• International journal of advanced smart convergence
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• v.12 no.1
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• pp.140-148
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• 2023

With the OTT media market growing rapidly, the significance of trustworthy data verification and certification cannot be emphasized enough. This study delves into the crucial need for such measures in South Korea, exploring the steps involved, the technological and policy-related considerations, and the challenges that may arise once these measures are put into place. Drawing on in-depth interviews and the analytical hierarchy process (AHP), this study surveyed various stakeholder groups, both directly and indirectly related to OTT data authentication and certification. By assessing the severity of OTT data-related issues and identifying the requirements for reliability-improvement policies, participants shared their valuable insights and opinions on this pressing matter. The survey results clearly indicate a divided opinion among stakeholders and industry experts on the reliability of OTT data, with some expressing trust while others remain skeptical. However, there was a consensus that advertising-based AVOD is more reliable than SVOD. By analyzing the priorities of authentication and verification, this study paves the way for the establishment and operation of a Korean MRC (KMRC), centered on the OTT media industry. The KMRC will serve as a vital platform for ensuring the authenticity and accuracy of OTT data in South Korea, providing businesses and industry players with a reliable source of information for informed decision-making. This study highlights the pressing need for reliable data authentication and certification in the rapidly growing OTT media market, and provides a persuasive case for the establishment of a KMRC in South Korea to meet this critical need.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.419-429
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• 2023

The objective of this study was to determine the management water level of an estuary reservoir considering three aspects: the water use, flood control and water quality, and to use a robust decision-making to consider uncertainty due to climate change. The watershed-reservoir linkage model was used to simulate changes in inflow due to climate change, and changes in reservoir water level and water quality. Five management level alternatives ranging from -1.7 El.m to 0.2 El.m were evaluated under the SSP1, 2, 3, and 5 scenariosof the ACCESS-CM2 Global Climate Model. Performance indicators based on period-reliability were calculated for robust decision-making considering the three aspects, and regret was used as a decision indicator to identify the alternatives with the minimum maximum regret. Flood control failure increased as the management level increased, while the probability of water use failure increased as the management level decreased. The highest number of failures occurred under the SSP5 scenario. In the water quality sector, the change in water quality was relatively small with an increase in the management level due to the increase in reservoir volume. Conversely, a decrease in the management level resulted in a more significant change in water quality. In the study area, the estuary reservoir was found to be problematic when the change in water quality was small, resulting in more failures.

• Physical Therapy Korea
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• v.18 no.4
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• pp.60-67
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• 2011

Ultrasonography (US) is a recent technique that has proven to be useful for assessing muscle thickness and guiding the rehabilitation decision-making of clinicians and researchers. The purpose of this study was to determine the inter-rater reliability of the US measurement of transversus abdominis (TrA), internal oblique (IO), and external oblique (EO) thicknesses for different probe locations and measurement techniques. Twenty healthy volunteers were recruited in this study. Muscle thicknesses of the transversus TrA, IO, and EO were measured three times in the hook-lying position. The three different probe locations were as follows: 1) Probe location 1 (PL1) was below the rib cage in direct vertical alignment with the anterior superior iliac spine (ASIS). 2) Probe location 2 (PL2) was halfway between the ASIS and the ribcage along the mid-axillary line. 3) Probe location 3 (PL3) was halfway between the iliac crest and the inferior angle of the rib cage, with adjustment to ensure the medial edge of the TrA. The two different techniques of thickness measurement from the captured images were as follows: 1) Muscle thickness was measured in the middle of the muscle belly, which was centered within the captured image (technique A; TA). 2) Muscle thickness was measured along a horizontal reference line located 2 cm apart from the medial edge of the TrA in the captured image (technique B; TB). The intraclass correlation coefficient (ICC [3,k]) was used to calculate the inter-rater reliability of the thickness measurement of TrA, IO and EO using the values from both the first and second examiner. In all three muscles, moderate to excellent reliability was found for all conditions (probe locations and measurement techniques) (ICC=.70~.97). In the PL1-TA condition, inter-rater reliability in the three muscle thicknesses was good to excellent (ICC=.85~.96). The reliability of all measurement conditions was excellent in IO (ICC=.95~.97). Therefore, the findings of this study suggest that TA can be applied to PL1 by clinicians and researchers in order to measure the thickness of abdominal muscles.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.11-16
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• 2022

As an interest in the development of artificial intelligence(AI) technology in the water supply sector increases, we have developed an AI algorithm that can predict improvement decision-making ratings through repetitive learning using the data of pipe condition evaluation results, and present the most reliable prediction model through a verification process. We have developed the algorithm that can predict pipe ratings by pre-processing 12 indirect evaluation items based on the 2020 Han River Basin's basic plan and applying the AI algorithm to update weighting factors through backpropagation. This method ensured that the concordance rate between the direct evaluation result value and the calculated result value through repetitive learning and verification was more than 90%. As a result of the algorithm accuracy verification process, it was confirmed that all water pipe type data were evenly distributed, and the more learning data, the higher prediction accuracy. If data from all across the country is collected, the reliability of the prediction technique for pipe ratings using AI algorithm will be improved, and therefore, it is expected that the AI algorithm will play a role in supporting decision-making in the objective evaluation of the condition of aging pipes.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.597-601
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• 2009

The purpose of this study is to closely examine the effect of exercise behavior change of casino securities on their physical self-description. This observation takes place in casino enterprises in Seoul, Busan, Kangwon and Jeju. Within these areas, we have selected companies with more than 30 securities. Among 450 persons sampling unit, we have excluded 77 copied which seem to be insincere, and actually used 373 copies in this study. Evaluation forms are used as a study method; each form consists of continuance 5 points Likert scales and nominal/proportional scaling and used after excluding a test through the analysis of validity and reliability. After encoding and inputting the framing completed data along with each purpose, it was computerized by computer process, making use of SPSS 15.0 version. Through the data analysis according to these methods and procedures, the result on this study is described below. First, the exercise behavior according to socio-demographic characteristics. Second, the decision-making balance according to socio-demographic characteristics. Third, the self-efficacy according to socio-demographic characteristics. Fourth, the physical self-concept according to socio-demographic characteristics. Fifth, the exercise behavior influence indirectly on the physical self-concept throughout the decision-making balance and self-efficacy.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.603-612
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• 2006

Recently the web service area is rapidly growing as the next generation IT paradigm because of increase of concern about SOA(Services-Oriented Architecture) and growth of B2B market. Since a service discovery through UDDI(Universal Description, Discovery and Integration) is limited to a functional requirement, it is not considered an effect on frequency of service using and reliability of mutual relation. That is, a quality as nonfunctional aspect of web service is regarded as important factor for a success between consumer and provider. Therefore, the web service selection method with considering the quality is necessary. This paper suggests the agent-based quality broker architecture and selection process which helps to find a service providing the optimum quality that the consumer needs in a position of service consumer. A theory of agent is accepted widely and suitable for proposed system architecture in the circumstance of distributed and heterogeneous environment like web service. In this paper, we considered the QoS and CoS in the evaluation process to solve the problem of existing researches related to the web service selection and used PROMETHEE(Preference Ranking Organization MeTHod for Enrichment Evaluations) as an evaluation method which is most suitable for the web service selection among MCDM approaches. PROMETHEE has advantages that solve the problem that a pair-wise comparison should be performed again when comparative services are added or deleted. This paper suggested a case study with the service composition scenario in order to verify the selection process. In this case study, the decision making problem was described on the basis of evaluated values for qualities from a consumer's point of view and the defined service level.

• The Journal of Industrial Distribution & Business
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• v.10 no.5
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• pp.77-86
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• 2019

Purpose - The present study examined the reliability of accounting information based on the pay slice (CPS) information of chief executive officers (CEOs) in the service industry. The difference in the size of CPS under the capitalist system can be used as an index to gauge the influence of top management. Research design, data, and methodology - In accordance with the amendment of the Financial Investment Services and Capital Market Act in 2013, the pay information of individual registered executives with annual salary of more than 500 million won has been disclosed. The sample of the current study is 232 companies listed on the Korea Exchange excluding financial services from 2013 to 2015, when the individual pay-slice information for registration officers was published in the business report in accordance with the revision of the Capital Market Act. The financial data required for this study were extracted from the FnGuide and the TS-2000. With the data, we tested the relationship between CPS and accounting information reliability through a linear regression analysis. Results - The first result showed that the relationship between the CPS and human resource in internal accounting control system in the service industry is significantly negative only with the accounting department personnel. This result implied that the CEO can negatively affect the retention of the accounting department in the firm. Second, both the CPS and quality of audit in the service industry are negatively related both to audit fees and to audit time. Nonetheless, the relationship between the number of the auditor and the CPS is insignificant. This result indicated that the CEO can negatively affect audit fees and audit time of external auditors. The results of the present study suggested that CPS information may have a negative impact on the reliability of accounting information. Conclusion - This study is the first study to examine the reliability of CPS and accounting information for the service industry in terms of human resources in internal accounting control system and audit quality. Therefore, the present study is expected to provide some useful information to economic decision-making of various external parties for service firms.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.163-179
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• 2010

Recentlythe concept of fast fashion is drawing attention as customer needs are diversified and supply lead time is getting shorter in fashion industry. It is emphasized as one of the critical success factors in the fashion industry how quickly and efficiently to satisfy the customer needs as the competition has intensified. Because the fast fashion is inherently susceptible to trend, it is very important for fashion retailers to make quick decisions regarding items to launch, quantity based on demand prediction, and the time to respond. Also the planning decisions must be executed through the business processes of procurement, production, and logistics in real time. In order to adapt to this trend, the fashion industry urgently needs supports from intelligent quick response(QR) system. However, the traditional functions of QR systems have not been able to completely satisfy such demands of the fast fashion industry. This paper proposes an intelligent quick response system for the fast fashion(IQRS-FF). Presented are models for QR process, QR principles and execution, and QR quantity and timing computation. IQRS-FF models support the decision makers by providing useful information with automated and rule-based algorithms. If the predefined conditions of a rule are satisfied, the actions defined in the rule are automatically taken or informed to the decision makers. In IQRS-FF, QRdecisions are made in two stages: pre-season and in-season. In pre-season, firstly master demand prediction is performed based on the macro level analysis such as local and global economy, fashion trends and competitors. The prediction proceeds to the master production and procurement planning. Checking availability and delivery of materials for production, decision makers must make reservations or request procurements. For the outsourcing materials, they must check the availability and capacity of partners. By the master plans, the performance of the QR during the in-season is greatly enhanced and the decision to select the QR items is made fully considering the availability of materials in warehouse as well as partners' capacity. During in-season, the decision makers must find the right time to QR as the actual sales occur in stores. Then they are to decide items to QRbased not only on the qualitative criteria such as opinions from sales persons but also on the quantitative criteria such as sales volume, the recent sales trend, inventory level, the remaining period, the forecast for the remaining period, and competitors' performance. To calculate QR quantity in IQRS-FF, two calculation methods are designed: QR Index based calculation and attribute similarity based calculation using demographic cluster. In the early period of a new season, the attribute similarity based QR amount calculation is better used because there are not enough historical sales data. By analyzing sales trends of the categories or items that have similar attributes, QR quantity can be computed. On the other hand, in case of having enough information to analyze the sales trends or forecasting, the QR Index based calculation method can be used. Having defined the models for decision making for QR, we design KPIs(Key Performance Indicators) to test the reliability of the models in critical decision makings: the difference of sales volumebetween QR items and non-QR items; the accuracy rate of QR the lead-time spent on QR decision-making. To verify the effectiveness and practicality of the proposed models, a case study has been performed for a representative fashion company which recently developed and launched the IQRS-FF. The case study shows that the average sales rateof QR items increased by 15%, the differences in sales rate between QR items and non-QR items increased by 10%, the QR accuracy was 70%, the lead time for QR dramatically decreased from 120 hours to 8 hours.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.1921-1929
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• 2015

The smart substation is the heart of a transmission system, which is particularly emphasized as the most significant composition of smart grids in China. In order to assess the functionality performance of substation technologies, this paper presents methods used to identify the most promising solutions for smart substation design and to evaluate the technical levels of available technologies. The multi-index optimization model is presented to address the issue of smart substation planning. A mathematical model of the planning decision problem is established with multiple objectives consisting of economic, reliability, and green key indices, and many kinds of concerns including physical and environmentally friendly operations are formulated as a set of constraints. With respect to the assessment of the technical level regarding integration of advanced technologies into a substation, a modified grey whitenization weight function is adopted to structure a novel grey clustering method. The proposed grey clustering approach is used to overcome the difficulty of insufficient quantitative assessment capacity for traditional methods. The evaluation of technical effects provides the classification definition for the development phase and the maturity level of the smart substation. The effectiveness of the proposed approaches in planning decision-making and evaluation of construction efforts is demonstrated with case studies involving the actual smart substation projects of Wenchongkou substation in China Southern Power Grid (CSG) and Mengzi substation in State Grid Corporation of China (SGCC).

• Journal of Power Electronics
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• v.18 no.3
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• pp.841-852
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• 2018

This paper presents a dual-algorithm search method (GWO-GSO) combining grey wolf optimization (GWO) and golden-section optimization (GSO) to realize maximum power point tracking (MPPT) for photovoltaic (PV) systems. First, a modified grey wolf optimization (MGWO) is activated for the global search. In conventional GWO, wolf leaders possess the same impact on decision-making. In this paper, the decision weights of wolf leaders are automatically adjusted with hunting progression, which is conducive to accelerating hunting. At the later stage, the algorithm is switched to GSO for the local search, which play a critical role in avoiding unnecessary search and reducing the tracking time. Additionally, a novel restart judgment based on the quasi-slope of the power-voltage curve is introduced to enhance the reliability of MPPT systems. Simulation and experiment results demonstrate that the proposed algorithm can track the global maximum power point (MPP) swiftly and reliably with higher accuracy under various conditions.