• Safety and Health at Work
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• v.11 no.2
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• pp.136-142
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• 2020

Background: Rheumatoid arthritis (RA) is an autoimmune disease with systemic inflammatory arthritis. This meta-analysis was conducted to examine the association between occupational exposure to silica and the risk of developing RA among different workers. Methods: In this meta-analysis, we searched relevant published studies using major electronic databases including Scopus, PubMed, ISI Web of Science, and Google Scholar search engine up to October 2019, and the references of retrieved articles were also checked for further possible sources. A random-effects model was used to account for heterogeneity among the results of the studies using the pooled odds ratios (ORs) and their 95% confidence intervals (CIs). The Q-statistic and I² tests were calculated to assess heterogeneity between the studies. Results: The pooled calculation of OR indicated a significant association between occupational exposure to silica and risk of developing RA among different workers (OR = 2.59, 95% CI = 1.73 to 3.45). In addition, the pooled estimates of OR in smokers were statistically significant (OR = 2.49, 95% CI = 1.13 to 3.86). Conclusions: The findings of the present study reveal that occupational exposure to silica may be associated with increased risk of developing RA.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.245-250
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• 2003

There are currently about 6000 bacterial species with validly published names, but scientists assume that these may be less than 1% of bacterial species present on the earth. Microbial resource is one of the most important bioresources in bioinderstry and provides us with high economic values. To find missing ones, the studies of metagenome, metabolome, and proteome about microbes have started recently in developed countries. We construct the information system that integrates information on microbial genome resources and manages the information to support efficient research of microbial genome application, and name this system 'Bio-Meta Information System (Bio-MIS)'. Bio-MIS consists of integrated microbial genome resources database, microbial genome resources input system, integrated microbial genome resources search engine, microbial resources on-line distribution system, portal service and management via internet. In the future, we will include public database connection and implement useful bioinformatics software for analyzing microbial genome resources. The web-site is accessible at http://biomis.probionic.com

• Journal of Microbiology and Biotechnology
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• v.16 no.2
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• pp.178-183
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• 2006

Microbes are one of the most important bioresources in bioindustry and provide high economic values. Although there are currently about 6,000 bacterial species with validly published names, microbiologists generally assume that the number may account for less than 1% of the bacterial species present on Earth. To discover the remaining species, studies of metagenomes, metabolomes, and proteomes related to microbes have recently been carried out in various fields. We have constructed an information system that integrates various data on microbial resources and manages bioinformation to support efficient research of microorganisms. We have designated this system 'Bio-Meta Information System (Bio-MIS).' Bio-MIS consists of an integrated microbial resource database, a microbial resource input system, an integrated microbial resource search engine, a microbial resource online distribution system, a portal service, and management via the Internet. In the future, this system is expected to be connected with various public databases. We plan to implement useful bioinformatics software for analyzing microbial genome resources. The Web site is accessible at http://biomis.probionic.com.

• Korean Journal of Biological Psychiatry
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• v.25 no.4
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• pp.89-100
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• 2018

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation method that delivers 1-2 mA of current to the scalp. Several clinical studies have been conducted to confirm the therapeutic effect of major depressive disorder (MDD) patients with tDCS. Some studies have shown tDCS's antidepressant effect, while the others showed conflicting results in antidepressant effects. Our aim of this review is to understand the biological bases of tDCS's antidepressant effect and review the results of studies on tDCS's antidepressant effect. For the review and search process of MDD treatment using tDCS, the US National Library of Medicine search engine PubMed was used. In this review, we discuss the biological mechanism of tDCS's antidepressant effect and the existing published literature including meta-analysis, systematic review, control trial, open studies, and case reports of antidepressant effects and cognitive function improvement in patients with MDD are reviewed. We also discuss the appropriate tDCS protocol for MDD patients, factors predictive of response to tDCS treatment, the disadvantages of tDCS in MDD treatment, and side effects.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.292-294
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• 2000

대부분의 검색엔진들이 사용하는 내용 기반 검색 방법은 웹 페이지에 있는 단어의 빈도만을 이용하여 순위를 결정함으로써 비슷한 단어 빈도를 가지고 있는 방대한 양의 검색 결과로부터 참조할만한 가치가 있는 중요한 페이지를 찾아내기가 매우 어렵다. 중요한 페이지를 구분해 내는 한가지 방법은 얼마나 많은 웹 페이지들이 참조하고 있는가 또한 얼마나 많은 사용자들이 그 웹 페이지에 접속하는가를 보는 것이다. 본 논문에서는 링크 빈도와 클릭 빈도를 이용하여 웹 페이지의 중요도를 계산하는 메타 검색엔진의 프로토타입을 구현하였다. 링크 빈도는 검색엔진에 해당 웹 페이지의 URL을 질의로 던져 구하고 클릭 빈도는 servlet을 이용하여 사용자의 클릭 행위를 감시하여 얻어내도록 하였다. 메타 검색엔진은 이 두 값의 가중치 합으로 각 페이지의 중요도를 계산하고 중요도 순으로 검색 결과를 재배열하여 사용자에게 보여 준다.

• The Journal of Internal Korean Medicine
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• v.41 no.3
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• pp.306-325
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• 2020

Objectives: The aim of this study is to investigate the effect of a Dachaihu decoction for hyperlipidemic acute pancreatitis (HLAP) by systematic review and meta-analysis of Chinese clinical studies. Methods: China National Knowledge Infrastructure (CNKI) was utilized as the major search engine. The date of the literature search was March 7, 2020. Randomized controlled trials (RCTs) about using a Dachaihu decoction for HLAP were included in this study. Meta-analysis was performed by synthesizing outcome data, including total effective rate, abdomen pain relief time, first bowel movement time, blood amylase recovery time, and triglyceride (TG) levels (mmol/L). The selected literature was assessed using Cochrane's risk of bias (RoB). Results: Twelve of 44 RCTs met the inclusion criteria. Most studies were evaluated with RoB as having unclear risk. The total effective rate of herbal medicine treatment based on the Dachaihu decoction was significantly higher than that of symptomatic supportive treatment in 10 articles (risk ratio=1.15, 95% CI: 1.08 to 1.21, p<0.00001, I²=0%). Herbal medicine treatment based on a Dachaihu decoction was significantly more effective than symptomatic supportive treatment in terms of reducing abdomen pain relief time (in all articles; mean difference=-1.70, 95% CI: -1.91 to -1.41, p<0.00001, I²=45%), first bowel movement time (in 7 articles; mean difference=-1.46, 95% CI: -1.86 to -1.05, p<0.00001, I²=73%), blood amylase recovery time (in 8 articles; mean difference=-1.48, 95% CI: -2.04 to -0.92, p<0.00001, I²=90%), and TG levels (in 8 articles; mean difference=-1.59, 95% CI: -2.28to -0.91, p<0.00001, I²=90%). Only one article reported side effects of treatment among the intervention group and control group, citing pancreatic ulcer and pancreatic pseudocyst formation. Conclusions: This study suggests that herbal medicine treatment based on a Dachaihu decoction could yield higher efficacy for HLAP than symptomatic supportive treatment alone. However, the results might be somewhat biased because of the poor quality and small sample size of the included RCTs. Well-qualified clinical studies are needed to prove the effectiveness of Dachaihu decoction therapy for HLAP.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.6
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• pp.2026-2036
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• 1991

An expert system is developed which can diagnose the causes and remedies of the failures of power transmission gears. The basic components of the expert system are knowledge base, inference engine, and working memory. The knowledges in knowledge base are classified into the knowledges for determining the failure types and for diagnosis of causes and remedies of the failures. The former is represented hierarchically into the main category of eleven groups by rules and the sub category of twenty four groups by facts, while the later is represented by facts according to the each group of knowledges. In the inference engine some considerations are implemented, i.e., the backward chaining method and depth first search to determine the category of the failures, the meta-knowledges to shorten the search space, the certainty factor to evaluate the reliability of result, and the unification strategy to diagnose the causes and remedies of the failures. The working memory is established to hold the results during inference temporarily. In addition, knowledge acquisition facility, explanation facility, and user interface are included for the usefulness of user. This expert system is written with the PROLOG programming language on IBM-PC compatible computer operated by MS-DOS and be executed alone.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7567-7573
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• 2015

Background: Catastrophic effects of mustard gas as a chemical warfare agent have always been a major problem for those exposed to this agent. In this meta-analysis it was tried to evaluate carcinogenesis, ocular, cutaneous and respiratory complications of mustard gas exposure among Iranians who had been exposed to this agent during the Iran-Iraq war. Materials and Methods: In this meta-analysis, the required data were collected using keywords "mustard gas", "sulfur mustard", "cancer", "neoplasm", "respiratory complications", "ocular complications", "lung disease", "chronic complication", "eye", "skin", "cutaneous complication", "carcinogenesis" and their combination with keywords "Iran", "Iranian", "prevalence", "mortality" and their Farsi equivalent terms from the databases of SID, Iranmedex, Magiran, Pubmed, Science Direct, Google Search engine, Gray Literature and Reference of References. To determine the prevalence of each complication and perform meta-analysis, CMA: 2 (Comprehensive Meta-Analysis) software with a randomized model was used. Results: Of the 542 articles found, 7 national articles, consistent with the aims of this study were selected. Meta-analysis of seven papers revealed that cancer risk, especially cancer of the respiratory system was elevated, so that the relative risk (RR) of cancer role of mustard gas was inconsistent from 2/1 to 4 in this survey. Also prevalence of delayed skin disorders due to sulfur mustard was 94.6%, pulmonary complications 94.5% and ocular complications 89.9%. The incidence of various cancers in victims exposed to mustard gas was 1.7% worldwide where the rate was 2.2% in Iranian victims of the Iraq-Iran war. Conclusions: Based on present study the prevalence of delayed mustard gas related cutaneous, pulmonary and ocular complications is above 90% and risk of carcinogenesis is higher in comparison to worldwide statistics. This may suggest need for long-term and persistent follow-up and rehabilitation procedures for populations exposed to this agent.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.59-66
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• 2010

We present a personalized clothing recommender system - one that mines association rules from transaction described in ontologies and infers a recommendation from the rules. The recommender system can forecast frequently changing trends of clothing using the Onto-Apriori algorithm, and it makes appropriate recommendations for each users possible through the inference marked as meta nodes. We simulates the rule generator and the inferential search engine of the system with focus on accuracy and efficiency, and our results validate the system.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.258-266
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• 2010

In this paper, we introduce a novel method to predict next update of blogs. The number of RSS feeds registered on meta-blogs is on the order of several million. Checking for updates is very time consuming and imposes a heavy burden on network resources. Since blog search engine has limited resources, there is a fix number of blogs that it can visit on a day. Nevertheless we need to maximize chances of getting new data, and the proposed method which predicts update probability on blogs could bring better chances for it. Also this work is important to avoid distributed denial-of-service attack for the owners of blogs. Furthermore, for the internet as whole this work is important, too, because our approach could minimize traffic. In this study, we assumed that there is a specific pattern to when a blogger is actively posting, in terms of days of the week and, more specifically, hours of the day. We analyzed 15,119 blogs to determine a blogger's posting preference. This paper proposes a method to predict the update probability based on a blogger's posting history and preferred days of the week. We applied proposed method to 12,115 blogs to check the precision of our predictions. The evaluation shows that the model has a precision of 0.5 for over 93.06% of the blogs examined.