• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6C
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• pp.512-519
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• 2008

The proof of a cellular phone used to a crime important data of a criminal investigation and legal judgment become. A lot of on a process use the file format that do not become that is kind of various cellular phones and model pipe, and collect criminal proof, and to analyze be difficult. Also, standardization is not made, and can be adopted on procedures from confiscation search processes regarding a cellular phone to integrity extractions of Forensic data in courts in the confiscation criminal investigation spots. Standardize confiscation search procedures of a cellular phone at these papers. Use a radio waves interception envelope and radio waves interception device for a movement which a security does integrity of criminal on-site cellular phone confiscation search data by standard procedures, and was devoted to. Analyze corroborative facts of a cellular phone seized, and verify integrity, and present problems regarding cellular phone confiscation search procedures and measures, and will contribute in development of Mobile Forensic through integrity damage experiment.

• The Journal of Korean Medicine
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• v.44 no.3
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• pp.74-86
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• 2023

Objectives: The purpose of this study was to examine search trends and their meanings for major uninsuired Korean medicine (KM) treatments through analysis of an online portal search results. Methods: Keywords searches were performed using Naver Datalab on 4 July 2023. From January 2016 to June 2023, monthly relative search volume (RSV) for keywords 'pharmacopuncture', 'Chuna', and 'needle-embedding therapy', and 'herbal decoction' were extracted with a score between 0 and 100. For the obtained RSVs, longitudinal changes over time, characteristics according to sex and age group, and correlations between them were investigated. Results: The ranking of RSV for each keyword has changed from 'Chuna', 'herbal decoction', 'needle-embedding therapy', and 'pharmacopuncture' to 'Chuna', 'herbal decoction', 'pharmacopuncture', and 'needle-embedding therapy' after 2019. Overall, the RSV of needle-embedding therapy continuously decreased, while that of pharmacopuncture continuously increased. In 2019, a rapid increase in the RSV of Chuna was observed, and in 2020, a rapid increase in the RSV of herbal decoction was observed. There was a difference in the longitudinal change pattern of RSV for the keywords by age group. Importantly, in the elderly, changes in RSV were observed in a favorable pattern to KM treatment. Conclusion: Our findings enable estimation of the public's interest and its changes for the four uninsuired KM treatment, and can be used as basic data to strengthen health insurance coverage in Korea. Specifically, changes in interest in KM treatments according to sex and age can be referred to.

• Journal of the East Asian Society of Dietary Life
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• v.19 no.1
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• pp.116-129
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• 2009

The study was conducted to evaluate consumer awareness of the risk elements associated with foods and their information search behavior regarding food safety. The data were collected from 504 adult consumers living in Seoul, Busan, Incheon, Daegu, Daejeon, and Gwangju through a self-administered questionnaire on August, 2006. Frequency analyses, t tests, one-way analysis of variance, and Duncan's multiple range comparison tests were conducted to analyze the responses using SPSS v. 14.0. The levels of recognition of consumers regarding each risk element were generally low. Many respondents answered that they obtained information regarding food safety from TV/radio/newspapers and family/relatives/friends/neighbors. The respondents also indicated that they had strong confidence in the information from family/relatives/friends/neighbors. Additionally, most respondents required information regarding heavy metal contamination, endoctrine disruptors, and avian influenza.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.183-190
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• 2012

This study constructs an expert search system which has a mutual cooperation function based on thesis and author profile. The proposed methodology is as follows. First, we propose weighting method which can search a keyword and the most relevant keyword. Second, we propose a method which can search the experts efficiently with this weighting method. On the preferential basis, keywords and author profiles are extracted from the papers, and experts can be searched through this method. This system will be available to many fields of social network. However, this information is distributed to many systems. We propose a method using multi-ontology to integrate distributed data. The multi-ontology is composed of meta ontology, instance ontology, location ontology and association ontology. The association ontology is constructed through analysis of keyword association dynamically. An expert network is constructed using this multi-ontology, and this expert network can search expert through association trace of keyword. The expert network can check the detail area of expertise through the research list which is provided by the system.

• Journal of Preventive Medicine and Public Health
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• v.55 no.2
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• pp.125-133
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• 2022

Objectives: No systematic review has explored the challenges related to worldwide universal health coverage (UHC). This study reviewed challenges on the road to UHC. Methods: A systematic electronic search of all studies that identified the challenges of worldwide UHC was conducted, without any restrictions related to the publication date or language. A hand search and a bibliographic search were also conducted to identify which texts to include in this study. These sources and citations yielded a total of 2500 articles, only 26 of which met the inclusion criteria. Relevant data from these papers were extracted, summarized, grouped, and reported in tables. Results: Of the 26 included studies, 7 (27%) were reviews, 6 (23%) were reports, and 13 (50%) had another type of study design. The publication dates of the included studies ranged from 2011 to 2020. Nine studies (35%) were published in 2019. Using the World Health Organization conceptual model, data on all of the challenges related to UHC in terms of the 4 functions of health systems (stewardship, creating resource, financing, and delivering services) were extracted from the included studies and reported. Conclusions: This study provides a straightforward summary of previous studies that explored the challenges related to UHC and conducted an in-depth analysis of viable solutions.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.209-228
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• 2011

Web search behavior has evolved. People now search using many diverse information devices in various situations. To monitor these scattered and shifting search patterns, an improved way of learning and analysis are needed. Traditional web search studies relied on the server transaction logs and single query instance analysis. Since people use multiple smart devices and their searching occurs intermittently through a day, a bundled query research could look at the whole context as well as penetrating search needs. To observe and analyze bundled queries, we developed a proprietary research software set including a log catcher, query bundling tool, and bundle monitoring tool. In this system, users' daily search logs are sent to our analytic server, every night the users need to log on our bundling tool to package his/her queries, a built in web survey collects additional data, and our researcher performs deep interviews on a weekly basis. Out of 90 participants in the study, it was found that a normal user generates on average 4.75 query bundles a day, and each bundle contains 2.75 queries. Query bundles were categorized by; Query refinement vs. Topic refinement and 9 different sub-categories.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.261-266
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• 2021

The spread of cloud computing, digital computing, and the popular social media platforms have led to increased growth of data. That growth of data results in what is known as big data (BD), which seen as one of the most strategic resources. The analysis of these BD has allowed generating value from massive raw data that helps in making effective decisions and providing quality of service. With Vision 2030, Saudi Arabia seeks to invest in BD technologies, but many challenges and barriers have led to delays in adopting BD. This research paper aims to search in the state of Big Data Analytics (BDA) in Saudi higher education sector, identify the barriers by reviewing the literature, and then to apply the design-reality gap model to assess these barriers that prevent effective use of big data and highlights priority areas for action to accelerate the application of BD to comply with Vision 2030.

• Journal of Nutrition and Health
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• v.36 no.5
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• pp.515-527
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• 2003

Objectives： A meta-analysis of the literatures was conducted to evaluate the cost-effectiveness of medical nutrition therapy by dietitians. Methods : The 30 studies were identified from a computerized search of published research on MEDLINE, Science-Direct and the PQD database until May, 2002 and a review of reference lists. The main search terms were“dietitian”,“dietary intervention”,“nutrition intervention”, “cost”,“cost-effectiveness”and“cost-benefit analysis”. The subgroup analysis was performed by publication year, study design, intervention provider, type of patient (in/out-patient) and type of cost (total cost/direct cost). Two reviewers independently selected trials for inclusion, assessed the quality and extracted the data. Results : The 30 studies were identified using the electric database search and bibliographies. The 17 trials were eligible for inclusion criteria, then the systematic review and a meta-analysis were conducted on effectiveness and cost-effectiveness of medical nutrition therapy. The quality of the studies was evaluated using the quality assessment tool for observational studies. The quality score was 0.515 $\pm$ 0.121 (range : 0.279-0.711, median : 0.466). The meta-analysis of 17 studies based on the random effect model showed that medical nutrition therapy was highly effective in treating the diseases (effect size 0.3092 : 95% confidence interval 0.2282-0.3303). The vote-counting method, one of meta-analysis methods, was applied to evaluate the cost-effectiveness of medical nutrition therapy conducted by dietitians. Two criteria (method 1, method 2) for voting were used. The calculated p-values for method 1 (more conservative method) and method 2 (less conservative method) were 0.1250 and 0.0106, respectively. Medical nutrition therapy by dietitians was significantly cost-effective in the method 2. Conclusion. This meta-analysis showed that the effectiveness of medical nutrition therapy was statistically significant in treating disease (effect size 0.3092), and that the cost-effectiveness of medical nutrition therapy was statistically significant in the method 2 (less conservative method) of vote counting. (Korean J Nutrition 36(5): 515~527, 2003)

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.755-767
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• 1997

Analyzing autocorrelated data set is still an open problem. Developing on easy and efficient method for severe positive correlated data set, which is common in simulation output, is vital for the simulation society. Bootstrap is on easy and powerful tool for constructing non-parametric inferential procedures in modern statistical data analysis. Conventional bootstrap algorithm requires iid assumption in the original data set. Proper choice of resampling units for generating replicates has much to do with the structure of the original data set, iid data or autocorrelated. In this paper, a new bootstrap resampling scheme is proposed to analyze the autocorrelated data set : the Threshold Bootstrap. A thorough literature search of bootstrap method focusing on the case of autocorrelated data set is also provided. Theoretical foundations of Threshold Bootstrap is studied and compared with other leading bootstrap sampling techniques for autocorrelated data sets. The performance of TB is reported using M/M/1 queueing model, else the comparison of other resampling techniques of ARMA data set is also reported.