• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.5
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• pp.1191-1199
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• 2016

To ensure the fairness, journal reviewers use blind-review system which hides the author information of the journal. Even though the author information is blinded, we could identify the author by looking at the field of the journal or containing words and phrases in the text. In this paper, we collected 315 journals of 20 authors and extracted text data. Bag-of-words were generated after preprocessing and used as an input of artificial neural network. The experiment shows the possibility of circumventing the blind review through identifying the author of the journal. By the experiment, we demonstrate the limitation of the current blind-review system and emphasize the necessity of robust blind-review system.

• Health Policy and Management
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• v.16 no.2
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• pp.49-76
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• 2006

The aim of this study was to explore the effects of a computerized review program which was introduced in August 1, 2003, using claims data for acute respiratory infection related diseases. National Health Insurance (NHI) claims data on respiratory infection related diseases before and after the introduction, with six month intervals respectively, were used for the analysis. Clinic was the unit of observation, and clinics with only one physician whose specialty was internal medicine, pediatrics, otorhinolaryngology and family medicine and clinics with a general practitioner were selected. The final sample had 7,637 clinics in total. Indices used to measure practice pattern was prescription rates of antibiotics, prescription rates of injection drug per visit, treatment costs per claim, and total costs per claim. Changes in the number of claims for major disease categories and upcoding index for disease categories were used to measure claiming behavior. Data were analysed using descriptive analysis, t-test for indices changes before and after the introduction, analysis of variance (ANOVA) for practice pattern change for major disease categories, and multiple regression analysis to identify whether new system influenced on provider' practice patterns or not. Prescription of antibiotics, prescription rates of injection drug, treatment costs per claim, and total costs per claim decreased significantly. Results from multiple regression analysis showed that a computerized review system had effects on all the indices measuring behavior. Introduction of the new system had the spillover effects on the provider's behavior in the related disease categories in addition to the effects in the target diseases, but the magnitude of the effects were bigger among the target diseases. Rates of claims for computerized review over total claims for respiratory diseases significantly decreased after the introduction of a computerized review system and rates of claims for non target diseases increased, which was also statistically significant. Distribution of the number of claims by disease categories after the introduction of a computerized review system changed so as to increase the costs per claims. Analysis of upcoding index showed index for 'other acute lower respiratory infection (J20-22)', which was included in the review target, decreased and 'otitis media (H65, H66)', which was not included in the review target, increase. Factors affecting provider's practice patterns should be taken into consideration when policies on claims review method and behavior changes. It is critical to include strategies to decrease the variations among providers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.1
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• pp.165-171
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• 2014

We develop an optimization algorithm for a periodic review inventory system under a stochastic budget constraint. While most conventional studies on the periodic review inventory system consider a simple budget limit in terms of the inventory investment being less than a fixed budget, this study adopts more realistic assumption in that purchasing costs are paid at the time an order is arrived. Therefore, probability is employed to express the budget constraint. That is, the probability of total inventory investment to be less than budget must be greater than a certain value assuming that purchasing costs are paid at the time an order is arrived. We express the budget constraint in terms of the Lagrange multiplier and suggest a numerical method to obtain optional values of the cycle time and the safety factor to the system. We also perform the sensitivity analysis in order to investigate the dependence of important quantities on the budget constraint. We find that, as the amount of budget increases, the cycle time and the average inventory level increase, whereas the Lagrange multiplier decreases. In addition, as budget increases, the safety factor increases and reaches to a certain level. In particular, we derive the condition for the maximum safety factor.

• Korean Journal of Clinical Pharmacy
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• v.29 no.1
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• pp.25-32
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• 2019

Objective: South Korea made a list of potentially inappropriate medications (PIMs) for elderly patients in 2015 and has prompted medical professionals to prescribe proper medication by using the drug utilization review (DUR) system. It has been three years since the system was introduced, but related studies have rarely been conducted. This study aimed to evaluate the effect of the DUR system on the prescription of PIMs for elderly patients. Methods: The data on the prescription of PIMs for elderly patients (${\geq}65$ years) who received medical treatment between March 1st and May 31st in 2015 (before introduction of the DUR system) and who received medical treatment between March 1st and May 31st in 2018 (after introduction of the DUR system) were retrospectively collected from electronic medical records. Results: The prescriptions of PIMs decreased from 3,716 (7.7%) to 3,857 (6.9%) (p < 0.001). The prescription of escitalopram and paroxetine, among selective serotonin reuptake inhibitors, increased significantly, and that of short-acting benzodiazepines also increased significantly from 454 (0.93%) to 624 (1.2%). Conclusion: Prescription of PIMs for elderly patients significantly decreased (p < 0.001) after the DUR system was introduced. Further expanded studies of PIMs need to be conducted for the safety of elderly patients.

• Journal of Acupuncture Research
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• v.41 no.2
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• pp.87-95
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• 2024

This review aims to analyze the efficacy of acupotomy in treating superior cluneal nerve entrapment syndrome (SCNES) by summarizing the findings of randomized controlled trials (RCTs). The RCTs were retrieved from seven databases (i.e., the Cochrane Library, PubMed, Embase, China National Knowledge Infrastructure, Korean Studies Information Service System, Research Information Service System, and Oriental Medicine Advanced Searching Integrated System). Seven RCTs were selected for this review. The results indicate that acupotomy is promising for providing significant pain relief and improving function in patients with SCNES. However, more high-quality RCTs are required to establish the long-term effectiveness and safety of acupotomy. This review provides valuable insights for clinicians and researchers in the management of SCNES.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• International Journal of Air-Conditioning and Refrigeration
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• v.14 no.4
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• pp.131-137
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• 2006

The absorber in which heat and mass transfer phenomena occur simultaneously is one of the most critical components in the absorption system. It has the most significant influence on the performance and the size of the absorption system. During the absorption process, heat and mass transfer resistances exist in both liquid and vapor regions, so that the heat transfer mode should be carefully selected to reduce them. The objective of this paper is to review the previous papers analysing mathematical models of simultaneous heat and mass transfer phenomena during the absorption process. The most conventional working fluids ($H_2O$LiBr and $NH_3/H_2O$) are considered and the most common absorption modes (falling film and bubble mode) are dealt with in this review.

• Journal of the Korean Solar Energy Society
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• v.31 no.3
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• pp.57-66
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• 2011

A Photovoltaic/Thermal(PVT) solar system consists of PV module and thermal absorber plate which convert the absorbed solar radiation into electricity and heat. Meaningful researches and development (R&D) on the PVT technologies have been performed since the 1970s. This paper presents a review of the previous works covering the various types of PVT and their performance analysis in terms of electrical and thermal efficiency. This review compares electrical and thermal efficiency of the different types of PVT collectors and analyzes the parameters affecting PVT performance. Based on the literature review, box channel type PVT with unglazed, or flat plate PVT with glazed have the highest efficiency among them. From the literature review, R&D should be carried out aiming at improving their overall electrical and thermal efficiency, cutting down the cost, and making them more competitive in the energy consumption market.

• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.201-208
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• 1997

In order to improve the safety of nuclear power plant, we performed a human factors review for the CFMS(Critical Function Monitoring system) design of nuclear power plant. Three works were performed in this study. In first work, we developed human factors engineering program plan(HFEPP) and human factors engineering verification and validation plan (HFE-V & V plan) to effectively perform CFMS design and review. In second work, we identified human engineering discrepancies(HEDs) for CFMS design through human factors design review and proposed those resolutions. In the third work, we developed the evaluation and management methodology for identified KEDs. Methodology developed in this study can be used in other complex system as well as in CFMS design review.

• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.209-217
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• 2016

As smartphone usage increases, the number of consumers who refer to review data of e-commercial products using web sites and SNS is also explosively multiplying. However, reading review data using traditional websites and SNS is time consuming. Also, it is impossible for consumers to read all the reviews. Therefore, a system that collects review data of products and conducts sentiment word analysis of the review is required to provide useful information. The majority of systems that provide such information inadequately reflect the properties of the product. In this study, we described a system that provides analysis and evaluation of e-commerce products through review sentiment words as reflected properties of the product. Furthermore, the system enables consumers to access processed information about reviews quickly and in visual format.