• Journal of Mushroom
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• v.5 no.3_4
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• pp.91-97
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• 2007

Shiitake mushroom (Lentinula edodes) is usually cultivated on the oak log. Log cultivation of this mushroom is getting difficult to get oak logs and has a weak point of its long cultivation period. Recently sawdust cultivation is getting increase. It is important to make mycelia browning on the substrate surface. This browned surface in sawdust cultivation plays an important role like as artificial bark of the oak log, which protects the other pests and suppresses water evaporation in the substrate. The period for mycelia browning is so long that the sawdust cultivation of Shiitake mushroom can not spread well into the mushroom farms. The development of methods for the rapid mycelia browning is quite required. In this article we would like to discuss about the enzymatic activities related mycelia browning and search the methods of cultivation period reduction.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.357-362
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• 2009

We propose a method to recommend most likely people to call based on call log of mobile phone user. Call logs of an user can reflect calling pattern of the user include regular calling behavior. When user got a list of people to call with a click of 'send' button on the phone, the time and effort to search a person with several typing or to select a person from the list can be definitely reduced. This paper presents the design process of an algorithm to find most likely people to call at a certain moment and the verification process with recorded call log and Experience Sampling Method(ESM) on mobile phone.

• Journal of Korean Library and Information Science Society
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• v.35 no.1
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• pp.1-17
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• 2004

Most web portals provide a web directory service which selects and classifies web sites according to their subject matter. In order to investigate the directory access behavior of general Korean web users, this study analyzes directory access logs of NAVER, a major Korean web search engine. This study suggests a methodology to classify the total sessions into six different session types. This study also discusses directory access behaviors of the NAVER users by examining the distribution of sessions according to session types, the lengths of navigation within a session, and the most frequently visited categories. It is expected that this study could contribute to the development of more effective web directory services.

• Korean Journal of Construction Engineering and Management
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• v.11 no.6
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• pp.14-23
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• 2010

A considerable number of construction disasters occurs on pathway. A safety management in construction sites is usually performed to prevent accidents in activity areas. This means that safety management level of hazards on pathway is relatively minified. Many researchers have introduced that a hazard identification is fundamental of safety management. Thus, algorithms for helping safety managers' hazardous area identification is developed using automated data collection technology. These algorithms primarily search potential hazardous area by comparing workers' location logs based on real-time locating system and optimal routes based on BIM. And potential hazardous areas is filtered by identified hazardous areas and activity areas. After that, safety managers are provided with information about potential hazardous areas and can establish proper safety countermeasures. This can help improving safety in construction sites.

• Korean Journal of Cognitive Science
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• v.13 no.3
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• pp.33-46
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• 2002

Recently, unstructured random data such as website logs, texts and tables etc, have been flooding in the internet. Among these unstructured data there are potentially very useful data such as bulletin boards and e-mails that are used for customer services and the output from search engines. Various text mining tools have been introduced to deal with those data. But most of them lack accuracy compared to traditional data mining tools that deal with structured data. Hence, it has been sought to find a way to apply data mining techniques to these text data. In this paper, we propose a text mining system which can incooperate existing data mining methods. We use text mining as a preprocessing tool to generate formatted data to be used as input to the data mining system. The output of the data mining system is used as feedback data to the text mining to guide further categorization. This feedback cycle can enhance the performance of the text mining in terms of accuracy. We apply this method to categorize web sites containing adult contents as well as illegal contents. The result shows improvements in categorization performance for previously ambiguous data.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.253-262
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• 2018

Objectives: We reviewed digital epidemiological studies to characterize how researchers are using digital data by topic domain, study purpose, data source, and analytic method. Methods: We reviewed research articles published within the last decade that used digital data to answer epidemiological research questions. Data were abstracted from these articles using a data collection tool that we developed. Finally, we summarized the characteristics of the digital epidemiological studies. Results: We identified six main topic domains: infectious diseases (58.7%), non-communicable diseases (29.4%), mental health and substance use (8.3%), general population behavior (4.6%), environmental, dietary, and lifestyle (4.6%), and vital status (0.9%). We identified four categories for the study purpose: description (22.9%), exploration (34.9%), explanation (27.5%), and prediction and control (14.7%). We identified eight categories for the data sources: web search query (52.3%), social media posts (31.2%), web portal posts (11.9%), webpage access logs (7.3%), images (7.3%), mobile phone network data (1.8%), global positioning system data (1.8%), and others (2.8%). Of these, 50.5% used correlation analyses, 41.3% regression analyses, 25.6% machine learning, and 19.3% descriptive analyses. Conclusions: Digital data collected for non-epidemiological purposes are being used to study health phenomena in a variety of topic domains. Digital epidemiology requires access to large datasets and advanced analytics. Ensuring open access is clearly at odds with the desire to have as little personal data as possible in these large datasets to protect privacy. Establishment of data cooperatives with restricted access may be a solution to this dilemma.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.247-264
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• 2016

With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

• Journal of Environmental Impact Assessment
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• v.24 no.5
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• pp.532-548
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• 2015

The winter ecology of individual yellow-throated martens(Martes flavigula) intemperate region of Korea were studied through snow-tracking. The study was performed across 3 winter seasons, from January 2011 to February 2013. Total distance of 49.8km was snow tracked (comprising 13 snow-tracking routes) to determine winter foraging habits, general behavior and movement paths of solitary and small groups (1-6 individuals; $mean=2.9{\pm}1.6$) of yellow-throated martens. The martens in the current study were omnivorous, with their winter diet including 9 animal and 5 plant species. Yellow-throated martens searched for food near and under the fallen logs and branches, root plates of fallen trees, around the roots of growing trees, and in small holes in the ground. They also climbed trees to search inside the tree holes and vacant bird nests. Foraging activity was estimated to occur at a frequency of 1.20 times/km, while territory marking occurred 1.42 times/km on average. Of the 60 documented foraging activities we observed, 17 were successful (28.3%). Moving activity and territory marking mainly occurred along ridges, whereas foraging activity was recorded in valleys, slopes, and forest edges. To protect the habitat of this species, the entire forest should be preserved, including the valleys, slopes, and even forest edges as well as main ridges.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.5
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• pp.303-314
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• 2018

In the past few years, government agencies and corporations have succumbed to stealthy, tailored cyberattacks designed to exploit vulnerabilities, disrupt operations and steal valuable information. Security Information and Event Management (SIEM) is useful tool for cyberattacks. SIEM solutions are available in the market but they are too expensive and difficult to use. Then we implemented basic SIEM functions to research and development for future security solutions. We focus on collection, aggregation and analysis of real-time logs from host. This tool allows parsing and search of log data for forensics. Beyond just log management it uses intrusion detection and prioritize of security events inform and support alerting to user. We select Elastic Stack to process and visualization of these security informations. Elastic Stack is a very useful tool for finding information from large data, identifying correlations and creating rich visualizations for monitoring. We suggested using vulnerability check results on our SIEM. We have attacked to the host and got real time user activity for monitoring, alerting and security auditing based this security information management.

• Journal of Food Hygiene and Safety
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• v.38 no.5
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• pp.402-408
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• 2023

Consumer interest in food nutrition continues to grow; however, research on consumer preferences related to nutrition remains limited. In this study, big data analysis was conducted using keyword logs collected from the national information service, the Korean Food Composition Database (K-FCDB), to determine consumer preferences for foods of nutritional interest. The data collection period was set from January 2020 to December 2022, covering a total of 2,243,168 food name keywords searched by K-FCDB users. Food names were processed by merging them into representative food names. The search frequency of food names was analyzed for the entire period and by season using R. In the frequency analysis for the entire period, steamed rice, chicken, and egg were found to be the most frequently consumed foods by Koreans. Seasonal preference analysis revealed that in the spring and summer, foods without broth and cold dishes were consumed frequently, whereas in fall and winter, foods with broth and warm dishes were more popular. Additionally, foods sold by restaurants as seasonal items, such as Naengmyeon and Kongguksu, also exhibited seasonal variations in frequency. These results provide insights into consumer interest patterns in the nutritional information of commonly consumed foods and are expected to serve as fundamental data for formulating seasonal marketing strategies in the restaurant industry, given their indirect relevance to consumer trends.