• Journal of Digital Convergence
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• v.19 no.4
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• pp.33-38
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• 2021

The data economy' is growing rapidly with the corona era. The quantity and quality of digital data is increasing rapidly. The domestic data industry needs a variety of data manpower, but there is still a shortage of high-quality data manpower. The data manpower in high demand is the development manpower, but the data business manpower is needed to increase the added value of the data industry. The role of a data trade manager that creates high core value among data business personnel is attracting attention. This study derives the job definition of the data trade manager, the necessary knowledge and skills, and the educational content necessary for the training course through Delphi research. In order to validate the results of the research, the study try to verifies the role of data trade managers. This study can be used as a theoretical basis for an educational model that is the basis for training data manpower, and can be used to establish a manpower training policy in the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.117-129
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• 2023

Organizations must seek change in order to adapt to environmental changes and achieve better performance. However, despite this obvious statement, empirical analysis has been almost non-existent due to the difficulty of manipulating organizational performance or change. In this study, we overcame these limitations and analyzed the causes and effects of organizational change by assuming a professional sports team as a venture company, which is relatively easy to objectively measure and evaluate organizational change or performance. We systematically collected and preprocessed traditional and advanced metrics of National Basketball Association (NBA) statistics along with preprocessed trade data from eight years of regular seasons (2014~2015-2021~2022) to analyze our research model. Assessment of process macro model 7 derives the following empirical result. The results of the empirical analysis depict that NBA teams with low organizational performance in the previous season are more likely to make organizational changes through player trades to improve performance. Into the bargain player trades mediate the static relationship between the winning percentage in the previous season and the winning percentage in the current season. However, the indirect effect of a team's previous season's performance on player trades appears to vary depending on the current situations and context of each NBA team. Teams that made the playoffs in the previous season tend to make fewer trades than teams that did not and the previous season's performance is highly correlated with the current season's performance. On the other hand, teams that did not make the playoffs in the previous season tend to make a relatively larger amount of player trades in total, and the mediating effect of trades vanishes in this case. In other words, teams that did not make the playoffs in the previous season experience a larger change in performance due to trades than teams that made the playoffs, even if they achieved the same winning percentage. This empirical analysis of the inverse relationship between organizational change and the performance of professional sports teams has both theoretical and practical implications in the field of sports industry and management by analyzing the fundamentals of organizational change and the performance of professional sports teams.

• The Journal of the Acoustical Society of Korea
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• v.19 no.5
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• pp.79-83
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• 2000

When passband ripple α/sub p/ and stopband attenuation α/sub s/ at the w/sub s/ where the stopband begins are specified in filter design, △α/sub s/ usually exceeds the specification by △α/sub s/ due to the necessity that the order n of the filter function be an integer. In this paper, we apply a trade-off method to remove the excess stopband attenuation △α/sub s/ for reducing the value of pole-Q and improving the characteristics of the Chebyshev filter function. We also apply the trade-off method of pole-Q reduction to the modified Chebyshev function, and then the 4 types of function have been analyzed to compare in frequency and time domain characteristics. The trade-off method reduces the pole-Q which influences the filter characteristics to maximum 49.6% without increase of the order n. Thus implies that they have the improved characteristics such as the reduced passband ripple and flatter delay characteristics as compared Chebyshev filter function before trade-off. And the unit step response shows shorter delay time and settling time in time domain performance.

• Smart Media Journal
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• v.9 no.3
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• pp.18-24
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• 2020

Existing energy was a system produced by a specific company and sold to consumers, but it is expected that in the near future, producers will become consumers and consumers will become producers. Recently, the emergence of cloud systems, 5G network construction, and energy reuse, including solar energy, are changing the shape of the energy market. In order to share energy, there are various agent systems, energy networks, and structures that form markets. In this study, we defined the above three and proposed a strategy using the Secure Energy Model (SEM) by applying a blockchain for a safe and fair energy market. The analytical results showed that the trust between the energy producers and consumers participating in the energy trade was formed.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.9 no.4
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• pp.219-230
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• 2011

The nuclear fuel cycle (NFC) analysis is a study to set a NFC policy and to promote systematic researches by analyzing technologies and deriving requirements at each stage of a fuel cycle. System analysis techniques are utilized for comparative analysis and assessment of options on a considered system. In case that NFC is taken into consideration various methods of the system analysis techniques could be applied depending on the range of an interest. This study presented NFC analysis strategies for the development of a domestic advanced NFC and analysis techniques applicable to different phases of the analysis. Strategically, NFC analysis necessitates the linkage with technology analyses, domestic and international interests, and a national energy program. In this respect, a trade-off study is readily applicable since it includes various aspects on NFC as metrics and then analyzes the considered NFC options according to the derived metrics. In this study, the trade-off study was identified as a method for NFC analysis with the derived strategies and it was expected to be used for development of an advanced NFC. A technology readiness level (TRL) method and NFC simulation codes could be utilized to obtain the required metrics and data for assessment in the trade-off study. The methodologies would guide a direction of technology development by comparing and assessing technological, economical, environmental, and other aspects on the alternatives. Consequently, they would contribute for systematic development and deployment of an appropriate advanced NFC.

• Journal of the Korean Society of Costume
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• v.58 no.4
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• pp.139-154
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• 2008

The purpose of this study was to investigate distribution structure system in the Italian Fashion market through the buying office and trade show. The role of trade show in Italian fashion market is facilitate interactions between the producers and buyers. Milano Unica is an example of Italian fashion trade show that successfully create the right image and attract the right audience through the differentiation policy of management strategy for the show organization. The role of buying office is to offer satisfactions for their customers through giving right informations about the product that they request to buy and confidence of quality and price.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.81-87
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• 1999

This paper discusses a bicriterion approach to sequencing with time/cost trade-offs. The first problem is to minimize the total flow time and the maximum tardiness. And second is to the maximum tardiness and resource allocation costs. This approach, which produces an efficient flintier of possible schedules, has the advantage that it does not require the sequencing criteria to be measurable in the same units as the m allocation cost. The basic single machine model is used to treat a class of problems in which the sequencing objective is to minimize the maximum completion penalty. It is further assumed that resource allocation costs can be represented by linear time/cost function.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.779-781
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• 2010

Trench D-MOS(double-diffusion MOS)는 기존의 D-MOS를 대체한 것으로 전체 전류의 길이를 짧게 함으로써 온전압강하가 낮아지게 된다. 따라서 소자가 턴-온시에 전력소모가 작게 되며, 온저항과 트레이드 오프관계인 턴-오프 특성도 그다지 나빠지지 않아 트레이드 오프 특성도 개선되어지는 장점이 있다. 본 논문은 MicoroTec 시뮬레이션을 이용하여 Trench D-MOS의 산화벽을 다르게하여 전류-전압 특성을 연구하였다.

• Proceedings of the Korea Society of Design Studies Conference
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• 1999.10a
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• pp.58-59
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• 1999

성인전용 제품을 위한 광고가 아동들에게 미치는 영향에 대한 실험적 연구는 미비한 편이다. 대부분의 연구는 아동들이 어떻게 반응하는지에 대한 사례 설명이나 설문응답에 관한 것들이다. (중략)

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.1-9
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• 2024

Although federated learning is designed to be safer than centralized methods in terms of security and privacy, it still has many vulnerabilities. An attacker performing an adversarial attack intentionally manipulates the deep learning model by injecting carefully crafted input data, that is, adversarial examples, into the client's training data to induce misclassification. A common defense strategy against this is so-called adversarial training, which involves preemptively learning the characteristics of adversarial examples into the model. Existing research assumes a scenario where all clients are under adversarial attack, but considering the number of clients in federated learning is very large, this is far from reality. In this paper, we experimentally examine aspects of adversarial training in a scenario where some of the clients are under attack. Through experiments, we found that there is a trade-off relationship in which the classification accuracy for normal samples decreases as the classification accuracy for adversarial examples increases. In order to effectively utilize this trade-off relationship, we present a method to perform adversarial training by adaptively selecting a loss function depending on whether the client is attacked.