using the daily sales slip catch data by a set net in the inshore waters off Dolsan Islands in Yeosu from April to October 2001, off Yeon Islands of Yeosu from April to October 2002 and in the offshore waters off Dolsan Islands of Yeosu from April to December 2003, respectively. Scomberomorus niphonius, Seriola spp., Trichiurus lepturus, Engraulis japonicus, Sarda orientalis, Todarodes pacificus, Pampus echinogaster, Sardinella zunasi, Scomber japonicus, Lophius litulon and Loligo beka were dominant species in abundance, indicating that pelagic fish were mainly caught by a set net off Yeosu. S. zunasi, P. echinogaster, Platycephalus indicus and L. beka inhabited mainly in the inshore waters, and S. niphonius, Seriola spp., T. lepturus, P. echinogaster, T. pacificus, Takifugu porphyreus and Pagrus major resided mainly in the offshore waters as the pelagic resident species. E. japonicus was a representative dominant species moving between the inshore and the offshore waters seasonally. S. zunasi and E. japonicus occurred in the inshore waters, and E. japonicus, L. litulon and Seriola spp. begain to be caught in the deep offshore waters in spring. Total catch was high during the summer season by migration of the open sea species such as T. lepturus, S. niphonius, S. japonicus, Seriola spp., S. orientalis, P. echinogaster and T. pacificus. In fall, S. niphonius, E. japonicus, Sphyraena pinguis, Siganus fuscescens and Leiognathus nuchalis were dominant in the inshore waters, and S. niphonius, P. echinogaster, Hyporhamphus sajori, S. japonicus and T. lepturus continued to occur from summer in the offshore waters but total catch decreased, indicating the typical seasonal variation pattern of the temperate region. Most of catchable fishes by a set net were the pelagic species showing a significant temporal variation. Collection and analysis of daily catch data by large set nets can be used to determine seasonal variation in species composition of pelagic fish in a study area.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.3
• /
• pp.572-580
• /
• 2010

The Wireless Mesh Network uses a wireless communication technology with transmission rates simular to a cable which is used as a backbone networks. The topology structure is in a Mesh form which resembles an Ad-hoc networks. However, a metric is needed in order to set the channel access control method to operate intentions and interior motions are different. In this document, an efficient channel for delivering datas to improve access controls to a wireless mesh networks. The improved performance of the proposed plan is for a hidden and exposed mesh client through an exclusive channels to perform a proposed and analyzed methods.

• Journal of Korea Multimedia Society
• /
• v.18 no.4
• /
• pp.524-532
• /
• 2015

All data created in BigData times is included potentially meaning and correlation in data. A variety of data during a day in all society sectors has become created and stored. Research areas in analysis and grasp meaning between data is proceeding briskly. Especially, accuracy of meaning prediction and data imbalance problem between data for analysis is part in course of something important in data analysis field. In this paper, we proposed data prediction model based on data weights and neural network using R for meaning analysis between data. Proposed data prediction model is composed of classification model and analysis model. Classification model is working as weights application of normal distribution and optimum independent variable selection of multiple regression analysis. Analysis model role is increased prediction accuracy of output variable through neural network. Performance evaluation result, we were confirmed superiority of prediction model so that performance of result prediction through primitive data was measured 87.475% by proposed data prediction model.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.3
• /
• pp.51-55
• /
• 2020

In this paper, an improved FAM is proposed by adopting similarity learning in the existing FAM (Fuzzy Associative Memory) used in image restoration. Image restoration refers to the recovery of the latent clean image from its noise-corrupted version. In serious application like face recognition, this process should be noise-tolerant, robust, fast, and scalable. The existing FAM is a simple single layered neural network that can be applied to this domain with its robust fuzzy control but has low capacity problem in real world applications. That similarity measure is implied to the connection strength of the FAM structure to minimize the root mean square error between the recovered and the original image. The efficacy of the proposed algorithm is verified with significant low error magnitude from random noise in our experiment.

• Culinary science and hospitality research
• /
• v.24 no.3
• /
• pp.167-176
• /
• 2018

In this study, Big Data was used to collect the information related to 'Cooking Academy' keywords. After collecting all the data, we calculated the frequency through the text mining and selected the main words for future data analysis. Data collection was conducted from Google Web and News during the period from January 1, 2013 to December 31, 2017. The selected 64 words were analyzed by using UCINET 6.0 program, and the analysis results were visualized with NetDraw in order to present the relationship of main words. As a result, it was found that the most important goal for the students from cooking school is to work as a cook, likewise to have practical classes. In addition, we obtained the result that SNS marketing system that the social sites, such as Facebook, Twitter, and Instagram are actively utilized as a marketing strategy of the institute. Therefore, the results can be helpful in searching for the method of utilizing big data and can bring brand-new ideas for the follow-up studies. In practical terms, it will be remarkable material about the future marketing directions and various programs that are improved by the detailed curriculums through semantic network of cooking school by using big data.