• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.6
• /
• pp.460-471
• /
• 2019

The aim of this study was to examine the scale and market share of Chinese's research facility & equipment in the domestic research equipment market of basic and analytical science field for analyzing the difference of the number and amount of construction by year of acquisition, national research facility equipment standard classification code, and type of institution based on the information of the research equipment invested by the Korean government for the past 14 years. In addition, we analyzed the correlation among the year of acquisition, equipment standard classification code, and type of institution variables. As of January 1 2019, from 2005 to 2018, 50 Chinese's research facilities & equipments (main equipment with a construction cost of 30 million won or more) built in the basic and analytical science fields were selected for this study and their number of construction, amount of construction, year of acquisition, type of institution, and standard classification code were analyzed. Differences of the number and amount of construction with-in and by year of acquisition, standard classification code, and type of institution were tested using a single sample Chi-square test, Mann-Whitney U test, and Kruskal-wallis test. The correlation among the three variables was analyzed by using the Chi-square test of cross-tabulation analysis. And there was a statistically significant correlation among the year of acquisition, standard classification code, and type of institution (p<.05). Compared to the 2000s, in the 2010s, high-priced Optical Electronics/Video Equipment was installed at private universities, private enterprises, and government-affiliated research institute. Therefore, the domestic construction status of Chinese's research facility & equipment in the basic science and analytical science field is less than that of the domestic ones, but the number and the amount of construction are increasing statistically. So it is necessary for the government to be able to recognize the possibility that the Chinese's research facility and equipment can encroach on the domestic research industry market and to prepare related provision.

• Proceedings of the Korea Society of Information Technology Applications Conference
• /
• 2006.06a
• /
• pp.573-601
• /
• 2006

IS 실무자들은 과거처럼 단순한 시스템 분석이나 프로그래밍 기법만을 갖추는 것만으로는 조직이 원하는 정보기술을 효과적으로 운용하는 것이 어렵게 되고 있다. 예전과는 달리 최근의 기업에서는 통신 시스템을 포함하는 다양한 정보기술에 관련된 지식과 기술을 전문적으로 다룰 수 있는 전문가를 원하는 추세이다. 이러한 맥락에서 IS 실무자들이 자신의 업무를 성공적으로 수행하기 위해 필요한 전문 지식과 기술은 무엇인가라는 질문에 대한 대답을 알 수 있어야만 한다. 본 연구는 IS 실무자들이 그들이 직면하고 있는 ‘IS 지식과 기술의 빠른 변화’를 얼마만큼 인식하고 있으며, 그들이 필요로 하는 지식과 기술과 업무를 수행함에 있어 필수적인 지식과 기술을 얼마만 큼 보유하고 있는지를 조사하였다. 본 연구에서는 조사된 자료를 통하여, 기존의 국내외의 문화에서 밝혀진 인구 통계학적 분류기준 (예를 들자면, 경력 수준, 지역, 직종) 이외에 이들을 분류할 수 있는 기준에는 어떠한 것이 있는가에 대한 연구를 수행하였다. 분석을 위하여 실무자들이 현업에서 많은 시간과 노력을 들이고 있는 IS 활동영역에 대한 투자시간을 기준으로 실무자들을 분류하였다. 분석에서는 조사자의 군집분석과 다차원 분석을 통하여 분류된 실무자 그룹에 대한 여러 가지 기술적인 특성과, 인구 통계학적 특성을 파악하고, 그룹들에 대하여 새로운 분류에 적합한 표기를 제시하고자 하였다. 본 논문은 정보시스템 영역에서 수행된 IS 실무자들에 다양한 연구의 한 부분으로서, 기업 환경, 조직 환경, 나아가 실무자들의 직무환경의 개선에 필요한 지식과 기술을 제공할 것이다.아날로그 방식에서 IT 기반에 의한 디지털 환경으로 변화되고 있다. 또한 e러닝, T러닝, m러닝, u러닝 등의 용어가 생성되고 있다.키지에어컨에서 사용되고 있는 밀폐형 압축기에 대해서 그림 2에서 나타내고 있는 냉방능력 10tons(120,000Btu/h) 이하를 중심으로 상기의 최근 기술 동향을 간략하게 소개하고자 한다.질표준의 지표성분으로 간주되는 진세노사이드의 절대함량과 그 성분조성 차이에 따른 임상효과의 차별성이 있는지에 대한 검토와, 특히 최근 실험적으로 밝혀지고 있는 사포닌 성분의 장내 세균에 의한 생물전환체의 인체 실험을 통한 효과 검정이 필요하다. 나아가서는 적정 복용량의 설정과 이와 관련되는 생체내 동태 및 생체이용율(bioavilability)에 관한 정보가 거의 없으므로 이것도 금후 검토해야 할 과제로 사료된다. 인삼은 전통약물로서 오랜 역사성과 그동안의 연구결과에 의한 과학성을 가지고 있으므로 건강유지와 병의 예방 및 회복촉진을 위한 보조요법제 또는 기능성 식품으로써의 유용성이 있는 것으로 판단된다. 앞으로 인삼의 활용성 증대를 위해서는 보다 과학적인 임상평가에 의한 안전성 및 유효성 입증과 제품의 엄격한 품질관리의 필요성이 더욱 강조되어야 할 것이다.xyl radical 생성 억제 효과를 보여 주었다. 본 실험을 통하여 BHT 를 제외하고 전반적으로 세포 수준에서의 oxidative stress 에 대한 억제 효과를 확인해 볼 수 있었으며 특히 수용성 항산화제들에서 두드러진 효과를 보여 주었다. 제공하여 내수기반 확충에도 노력해야 할 것 이다.있었다., 인삼이 성장될 때 부분적인 영양상태의

• Korean journal of applied entomology
• /
• v.41 no.2
• /
• pp.75-83
• /
• 2002

The hypertext-based polychotomous key in m (World Wide Web) was developed to improve the identification accuracy of planthoppers caught by the light trap in Korean paddy fields. The effects of it were tested by 12 students who are not familiar at the identification of insects. When they used the hypertext, it was improved that the ability of them to recognize Sogatella furcifera (Horvath) and Laodelphax striatellus (Fallen). Identification accuracy of the former was increased significantly from 56% to 83% and that of the latter was also increased significantly from 47% to 80%. However, many students still have difficulty in the recognition of Nilaparvata lugens (Stal).

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.4
• /
• pp.43-53
• /
• 2014

In this paper, we propose an ontology-based approach to measuring degree-of-interest in country by analyzing wikipedia usage data. First, we developed the degree-of-interest ontology called DOI ontology by extracting concept hierarchies from wikipedia categories. Second, we map the title of frequently edited articles into DOI ontology, and we measure degree-of-interest based on DOI ontology by analyzing wikipedia page views. Finally, we perform chi-square test of independence to figure out if interesting fields are independent or not by country. This approach shows interesting fields are closely related to each country, and provides degree of interests by country timely and flexibly as compared with conventional questionnaire survey analysis.

• Journal of Convergence for Information Technology
• /
• v.11 no.5
• /
• pp.38-49
• /
• 2021

This study is single-group pretest-posttest design study to examine the effects of web-based cognitive training program using tablet on cognition and depression in the elderly with high risk of dementia or mild dementia living in a rural area, enrolled in dementia center. Intervention was provided to the 18 participants once a week for 10 weeks within 1 hour. Data was analyzed with SPSS 24.0 and interview data was categorized. The study result proves that after intervention, the participants' cognitive score increased significantly(Z=-3.35, p=.001) and the depression scores were significantly decreased(Z=-3.13, p=.002). Also, interview shows positive effect of the intervention on cognition and depression. It is necessary to improve access environment for smart devices so as not to be restricted by time and place, and to develop and apply various types of web-based programs for each cognitive level. Then, the intervention could be used as a cognitive training program incorporating information and communication technology for the prevention and management of dementia in rural areas.

• Korean Journal of Remote Sensing
• /
• v.27 no.4
• /
• pp.457-466
• /
• 2011

The objectives of this study are to produce level 3 type LULC map and analysis of phenological features of North Korea, ISODATA clustering of the 88scenes of MVC of MODIS NDVI in 2008 and 8scenes in 2009 was carried out. Analysis of phenological phases based mapping method was conducted, In level 2 type map, the confusion matrix was summarized and Kappa coefficient was calculated. Total of 27 typical habitat types that represent the dominant species or vegetation density that cover land surface of North Korea in 2008 were made. The total of 27 classes includes the 17 forest biotopes, 7 different croplands, 2 built up types and one water body. Dormancy phase of winter (${\sigma}^2$ = 0.348) and green up phase in spring (${\sigma}^2$ = 0.347) displays phenological dynamics when much vegetation growth changes take place. Overall accuracy is (851/955) 85.85% and Kappa coefficient is 0.84. Phenological phase based mapping method was possible to minimize classification error when analyzing the inaccessible land of North Korea.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.6
• /
• pp.205-220
• /
• 2018

Software defect prediction is helpful for allocating valuable project resources effectively for software quality assurance activities thanks to focusing on the identified fault-prone modules. If historical data collected within a company is sufficient, a Within-Project Defect Prediction (WPDP) can be utilized for accurate fault-prone module prediction. In case a company does not maintain historical data, it may be helpful to build a classifier towards predicting comprehensible fault prediction based on Cross-Project Defect Prediction (CPDP). Since CPDP employs different project data collected from other organization to build a classifier, the main obstacle to build an accurate classifier is that distributions between source and target projects are not similar. To address the problem, because it is crucial to identify effective similarity measure techniques to obtain high performance for CPDP, In this paper, we aim to identify them. We compare various similarity measure techniques. The effectiveness of similarity weights calculated by those similarity measure techniques are evaluated. The results are verified using the statistical significance test and the effect size test. The results show k-Nearest Neighbor (k-NN), LOcal Correlation Integral (LOCI), and Range methods are the top three performers. The experimental results show that predictive performances using the three methods are comparable to those of WPDP.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.1
• /
• pp.139-144
• /
• 2008

Generally, real system that is the object of decision-making is very variable and sometimes it lies situations with uncertainty. To solve these problem, it has used statistical methods as significance level, certainty factor, sensitivity analysis and so on. In this paper, we propose a method for fuzzy decision-making based on MFAC(Multiple Fuzzy Alpha Cut) to improve the definiteness of classification results with similarity evaluation. In the proposed method, MFAC is used for extracting multiple a ${\alpha}$-level with proximity degree at proximity relation between relative Hamming distance and max-min method and for minimizing the number of data which are associated with the partition intervals extracted by MFAC. To determine final alternative of decision-making, we compute the weighted value between extracted data by MFAC From the experimental results, we can see the fact that the proposed method is simpler and more definite than classification performance of the conventional methods and determines an alternative efficiently for decision-maker by testing significance of sample data through statistical method.

• Journal of Intelligence and Information Systems
• /
• v.22 no.3
• /
• pp.71-89
• /
• 2016

Sentiment analysis is used for identifying emotions or sentiments embedded in the user generated data such as customer reviews from blogs, social network services, and so on. Various research fields such as computer science and business management can take advantage of this feature to analyze customer-generated opinions. In previous studies, the star rating of a review is regarded as the same as sentiment embedded in the text. However, it does not always correspond to the sentiment polarity. Due to this supposition, previous studies have some limitations in their accuracy. To solve this issue, the present study uses a supervised sentiment classification model to measure a more accurate sentiment polarity. This study aims to propose an advanced sentiment classifier and to discover the correlation between movie reviews and box-office success. The advanced sentiment classifier is based on two supervised machine learning techniques, the Support Vector Machines (SVM) and Feedforward Neural Network (FNN). The sentiment scores of the movie reviews are measured by the sentiment classifier and are analyzed by statistical correlations between movie reviews and box-office success. Movie reviews are collected along with a star-rate. The dataset used in this study consists of 1,258,538 reviews from 175 films gathered from Naver Movie website (movie.naver.com). The results show that the proposed sentiment classifier outperforms Naive Bayes (NB) classifier as its accuracy is about 6% higher than NB. Furthermore, the results indicate that there are positive correlations between the star-rate and the number of audiences, which can be regarded as the box-office success of a movie. The study also shows that there is the mild, positive correlation between the sentiment scores estimated by the classifier and the number of audiences. To verify the applicability of the sentiment scores, an independent sample t-test was conducted. For this, the movies were divided into two groups using the average of sentiment scores. The two groups are significantly different in terms of the star-rated scores.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.5
• /
• pp.1057-1067
• /
• 2014

Many genetic variants have been identified to be associated with complex diseases such as hypertension, diabetes and cancers throughout genome-wide association studies (GWAS). However, there still exist a serious missing heritability problem since the proportion explained by genetic variants from GWAS is very weak less than 10~15%. Gene-gene interaction study may be helpful to explain the missing heritability because most of complex disease mechanisms are involved with more than one single SNP, which include multiple SNPs or gene-gene interactions. This paper focuses on gene-gene interactions with the survival phenotype by extending the multifactor dimensionality reduction (MDR) method to the accelerated failure time (AFT) model. The standardized residual from AFT model is used as a residual score for classifying multiple geno-types into high and low risk groups and algorithm of MDR is implemented. We call this method AFT-MDR and compares the power of AFT-MDR with those of Surv-MDR and Cox-MDR in simulation studies. Also a real data for leukemia Korean patients is analyzed. It was found that the power of AFT-MDR is greater than that of Surv-MDR and is comparable with that of Cox-MDR, but is very sensitive to the censoring fraction.