• Journal of Agricultural Extension & Community Development
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• v.21 no.2
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• pp.1-28
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• 2014

Private consulting firms that are currently participating in rural area development projects with a bottom-up approach are involved in nearly all areas of rural area development, and the policy environment that emphasizes the bottom-up approach will further expand their participation. Reviews of private consulting firms, which started out with high expectations in the beginning, are now becoming rather negative. Expertise is the key issue in the controversy over private consulting firms, and the analysis tends to limit the causes of the problems within firms. This study was conducted on the premise that the fixation on cause and structure results in policy issues in the promotion process. That is because the government authorities are responsible for managing and supervising the implementation of policies, not developing the policies. The current issues with consulting firms emerged because of the hasty implementation of private consulting through the government policy trend without sufficient consideration, as well as the policy environment that demanded short-term outcomes even though the purpose of bottom-up rural area development lies in the ideology of endogenous development focused on the changes in residents' perceptions. Research was conducted to determine how the problems of private consulting firms that emerged and were addressed in this context influenced the consulting market, using current data and based on the firms' business performance. In analyzing the types, firms were divided into three groups: top performers including market leaders (9), excellent performers (36), and average performers (34). An analysis of the correlation between the business performance of each type and managerial resources such as each firm's expertise revealed that there was only a correlation between human resources and regional development in excellent performers, and none was found with the other types. These results imply that external factors other than a firm's capabilities (e.g., expertise) play a significant role in the standards of selecting private consulting firms. Thus, government authorities must reflect on their error of hastily adopting private consulting firms without sufficient consideration and must urgently establish response measures.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.19-38
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• 2017

Collaborative filtering (CF) algorithm has been popularly used for implementing recommender systems. Until now, there have been many prior studies to improve the accuracy of CF. Among them, some recent studies adopt 'hybrid recommendation approach', which enhances the performance of conventional CF by using additional information. In this research, we propose a new hybrid recommender system which fuses CF and the results from the social network analysis on trust and distrust relationship networks among users to enhance prediction accuracy. The proposed algorithm of our study is based on memory-based CF. But, when calculating the similarity between users in CF, our proposed algorithm considers not only the correlation of the users' numeric rating patterns, but also the users' in-degree centrality values derived from trust and distrust relationship networks. In specific, it is designed to amplify the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the trust relationship network. Also, it attenuates the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the distrust relationship network. Our proposed algorithm considers four (4) types of user relationships - direct trust, indirect trust, direct distrust, and indirect distrust - in total. And, it uses four adjusting coefficients, which adjusts the level of amplification / attenuation for in-degree centrality values derived from direct / indirect trust and distrust relationship networks. To determine optimal adjusting coefficients, genetic algorithms (GA) has been adopted. Under this background, we named our proposed algorithm as SNACF-GA (Social Network Analysis - based CF using GA). To validate the performance of the SNACF-GA, we used a real-world data set which is called 'Extended Epinions dataset' provided by 'trustlet.org'. It is the data set contains user responses (rating scores and reviews) after purchasing specific items (e.g. car, movie, music, book) as well as trust / distrust relationship information indicating whom to trust or distrust between users. The experimental system was basically developed using Microsoft Visual Basic for Applications (VBA), but we also used UCINET 6 for calculating the in-degree centrality of trust / distrust relationship networks. In addition, we used Palisade Software's Evolver, which is a commercial software implements genetic algorithm. To examine the effectiveness of our proposed system more precisely, we adopted two comparison models. The first comparison model is conventional CF. It only uses users' explicit numeric ratings when calculating the similarities between users. That is, it does not consider trust / distrust relationship between users at all. The second comparison model is SNACF (Social Network Analysis - based CF). SNACF differs from the proposed algorithm SNACF-GA in that it considers only direct trust / distrust relationships. It also does not use GA optimization. The performances of the proposed algorithm and comparison models were evaluated by using average MAE (mean absolute error). Experimental result showed that the optimal adjusting coefficients for direct trust, indirect trust, direct distrust, indirect distrust were 0, 1.4287, 1.5, 0.4615 each. This implies that distrust relationships between users are more important than trust ones in recommender systems. From the perspective of recommendation accuracy, SNACF-GA (Avg. MAE = 0.111943), the proposed algorithm which reflects both direct and indirect trust / distrust relationships information, was found to greatly outperform a conventional CF (Avg. MAE = 0.112638). Also, the algorithm showed better recommendation accuracy than the SNACF (Avg. MAE = 0.112209). To confirm whether these differences are statistically significant or not, we applied paired samples t-test. The results from the paired samples t-test presented that the difference between SNACF-GA and conventional CF was statistical significant at the 1% significance level, and the difference between SNACF-GA and SNACF was statistical significant at the 5%. Our study found that the trust/distrust relationship can be important information for improving performance of recommendation algorithms. Especially, distrust relationship information was found to have a greater impact on the performance improvement of CF. This implies that we need to have more attention on distrust (negative) relationships rather than trust (positive) ones when tracking and managing social relationships between users.

• Korean Journal of Veterinary Research
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• v.5 no.1
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• pp.61-96
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• 1965

Observations were made on the blood picture of total 196 heads of healthy Korean cattles, including 98 males and 98 females in the purpose of determination of hematological values and its sex difference, and seasonal variations during one year period from December 1963 to November 1964. The blood sampling were scheduled by random in four different seasons and the sample size of both sex included in each season were designated to be same size. The ranges, averages or mean values of the erythrocytes, hemoglobin, hematocrit, mean corpuscular hemoglobin concentration, total white blood cell count and differential count were determined in this studies and their respective standard deviation, standard error of means, sex defferences and seasonal variations were as follows; 1. The erythrocyte count of male showed a range of $5.0{\times}10^6/c.mm$ to $8.75{\times}10^6/c.mm$ with a mean of $6.5{\pm}0.096{\times}10^6/c.mm$. Female showed a range of $5.0{\times}10^6/c.mm$ to $8.30{\times}10^6/c.mm$, with a mean of 6. $131{\pm}0.078{\times}10^6/c.mm$. There was a highly significant sex difference and seasomal variation was not found to be significant. 2. The hemoglobin value of male showed a range of 9.0g/100cc. to 14.5g/100cc. with a mean of $11.074{\pm}0.143g/100cc$. Female showed a range of 9.0g/100cc to 13.0g/100cc. with a mean of $10.745{\pm}0.034g/100cc$. There was a highly significant sex difference and seasonal variation was not found to be significant. 3. The hematocrit value of male showed a range of 28% to 45% and with a mean of $34.867{\pm}0.468%$. Female showed a range of 28% to 42% with a mean of $32.888{\pm}0.322%$. There was a highly significant sex difference and seasonal variation was not found to be significant. 4. The mean corpuscular hemoglobin of male showed a range of 14.4rr. to 19.6rr. with a mean of $17.1{\pm}0.112rr$. Female showed a range of 14.7rr. to 19.5rr. with a mean of $17.6{\pm}0.113rr$. 5. The mean corpusular volume of male showed a range of $42.5{\mu}^3$ to $62.2{\mu}^3$ with a mean of $53.9{\pm}0.419{\mu}^3$, Female showed a range of $44.2{\mu}^3$ to $60.0{\mu}^3$ with a mean of $53.8{\pm}0.375{\mu}^3$. 6. The mean corpuscular hemoglobin concentration of male showed a range of 28.1 % to 34.9% with a mean of $31.4{\pm}0.161%$. Female showed a range of 28.0% to 34.9% with a mean of $30.9{\pm}0.169%$. 7. The total leucocyte count of male showed a range of 4,000/c.mm to 13,100/c.mm. with a mean of $9,338{\pm}218.23/c.mm$. Female showed a range of 4,000/c.mm. to 14,000/c.mm. with a mean of $9,338{\pm}235.90/c.mm$. Six difference was not found to be significant and there was a highly significant seasonal variation. 8. The differential count of male, the means of neutrophil, stab, segmented cell, Iymphocyte, monocyte, eosinophil and basophil were $31.173{\pm}0.570%$, 0.3%. $30.867{\pm}0.564%$, $55.112{\pm}0.603%$, $3.745{\pm}0.082%$, $9.867{\pm}0.422%$ and 0.14% rspectively. Female showed means of $31.010{\pm}0.572%$, 0.2%, $30.806{\pm}0.569%$, $53.929{\pm}0.634%$, $4.082{\pm}0.109%$, $10.908{\pm}0.503%$ and 0.12% respectively. There were significant sex differences in monocyte and highly significant sex difference in eosinophil, and seasonal variation were found to be highly significant in neutrophil, monocyte and eosinophil. 9. Hematological comparison made between cattles infested with so called "small type piroplasma" and non-infested group. The result of investigation showed no significant difference upon the red blood cell, hemoglobin and hematocrit values between lighty infested group and non-infested group. 10. Age distribution of test group in this study ranged from 2 years to 6 years in both sex and their average age were $4.45{\pm}0.114$(male) and $4.50{\pm}0.116$(female). There found to be no significant sex difference and seasonal variations in the age of test group.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.12
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• pp.1784-1792
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• 2007

This study set out to identify the problems with hat labels and to search for improvement measures by examining and analyzing consumers' practice of managing their hats. It also intended to provide accurate and enough information about how to keep and wash hats and thus help consumers use their hats for a long period. In an attempt to investigate how consumers wash and manage their hats, a survey was carried out to 395 individuals in their twenties and over who owned hats living in urban areas including Seoul, and were quota sampled according to age and gender. The survey period is March to April 2007. The collected data were statistically treated with the SPSS 12.0 program in terms of frequency, percentage, mean, standard error, cross tabulation, t-test, and one-way ANOVA. The findings were as followed. First, the respondents were in the average level of perceiving and practicing the washing methods of their hats. The female respondents who had more experiences with laundering than the males knew and practiced the washing methods for hats better than males. Second, compared to other clothing items, hat wearers were more likely to pay careful attention to their hats by putting their hats in a laundry net and applying a laundry detergent for wool fabrics when using a washing machine or washing their hats with their own hands. And third, most of the hat wearers were aware of the importance of hat labels and showed a lower level of trust in them than other clothing items. The suppliers need to offer accurate and practical labels in order to regain the consumers' trust. Many consumers had some difficulties figuring out the size system of hats. In particular, the male consumers had a low level of perception of labels, which implies that there should be specific efforts to educate them about general labels.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.1
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• pp.15-22
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• 2018

Purpose Respiratory motion during PET/MRI acquisition may result in image blurring and error in measurement for volume and quantification of lesion. The aim of this study was to evaluate changes of quantitative accuracy, tumor size and image quality by applying MR based respiratory motion correction technique (MBRMCT) using integrated PET/MR scanner. Materials and Methods Data of 30 patients (aged $62.5{\pm}10.2y$) underwent $^{18}F-FDG$ liver PET/MR (Biograph mMR 3.0T, Siemens) study were collected. PET listmode data for 7 minutes was simultaneously acquired with maximum average gate (MAG), minimum time gate (MTG) and non gate (NG) T1 weighted MR images. Gated PET reconstruction was performed using mu-maps generated from MAG and MTG by setting 35% of efficiency window. Maximum SUV ($SUV_{max}$), peak SUV ($SUV_{peak}$), tumor size and full width at half maximum (FWHM) in the z-axis direction of MAG, MTG and NG PET images were evaluated. Results Compared to NG, mean $SUV_{max}$ and $SUV_{peak}$ were increased in MAG 13.15%(p<0.0001), 8.66%(p<0.0001), MTG 13.27%(p<0.0001), 8.80%(p<0.0001) and mean tumor size and FWHM were decreased in MAG 14.47%(p<0.0001), 15.49%(p=0.0004), MTG 14.89%(p<0.0001), 15.79%(p=0.0003) respectively. Mean $SUV_{max}$ and $SUV_{peak}$ of MTG were increased by 0.07%(p=0.8802), 0.13%(p=0.7766). Mean tumor size and FWHM of MTG were decreased by 0.49%(p=0.2786), 0.36%(p=0.2488) compared to MAG. There was no statistically significant difference between MAG and MTG which increase total scan time for about 7 and 2 minutes. Conclusion SUV, accuracy of tumor size and spatial resolution were improved in both of MAG and MTG by applying MBRMCT without installing additional hardware in liver PET/MR study. More accurate information can be provided with the increase of 2 minutes scan time if applying MTG of MBRMCT to various abdominal PET/MR studies affected by respiratory motion.

• Journal of Soil and Groundwater Environment
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• v.13 no.6
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• pp.72-84
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• 2008

This study was carried out to provide proper management plans for small portable water supply system in the Nonsan area through water quality monitoring, hydrogeochemical investigation and multivariate statistical analyses. Nonsan area is a typical rural area heavily depending on small water supply system for portable usage. Geology of the area is composed of granite dominantly along with metasedimentary rocks, gneiss and volcanic rocks. The monitoring results of small portable water supply system showed that 13-21% of groundwaters have exceeded the groundwater standard for drinking water, which is 5 to 8 times higher than the results from the whole country survey (2.5% in average). The major components exceeding the standard limits are nitrate-nitrogen, turbidity, total coliform, bacteria, fluoride and arsenic. High nitrate contamination observed at southern and northern parts of the study area seems to be caused by cultivation practices such as greenhouses. Although Ca and $HCO_3$ are dominant species in groundwater, concentrations of Na, Cl and $NO_3$ have increased at the granitic area indicating anthropogenic contamination. The groundwaters are divided into 2 groups, granite and metasedimentary rock/gneiss areas, with the second principal component presenting anthropogenic pollution by cultivation and residence from the principal components analysis. The discriminant analysis, with an error of 5.56% between initial classification and prediction on geology, can explain more clearly the geochemical characteristics of groundwaters by geology than the principal components analysis. Based on the obtained results, it is considered that the multivariate statistical analysis can be used as an effective method to analyze the integrated hydrogeochemical characteristics and to clearly discriminate variations of the groundwater quality. The research results of small potable water supply system in the study area showed that the groundwater chemistry is determined by the mixed influence of land use, soil properties, and topography which are controlled by geology. To properly control and manage small water supply systems for central and local governments, it is recommended to construct a total database system for groundwater environment including geology, land use, and topography.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.187-206
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• 2007

The development of computer and information technology has been combined with the information superhighway internet infrastructure, so information widely spreads not only in special fields but also in the daily lives of people. Information ubiquity influences the traditional way of transaction, and leads a new E-commerce which distinguishes from the existing E-commerce. Not only goods as physical but also service as non-physical come into E-commerce. As the scale of E-Commerce is being enlarged as well. It keeps people from finding information they want. Recommender systems are now becoming the main tools for E-Commerce to mitigate the information overload. Recommender systems can be defined as systems for suggesting some Items(goods or service) considering customers' interests or tastes. They are being used by E-commerce web sites to suggest products to their customers who want to find something for them and to provide them with information to help them decide which to purchase. There are several approaches of recommending goods to customer in recommender system but in this study, the main subject is focused on collaborative filtering technique. This study presents a possibility of pre-evaluation for the prediction performance of customer's preference in collaborative filtering before the process of customer's preference prediction. Pre-evaluation for the prediction performance of each customer having low performance is classified by using the statistical features of ratings rated by each customer is conducted before the prediction process. In this study, MovieLens 100K dataset is used to analyze the accuracy of classification. The classification criteria are set by using the training sets divided 80% from the 100K dataset. In the process of classification, the customers are divided into two groups, classified group and non classified group. To compare the prediction performance of classified group and non classified group, the prediction process runs the 20% test set through the Neighborhood Based Collaborative Filtering Algorithm and Correspondence Mean Algorithm. The prediction errors from those prediction algorithm are allocated to each customer and compared with each user's error. Research hypothesis : Two research hypotheses are formulated in this study to test the accuracy of the classification criterion as follows. Hypothesis 1: The estimation accuracy of groups classified according to the standard deviation of each user's ratings has significant difference. To test the Hypothesis 1, the standard deviation is calculated for each user in training set which is divided 80% from MovieLens 100K dataset. Four groups are classified according to the quartile of the each user's standard deviations. It is compared to test the estimation errors of each group which results from test set are significantly different. Hypothesis 2: The estimation accuracy of groups that are classified according to the distribution of each user's ratings have significant differences. To test the Hypothesis 2, the distributions of each user's ratings are compared with the distribution of ratings of all customers in training set which is divided 80% from MovieLens 100K dataset. It assumes that the customers whose ratings' distribution are different from that of all customers would have low performance, so six types of different distributions are set to be compared. The test groups are classified into fit group or non-fit group according to the each type of different distribution assumed. The degrees in accordance with each type of distribution and each customer's distributions are tested by the test of ${\chi}^2$ goodness-of-fit and classified two groups for testing the difference of the mean of errors. Also, the degree of goodness-of-fit with the distribution of each user's ratings and the average distribution of the ratings in the training set are closely related to the prediction errors from those prediction algorithms. Through this study, the customers who have lower performance of prediction than the rest in the system are classified by those two criteria, which are set by statistical features of customers ratings in the training set, before the prediction process.

• Journal of the Korean Society of Radiology
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• v.7 no.2
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• pp.157-163
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• 2013

This study was to analyze quantitatively movement of planning target volume (PTV) and change of PTV volume through movement of diaphragm according to breathing phase. The purpose of present study was to investigate optimized respiration phase for radiation therapy of lung cancer. Simulated breathing training was performed in order to minimize systematic errors which is caused non-specific or irregular breathing. We performed 4-dimensional computed tomography (4DCTi) in accordance with each respiratory phase in the normalized respiratory gated radiation therapy procedures, then not only defined PTVi in 0 ~ 90%, 30 ~ 70% and 40 ~ 60% in the reconstructed 4DCTi images but analyzed quantitatively movement and changes of volume in PTVi. As a results, average respiratory cycle was $3.4{\pm}0.5$ seconds by simulated breathing training. R2-value which is expressed as concordance between clinically induced expected value and actual measured value, was almost 1. There was a statistically significant. And also movement of PTVi according to each respiration phase 0 ~ 90%, 30 ~ 70% and 40 ~ 60% were $13.4{\pm}6.4mm$, $6.1{\pm}2.9mm$ and $4.0{\pm}2.1mm$ respectively. Change of volume in PTVi of respiration phase 30 ~ 70% was decreased by $32.6{\pm}8.7%$ and 40 ~ 60% was decreased by $41.6{\pm}6.2%$. In conclusion, PTVi movement and volume change was reduced, when we apply a short breathing phase (40 ~ 60%: 30% duty cycle) range. Furthermore, PTVi margin considered respiration was not only within 4mm but able to get uniformity of dose.

• The Journal of Korean Society for Radiation Therapy
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• v.22 no.1
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• pp.11-18
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• 2010

Purpose: In every time radiation therapy set up errors occur because internal anatomical organs move due to breathing and change of patient's position. These errors may affect the change of dose distribution between target area and normal structure. This study investigates the usefulness of body-fix in clinical treatment. Materials and Methods: Among 55~60 aged male patients who has hepatocellular carcinoma in area of liver's couinaud classification, we chose 10 patients and divided two groups by using body-fix or not. When applying body-fix, we maintained a vacuum of 80 mbar pressure by using vacuum pump (Medical intelligence, Germany). Patients had free breathing with supine position. After working to fuse and consist MV-CT (megavoltage computed tomography) with KV-CT (kilovoltage computed tomography) obtained by 5 times treatments, we compared and analyzed set up errors occurred to (Right to Left, RL) of X axis, (Anterioposterio, AP) of Z axis, (Cranicoudal, CC) of Y axis. Results: Average Set up errors through image fusion showed that group A moved $0.3{\pm}1.1\;mm$ (Cranicoudal, CC), $-1.1{\pm}0.7\;mm$ (Right to Left, RL), $-0.2{\pm}0.7\;mm$ (Anterioposterio, AP) and group B moved $0.62{\pm}1.94\;mm$ (Cranicoudal, CC), $-3.62{\pm}1.5\;mm$ (Right to Left, RL), $-0.22{\pm}1.2\;mm$ (Anterioposterio, AP). Deviations of X, Y and Z axis directions by applying body-fix indicated that maximum X axis was 5.5 mm, Y axis was 19.8 mm and Z axis was 3.2 mm. In relation to analysis of error directions, consistency doesn't exist for every patient but by using body-fix showed that the result of stable aspect in spite of changes of everyday's patient position and breathing. Conclusion: Using body-fix for liver cancer patient is considered effectively for tomotherapy. Because deviations between group A and B exist but they were stable and regular.