• Title/Summary/Keyword: Research performance-based class

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Perception of the importance and educational needs of job performance competency of National Competency Standards based vocational education curriculum in technical specialized high schools and meister high schools (NCS 기반 직업교육과정 도입에 따른 공업계열 특성화고·마이스터고 교사의 직무수행능력 중요도 및 교육적 요구에 대한 인식)

  • Hahm, Seung-Yeon
    • 대한공업교육학회지
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    • v.41 no.2
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    • pp.69-88
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    • 2016
  • The study tried to investigate perception of the importance and educational needs of job performance competency of National Competency Standards based vocational education curriculum in technical specialized high schools and meister high schools. For this, the survey was conducted targeting 269 specialty subject teachers in technical specialized high schools and meister high schools. And the results are as follow: First, job performance competency were divided into 5 categories(curriculum guidance, school life guidance, class management, extraordinary activities and administrative duties) and 34 sub-categories. Second, higher importance values were curriculum guidance, extraordinary activities and school life guidance. Higher educational needs values were curriculum guidance, extraordinary activities and administrative duties in categories. Third, higher importance values were construction and reconstruction of NCS learning modules, organization and manage of NCS based vocational education curriculum, guide of the new laws and employment, student records manage, research activities of NCS, hands-on-background training, NCS projects in sub-categories. Fourth, the results show that the NCS experienced teachers more highly evaluated the importance and educational needs of the job performance competency than the NCS inexperienced teachers did.

How Enduring Product Involvement and Perceived Risk Affect Consumers' Online Merchant Selection Process: The 'Required Trust Level' Perspective (지속적 관여도 및 인지된 위험이 소비자의 온라인 상인선택 프로세스에 미치는 영향에 관한 연구: 요구신뢰 수준 개념을 중심으로)

  • Hong, Il-Yoo B.;Lee, Jung-Min;Cho, Hwi-Hyung
    • Asia pacific journal of information systems
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    • v.22 no.1
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    • pp.29-52
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    • 2012
  • Consumers differ in the way they make a purchase. An audio mania would willingly make a bold, yet serious, decision to buy a top-of-the-line home theater system, while he is not interested in replacing his two-decade-old shabby car. On the contrary, an automobile enthusiast wouldn't mind spending forty thousand dollars to buy a new Jaguar convertible, yet cares little about his junky component system. It is product involvement that helps us explain such differences among individuals in the purchase style. Product involvement refers to the extent to which a product is perceived to be important to a consumer (Zaichkowsky, 2001). Product involvement is an important factor that strongly influences consumer's purchase decision-making process, and thus has been of prime interest to consumer behavior researchers. Furthermore, researchers found that involvement is closely related to perceived risk (Dholakia, 2001). While abundant research exists addressing how product involvement relates to overall perceived risk, little attention has been paid to the relationship between involvement and different types of perceived risk in an electronic commerce setting. Given that perceived risk can be a substantial barrier to the online purchase (Jarvenpaa, 2000), research addressing such an issue will offer useful implications on what specific types of perceived risk an online firm should focus on mitigating if it is to increase sales to a fullest potential. Meanwhile, past research has focused on such consumer responses as information search and dissemination as a consequence of involvement, neglecting other behavioral responses like online merchant selection. For one example, will a consumer seriously considering the purchase of a pricey Guzzi bag perceive a great degree of risk associated with online buying and therefore choose to buy it from a digital storefront rather than from an online marketplace to mitigate risk? Will a consumer require greater trust on the part of the online merchant when the perceived risk of online buying is rather high? We intend to find answers to these research questions through an empirical study. This paper explores the impact of enduring product involvement and perceived risks on required trust level, and further on online merchant choice. For the purpose of the research, five types or components of perceived risk are taken into consideration, including financial, performance, delivery, psychological, and social risks. A research model has been built around the constructs under consideration, and 12 hypotheses have been developed based on the research model to examine the relationships between enduring involvement and five components of perceived risk, between five components of perceived risk and required trust level, between enduring involvement and required trust level, and finally between required trust level and preference toward an e-tailer. To attain our research objectives, we conducted an empirical analysis consisting of two phases of data collection: a pilot test and main survey. The pilot test was conducted using 25 college students to ensure that the questionnaire items are clear and straightforward. Then the main survey was conducted using 295 college students at a major university for nine days between December 13, 2010 and December 21, 2010. The measures employed to test the model included eight constructs: (1) enduring involvement, (2) financial risk, (3) performance risk, (4) delivery risk, (5) psychological risk, (6) social risk, (7) required trust level, (8) preference toward an e-tailer. The statistical package, SPSS 17.0, was used to test the internal consistency among the items within the individual measures. Based on the Cronbach's ${\alpha}$ coefficients of the individual measure, the reliability of all the variables is supported. Meanwhile, the Amos 18.0 package was employed to perform a confirmatory factor analysis designed to assess the unidimensionality of the measures. The goodness of fit for the measurement model was satisfied. Unidimensionality was tested using convergent, discriminant, and nomological validity. The statistical evidences proved that the three types of validity were all satisfied. Now the structured equation modeling technique was used to analyze the individual paths along the relationships among the research constructs. The results indicated that enduring involvement has significant positive relationships with all the five components of perceived risk, while only performance risk is significantly related to trust level required by consumers for purchase. It can be inferred from the findings that product performance problems are mostly likely to occur when a merchant behaves in an opportunistic manner. Positive relationships were also found between involvement and required trust level and between required trust level and online merchant choice. Enduring involvement is concerned with the pleasure a consumer derives from a product class and/or with the desire for knowledge for the product class, and thus is likely to motivate the consumer to look for ways of mitigating perceived risk by requiring a higher level of trust on the part of the online merchant. Likewise, a consumer requiring a high level of trust on the merchant will choose a digital storefront rather than an e-marketplace, since a digital storefront is believed to be trustworthier than an e-marketplace, as it fulfills orders by itself rather than acting as an intermediary. The findings of the present research provide both academic and practical implications. The first academic implication is that enduring product involvement is a strong motivator of consumer responses, especially the selection of a merchant, in the context of electronic shopping. Secondly, academicians are advised to pay attention to the finding that an individual component or type of perceived risk can be used as an important research construct, since it would allow one to pinpoint the specific types of risk that are influenced by antecedents or that influence consequents. Meanwhile, our research provides implications useful for online merchants (both online storefronts and e-marketplaces). Merchants may develop strategies to attract consumers by managing perceived performance risk involved in purchase decisions, since it was found to have significant positive relationship with the level of trust required by a consumer on the part of the merchant. One way to manage performance risk would be to thoroughly examine the product before shipping to ensure that it has no deficiencies or flaws. Secondly, digital storefronts are advised to focus on symbolic goods (e.g., cars, cell phones, fashion outfits, and handbags) in which consumers are relatively more involved than others, whereas e- marketplaces should put their emphasis on non-symbolic goods (e.g., drinks, books, MP3 players, and bike accessories).

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An Adaptive Contention Windows Adjustment Scheme Based on the Access Category for OnBord-Unit in IEEE 802.11p (IEEE 802.11p에서 차량단말기간에 혼잡상황 해결을 위한 동적 충돌 윈도우 향상 기법)

  • Park, Hyun-Moon;Park, Soo-Hyun;Lee, Seung-Joo
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.6
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    • pp.28-39
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    • 2010
  • The study aims at offering a solution to the problems of transmission delay and data throughput decrease as the number of contending On-Board Units (OBU) increases by applying CSMA medium access control protocol based upon IEEE 802.11p. In a competition-based medium, contention probability becomes high as OBU increases. In order to improve the performance of this medium access layer, the author proposes EDCA which a adaptive adjustment of the Contention Windows (CW) considering traffic density and data type. EDCA applies fixed values of Minimum Contention Window (CWmin) and Maximum Contention Window (CWmax) for each of four kinds of Access Categories (AC) for channel-specific service differentiation. EDCA does not guarantee the channel-specific features and network state whereas it guarantees inter-AC differentiation by classifying into traffic features. Thus it is not possible to actively respond to a contention caused by network congestion occurring in a short moment in channel. As a solution, CWminAS(CWmin Adaptation Scheme) and ACATICT(Adaptive Contention window Adjustment Technique based on Individual Class Traffic) are proposed as active CW control techniques. In previous researches, the contention probabilities for each value of AC were not examined or a single channel based AC value was considered. And the channel-specific demands of IEEE 802.11p and the corresponding contention probabilities were not reflected in the studies. The study considers the collision number of a previous service section and the current network congestion proposes a dynamic control technique ACCW(Adaptive Control of Contention windows in considering the WAVE situation) for CW of the next channel.

Vehicle Detection in Dense Area Using UAV Aerial Images (무인 항공기를 이용한 밀집영역 자동차 탐지)

  • Seo, Chang-Jin
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.3
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    • pp.693-698
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    • 2018
  • This paper proposes a vehicle detection method for parking areas using unmanned aerial vehicles (UAVs) and using YOLOv2, which is a recent, known, fast, object-detection real-time algorithm. The YOLOv2 convolutional network algorithm can calculate the probability of each class in an entire image with a one-pass evaluation, and can also predict the location of bounding boxes. It has the advantage of very fast, easy, and optimized-at-detection performance, because the object detection process has a single network. The sliding windows methods and region-based convolutional neural network series detection algorithms use a lot of region proposals and take too much calculation time for each class. So these algorithms have a disadvantage in real-time applications. This research uses the YOLOv2 algorithm to overcome the disadvantage that previous algorithms have in real-time processing problems. Using Darknet, OpenCV, and the Compute Unified Device Architecture as open sources for object detection. a deep learning server is used for the learning and detecting process with each car. In the experiment results, the algorithm could detect cars in a dense area using UAVs, and reduced overhead for object detection. It could be applied in real time.

A Study on the Influence of Educational Environment for Reemployment of Cooking Schools on Job Satisfaction (요리직업전문학교의 재취업 교육 환경이 취업 만족도에 미치는 영향에 관한 연구)

  • Seo, Hyun-Ju;Cho, Han-Yung;Lee, Jong-Ho
    • Culinary science and hospitality research
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    • v.16 no.1
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    • pp.280-291
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    • 2010
  • This study investigates the influence of educational satisfaction on job satisfaction. The sample consists of 243 students who took a re-vocational cooking class program at a cooking school. To accomplish the result, frequency analysis, factor and reliability analysis, t-test, ANOVA and Multiple Regression Analysis were used. Based on the result, educational satisfaction is related to satisfaction with education time, satisfaction with facilities and satisfaction with contents. Also, job satisfaction is related to satisfaction with payment and satisfaction with performance. The result showed that gender and possession of a license are statistically significant on education time and educational contents; however, it didn't show the significance of educational facilities.

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Federated Learning Privacy Invasion Study in Batch Situation Using Gradient-Based Restoration Attack (그래디언트 기반 재복원공격을 활용한 배치상황에서의 연합학습 프라이버시 침해연구)

  • Jang, Jinhyeok;Ryu, Gwonsang;Choi, Daeseon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.31 no.5
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    • pp.987-999
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    • 2021
  • Recently, Federated learning has become an issue due to privacy invasion caused by data. Federated learning is safe from privacy violations because it does not need to be collected into a server and does not require learning data. As a result, studies on application methods for utilizing distributed devices and data are underway. However, Federated learning is no longer safe as research on the reconstruction attack to restore learning data from gradients transmitted in the Federated learning process progresses. This paper is to verify numerically and visually how well data reconstruction attacks work in various data situations. Considering that the attacker does not know how the data is constructed, divide the data with the class from when only one data exists to when multiple data are distributed within the class, and use MNIST data as an evaluation index that is MSE, LOSS, PSNR, and SSIM. The fact is that the more classes and data, the higher MSE, LOSS, and PSNR and SSIM are, the lower the reconstruction performance, but sufficient privacy invasion is possible with several reconstructed images.

Skin Disease Classification Technique Based on Convolutional Neural Network Using Deep Metric Learning (Deep Metric Learning을 활용한 합성곱 신경망 기반의 피부질환 분류 기술)

  • Kim, Kang Min;Kim, Pan-Koo;Chun, Chanjun
    • Smart Media Journal
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    • v.10 no.4
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    • pp.45-54
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    • 2021
  • The skin is the body's first line of defense against external infection. When a skin disease strikes, the skin's protective role is compromised, necessitating quick diagnosis and treatment. Recently, as artificial intelligence has advanced, research for technical applications has been done in a variety of sectors, including dermatology, to reduce the rate of misdiagnosis and obtain quick treatment using artificial intelligence. Although previous studies have diagnosed skin diseases with low incidence, this paper proposes a method to classify common illnesses such as warts and corns using a convolutional neural network. The data set used consists of 3 classes and 2,515 images, but there is a problem of lack of training data and class imbalance. We analyzed the performance using a deep metric loss function and a cross-entropy loss function to train the model. When comparing that in terms of accuracy, recall, F1 score, and accuracy, the former performed better.

Evaluation of the Basic Property Evaluation of Eco-powder, a Hydrothermal Synthesis Product for Improving Waste Vinyl Recycling Efficiency (농촌 폐비닐 활용률 제고를 위한 수열합성 생성물인 에코 파우더(Eco-powder)의 기초물성 평가)

  • Sun-Mi Choi;Min-Chul Lee;Jin-Man Kim;Young-Gon Son;Nam-Ho Kim
    • Resources Recycling
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    • v.33 no.1
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    • pp.48-57
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    • 2024
  • This study aimed to improve utilization of the Class C vinyl waste generated in rural areas based on a preliminary investigation on the use of eco-powder, generated through pyrolysis, as a raw material for plastic. The efficiency of pre-processing treatments in controlling ash content of the generated eco-powder and its effect on the basic properties of manufactured plastic were evaluated. The basic properties included ash content of the compressed eco-powder at different levels of ash content, impact strength, flexural strength, and tensile strength. The experimental results confirmed that pre-processing improved the separation efficiency of soil particles and vinyl waste through physical impact. The eco-powder with ash content of less than or equal to 26% was found to satisfy the target performance during impact strength, flexural strength, and tensile strength evaluation. Thus, it was confirmed that the Class C vinyl waste, having low utilization and recovery rates, could be effectively utilized as a plastic raw material after optimum thermal treatment and physical processing using the eco-powder.

A Content Analysis on Learning Experience of K-MOOC(Korea-Massive Open Online Course) : Focused on Korean University Students (한국 대학생의 K-MOOC 학습 경험에 대한 내용 분석)

  • Park, Tae-Jung;Rah, Ilju
    • The Journal of the Korea Contents Association
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    • v.16 no.12
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    • pp.446-457
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    • 2016
  • The purpose of the study was to understand the various aspects of learning experiences of Korean university students on K-MOOC. Analyses on the major motivation of the enrollment in a certain MOOC class, the actual learning experiences in the class and the perception of the achievement of the class were the three main foci of the current study. The study employed inductive content analysis as a major analysis tool. Reflective journals from 94 students who enrolled in K-MOOC classes were collected and analyzed at the end of the semester. The result of this study indicated that most of students selected the specific K-MOOC classes based on their general interests on the topics the class offered. Other factors such as intellectual curiosity, practical reasons for their study or work and popularity were also influential on the selection of MOOC classes. Watching videos, taking quizzes and taking tests were the three major sources of the students' satisfaction. Most students felt that K-MOOC is technically satisfactory. However, some students reported on simple errors and absence of advanced functions in the platform. Students perceived positively on their academic achievements of obtaining knowledge(remembering and understanding), attitudes (receiving), and skills through K-MOOC. This study ultimately showed a new awareness of learning experiences around K-MOOC from the perspective of the students. Future research is needed to understand the relationships between the students' learning experience and the students' performance in MOOC classes.

A Study on Interaction Pattern, Learning Attitude, Task Performance by Meta-cognitive Level in Web-Based Learning (웹 기반 학습자의 메타인지수준별 학습활동분석 -간호학 대학원 학생을 중심으로-)

  • Lee, Sun-Ock;Suh, Min-Hee
    • The Journal of Korean Academic Society of Nursing Education
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    • v.18 no.2
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    • pp.323-331
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    • 2012
  • Purpose: Level of meta-cognition of students has been regarded as one of the crucial factors on web-based learning. This study aimed to describe interaction type in small group discussion of the nursing graduate students and to investigate learning consequences and interaction types in group discussion on meta-cognition level. Method: Twenty six graduate nursing students attending the class on-line at the K university in Seoul were included in the study. We measured their meta-cognition level and learning attitude. We also scored their individual and group reports as well as analyzed interaction type by reviewing the dialogue of the group discussion. Results: The participants showed low frequency of exploratory interaction and high frequency of integrative interaction in the cognitive interaction category. They showed frequent modification interaction in the meta-cognitive interaction category. Interestingly, the students with lower level of meta-cognition achieved significantly greater scores in the individual assignments. High functioning group consisting of the students with high meta-cognitive level produced greater group report. Conclusion: A new strategy is needed to encourage in-depth interaction in a group discussion of nursing students. Meta-cognitive level of the students should be considered to form a small group for discussion in order to improve group activities.