• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.159-172
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• 2010

The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.2
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• pp.29-39
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• 2011

Recent interests in the quality of urban space have raised awareness on the role and importance of landscape planning. Although laws and guidelines are officially ready to be imposed as for landscape planning, we do not have concrete materials that can be utilized in the course of practices. The aim of this paper in this regard is to disclose the possible difference in awareness on 'visual landscape control elements' among experts engaged with urban space planning. The expert groups are distinguished to three which are for a planning, design and engineering and the survey is made by questionnaires. The results are analyzed through basic technology statistics in SPSS and independent-sample t-test provided. The survey is done by tens of 'control elements' and the result is that specially, group 1 and group 2 in mixed landscape has the most discrepancy in awareness on those elements but relatively, they has less discrepancy in awareness on compare with other groups through all landscape area. In case of artificial landscape and mixed landscape in 'landscape controled area', the result for comparing between G1 and G2 is that there are the most discrepancy in awareness which are 7 control elements. In case of mixed landscape in 'landscape promoted area', there are 4 control elements for discrepancy in awareness between G2 and G3 which is quite different. The control elements which show the most discrepancy in awareness is height, floor space and building to land ratio in order. The shape elements has only discrepancy in awareness for comparing between G1 and G2 of artificial landscape in 'landscape controled area'. In terms of the average evaluation score of the appropriateness of these control elements, G1 seems to appreciate the role of these elements in systematic landscape planning more than the other group does. In other words, relatively low scores are given by G2 as for the overall functionality of visual landscape control elements. The texture, floor space and building of land ratio has low evaluation score for all area and types. It means that it should reverify for appropriateness of performance for landscape planning as visual landscape control elements.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.6
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• pp.346-361
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• 2013

This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2012. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. The conclusions are as follows : (1) The research works on thermal and fluid engineering have been reviewed as groups of fluid machinery, pipes and valves, fuel cells and power plants, ground-coupled heat pumps, and general heat and mass transfer systems. Research issues are mainly focused on new and renewable energy systems, such as fuel cells, ocean thermal energy conversion power plants, and ground-coupled heat pump systems. (2) Research works on the heat transfer area have been reviewed in the categories of heat transfer characteristics, pool boiling and condensing heat transfer, and industrial heat exchangers. Researches on heat transfer characteristics included the results for natural convection in a square enclosure with two hot circular cylinders, non-uniform grooved tube considering tube expansion, single-tube annular baffle system, broadcasting LED light with ion wind generator, mechanical property and microstructure of SA213 P92 boiler pipe steel, and flat plate using multiple tripping wires. In the area of pool boiling and condensing heat transfer, researches on the design of a micro-channel heat exchanger for a heat pump, numerical simulation of a heat pump evaporator considering the pressure drop in the distributor and capillary tubes, critical heat flux on a thermoexcel-E enhanced surface, and the performance of a fin-and-tube condenser with non-uniform air distribution and different tube types were actively carried out. In the area of industrial heat exchangers, researches on a plate heat exchanger type dehumidifier, fin-tube heat exchanger, an electric circuit transient analogy model in a vertical closed loop ground heat exchanger, heat transfer characteristics of a double skin window for plant factory, a regenerative heat exchanger depending on its porous structure, and various types of plate heat exchangers were performed. (3) In the field of refrigeration, various studies were executed to improve refrigeration system performance, and to evaluate the applicability of alternative refrigerants and new components. Various topics were presented in the area of refrigeration cycle. Research issues mainly focused on the enhancement of the system performance. In the alternative refrigerant area, studies on CO2, R32/R152a mixture, and R1234yf were performed. Studies on the design and performance analysis of various compressors and evaporator were executed. (4) In building mechanical system research fields, twenty-nine studies were conducted to achieve effective design of mechanical systems, and also to maximize the energy efficiency of buildings. The topics of the studies included heating and cooling, HVAC system, ventilation, renewable energy systems, and lighting systems in buildings. New designs and performance tests using numerical methods and experiments provide useful information and key data, which can improve the energy efficiency of buildings. (5) In the fields of the architectural environment, studies for various purposes, such as indoor environment, building energy, and renewable energy were performed. In particular, building energy-related researches and renewable energy systems have been mainly studied, reflecting interests in global climate change, and efforts to reduce building energy consumption by government and architectural specialists. In addition, many researches have been conducted regarding indoor environments.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.2
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• pp.172-180
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• 2007

Among the nuclear medicine imaging methods available today, $H_2^{15}O-PET$ is most widely used by cognitive neuroscientists to examine regional brain function via the measurement of regional cerebral blood flow (rCBF). The short half-life of the radioactively labeled probe, $^{15}O$, often allows repeated measures from the same subjects in many different task conditions. $H_2^{15}O-$ PET, however, has technical limitations relative to other methods of functional neuroimaging, e.g., fMRI, including relatively poor time and spatial resolutions, and, frequently, insufficient statistical power for analysis of individual subjects. However, recent technical developments, such as the 3-D acquisition method provide relatively good image quality with a smaller radioactive dosage, which in turn results in more PET scans from each individual, thus providing sufficient statistical power for the analysis of individual subject's data. Furthermore, the noise free scanner environment $H_2^{15}O$ PET, along with discrete acquisition of data for each task condition, are important advantages of PET over other functional imaging methods regarding studying state-dependent changes in brain activity. This review presents both the limitations and advantages of $^{15}O-PET$, and outlines the design of efficient PET protocols, using examples of recent PET studies both in the normal healthy population, and in the clinical population.

• 대한공업교육학회지
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• v.41 no.1
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• pp.128-146
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• 2016

The purpose of this study was to provide a basic research data for increasing the quality of 'creative engineering design' lesson and the teaching learning capability of high school teachers by analyzing the teaching learning management status and improvement plan of 'technology home economics subject' lesson for high school teachers. In order to investigate the teaching learning management status, the survey questionnaires from 63 teachers were collected from high school teachers who teach technology home economics subject currently and analyzed by statistical program SPSS 20. The main results of this study were as follows: First, for the contents of 'creative engineering design' lesson, the highest mean of response was 'creative thinking method'(M=4.22). In the learning activities, the teachers perceived the importance of the 'idea concept' highly. Second, in the management of 'creative engineering design' lesson, the teachers perceived the importance of the secure of tool, material budget, and practice space for the lesson highly. In the teaching capabilities, the teacher perceived the importance of the preparing teaching learning strategy most($$M{\frac{._-}{.}}4.14$$). Third, the teachers preferred to product for making uncomfortable things better in life and the other production outside from the content of textbook. Fourth, in the ratio of practice:theory lesson, they perceived the ratio of 3:7(36.5%), 4:6(25.4%), and 2:8(23.8%) are appropriate. In the assessment, the combination of production, portfolio, and presentation was preferred most. Fifth, there were statistically significant difference in teachers' interest and satisfaction and contents about 'creative engineering design' lesson between groups divided by the existence of practice space, certification held(technology teacher, non technology teacher), etc. Therefore, in order to improve the interest and satisfaction about the 'creative engineering design' lesson, the secure of space for technology practice and material budget were required. In addition, training and seminars program for improving the teaching capability for 'creative engineering design' lesson were required.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.129-141
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• 2010

An Internet shopping mall for clothing operates a warehouse for packing and shipping products to fulfill its orders. All the products in the warehouse are put into the boxes of same brands and the boxes are stored in a row on shelves equiped in the warehouse. To make picking and managing easy, boxes of the same brands are located side by side on the shelves. When new products arrive to the warehouse for storage, the products of a brand are put into boxes and those boxes are located adjacent to the boxes of the same brand. If there is not enough space for the new coming boxes, however, some boxes of other brands should be moved away and then the new coming boxes are located adjacent in the resultant vacant spaces. We want to minimize the movement of the existing boxes of other brands to another places on the shelves during the warehousing of new coming boxes, while all the boxes of the same brand are kept side by side on the shelves. Firstly, we define the adjacency of boxes by looking the shelves as an one dimensional series of spaces to store boxes, i.e. cells, tagging the series of cells by a series of numbers starting from one, and considering any two boxes stored in the cells to be adjacent to each other if their cell numbers are continuous from one number to the other number. After that, we tried to formulate the problem into an integer programming model to obtain an optimal solution. An integer programming formulation and Branch-and-Bound technique for this problem may not be tractable because it would take too long time to solve the problem considering the number of the cells or boxes in the warehouse and the computing power of the Internet shopping mall. As an alternative approach, we designed a fast heuristic method for this reallocation problem by focusing on just the unused spaces-empty cells-on the shelves, which results in an assignment problem model. In this approach, the new coming boxes are assigned to each empty cells and then those boxes are reorganized so that the boxes of a brand are adjacent to each other. The objective of this new approach is to minimize the movement of the boxes during the reorganization process while keeping the boxes of a brand adjacent to each other. The approach, however, does not ensure the optimality of the solution in terms of the original problem, that is, the problem to minimize the movement of existing boxes while keeping boxes of the same brands adjacent to each other. Even though this heuristic method may produce a suboptimal solution, we could obtain a satisfactory solution within a satisfactory time, which are acceptable by real world experts. In order to justify the quality of the solution by the heuristic approach, we generate 100 problems randomly, in which the number of cells spans from 2,000 to 4,000, solve the problems by both of our heuristic approach and the original integer programming approach using a commercial optimization software package, and then compare the heuristic solutions with their corresponding optimal solutions in terms of solution time and the number of movement of boxes. We also implement our heuristic approach into a storage location assignment system for the Internet shopping mall.

• Journal of Animal Science and Technology
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• v.50 no.3
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• pp.301-308
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• 2008

DNA variation of MYL2 intron 5 A345G and ADCYAP1R1 intron 2 A337G were investigated for carcass trait association in finished pigs. Three genotypes(two homozygotes and their heterozygote) were found at 10.6% AA, 45.6% AG and 43.8% GG in MYL2 and 60.5% AA, 34.6% AG, and 22.2% GG for ADCYAP1R1. In finished pig population, individuals containing genotype G- of MYL2 had significantly heavier carcass weight by more than 2.4 kg and thicker backfat thickness by more than 1.3 mm than those of AA homozygous pigs(p<0.05). No significant difference was found in other traits tested in this study such as marbling score, meat color, texture, moisture and separation score(p>0.05). The ADCYAP1R1 intron 2 377GG homozygotes showed coarse texture, i.e., meat quality was inferior than those of AG and AA genotypes, and the moisture level of homozygote AA was higher than those of AG and GG genotypes(p<0.05). The other carcass traits were not significantly associated with ADCYAP1R1 genotypes(p>0.05). The genetic polymorphism of MYL2 and ADCYAP1R1 genes affected the carcass traits in finished pig population. Further studies to explain the association between genetic variations and their phenotypic effects including economic traits in pigs are required including critical mutation in both genes through molecular approaches.

• Asia pacific journal of information systems
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• v.20 no.1
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• pp.81-99
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• 2010

Lately, in consumers' markets the number of new items is rapidly increasing at an overwhelming rate while consumers have limited access to information about those new products in making a sensible, well-informed purchase. Therefore, item providers and customers need a system which recommends right items to right customers. Also, whenever new items are released, for instance, the recommender system specializing in new items can help item providers locate and identify potential customers. Currently, new items are being added to an existing system without being specially noted to consumers, making it difficult for consumers to identify and evaluate new products introduced in the markets. Most of previous approaches for recommender systems have to rely on the usage history of customers. For new items, this content-based (CB) approach is simply not available for the system to recommend those new items to potential consumers. Although collaborative filtering (CF) approach is not directly applicable to solve the new item problem, it would be a good idea to use the basic principle of CF which identifies similar customers, i,e. neighbors, and recommend items to those customers who have liked the similar items in the past. This research aims to suggest a hybrid recommendation procedure based on the preference boundary of target customer. We suggest the hybrid recommendation procedure using the preference boundary in the feature space for recommending new items only. The basic principle is that if a new item belongs within the preference boundary of a target customer, then it is evaluated to be preferred by the customer. Customers' preferences and characteristics of items including new items are represented in a feature space, and the scope or boundary of the target customer's preference is extended to those of neighbors'. The new item recommendation procedure consists of three steps. The first step is analyzing the profile of items, which are represented as k-dimensional feature values. The second step is to determine the representative point of the target customer's preference boundary, the centroid, based on a personal information set. To determine the centroid of preference boundary of a target customer, three algorithms are developed in this research: one is using the centroid of a target customer only (TC), the other is using centroid of a (dummy) big target customer that is composed of a target customer and his/her neighbors (BC), and another is using centroids of a target customer and his/her neighbors (NC). The third step is to determine the range of the preference boundary, the radius. The suggested algorithm Is using the average distance (AD) between the centroid and all purchased items. We test whether the CF-based approach to determine the centroid of the preference boundary improves the recommendation quality or not. For this purpose, we develop two hybrid algorithms, BC and NC, which use neighbors when deciding centroid of the preference boundary. To test the validity of hybrid algorithms, BC and NC, we developed CB-algorithm, TC, which uses target customers only. We measured effectiveness scores of suggested algorithms and compared them through a series of experiments with a set of real mobile image transaction data. We spilt the period between 1st June 2004 and 31st July and the period between 1st August and 31st August 2004 as a training set and a test set, respectively. The training set Is used to make the preference boundary, and the test set is used to evaluate the performance of the suggested hybrid recommendation procedure. The main aim of this research Is to compare the hybrid recommendation algorithm with the CB algorithm. To evaluate the performance of each algorithm, we compare the purchased new item list in test period with the recommended item list which is recommended by suggested algorithms. So we employ the evaluation metric to hit the ratio for evaluating our algorithms. The hit ratio is defined as the ratio of the hit set size to the recommended set size. The hit set size means the number of success of recommendations in our experiment, and the test set size means the number of purchased items during the test period. Experimental test result shows the hit ratio of BC and NC is bigger than that of TC. This means using neighbors Is more effective to recommend new items. That is hybrid algorithm using CF is more effective when recommending to consumers new items than the algorithm using only CB. The reason of the smaller hit ratio of BC than that of NC is that BC is defined as a dummy or virtual customer who purchased all items of target customers' and neighbors'. That is centroid of BC often shifts from that of TC, so it tends to reflect skewed characters of target customer. So the recommendation algorithm using NC shows the best hit ratio, because NC has sufficient information about target customers and their neighbors without damaging the information about the target customers.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.1
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• pp.3-11
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• 2015

Purpose It is hard to obtain high quality images of knee and T.M joint because of a lot of soft tissues in the knee and T.M joint area. Most conventional system for high resolution scintigraphy was used by 4 mm aperture pinhole collimator. Performance comparison of high-resolution pinhole SPECT for Micro deluxe phantom using conventional system. the aim of this study is to evaluate performance of each aperture according to the diameter size and the usefulness of 24-hour delayed bone scintigraphy. Materials and Methods In this study 6 mm, 8 mm diameter pinhole collimators were mounted on Siemens E.CAM systems. In order to evaluate performance evaluation of each aperture and Micro Deluxe phantom was used for performance comparison of conventional SPECT system, Projection data were obtained with 9 degree increment per 30 second. Transverse images were reconstructed using dedicated OSEM algorithm with recovery of detector blurring. $^{99m}Tc-HDP$ source was used for 24-hour delayed bone scintigraphy. Results The knee joint images obtained with 24-hour delay were improved more than those obtained with 3-hour delay in our study. The 6 mm and 8 mm pinhole collimators FWHM have improved by 28% SNR and Uniformity have improved by 35%, Contrast has improved by 7% in 24-hour delayed knee joint image. While in 24-hour delayed T.M joint image of the 6 mm and 8 mm pinhole collimators FWHM have decreased by 60% SNR has decreased by 20% and Uniformity has decreased by 25%, Contrast has decreased significantly. Conclusion Pinhole collimators with 6 mm and 8 mm diameter could offer a superior performance for 24-hour delayed bone scintigraphy. The use of 24-hour delayed image provides additional benefits for pinhole scintigraphy of knee joint. Therefore, we expect that it is useful for precise diagnosis of knee joint and it is applicable to others joint imaging.

• Journal of Food Hygiene and Safety
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• v.32 no.2
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• pp.154-162
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• 2017

The purpose of this study was to investigate the microbial reduction effect of chlorine dioxide and sodium hypochlorite in Korean chive. Korean chive inoculated with foodborne pathogens at the level of approximately 7~8 log CFU/g was treated with various concentration of chlorine dioxide (3, 4, 10, 25 and 100 ppm and sodium hypochlorite (100, 150 and 200 ppm) for 5, 10, 30 and 60 minutes. The treatment of 150 ppm sodium hypochlorite and 50 ppm chlorine dioxide for 30 min reduced the number of total bacteria in Korean chive up to 2.0 log CFU/g. Reduction of microbial levels was observed for all concentrations of sanitizers but their effectiveness did not correspond to their concentration. Due to the quality degradation, 50 ppm chlorine dioxide was not appropriate for Korean chive. Most effective reduction of microbial levels was observed when Korean chive were treated with 9 times more sanitizer in volume. For field application, the treatment of 150 ppm sodium hypochlorite showed 2.7 and 4.0 log CFU/g reductions for numbers of total bacteria and coliforms, respectively. Therefore, washing with sodium hypochlorite of a ratio of 1:9 (Korean chive : 150 ppm sodium hypochlorite (w/v)) for 30 minutes can reduce the number of foodborne pathogen in Korean chive.