• Journal of Intelligence and Information Systems
• /
• v.23 no.4
• /
• pp.77-110
• /
• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

• Spatial Information Research
• /
• v.11 no.3
• /
• pp.261-274
• /
• 2003

The effective probability-based tile pre-fetching algorithm and the collaborative cache replacement algorithm are able to reduce the response time for user's requests by transferring tiles which will be used in advance and determining tiles which should be removed from the restrictive cache space of a client based on the future access probabilities in Web GISs(Geographical Information Systems). The Web GISs have multi-level abstracted data for the quick response time when zoom-in and zoom-out queries are requested. But, the previous pre-fetching algorithm is applied on only two-dimensional pre-fetching space, and doesn't consider expanded pre-fetching space for multi-level abstracted data in Web GISs. In this thesis, a probability-based pre-fetching algorithm for multi-level abstracted in Web GISs was proposed. This algorithm expanded the previous two-dimensional pre-fetching space into three-dimensional one for pre-fetching tiles of the upper levels or lower levels. Moreover, we evaluated the effect of the proposed pre-fetching algorithm by using a simulation method. Through the experimental results, the response time for user requests was improved 1.8%∼21.6% on the average. Consequently, in Web GISs with multi-level abstracted data, the proposed pre-fetching algorithm and the collaborative cache replacement algorithm can reduce the response time for user requests substantially.

• Management & Information Systems Review
• /
• v.36 no.4
• /
• pp.1-19
• /
• 2017

These days, the concept of creating shared value is drawn keen attentions to. This interest comes out of the expectation that Creating Shared Value(CSV) can offer an answer to some social issues by creating societal and economic values on the top of the achievements that existing Corporate Social Responsibility(CSR) has made. However, it is difficult to make a clear distinction between the achievements that the activities of CSR and CSV have made. In this regard, developing a methodology to make an actual proof analysis on the accomplishments of CSV and to verify customer's awareness of and attitude towards the CSV is necessarily required. A company needs to gain a competitive advantage in the marketplace as well as resolve a social issue by innovating value chain. The research has verified the cause and effect relationship between the CSV from the point of view of value chain and the purchase intention aroused by its economic, societal and cultural values through the company image and credibility with actual proof analysis and come up with following results. First, a societal and cultural value resulted in giving positive impact on a company's image, which implies that CSV activities can be the thin end of the wedge through which customers have a good image of the company involved in CSV. Second, a societal value makes a positive influence on the credibility of a company. In this regard, CSV should be recognized not just as a thing that generates a cost, but a way to win-win as well as future development. Third and last, the research results show that both company image and credibility influence on purchase intention. Considering that CSV generates a positive evaluation on a company that will ultimately cause continuous profit-making, the company's ultimate goal of activities, it should be approached from the perspective of making a mid-and-long term strategy.

• 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.

• Education of Primary School Mathematics
• /
• v.15 no.2
• /
• pp.107-134
• /
• 2012

The purpose of this study is to investigate the effectiveness of two teaching methods of word problems, one based on mathematical modeling learning(ML) and the other on traditional learning(TL). Additionally, the influence of mathematical modeling learning in word problem solving behavior, application ability of real world experiences in word problem solving and the beliefs of word problem solving will be examined. The results of this study were as follows: First, as to word problem solving behavior, there was a significant difference between the two groups. This mean that the ML was effective for word problem solving behavior. Second, all of the students in the ML group and the TL group had a strong tendency to exclude real world knowledge and sense-making when solving word problems during the pre-test. but A significant difference appeared between the two groups during post-test. classroom culture improvement efforts. Third, mathematical modeling learning(ML) was effective for improvement of traditional beliefs about word problems. Fourth, mathematical modeling learning(ML) exerted more influence on mathematically strong and average students and a positive effect to mathematically weak students. High and average-level students tended to benefit from mathematical modeling learning(ML) more than their low-level peers. This difference was caused by less involvement from low-level students in group assignments and whole-class discussions. While using the mathematical modeling learning method, elementary students were able to build various models about problem situations, justify, and elaborate models by discussions and comparisons from each other. This proves that elementary students could participate in mathematical modeling activities via word problems, it results form the use of more authentic tasks, small group activities and whole-class discussions, exclusion of teacher's direct intervention, and classroom culture improvement efforts. The conclusions drawn from the results obtained in this study are as follows: First, mathematical modeling learning(ML) can become an effective method, guiding word problem solving behavior from the direct translation approach(DTA) based on numbers and key words without understanding about problem situations to the meaningful based approach(MBA) building rich models for problem situations. Second, mathematical modeling learning(ML) will contribute attitudes considering real world situations in solving word problems. Mathematical modeling activities for word problems can help elementary students to understand relations between word problems and the real world. It will be also help them to develop the ability to look at the real world mathematically. Third, mathematical modeling learning(ML) will contribute to the development of positive beliefs for mathematics and word problem solving. Word problem teaching focused on just mathematical operations can't develop proper beliefs for mathematics and word problem solving. Mathematical modeling learning(ML) for word problems provide elementary students the opportunity to understand the real world mathematically, and it increases students' modeling abilities. Futhermore, it is a very useful method of reforming the current problems of word problem teaching and learning. Therefore, word problems in school mathematics should be replaced by more authentic ones and modeling activities should be introduced early in elementary school eduction, which would help change the perceptions about word problem teaching.

• Cartoon and Animation Studies
• /
• s.26
• /
• pp.109-130
• /
• 2012

The purpose of this study is to suggest the direction of the development of the feature length animation for movie theater by analyzing of the reasons of the success of . released in 2011 has broken box office records by drawing 2 millions since drew 760 thousands in 1976. This can be one of the success model of the animation for movie theater, considering it has had trouble not only in planning ability and scenario power but also in producing environment where subcontracts are prevalent. This box office hit seems to have been possible through cooperation and division of movie crews and animation crews. Many kinds of materials are reviewed and producer Kim Seonku was interviewed for analysis of the reasons of box office success. Followings are five reasons of success found as the result of analysis and the body of this article is composed of the argument and analysis of each. 1.This animation was planned and produced in the same way of commercial feature films. 2.There was detailed division of work while producing 3. Various kinds of investments were made sequentially, 4. Major film distributor like Lotte and CJ could be motivated 5. There were producers who can mediate between the animation and film field This study suggests the direction both in the aspect of industry and the aspect of training professionals as the result of analysis. In the industrial aspect, transitional cooperation is needed between animation filed and film field which can motivate distributor. Industrial approach like planning, investment, distribution and marketing is absolute for the success of animation for movie theater. Also in the aspect of training professionals, curriculum needs to be improved in the university because the ability and passion of the professionals in the field of animation industry are the most important and education is the most approachable way.

• Investigative Magnetic Resonance Imaging
• /
• v.14 no.2
• /
• pp.103-114
• /
• 2010

Purpose : To generate a Korean specific brain template, especially in patients with Alzheimer's disease (AD) by optimizing the voxel-based analysis. Materials and Methods : Three-dimensional T1-weighted images were obtained from 123 subjects who were 43 cognitively normal subjects and patients with 44 mild cognitive impairment (MCI) and 36 AD. The template and the corresponding aprior maps were created by using the matched pairs approach with considering differences of age, gender and differential diagnosis (DDX). We measured several characteristics in both our and the MNI templates, including in the ventricle size. Also, the fractions of gray matter and white matter voxels normalized by the total intracranial were evaluated. Results : The high resolution template and the corresponding aprior maps of gray matter, white matter (WM) and CSF were created with the voxel-size of $1{\times}1{\times}1\;mm$. Mean distance measures and the ventricle sizes differed between two templates. Our brain template had less gray matter and white matter areas than the MNI template. There were volume differences more in gray matter than in white matter. Conclusion : Gray matter and/or white matter integrity studies in populations of Korean elderly and patients with AD are needed to investigate with this template.

• The Journal of Engineering Geology
• /
• v.14 no.1
• /
• pp.29-46
• /
• 2004

It is important to identify geometries of fracture that act as a conduit of fluid flow for characterization of ground water flow in fractured rock. Fracture geometries control hydraulic conductivity and stream lines in a rock mass. However, we have difficulties to acquire whole geometric data of fractures in a field scale because of discontinuous distribution of outcrops and impossibility of continuous collecting of subsurface data. Therefore, it is needed to develop a method to describe whole feature of a target fracture geometry. This study suggests a new approach to develop a method to characterize on the whole feature of a target fracture geometry based on the Fourier transform. After sampling of specimens along a target fracture from borehole cores, effective frequencies among roughness components were selected by the Fourier transform on each specimen. Then, the selected effective frequencies were averaged on each frequency. Because the averaged spectrum includes all the frequency profiles of each specimen, it shows the representative components of the fracture roughness of the target fracture. The inverse Fourier transform is conducted to reconstruct an averaged whole roughness feature after low pass filtering. The reconstructed roughness feature also shows the representative roughness of the target subsurface fracture including the geometrical characteristics of each specimen. It also means that overall roughness feature by scaling up of a fracture. In order to identify the characteristics of permeability coefficients along the target fracture, fracture models were constructed based on the reconstructed roughness feature. The computation of permeability coefficient was performed by the homogenization analysis that can calculate accurate permeability coefficients with full consideration of fracture geometry. The results show a range between $10^{-4}{\;}and{\;}10^{-3}{\;}cm/sec$, indicating reasonable values of permeability coefficient along a large fracture. This approach will be effectively applied to the analysis of permeability characteristics along a large fracture as well as identification of the whole feature of a fracture in a field scale.

• Journal of Distribution Research
• /
• v.16 no.5
• /
• pp.193-209
• /
• 2011

The fast expansion of super supermarket(SSM) in Korean retail industries has attracted serious social attentions and some types of regulations to slow down its growth are prepared. However, the regulations are hardly justified because they attempt to establish entry barriers which are not recommendable economic policy. Accordingly, the regulations should be justified at least on the basis of social and political causes. The study interprets the social and political causes as the effects of entry of SSM on trading ares where SSM is located. The study is distinguished from the past studies which focused only on intertype and intratype competition between retailers Another goal of the study is to complement the weakness of past studies and provide additional information to settle the issues. More closely, the study investigates the relationships between the changes in sales of convenience stores, which may be a surrogate measure of the viability of a local economy, and the changes in the composition of business types within 500m radius of a SSM. Further, the study investigates the effects of the establishment of SSM and the retail sales index on the sales of convenience stores. The study analyzed the panel data and adopts Swamy's random coefficient models. The results show that the effects of the establishment of SSM on the sales of convenience stores are not statistically significant. The relationship between the change in the portion of restaurants among the local business and the change in the sales of convenience stores is positive. On the other hand the relationship between the change in the portion of retailers in the composition of local businesses and the change in the sales of convenience stores is negative. In conclusion, even though any negative effects of the establishments of SSM on local economies are expected, as long as other types business especially restaurant businesses fill the space left by retailers, the net effect on the local economy may not be signification or even positive.

• 한국유가공학회:학술대회논문집
• /
• 2007.09a
• /
• pp.49-58
• /
• 2007

Inflammatory process leads to the well-known mucosal damage and therefore a further disturbance of the epithelial barrier function, resulting abnormal intestinal wall function, even further accelerating the inflammatory process[1]. Despite of the records, etiology and pathogenesis of IBD remain rather unclear. There are many studies over the past couple of years have led to great advanced in understanding the inflammatory bowel disease(IBD) and their underlying pathophysiologic mechanisms. From the current understanding, it is likely that chronic inflammation in IBD is due to aggressive cellular immune responses including increased serum concentrations of different cytokines. Therefore, targeted molecules can be specifically eliminated in their expression directly on the transcriptional level. Interesting therapeutic trials are expected against adhesion molecules and pro-inflammatory cytokines such as TNF-${\alpha}$. The future development of immune therapies in IBD therefore holds great promises for better treatment modalities of IBD but will also open important new insights into a further understanding of inflammation pathophysiology. Treatment of cytokine inhibitors such as Immunex(Enbrel) and J&J/Centocor(Remicade) which are mouse-derived monoclonal antibodies have been shown in several studies to modulate the symptoms of patients, however, theses TNF inhibitors also have an adverse effect immune-related problems and also are costly and must be administered by injection. Because of the eventual development of unwanted side effects, these two products are used in only a select patient population. The present study was performed to elucidate the ability of TNF-${\alpha}$ antibodies produced in sheep colostrums to neutralize TNF-${\alpha}$ action in a cell-based bioassay and in a small animal model of intestinal inflammation. In vitro study, inhibitory effect of anti-TNF-${\alpha}$ antibody from the sheep was determined by cell bioassay. The antibody from the sheep at 1 in 10,000 dilution was able to completely inhibit TNF-${\alpha}$ activity in the cell bioassay. The antibodies from the same sheep, but different milkings, exhibited some variability in inhibition of TNF-${\alpha}$ activity, but were all greater than the control sample. In vivo study, the degree of inflammation was severe to experiment, despite of the initial pilot trial, main trial 1 was unable to figure out of any effect of antibody to reduce the impact of PAF and LPS. Main rat trial 2 resulted no significant symptoms like characteristic acute diarrhea and weight loss of colitis. This study suggested that colostrums from sheep immunized against TNF-${\alpha}$ significantly inhibited TNF-${\alpha}$ bioactivity in the cell based assay. And the higher than anticipated variability in the two animal models precluded assessment of the ability of antibody to prevent TNF-${\alpha}$ induced intestinal damage in the intact animal. Further study will require to find out an alternative animal model, which is more acceptable to test anti-TNF-${\alpha}$ IgA therapy for reducing the impact of inflammation on gut dysfunction. And subsequent pre-clinical and clinical testing also need generation of more antibody as current supplies are low.