• Korean journal of food and cookery science
• /
• v.29 no.2
• /
• pp.95-104
• /
• 2013

This study was conducted to investigate the current use and the demand for processed rice food products by full-time and working housewives in a metropolitan area. Out of 330 questionnaires distributed, 300 were analyzed(90.9% response rate). It was revealed that more than half of the respondents(54.0%) had used processed rice food products, regardless of their occupation. Most respondents stated that they used rice food products because of the variety of the products, digestibility and the taste. The development necessity for processed rice food products was analyzed, showing that rice cake(3.86), rice sauce(3.64), and rice cookie(3.89) had the highest score in each category. The average demand for education and promotion of rice food products was 3.89; among 7 items, menu recipe using rice flour was highly demanded(4.18) by the respondents. Approximately 43.0% of the respondents agreed that the internet is the most effective method for learning about rice flour cooking, and the respondents who have used processed rice food products(59.5%) were more likely to attend education programs compared to housewives who have not used processed rice food products (44.5%)(p<.05). Full-time housewife(59.4%) had a greater tendency to participate in the education program than working woman(44.4%)(p<.001). The findings suggested that various processed rice flour products with convenience to use and prolonged shelf-life will be needed.

• Korean Educational Research Journal
• /
• v.37 no.1
• /
• pp.67-101
• /
• 2016

The purpose of this study is to explore and propose policy alternatives by examining students' educational experiences at Chungbuk National University (CBNU). Some of the outstanding research findings of the study as follows. Students at CBNU think that they are capable of team-working and utilizing internet while less so with foreign language skill. With regard to academic achievement, students responded that they have seen a relatively low outcome in foreign language competency. In terms of their job placement, CBNU students highly recognize their logical thinking skill, creativity, and activity, whereas lower satisfaction with social service, study abroad, and internship experience. For further development of the survey analysis, this study suggests additional items included to make a sophisticated analysis possible such as scholarship, part-time job, educational outcome. This is expected to allow researchers to tab into the effect of finance of CBNU students. More detailed information on students' characteristics also need to be added; collaborative learning, student faculty interaction, co-work with students from diverse background, etc., which would allow the analysis of the impact of extra-curricula activities.

• Journal of the Korean Society of Food Culture
• /
• v.29 no.3
• /
• pp.250-258
• /
• 2014

This research investigated the relationship among Korean Wave Cultural Contents consumption of Korean food, Korean products, and Learning of the Korean language. The survey targeted non-Koreans who were either interested in or experienced Korean Wave Cultural Contents. Exactly 61.3% of subjects had traveled to Korea. The most common method of experiencing the Korean Wave was via the Internet (57.7%), followed by TV (21.1%) and Mobile (7.7%). The most popular Korean Wave Contents were K-pop (35.2%) and TV Dramas (31.0%). Movies were preferred in the Americas ($3.63{\pm}0.83$) and Asia ($3.63{\pm}1.09$), whereas K-pop was preferred in Asia ($3.68{\pm}1.12$) and games preferred in Europe ($2.50{\pm}1.56$). Regarding Korean food, most participants had tasted Kimchi (81.7%), followed by Bulgogi (74.6%), Bibimbap (66.9%), and Galbi (66.2%). According to the country-by-country survey, in the case of Galbi (p<0.05), Bibimbap (p<0.05), and Bulgogi (p<0.05), Asians had more experiences with Korean food compared to those from other regions. Meanwhile, in the case of satisfaction of Korean food, Bulgogi ($4.22{\pm}1.05$) was ranked highest, whereas Kimchi ($3.85{\pm}1.15$) was ranked lowest. According to the region-by-region survey, those from Oceania and other regions preferred Kimchi ($4.25{\pm}0.71$) and Bulgogi ($4.50{\pm}4.50$) while the Americas preferred Galbi ($4.82{\pm}0.39$) and Bibimbap ($4.54{\pm}0.81$). Bulgogi ($2.76{\pm}0.06$) was highly ranked as a representative Korean Food while Kimchi ($2.44{\pm}0.71$) was ranked the lowest. This research explained that among Korean Wave Cultural Contents, movies and music positively influenced on the 'Image of Korea', movies and K-pop effected 'Purchasing intention of Korean products', and TV Dramas, movies, and K-pop effected 'Purchasing intention of Korean Food'.

• Journal of KIISE
• /
• v.43 no.1
• /
• pp.87-95
• /
• 2016

Recently, due to the development of the Internet and electronic devices, there has been an enormous increase in the amount of available knowledge and information. As this growth has proceeded, studies on large-scale ontological reasoning have been actively carried out. In general, a machine learning program or knowledge engineer measures and provides a degree of confidence for each triple in a large ontology. Yet, the collected ontology data contains specific uncertainty and reasoning such data can cause vagueness in reasoning results. In order to solve the uncertainty issue, we propose an RDFS reasoning approach that utilizes confidence values indicating degrees of uncertainty in the collected data. Unlike conventional reasoning approaches that have not taken into account data uncertainty, by using the in-memory based cluster computing framework Spark, our approach computes confidence values in the data inferred through RDFS-based reasoning by applying methods for uncertainty estimating. As a result, the computed confidence values represent the uncertainty in the inferred data. To evaluate our approach, ontology reasoning was carried out over the LUBM standard benchmark data set with addition arbitrary confidence values to ontology triples. Experimental results indicated that the proposed system is capable of running over the largest data set LUBM3000 in 1179 seconds inferring 350K triples.

• Journal of Korea Society of Industrial Information Systems
• /
• v.13 no.2
• /
• pp.69-79
• /
• 2008

Due to popularization of the wireless Internet and mobile devices the infrastructure of the ubiquitous environment, where users can get information whatever they want anytime and anywhere, is created. Therefore, a variety of fields including the education studies methods for efficiency of information transmission using on-line and off-line contents. In this paper, we propose the Mixed Mobile Education system(MME) that improves educational efficiency using on-line and off-line contents on mobile devices. Because it is hard to input new data and cannot use similar off-line contents in systems used additional tags, the proposed system does not use additional tags but recognizes of-line contents as we extract feature points in the input image using the mobile camera. We use the Scale Invariant Feature Transform(SIFT) algorithm to extract feature points which are not affected by noise, color distortion, size and rotation in the input image captured by the low resolution camera. And we use the client-server architecture for solving the limited storage size of the mobile devices and for easily registration and modification of data. Experimental results show that compared with previous work, the proposed system has some advantages and disadvantages and that the proposed system has good efficiency on various environments.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.2
• /
• pp.76-86
• /
• 2016

SQL Injection attacks are the most widely used and also they are considered one of the oldest traditional hacking techniques. SQL Injection attacks are getting quite complicated and they perform a high portion among web hacking. The big data environments in the future will be widely used resulting in many devices and sensors will be connected to the internet and the amount of data that flows among devices will be highly increased. The scale of damage caused by SQL Injection attacks would be even greater in the future. Besides, creating security solutions against SQL Injection attacks are high costs and time-consuming. In order to prevent SQL Injection attacks, we have to operate quickly and accurately according to this data analysis techniques. We utilized data analytics and machine learning techniques to defend against SQL Injection attacks and analyzed the execution plan of the SQL command input if there are abnormal patterns through checking the web log files. Herein, we propose a way to distinguish between normal and abnormal SQL commands. We have analyzed the value entered by the user in real time using the automated SQL Injection attacks tools. We have proved that it is possible to ensure an effective defense through analyzing the execution plan of the SQL command.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.21 no.3
• /
• pp.151-163
• /
• 2010

It is necessary, due to changes in the information environment, to investigate problems in existing information retrieval systems. Ontologies and social tagging, which are a relatively new means of information organization, enable exploratory discovery of information. These two connect a thought of a user with the thoughts of numerous other people on the Internet. With these connection chains through the interactions, users are foraging information actively and exploratively. Thus, the purpose of this study is, through qualitative research methods, to identify numerous discovery facilitators provided by ontologies and social tagging, and to create an exploratory discovery model based on them. The results show that there are three uppermost categories in which 5, 4 and 4 subcategories are enumerated respectively. The first category, 'Browsing and Monitoring,' has 5 sub categories: Noticing the Needs, Being Aware, Perceiving, Stopping, and Examining a Resource. The second category, Actively Participating, has 4 categories: Constructing Meaning, Social Bookmarking and Tagging, Sharing on Social Networking, Specifying the Original Needs. The third category, Actively Extends Thinking, also has 4 categories: Social Learning, Emerging Fortuitous Discovery, Creative Thinking, Enhancing Problem Solving Abilities. This model could contribute to the design of information systems, which enhance the ability of exploratory discovery.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.469-469
• /
• 2017

기후 변화 및 환경오염으로 인하여 물부족 국가가 세계적으로 증가하고 있는 추세이며, 특히 집중형 강우의 형태가 많아짐에 따라 홍수피해 및 상수공급의 문제가 사회적으로 큰 이슈가 되고 있다. 최근 20여 년간의 급속한 경제성장과 도시화 과정에서 인도네시아는 인구와 산업의 과도한 도시집중으로 지난 1960-80년대 한국이 산업화 과정에서 겪었던 것보다 훨씬 심각한 환경문제에 직면하고 있으며, 자카르타와 반둥을 포함하는 광역 수도권 지역의 물 부족과 수질 오염, 환경문제가 이미 매우 위험한 수준에 도달하고 있는 실정이다. 특히, 찌따룸강 중상류에 위치한 인도네시아 3대 도시인 반둥시는 고질적인 용수부족 문제를 겪고 있다. 2010년 현재 약 일평균 15 CMS의 용수가 부족한 상황이며, 2030년에는 지속적인 인구증가로 약 23 CMS의 용수가 추가로 더 필요한 것으로 전망된다. 이러한 용수공급 문제 해결을 위해 반둥시 및 찌따룸강 유역관리청은 댐 및 지하수 개발, 유역 간 물이동 등의 구조적인 대책뿐만 아니라 비구조적인 대책으로써 기존 및 신규 저수지 연계운영을 통한 용수이용의 효율성을 높이는 방안을 모색하고 있다. 이에 따라 본 연구에서는 해당유역의 용수공급 부족 문제를 해소할 수 있는 비구조적인 대책의 일환으로써 다양한 댐 및 보, 소수력 발전, 취수장 등 유역 내 수리 시설물의 운영 최적화를 위한 지능형 물관리 시스템 적용 방안을 제시하고자 한다. 본 연구의 지능형 물관리 시스템은 센서 및 사물 인터넷(Internet of Things, IoT), 네트워크 기술을 바탕으로 시설물 및 운영자, 유관기관 간의 양방향 통신을 통해 유기적인 상호연계 체계를 제공 할 수 있다. 또한 유역의 수문상황과 시설물의 운영현황, 용수공급 및 수요 현황을 실시간으로 확인함으로써 수요에 따른 즉각적인 용수공급량의 조절이 가능하다. 또한, 빅데이터 분석 및 기계학습(Machine Learning)을 통해 개별 물관리 시설물에 대한 최적 운영룰을 업데이트할 수 있으며, 유역의 수문상황과 용수 수요 현황을 고려하여 최적의 용수공급 우선순위를 선정할 수 있다. 지능형 물관리 시스템 개발의 목적은 찌상쿠이 유역의 수문현황을 실시간으로 모니터링하고, 하천시설물의 운영을 분석하여 최적의 용수공급 및 배분을 통해 유역의 수자원 활용 효율성을 향상시키는 데 있다. 이를 위해 수문자료의 수집체계를 구축하고 기관간 정보공유체계를 수립함으로써 분석을 위한 기반 인프라를 구성하며, 이를 기반으로 유역 유출을 비롯한 저수지 운영, 물수지 분석을 수행하고, 분석 및 예측결과, 과거 운영 자료를 토대로 새로운 물관리 시설 운영룰 및 시설물 간 연계운영 방안, 용수공급 우선순위 의사결정 등을 지원하고자 한다. 본 연구의 지능형 물관리 시스템은 통합 DB를 기반으로 수리수문 현상의 모의 분석을 통해 하천 시설물 운영의 합리적 기준을 제시함으로써 다양한 관리주체들의 시설물운영에 대한 이견 및 분쟁을 해소하고, 한정된 수자원과 다양한 수요 간의 효율적이고 합리적인 분배 및 시설물 운영문제를 해결하기 위한 의사결정도구로써 활용할 수 있을 것으로 기대된다.

• Journal of Korean Library and Information Science Society
• /
• v.52 no.3
• /
• pp.177-196
• /
• 2021

The purpose of this study is to analyze priorities of competencies and to find the direction of development of teacher librarian training and retraining program. A total of 238 subjects were used for the final analysis. They were analayzed using IPA, Borich's needs analysis and the Locus for Focus model. As a result, First, teacher librarians perceived that the importance and performance of teacher and manager competency were higher than information specialist and cooperative leader. Second, they needed competencies of data-science, coding, Internet of Things in the field of information specialist as changing educational environment. Third, they needed competencies of information ethics, copyright instruction, and digital and media literacy education in the field of teacher. Fourth, they needed competencies of facility designing for future education, online and offline school library marketing skills, and establishment of makerspaces and learning commons in the field of ibrary manager. Fifth, they needed competencies of library based instruction, library cooperative instruction, and building a collection related to subject in the field of cooperative leader. Sixth, the highest required competency for teacher librarians was suggested for teacher librarians' role area.

• The Journal of the Korea Contents Association
• /
• v.21 no.9
• /
• pp.149-163
• /
• 2021

The 4th industrial revolution refers to the next-generation industrial revolution led by information and communication technologies such as artificial intelligence (AI), Internet of Things (IoT), robot technology, drones, autonomous driving and virtual reality (VR) and it also has made a significant impact on the development of the advertising industry. However, the world is rapidly changing to a non-contact, non-face-to-face living environment to prevent the spread of COVID 19. Accordingly, the role of the 4th industrial revolution and advertising is changing. Therefore, in this study, text analysis was performed using Big Kinds to examine the 4th industrial revolution and changes in advertising before and after COVID 19. Comparisons were made between 2019 before COVID 19 and 2020 after COVID 19. Main topics and documents were classified through LDA topic model analysis and Word2vec, a deep learning technique. As the result of the study showed that before COVID 19, policies, contents, AI, etc. appeared, but after COVID 19, the field gradually expanded to finance, advertising, and delivery services utilizing data. Further, education appeared as an important issue. In addition, if the use of advertising related to the 4th industrial revolution technology was mainstream before COVID 19, keywords such as participation, cooperation, and daily necessities, were more actively used for education on advanced technology, while talent cultivation appeared prominently. Thus, these research results are meaningful in suggesting a multifaceted strategy that can be applied theoretically and practically, while suggesting the future direction of advertising in the 4th industrial revolution after COVID 19.