• The KIPS Transactions:PartD
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• v.17D no.1
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• pp.1-8
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• 2010

Association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from voluminous transactional data. Certainly, one of the major purposes of association rule mining is utilizing the acquired knowledge to provide marketing strategies such as catalogue design, cross-selling and shop allocation. However, this requires too much time and high cost to only extract the actionable and profitable knowledge from tremendous numbers of discovered patterns. In currently available literature, a number of interest measures have been devised to accelerate and systematize the process of pattern evaluation. Unfortunately, most of such measures, including support and confidence, are prone to yielding impractical results because they are calculated only from the sales frequencies of items. For instance, traditional measures cannot differentiate between the purchases in a small basket and those in a large shopping cart. Therefore, some adjustment should be made to the size of market baskets because there is a strong possibility that mutually irrelevant items could appear together in a large shopping cart. Contrary to the previous approaches, we attempted to consider market basket's size in calculating interest measures. Because the devised measure assigns different weights to individual purchases according to their basket sizes, we expect that the measure can minimize distortion of results caused by accidental patterns. Additionally, we performed intensive computer simulations under various environments, and we performed real case analyses to analyze the correctness and consistency of the devised measure.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.33-39
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• 2016

With recent advances in sensor technology, CMOS-based semiconductor devices and networking protocol, the areas for application of wireless sensor networks greatly expanded and diversified. Such diversification of uses for wireless sensor networks creates a multitude of beneficial possibilities for several industries. In the application of wireless sensor networks for monitoring systems' data transmission process from the sensor node to the sink node, transmission through multi-hop paths have been used. Also mobile sink techniques have been applied. However, high energy costs, unbalanced energy consumption of nodes and time gaps between the measured data values and the actual value have created a need for advancement. Therefore, this thesis proposes a new model which alleviates these problems. To reduce the communication costs due to frequent data exchange, a State Prediction Model has been developed to predict the situation of the peripheral node using a geographic autocorrelation of sensor nodes constituting the wireless sensor networks. Also, a Risk Analysis Model has developed to quickly alert the monitoring system of any fatal abnormalities when they occur. Simulation results have shown, in the case of applying the State Prediction Model, errors were smaller than otherwise. When the Risk Analysis Model is applied, the data transfer latency was reduced. The results of this study are expected to be utilized in any efficient communication method for wireless sensor network monitoring systems where all nodes are able to identify their geographic location.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.346-353
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• 2016

In the design conditions of some research reactors, the siphon phenomenon can cause continuous efflux of water during pipe rupture. A siphon breaker is a safety device that can prevent water efflux effectively. However, the analysis of the siphon breaking is complicated because many variables must be included in the calculation process. For this reason, a simulation program was developed with a user-friendly GUI to analyze the siphon breaking easily. The program was developed by MFC programming using Visual Studio 2012 in Windows 8. After saving the input parameters from a user, the program proceeds with three steps of calculation using fluid mechanics formulas. Bernoulli's equation is used to calculate the velocity, quantity, water level, undershooting, pressure, loss coefficient, and factors related to the two-phase flow. The Chisholm model is used to predict the results from a real-scale experiment. The simulation results are shown in a graph, through which a user can examine the total breaking situation. It is also possible to save all of the resulting data. The program allows a user to easily confirm the status of the siphon breaking and would be helpful in the design of siphon breakers.

• Journal of Global Scholars of Marketing Science
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• v.16 no.1
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• pp.117-141
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• 2006

Daily sales volume in retailers seems to be changed because of five-days-work in a week resulting in growth of leisure time in Korea recently. The day of the week effect of sales volume that can not be theoretically explained, which sales pattern varies depending on days systematically and consistently, is so important. Especially the day of the week effect of sales volume exists in which retail branch and the extents of the day of the week effect from the perspective of marketing in retailing is very important. Thus, the purpose of this study was to investigate whether the day of the week effect of sales volume exists in men's clothing retailers and if so, there is difference in daily sales volume. There was insufficient researches in the field of anomaly such as the day of the week effect of sales volume in marketing. For this reason, this study has drawn upon research findings of finance, general demand theory, and previous studies of the day of the week effect in stock markets. In doing so, these works are referenced in theoretical background and applicability in retailing market of this study. This study empirically investigated the day of the week effect of sales volume through the revenues of a men's clothing retailers (P company) in past five years. As the result of this study, the day of the week effect of sales volume existed in men's clothing retailers and the day of the week effect showed positive from Monday to Sunday, which means Sunday, the biggest. Also, the day of the week effect by season was different. The result of this study is expected to provide some helpful evidence that offers effective operational strategies to retailers.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.71-78
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• 2020

Recently, as the issue of gentrification emerges, it becomes important to understand the dynamics of local commercial district, which plays the important role for facilitating the local economy and building the community in a city. This paper attempts to provide the framework for systemically analyzing and understanding the local commercial district. Then, this paper empirically analyzes the patterns of sales and flow of floating population by focusing on two representative local commercial districts in Seoul. In addition, the floating population data from telecommunication bases is further modeled with Markov chain for systemically understanding the local commercial districts. Finally, the transition patterns and consumption amounts of floating population are comprehensively analyzed for providing the implications on the evolutions of local commercial districts in a city. We expect that findings of our study could contribute to the economic growth of local commercial district, which could lead to the continuous development of city economy.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.167-174
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• 2016

The university and college turn into the field of job readiness to get a good job and students build a lot of job specification than others and are constantly studying for employment. Then since employment, some people are fortunate to keep the job for lifetime, but for many people work in the workplace did not meet his aptitude with patience and some people move for work several times without perseverance. One of the reasons for job dissatisfaction is that the job does not fit his aptitude. Meantime many organizations conducted the aptitude(Psychology) test. There are limits, however, to find a suitable job. This study was presented as a model of a platform that is a rational and scientific alternative to search course and job. This model is to better understand the individual characteristics using Big data and artificial intelligence, offers several jobs to meet the characteristics among the various professions selectively and supports to select and design an appropriate job based on the field experience, consulting and mentoring.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.31-36
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• 2019

Music therapy, a field that convergence music and treatment, which play a fundamental role in personality formation, possesses diverse and complex treatment methods. Music therapists in charge of music therapy may experience the same phenomenon as countertransference in consultation with clients. In addition, experiencing psychological burnout, there are many difficulties in reaching the final goal of music therapy. In this paper, we provide a collaborative filtering-based music therapy consultation data recommendation model for smooth music therapy consultation with clients who visited for music therapy. The proposed model grasps the similarity between the conventional consultation data and the new consultant data through the euclidean distance algorithm. This is to recommend similar consultation materials. Since music therapists can provide optimal consultation materials for consultants who need music therapy, smooth consultation is expected.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.15-23
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• 2022

Among the learning methods for Continuous Learning environments, "Learning without Forgetting" has fixed regularization strengths, which can lead to poor performance in environments where various data are received. We suggest a way to set weights variable by identifying the features of the data we want to learn. We applied weights adaptively using correlation and complexity. Scenarios with various data are used for evaluation and experiments showed accuracy increases by up to 5% in the new task and up to 11% in the previous task. In addition, it was found that the adaptive weight value obtained by the algorithm proposed in this paper, approached the optimal weight value calculated manually by repeated experiments for each experimental scenario. The correlation coefficient value is 0.739, and overall average task accuracy increased. It can be seen that the method of this paper sets an appropriate lambda value every time a new task is learned, and derives the optimal result value in various scenarios.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.128-128
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• 2020

최근 농업환경의 변화와 기후변화에 대응하기 위해 농업용수 관리 정보화 및 과학화의 필요성이 증대되어 실시간으로 저수지 저수량과 농업용수 공급량을 파악하기 위해 자동 수위계측시설이 도입되었다. 농림축산식품부의 저수지 자동수위측정기 설치 및 운영지침에 따라 현재 농어촌공사 관리 저수지 1,734개소 및 수로부 1,880개소에 자동수위계가 설치되어 있으며, 저수지와 수로에서 10분 간격으로 수위자료가 생성되고 있다. 농업용 저수지 수문자료의 공인지점은 2016년 6개소에서 2019년 49개소로 증대되고 있으며, 데이터 품질 저하의 최소화 및 신뢰성 있는 수문자료 생성의 필요성이 증가함에 따라 농업용 저수지의 특성을 반영한 저수지 수위 오결측 데이터 보정 방안 및 수문 자료 품질관리 방안이 요구된다. 농업용 저수지의 수위 변화 및 강우-유출 현상은 물리적 모형을 구축하여 기상, 지형 등 영향 인자와 수위(또는 유출)와의 상관관계를 분석하는 것은 무적으로 불가능하였지만, 최근 인공신경망 (Artificial Neural Network, ANN) 등과 같이 black-box 형태의 모형을 이용하여 비선형적인 수문해석이 가능해졌다. 본 연구에서는 빅데이터와 인공신경망을 결합시킨 알고리즘인 딥러닝 (Deep Learning) 기반의 LSTM (Long Short-Term Memory) 모형을 활용하여 농업용 저수지 수위자료를 검토하여 자동계측기에서 발생하는 오류 보정을 위해 품질관리 방안을 제시하고자 한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.150-155
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• 2019

Cavitation refers to a phenomenon in which empty spaces occur in a fluid due to changes in pressure and a velocity. When a liquid moves at a high speed, the pressure drops below the vapor pressure, and vapor bubbles are generated in the liquid. This study used CFD to analyze the flow of fluid machinery used in marine and offshore plants. The goals are to ensure the validity of the analysis method for marine propellers in an open water test, to increase the forward ratio, and to use FLUENT to understand the flow pattern due to cavitation. A three-dimensional analysis was performed and compared with experimental data from MOERI. The efficiency was highest at advance ratios of 0.7 - 0.8. Thrust was generated due to the difference between the pressure surface and the suction surface, and it was estimated that bubbles would be generated in the vicinity of the back side surface rather than the face side of the propeller, resulting in more cavitation. The cavitation decreased sharply as the advance ratio increased. The thrust and torque coefficients were comparable to those of the MOERI experimental data except at the advance ratio of 1, which showed a difference of less than 5%. Therefore, it was confirmed that CFD can evaluate an open water propeller test.