• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.250-261
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• 2004

A novel method for ab initio prediction of protein tertiary structures, PROFESY (PROFile Enumerating SYstem), is introduced. This method utilizes secondary structure prediction information and fragment assembly. The secondary structure prediction of proteins is performed with the PREDICT method which uses PSI-BLAST to generate profiles and a distance measure in the pattern space. In order to predict the tertiary structure of a protein sequence, we assemble fragments in the fragment library constructed as a byproduct of PREDICT. The tertiary structure is obtained by minimizing the potential energy using the conformational space annealing method which enables one to sample diverse low lying minima of the energy function. We apply PROFESY for prediction of some proteins with known structures, which shows good performances. We also participated in CASP5 and applied PROFESY to new fold targets for blind predictions. The results were quite promising, despite the fact that PROFESY was in its early stage of development. In particular, the PROFESY result is the best for the hardest target T0161.

• YAKHAK HOEJI
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• v.53 no.4
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• pp.173-178
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• 2009

This study aimed to analyze the master's and doctoral theses in social pharmacy field over the past 10 years in Korea. Theses were searched based on the Korean National Assembly Digital Library System, and descriptive analyses were conducted using SAS. Among 669 theses, pharmacy/pharmacist accounted for 24.8%, followed by drug misuse with 16.9%, and pharmaceuticals industry related theses with 16.6%. Graduate school of pharmacy was responsible for a share of 27.2%, suggesting that approximately a quarter of the entire social pharmacy related theses are studies at the school of pharmacy.

• Journal of Mechanical Science and Technology
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• v.18 no.7
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• pp.1121-1130
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• 2004

The Genetic Algorithm (GA), an optimization technique based on the theory of natural selection, has proven to be a relatively robust means of searching for global optimum. It converges to the global optimum point without auxiliary information such as differentiation of function. In the case of a complex problem, the GA involves a large population number and requires a lot of computing time. To improve the process, this research used parallel processing with several personal computers. Parallel process technique is classified into two methods according to subpopulation's size and number. One is the fine-grained method (FGM), and the other is the coarse-grained method (CGM). This study selected the CGM as a parallel process technique because the load is equally divided among several computers. The given design domain should be reduced according to the degree of feasibility, because mechanical system problems have constraints. The reduced domain is used as an initial design domain. It is consistent with the feasible domain and the infeasible domain around feasible domain boundary. This parallel process used the Message Passing Interface library.

• Journal of Trauma and Injury
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• v.37 no.2
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• pp.97-105
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• 2024

Purpose: Massive transfusion protocols (MTPs) implementation improves clinical outcomes of the patient's resuscitation with hemorrhagic trauma. Various predictive scoring system have been used and studied worldwide to improve clinical decision. However, such research has not yet been studied in Korea. This systematic review aimed to assess the predictors of MTPs activation in patients with trauma in Korea. Methods: The PubMed, Embase, Cochrane Library, Research Information Sharing Service databases, KoreaMed, and KMbase were searched from November 2022. All studies conducted in Korea that utilized predictors of MTPs activation in adult patients with trauma were included. Results: Ten articles were eligible for analysis, and the predictors were assessed. Clinical assessments such as systolic and diastolic blood pressure, shock index (SI), prehospital modified SI, modified early warning system (MEWS) and reverse SI multiplied by the Glasgow Coma Scale (rSIG) were used. Laboratory values such as lactate level, fibrinogen degradation product/fibrinogen ratio, and rotational thromboelastometry (ROTEM) were used. Imaging examinations such as pelvic bleeding score were used as predictors of MTPs activation. Conclusions: Our systematic review identified predictors of MTPs activation in patients with trauma in Korea; predictions were performed using tools that requires clinical assessments, laboratory values or imaging examinations only. Among them, ROTEM, rSIG, MEWS, SI, and lactate level showed good effects for predictions of MTPs activation. The application of predictors for MTP's activation should be individualized based on hospital resource and skill set, also should be performed as a clinical decision supporting tools.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1326-1334
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• 2019

Knowledge base means a library stored in computer system providing useful information or appropriate solutions to specific area. Knowledge base associated with autism is the complex multidimensional information set related to the disease autism for its pathogenic factor and therapy. This paper focuses on the knowledge of biological molecular information extracted from massive biomedical texts with the aid of widespread used machine learning methods. Six classes of biological molecular information (such as protein, DNA, RNA, cell line, cell component, and cell type) are concerned and the probability statistics method, conditional random fields (CRFs), is utilized to discover these knowledges in this work. The knowledge base can help biologists to etiological analysis and pharmacists to drug development, which can at least answer four questions in question-answering (QA) system, i.e., which proteins are most related to the disease autism, which DNAs play important role to the development of autism, which cell types have the correlation to autism and which cell components participate the process to autism. The work can be visited by the address http://134.175.110.97/bioinfo/index.jsp.

• The Journal of Internal Korean Medicine
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• v.44 no.6
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• pp.1176-1185
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• 2023

Introduction: Non-erosive reflux disease (NERD) is the most common subtype of gastroesophageal reflux disease (GERD). This study aims to synthesize evidence on the efficacy and safety of various herbal medicines for the treatment of NERD. Methods and analysis: Ten electronic databases will be examined: MEDLINE (via PubMed), Cochrane Central Register of Controlled Trials, Embase, Allied and Complementary Medicine Database, China National Knowledge Infrastructure Database, Citation Information by Nii, Korean Medical Database, Korean Studies Information Service System, National Digital Science Library, and Oriental Medicine Advanced Searching Integrated System. All randomized controlled trials published from inception to May 2023 that meet the eligibility criteria will be selected. Two independent researchers will extract data, such as publication year, study design, intervention details, outcome measures, main results, and adverse events. The risk of bias and quality of evidence will be assessed, and subgroup analyses will be performed according to the type of control intervention and herbal medicine. The analysis process will be conducted using Review Manager 5.4 software. Discussion: This review will present a summary and rationale for herbal medicine's effectiveness in treating NERD. The findings of this review can help those who want to apply herbal medicine to the treatment of NERD.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.515-524
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• 2017

In this paper, we design and implement an expert system for diagnosing ADHD. As a result of the analysis with DSM-IV-TR, the ADHD diagnostic criteria are changed according to the age group. With this analyzed diagnostic, objects and their values are set and rules are created. We design a diagnostic system consisting of 'ADHD diagnostic system engine' and 'user query response program'. The ADHD diagnostic system engine is a rule-based reasoning engine that is implemented in the Prolog language and receives INPUT from the user query response program. By INPUT, the rule is executed based on the ADHD diagnostic criteria and the OUTPUT is sent back to the 'user query response program' by inferring the diagnostic result. The 'user query response program' is implemented in the Python language and serves as an interface for handling conversation with the user. The bridge between 'ADHD diagnostic system engine' and 'user query response program' is performed through the Pyswip library. As a result, the ADHD Diagnostic Expert System will help you plan your treatment with reduced diagnostic costs and use-complexity.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.3
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• pp.343-372
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• 2021

The purpose of this study is to select keywords that can recommend books by personality type, and to test whether the chosen keywords can be actually used in the categorization and customized recommendation of books for each personality type. To achieve the research goal, this study chose books that match the level of fifth and sixth grade elementary school students and first grade middle school students and commissioned an expert group to categorize the books into groups that are preferred by each personality type. As a result of the classification, half of the books in which more than five experts agreed showed high consensus. In addition, the results of classifying books by personality type with keywords extracted by the automatic word extraction system by collecting the book review data of the selected books were similar to the results of the final judgement by the expert group, except for a few books. In conclusion, this study proved that it is possible to classify and recommend books that are likely to be preferred by different personality types using review keywords.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.6
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• pp.1-11
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• 2021

To develop an efficient procedure related to the flamelet library, the machine learning process based on artificial neural network(ANN) is applied for the gaseous hydrogen/liquid oxygen combustor under a supercritical pressure condition. For hidden layers, 25 combinations based on Rectified Linear Unit(ReLU) and hyperbolic tangent are adopted to find an optimum architecture in terms of the computational efficiency and the training performance. For activation functions, the hyperbolic tangent is proper to get the high learning performance for accurate properties. A transformation learning data is proposed to improve the training performance. When the optimal node is arranged for the 4 hidden layers, it is found to be the most efficient in terms of training performance and computational cost. Compared to the interpolation procedure, the ANN procedure reduces computational time and system memory by 37% and 99.98%, respectively.

• Journal of Acupuncture Research
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• v.40 no.3
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• pp.238-244
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• 2023

Background: Occipital neuralgia (ON) is an established risk factor for headaches in the posterior cervical region. Several conservative treatments by nerve decompression and pain relief are available for ON, but these treatments have limitations. Acupuncture treatment, which is known to demonstrate analgesic effects, involves various stimulation methods, and several studies have reported their clinical benefit. No recent systematic review (SR) has compared each acupuncture type for ON treatment. Thus, this SR aims to investigate the clinical effectiveness of each acupuncture type for treating ON. Methods: We will identify relevant studies using electronic databases, including EMBASE, MEDLINE, Cochrane Library, China National Knowledge Infrastructure (CNKI), Korean Studies Information Service System (KISS), Korean Medical Database, KoreaMed, and National Digital Science Library (NDSL) from the inception until August 2023. The primary outcome will include the numerical change of pain symptoms (visual analog scale and numerical rating scale) and effective rate. Safety and secondary outcomes will include adverse events and quality of life. We will compare the conservative treatment with the acupuncture treatment using network meta-analysis. The Cochrane Collaboration "risk of bias" tools will be used to assess the quality of included trials. The Grades of Recommendation, Assessment, Development, and Evaluation will be used to examine the evidence level. Conclusion: This study will provide clinical evidence of several acupuncture types for ON and help clinicians decide on the best.