• The Journal of Internal Korean Medicine
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• v.37 no.1
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• pp.77-89
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• 2016

Objectives: The aim of this study was to develop a standard instrument of pattern identification and evaluation for chemotherapy-induced peripheral neuropathy (CIPN).Methods: The advisory committee for this study was organized by 12 professors of traditional Korean medicine from the Korean Association of Traditional Oncology. The items and structure of the instrument were designed based on a review of previous publications. We revised the instrument in consultation with the advisory committee and received additional advice via email.Results: We divided the symptoms and signs of CIPN into four pattern identifications: wind arthralgia (風痺), cold arthralgia (寒痺), dampness arthralgia (濕痺), and arthralgia of the deficiency type (虛痺). We obtained the mean weights to reflect the standard deviations from each symptom of the four pattern identifications, which were scored on a 5-point scale by the advisor committee. After we obtained the answers to discrimination between variable symptoms (變症) and ordinary symptoms (素症) from the 12 experts, we gained the final weight from the combination of the ratio of pattern identification to the number of total answers of the advisory committee and the mean weight.Conclusions: The Instrument on Pattern Identification and Evaluation for CIPN was developed through a discussion between 12 experts. There was a limitation that the validity and reliability of this instrument have not been proven. However, the significance of this study was that it is the first Instrument on Pattern Identification and Evaluation aimed at assessing CIPN in traditional Korean medicine.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.3
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• pp.98-106
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• 2011

This study was performed with the purpose of providing basic data for the improvement of zoning regulations of urban nature park by analyzing the present problem which occurred during last 6 years from the year of 2005 when the program was introduced for the first time. The study was processed first by the analysis of the cases of problems evoked by citizens, second the other problems was delineated by interviews of officials, at last the validity of all of the problems was verified by a group of professionals through delphi method. The results can be summarized as follows. 1. In relation to the designation and management of urban national park areas, designation criteria, designation process, maintenance, laws and regulations and 20 other items were found to be problematic. After Delphi method, 5 items were removed and 2 added. The results showed that there were 17 problematic items in total. 2. Regarding the problem of criteria for designation, which are, lack of priority(weights), lack of objectivity due to the difficulty to use quantitative evaluation method, incompatibility for contaminated land environmental impact assessment, incompatibility of land suitability assessment, lack of detailed field survey standards, lack of national park area standards, and 6 other items. 3. Regarding the problem of designation process, which are, the occurrence of civil appeals for designating a new national park, the needs of feasibility study on the urban national park areas constructed before urban national park guidelines came out, lack of a comprehensive review of the boundaries set when determining national park area management plan, poor temporal and financial conditions for an accurate field survey, and 4 other items. 4. Regarding the problem of maintenance management, which are, lack of management system in each space, lack of effectiveness of Urban Nature Park Area Management Plan among master plans for park and green areas, the occurrence of dual managers due to dual natures such as purpose area and city park, lack of professional manpower to manage park areas, and 4 other items. 5. Regarding the problems of regulation guidelines, which are, lack of separate urban park area management plan, incompatibility of the permitted facilities in the park to the park area standards, lack of feasibility study on urban park areas, and 3 other items.

• Journal of Korean Public Health Nursing
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• v.3 no.1
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• pp.38-60
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• 1989

The present analysis was undertaken to find out the relationships between birth weight & Apgar Score of newborn infant & maternal factors. The medical records of 1436 newborn infants who had been at the Korea University III Seoul from January. 1.1984. to December. 31. 1985, were examined. Measurements include weight and Apgar Score. As the possible factors influencing the birth weight & Apgar Score of newborn infant, 9 variables such as : mother's age, frequency ·of pregnancy, frequency of fullterm delivery, frequency. of premature, frequency of abortion, mother's hemoglobin level, complications during pregnancy gestational period and infant sex at birth were selected among the items recorded in the medical records of newborn infants and their mothers. The weight & Apgar Score of newborn infants were compared separately by sex with group percent of those variables. The results were summarized as follows: 1. All of those factors chosen are supposed to be influencing upon the birth weight and Apgar Score examined at birth indirectly through inducing early termination of pregnancy. 2. The most influencing variable of birth weight of newborn infants was gestation period. The most influencing variable of Apgar Score of infant newborn was gestation period. 3. The relationships of those influencing factors are more clear on the birth weights of newborn than on the Apgar Score. 4. More then half of low birth weight infants are turned out to be physiologically normal through the evaluation by Apgar Scoring. Conclusively, All of those factors chosen are supposed to be influencing upon the birth weight and apgar score examined at birth indirectly through inducing early termination of pregnancy.

• Information Systems Review
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• v.9 no.3
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• pp.157-181
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• 2007

Main concerns of IT project managements are concentrated on the output control and process management. IT project, however, is difficult to measure the quality of achievement, because it produces invisible and intangible outputs. Many studies have been carried on to quantify the intangible aspects of process management. However, most of them have been focused on the technological aspects. This study measures the priority of factors to manage IT project by applying the IT-BSC and PMBOK method. Established indexes include the factors of managerial, social and future-oriented perspectives to check the different aspects of project management over the technical factors. This study uses AHP method for quantitative measurement. This study can be meaningful because of following reasons. First, this study re-arranges IT project management evaluation indexes by balanced scorecard. Second, this model includes human factors of developers and users who are directly related to the project development and operation. Third, important items of each stakeholder have been separated, and the weights of each item have been quantified to have fixed values.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.951-958
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• 2021

With the growing cyber threat to information assets, it has become important to share threat information quickly. This paper examines the sharing of cyber threat information and presents a method to determine the importance of threat indicators in the information sharing market by calculating weights. The analysis was conducted using AHP techniques, with a pairwise comparison of the four factors(attacker & infected system indicators, role indicators, malicious file indicators, technique & spread indicators) and the details of each factor. Analysis shows that malicious file indicators are the most important among the higher evaluation factors and infected system IP, C&C and Smishing are the most important factors in comparison between detailed items. These findings could be used to measure the preference of consumers and the contribution of information provider for facilitating information sharing.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.107-120
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• 2014

This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.864-881
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• 2021

Purpose: This study aims is to provide a total care solution preventing disaster based on Big Data and AI technology and to service safety considered by individual situations and various risk characteristics. The purpose is to suggest a method that customized comprehensive index services to prevent and respond to safety accidents for calculating the living safety index that quantitatively represent individual safety levels in relation to daily life safety. Method: In this study, we use method of mixing AHP(Analysis Hierarchy Process) and Likert Scale that extracted from consensus formation model of the expert group. We organize evaluation items that can evaluate life safety prevention services into risk indicators, vulnerability indicators, and prevention indicators. And We made up AHP hierarchical structure according to the AHP decision methodology and proposed a method to calculate relative weights between evaluation criteria through pairwise comparison of each level item. In addition, in consideration of the expansion of life safety prevention services in the future, the Likert scale is used instead of the AHP pair comparison and the weights between individual services are calculated. Result: We obtain result that is weights for life safety prevention services and reflected them in the individual risk index calculated through the artificial intelligence prediction model of life safety prevention services, so the comprehensive index was calculated. Conclusion: In order to apply the implemented model, a test environment consisting of a life safety prevention service app and platform was built, and the efficacy of the function was evaluated based on the user scenario. Through this, the life safety index presented in this study was confirmed to support the golden time for diagnosis, response and prevention of safety risks by comprehensively indication the user's current safety level.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.2
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• pp.23-40
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• 2022

Many constructed wetlands have been installed in dam reservoirs nationwide for ecological purification of watershed pollutants, but aging and reduced efficiency are becoming issues. To improve the management of constructed wetlands, an objective evaluation of structural suitability is required. This study evaluated 39 constructed wetlands of 15 dams. First, through fogus group interview(FGI), survey analysis, and analytic hierarchy process(AHP), eight evaluation items in the physical and vegetative aspects were selected and the evaluation criteria applied with weights were prepared. Second, as a result of the structural suitability evaluation, the average score of the overall constructed wetlands was 80.8, with 10 sites rated as 'good grade(91~100)', 22 sites rated as 'normal grade(71~90)' and 7 sites rated as 'poor grade(70 or less)'. The average score of physical structure evaluation was 52.6, with 14 sites rated as 'good', 21 sites as 'normal' and 4 sites as 'poor'. The suitability of location was good level in most constructed wetlands, but the water supply system, depth of water, ratio of length-to-width, and slope of flow channel were evaluated as 'normal' or less in constructed wetlands of 50% or more. Therefore, it was found that overall improvement was necessary for stable flow supply and flow improvement in the constructed wetland. The average score of vegetative structure evaluation was 28.2, and about 84% of them were identified as 'normal' or lower. As a result of analyzing the Spearman's correlation coefficient between the physical structure evaluation score and the vegetation structure evaluation score, there was a significant correlation(r = 0.728, p < 0.001), and it was found that each evaluation factor also influences each other. As a result of the case review of 6 constructed wetlands, the appropriateness of the evaluation results was confirmed, and it was found that the location, flow rate supply, and type of wetland had a great influence on the efficiency and operation of the wetland. Through this study, it will be possible to derive structural weaknesses of constructed wetlands in dam reservoirs as a nature-based solution, to prepare types and practical alternatives for improved management of each constructed wetland in the future, and to contribute to enhancing various environmental functions.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.67-74
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• 2015

In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.709-718
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• 2016

The study considers viewpoints for qualitative improvement of landscape planning based on research literature, books and reports. By classifying items used in this study, evaluation criteria was derived for viewpoint selection using SPSS Statistics. In addition, we establish weights and prioritize viewpoints by measuring the relative importance within the hierarchical index. The analysis results are as follows: First, 16 viewpoints were determined using surveys from experts to establish specific and systematic plans for landscape simulation. Second, with respect to the medium classification level of viewpoint evaluation, the most important factor found was 'view' followed by 'publicness' and 'place.' Third, priority by viewpoint was found to exhibit the following order of relative importance: visual openness of viewpoint, favorability as view target, cultural property space, historicity, public place, gateway place, area where the target can be observed, thickly-populated or most-used place, place where various shapes of targets and surrounding landscape can be identified, ecological protection area, river and waterside area, viewing angle (relief-etching), viewing direction, major roads, distance between the viewpoint and the target, and plains and farmland. These results can contribute to developing systematic and reliable analysis frame for qualitative improvement of landscape planning and evaluating landscape simulation.