• Title/Summary/Keyword: 커뮤니케이션 품질

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Effect of Dietary Mogchotan Supplementation on Fattening Performance, Fatty acid Composition and Meat Quality in Pigs (사료내 목초탄 첨가가 비육돈의 비육능력, 지방산 조성 및 육질에 미치는 영향)

  • Kim, Jong-Min;Ahn, Byoung-Jun;Jo, Tae-Su;Cho, Sung-Taek;Choi, Don-Ha;Hwang, Sung-Gu
    • Korean Journal of Organic Agriculture
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    • v.13 no.4
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    • pp.401-412
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    • 2005
  • This study was conducted to examine the effects of dietary Mogchotan(the mixture of charcoal and pyroligneous acid, 80:20, w/w) supplementation on fattening performance, fatty acid composition and the physico-chemical characteristics of meat in pigs. The present study was also stressed to investigate the possibility of industrial utilization of charcoal and pyroligneous acid as a livestock feed additive. Weight gain and feed conversion in pigs fed the Mogchotan supplemented diet were higher than those of the control group. In fatty acids composition, palmitic acid(C16:0) contents of Mogchotan treatment groups were lower than that of control group. However, Mogchotan supplementation increased C16:1, C18:0, C18:1, C18:2 and C18:3 contents when compared with control group pigs. Also, Mogchotan supplementation groups decreased saturated fatty acids level than control group. On the other hand, Mogchotan supplementation showed higher unsaturated fatty acids value, especially polyunsaturated fatty acids value compared to control group. The carcass pH of pigs fed the Mogchotan tended to be higher than control, but was not significantly different. The water holding capacity was significantly higher in pigs fed the 3.0% Mogchotan-supplemented diet than those of other treatment groups(p<0.05). Altogether, it has been suggested that dietary $1{\sim}3%$ of Mogchotan supplementation improved the fattening performance and meat quality in pigs.

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Digital Hologram Compression Technique By Hybrid Video Coding (하이브리드 비디오 코팅에 의한 디지털 홀로그램 압축기술)

  • Seo, Young-Ho;Choi, Hyun-Jun;Kang, Hoon-Jong;Lee, Seung-Hyun;Kim, Dong-Wook
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.5 s.305
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    • pp.29-40
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    • 2005
  • According as base of digital hologram has been magnified, discussion of compression technology is expected as a international standard which defines the compression technique of 3D image and video has been progressed in form of 3DAV which is a part of MPEG. As we can identify in case of 3DAV, the coding technique has high possibility to be formed into the hybrid type which is a merged, refined, or mixid with the various previous technique. Therefore, we wish to present the relationship between various image/video coding techniques and digital hologram In this paper, we propose an efficient coding method of digital hologram using standard compression tools for video and image. At first, we convert fringe patterns into video data using a principle of CGH(Computer Generated Hologram), and then encode it. In this research, we propose a compression algorithm is made up of various method such as pre-processing for transform, local segmentation with global information of object image, frequency transform for coding, scanning to make fringe to video stream, classification of coefficients, and hybrid video coding. Finally the proposed hybrid compression algorithm is all of these methods. The tool for still image coding is JPEG2000, and the toots for video coding include various international compression algorithm such as MPEG-2, MPEG-4, and H.264 and various lossless compression algorithm. The proposed algorithm illustrated that it have better properties for reconstruction than the previous researches on far greater compression rate above from four times to eight times as much. Therefore we expect that the proposed technique for digital hologram coding is to be a good preceding research.

Analysis of Evaluator's Role and Capability for Institution Accreditation Evaluation of NCS-based Vocational Competency Development Training (NCS 기반 직업능력개발훈련 기관인증평가를 위한 평가자의 역할과 역량 분석)

  • Park, Ji-Young;Lee, Hee-Su
    • Journal of vocational education research
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    • v.35 no.4
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    • pp.131-153
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    • 2016
  • The purpose of this study was to derive evaluator's role and capability for institution accreditation evaluation of NCS-based vocational competency development training. This study attempted to explore in various ways evaluator's minute roles using Delphi method, and to derive knowledge, skill, attitude and integrity needed to verify the validity. To the end, this study conducted the Delphi research for over three rounds by selecting education training professionals and review evaluation professions as professional panels. From the results, roles of evaluators were defined as the total eight items including operator, moderator-mediator, cooperator, analyzer, verifier, institution evaluator, institution consultant, and learner, and the derived capabilities with respect to each role were 25 items in total. The area of knowledge included four items of capabilities such as HRD knowledge, NCS knowledge, knowledge of vocational competency development training, and knowledge of training institution accreditation evaluation, and the area of skill comprised fourteen items of capabilities such as conflict management ability, interpersonal relation ability, word processing ability, problem-solving ability, analysis ability, pre-preparation ability, time management ability, decision making ability, information comprehension and utilization ability, comprehensive thinking ability, understanding ability of vocational competency development training institutions, communication ability, feedback ability, and core understanding ability. The area of attitude was summarized with the seven items in total including subjectivity and fairness, service mind, sense of calling, ethics, self-development, responsibility, and teamwork. The knowledge, skill and attitude derived from the results of this study may be utilized to design and provide education programs conducive to qualitative and systematic accreditation and assessment to evaluators equipped with essential prerequisites. It is finally expected that this study will be helpful for designing module education programs by ability and for managing evaluator's quality in order to perform pre-service education and in-service education according to evaluator's experience and role.

Analysis on Topokki Franchise Industry and Its Proactive Activities: Focused on Kukdae Toppokki (떡볶이 프랜차이즈 산업의 분석과 그에 따른 선제적 대응 방안: 국대떡볶이를 중심으로)

  • Chi, I hyun;Han, Kyu won;Choi, Yae jin;Son, Jeong Sook;Kim, Ji-Hern
    • The Korean Journal of Franchise Management
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    • v.5 no.1
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    • pp.27-47
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    • 2014
  • This research was conducted on the purpose of seeking the measures of how to cope with the changing industry of Topokki franchises. Despite of the fact the number of Kukdae Topokki's stores is quite smaller than that of its competitors, such as Jaws Topokki and Addal Topokki, Kukdae Topokki is recognized as one of the front-runners in the industry. But the competition in the topokki industry has become fiercer, as the market became saturated. To find a desirable solutions, this study analyzes past-to-current status of the Topokki industry by dividing it into 4 stages and provides few strategies that Kukdae Topokki can apply to the 4th stage where 'brand awareness' is very important. To this end, few drawbacks of Kukdae Topokki are proposed as the following. First, the brand image that Kukdae Topokki pursue does not correspondent with the image in consumer's mind. Second, Kukdae Topokki has selected the wrong targeting group. It aims for the image of 'retro' to target people in their 30-40s. However, most of the consumers are people in their 20-30s. Third, the taste of Kukdae Topokki is not uniform among franchises. Fourth, the awareness and accessability are low. To provide a proactive actions for the next stages, several solutions are proposed as following. First, By managing consistent Kukdae Topokki's Brand Touch point, consumers may have a strong image on the brand by communicating with consumers consistently at all touch points. Second, instead of the existing guide from the head office(franchiser), a standardized criteria for the usage of materials and periodical education for franchisee are needed. Third, to raise the awareness of Kukdae Topokki, open many branches in the area where the main consumers(20-30s women) are mostly spread out.

Incorporating Social Relationship discovered from User's Behavior into Collaborative Filtering (사용자 행동 기반의 사회적 관계를 결합한 사용자 협업적 여과 방법)

  • Thay, Setha;Ha, Inay;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.1-20
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    • 2013
  • Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.