• Computers and Concrete
• /
• v.14 no.3
• /
• pp.315-325
• /
• 2014

Concrete is an important material in most of civil constructions. Many properties of concrete can be determined through analysis of concrete images. Image segmentation is the first step for the most of these analyses. An automated system for segmentation of concrete images into microstructures using texture analysis is proposed. The performance of five different classifiers has been evaluated and the results show that using an Artificial Neural Network classifier is the best choice for an automatic image segmentation of concrete.

• Asian Pacific Journal of Cancer Prevention
• /
• v.13 no.10
• /
• pp.5171-5176
• /
• 2012

We here performed a systematic review of PBIC literature using terms analysis in a hope of both identifying potential trends and patterns and exploring methods leveraging traditional literature reviews in this specific area. Articles meeting inclusion criteria were retrieved from PUBMED and translated into dichotomized article records representing presence or non-presence of MeSH terms and a metric consisting of numbers of times of co-occurrence between all pairs of terms identified using a self-designed program. The occurrence of and relations among the terms were calculated and visualized using Excel2007 and UCINET respectively. A total of 1,742 terms were identified from 997 articles retrieved. Put in a descending order, the lines representing the times of term occurrence formed a typical hyperbolic curve; when plotted along the x-axis of whole MESH terms, the lines clustered within four specific regions. Comparison of term occurrence between 2002 and 2011 revealed priority changes in population and subjects (from general groups to priority groups), intervention approaches (from medicine to exercise and psychotherapy), methodology and techniques (from cohort studies to randomized controlled trials) and outcomes (from health and mental health to quality of life, depression etc.). Networks of the terms featured a number of closely linked groups of topics including method and questionnaires, therapy and outcomes, survival management, psychological assessment and intervention, behavioral intervention (individual and community oriented). Terms analysis revealed interesting trends and patterns about PBIC publications and both the analysis methods and findings have implications for future research and literature reviews.

• Journal of Korea Multimedia Society
• /
• v.21 no.5
• /
• pp.599-608
• /
• 2018

As natural disasters are increasing due to the unusual weather and the modern society is getting complicated, the rapid change of the urban environment has increased human disasters. Thus, citizens are becoming more anxious about social safety. The importance of preparation for safety has been suggested by providing the disaster safety services such as regional safety index, life safety map, and disaster safety portal application. In this paper, we propose an application framework to predict the urban safety index based on user's location with realtime weather/atmosphere data after creating a predication model based on the machine learning using number of occurrence cases and weather/atmosphere history data. Also, we implement an application to provide traffic safety index with executing preprocessing occurrence cases of traffic and weather/atmosphere data. The existing regional safety index, which is displayed on the Si-gun-gu area, has been mainly utilized to establish safety plans for districts vulnerable to national policies on safety. The proposed system has an advantage to service useful information to citizens by providing urban safety index based on location of interests and current position with realtime related data.

• Korean journal of communication and information
• /
• v.16
• /
• pp.108-135
• /
• 2001

This study examines the structure of the problems of Korean newspaper reporting raised by the civil society. Based on the differences in the mode of presentation, the problems of newspaper reporting were classified into three types; prominent, associated, and isolate problem. The relations among these problems were defined as the degree of co-occurrence in the monitoring articles. A network analysis was conducted to examine the structure of the problems in Korean newspaper reporting. A $33{\times}33$ similarity matrix of the problems was created by analyzing the data from one monitoring report and two weekly media critics newspapers. The results showed that of the 33 problems, most of them were mentioned as prominent or associated problems. The problems related to the news contents were mostly treated as prominent ones, while the problems about the news writing and reporting styles were frequently treated as associated ones. The network structure of newspaper criticism based on the co-occurrence of 33 problems were divided into six clusters. Among them, the most central was the group including the problems of "unfairness,' "biased interpretation," and "vagueness". In addition, the problems were found to have different roles in the network. Of the 33 problems, two were liaisons and four were attached isolates, indicating the hierarchical structure of problems in newspaper reporting. These results were discussed in the light of two viewpoints; the absence of objective criteria in media criticism, and the need for the comparisons of the current study's results with the opinions of newspaper readers and journalists. finally, the implications for the future studies were presented.

• ETRI Journal
• /
• v.40 no.6
• /
• pp.745-758
• /
• 2018

A wide range of studies in various disciplines has focused on the Internet of Things (IoT) and cyber-physical systems (CPS). However, it is necessary to summarize the current status and to establish future directions because each study has its own individual goals independent of the completion of all IoT applications. The absence of a comprehensive understanding of IoT and CPS has disrupted an efficient resource allocation. To assess changes in the knowledge structure and emerging technologies, this study explores the dynamic research trends in IoT by analyzing bibliographic data. We retrieved 54,237 keywords in 12,600 IoT studies from the Scopus database, and conducted keyword frequency, co-occurrence, and growth-rate analyses. The analysis results reveal how IoT technologies have been developed and how they are connected to each other. We also show that such technologies have diverged and converged simultaneously, and that the emerging keywords of trust, smart home, cloud, authentication, context-aware, and big data have been extracted. We also unveil that the CPS is directly involved in network, security, management, cloud, big data, system, industry, architecture, and the Internet.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.307-310
• /
• 2021

In the recent years, studies using Computer-Aided Diagnostics(CAD) have been actively conducted, such as signal and image processing technology using breast ultrasound images, automatic image optimization technology, and automatic detection and classification of breast masses. As computer diagnostic technology is developed, it is expected that early detection of cancer will proceed accurately and quickly, reducing health insurance and test ice for patients, and eliminating anxiety about biopsy. In this paper, a quantitative analysis of tumors was conducted in ultrasound images using a gray level co-occurrence matrix(GLCM) to experiment with the possibility of use for computer assistance diagnosis.

• Journal of The Korean Association For Science Education
• /
• v.40 no.1
• /
• pp.41-50
• /
• 2020

Looking at the understanding of scientific concepts from a linguistic perspective, it is very important for students to develop a deep and sophisticated understanding of words used in scientific concept as well as the ability to use them correctly. This study intends to provide the basis for productive knowledge education of scientific words by noting that the foundation of productive knowledge teaching on scientific words is not well established, and by exploring ways to teach the relationship among words that constitute scientific concept in a productive and effective manner. To this end, we extracted the relationship among the words that make up the scientific concept from the text of science textbook by using quantitative text analysis methods, second, qualitatively examined the meaning of the word relationship extracted as a result of each method, and third, we proposed a writing activity method to help improve the productive knowledge of scientific concept words. We analyzed the text of the "Force and motion" unit on first grade science textbook by using four methods of quantitative linguistic analysis: word cluster, co-occurrence, text network analysis, and word-embedding. As results, this study suggests four writing activities, completing sentence activity by using the result of word cluster analysis, filling the blanks activity by using the result of co-occurrence analysis, material-oriented writing activities by using the result of text network analysis, and finally we made a list of important words by using the result of word embedding.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.12
• /
• pp.4467-4488
• /
• 2014

The bibliometric analysis is widely used for understanding research domains, trends, and knowledge structures in a particular field. The analysis has majorly been used in the field of information science, and it is currently applied to other academic fields. This paper describes the analysis of academic literatures for classifying research domains and for suggesting empty research areas in the telecommunications policy. The application software is developed for retrieving Thomson Reuters' Web of Knowledge (WoK) data via web services. It also used for conducting text mining analysis from contents and citations of publications. We used three text mining techniques: the Keyword Extraction Algorithm (KEA) analysis, the co-occurrence analysis, and the citation analysis. Also, R software is used for visualizing the term frequencies and the co-occurrence network among publications. We found that policies related to social communication services, the distribution of telecommunications infrastructures, and more practical and data-driven analysis researches are conducted in a recent decade. The citation analysis results presented that the publications are generally received citations, but most of them did not receive high citations in the telecommunications policy. However, although recent publications did not receive high citations, the productivity of papers in terms of citations was increased in recent ten years compared to the researches before 2004. Also, the distribution methods of infrastructures, and the inequity and gap appeared as topics in important references. We proposed the necessity of new research domains since the analysis results implies that the decrease of political approaches for technical problems is an issue in past researches. Also, insufficient researches on policies for new technologies exist in the field of telecommunications. This research is significant in regard to the first bibliometric analysis with abstracts and citation data in telecommunications as well as the development of software which has functions of web services and text mining techniques. Further research will be conducted with Big Data techniques and more text mining techniques.

• Journal of the Institute of Convergence Signal Processing
• /
• v.20 no.2
• /
• pp.70-77
• /
• 2019

Breast ultrasound readings are very important to diagnose early breast cancer. In Ultrasonic inspection, it shows a significant difference in image quality depending on the ultrasonic equipment, and there is a large difference in diagnosis depending on the experience and skill of the inspector. Therefore, objective criteria are needed for accurate diagnosis and treatment. In this study, we analyzed texture characteristics by applying GLCM (Gray Level Co-occurrence Matrix) algorithm and extracted characteristic parameters and diagnosed breast cancer using neural network classifier. Breast ultrasound images were classified into normal, benign and malignant tumors and six texture parameters were extracted. Fourteen cases of normal, malignant and benign tumor diagnosed by mammography were studied by using the extracted six parameters and learning by multi - layer perceptron neural network back propagation learning method. As a result of classification using 51 normal images, 62 benign tumor images, and 74 malignant tumor images of the learned model, the classification rate was 95.2%.

• Journal of the Korean Society of School Health
• /
• v.28 no.2
• /
• pp.99-110
• /
• 2015

Purpose: This study aims to investigate the association between suicidal thoughts and the co-occurrence of alcohol, tobacco, and drug use among adolescents. Methods: This study used the data of the Korea Youth Risk Behavior Web-based Survey from 2008 through 2014. The subjects of this study were 517,866 students, in total (Male 266,500, Female 251,366). Frequency analysis was conducted on the data about the subjects' general characteristics and their experience of smoking, drinking, and drug use. The relationship between suicidal thoughts and the co-occurrence of alcohol, tobacco, and drug use was analyzed through ${\chi}^2-test$ and logistic regression. The analyses were done using SAS 9.4. Results: According to the study, adolescents who used alcohol, cigarettes, and drugs at the same time engaged in suicidal ideation 3.69 times more than their peers who didn't use such substances (95% CI: 3.40~4.00, p<.001). Also, adolescents who used only tobacco, only alcohol, and only drugs engaged in suicidal ideation 1.49 times (95% CI: 1.43~1.56, p<.001), 1.28 times (95% CI: 1.26~1.31, p<.001) and 2.34 times (95% CI: 2.04~2.69, p<.001) more than the students who didn't use any substances, respectively. Conclusion: Adolescents' suicidal ideation and the co-occurrence of alcohol, tobacco, and drug use had a statistically significant relationship.