• The Journal of Industrial Distribution & Business
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• v.11 no.3
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• pp.19-28
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• 2020

Purpose: As nonprofit organizations have made strides in international development, ensuring financial resources has become pivotal to determine what nonprofits strive for and how they perform with the budget generated without efforts for profit-making. The purpose of this research aims to investigate the determinants of donation intention that are affected by television fundraising campaigns in order to improve financial sustainability. This study applied the effects of emotional sympathy, economic value, accountability, relevance, and sustainability on donation intention. Research design, data, and methodology: This study collected data via an online survey by classifying respondents based on donation experiences and applied statistical analyses such as factor analysis, regression, and ANOVA. This study selected television fundraising campaigns aligned with criteria of the Sustainable Development Goals (SDGs). Results: The results of this study showed that emotional sympathy was a dominant variable regardless of previous donation experiences, while economic value was significant for inexperienced donors. Conclusions: The results provide implications to nonprofit organizations for fundraising as to what aspects need to be addressed in order to draw donors' motivation for giving behavior. Given efforts for successful implementation of development agenda, it is fundamental to establish financial sustainability of nonprofit organizations and build up public awareness.

• Journal of Korean Society of Rural Planning
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• v.26 no.2
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• pp.51-59
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• 2020

In this study, we analyzed the characteristics of 511 agricultural districts through statistical data, and classify these districts as the vulnerable area to drought through correlation and cluster analysis. The criteria for classification was related to ground-water recharge, irrigation water demand, and water supply. As a result, 8 types of agricultural districts were extracted. For example, the type 1 indicated the high priority area for ground-water development, thus the districts which were classified as type 1 showed ground-water use was less than 80 % of maximum capacity, and irrigation water supply was only 37.5 % and 76.5 % of irrigation water demand in upland and paddy field, respectively. As a result, 44 of 511 districts were classified as type 1.36 districts (types 5-8) were areas where groundwater development is limited. The results of this study are expected to provide useful information for establishing the direction of the rural area development project in connection with the revitalization of policy of people return to rural area.

• Journal of the Korean Solar Energy Society
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• v.40 no.3
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• pp.1-20
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• 2020

In accordance with the Government's policy, renewable power generation is expanding very largely. This leads to increasing uncertainty in the power market and power system owing to the intermittent and fluctuating output characteristics of renewable power generators. Data on the acquisition of renewable power generators can be largely classified according to the operation of the power market and power system. Data on the settlement for the payment for the power amount are acquired in the power market, and real-time data for monitoring the status and output of the generators are acquired in the power system. However, renewable power generators operating in the power market have different acquisition cycles depending on the method of communication of the power meter. They acquire data only for settlement purposes and have no real-time data, which requires improvement. In this paper, the acquisition status is reviewed by classifying the data of renewable power generators into settlement and real-time data. In addition, measures and acquisition criteria for real-time data of renewable power generators for improving the acquisition method are proposed.

• Transactions of Materials Processing
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• v.31 no.4
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• pp.229-239
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• 2022

Convolution Neural Network(CNN) is a class of deep learning algorithms and can be used for image analysis. In particular, it has excellent performance in finding the pattern of images. Therefore, CNN is commonly applied for recognizing, learning and classifying images. In this study, the surface defect classification performance of Al 6061 extruded material using CNN-based algorithms were compared and evaluated. First, the data collection criteria were suggested and a total of 2,024 datasets were prepared. And they were randomly classified into 1,417 learning data and 607 evaluation data. After that, the size and quality of the training data set were improved using data augmentation techniques to increase the performance of deep learning. The CNN-based algorithms used in this study were VGGNet-16, VGGNet-19, ResNet-50 and DenseNet-121. The evaluation of the defect classification performance was made by comparing the accuracy, loss, and learning speed using verification data. The DenseNet-121 algorithm showed better performance than other algorithms with an accuracy of 99.13% and a loss value of 0.037. This was due to the structural characteristics of the DenseNet model, and the information loss was reduced by acquiring information from all previous layers for image identification in this algorithm. Based on the above results, the possibility of machine vision application of CNN-based model for the surface defect classification of Al extruded materials was also discussed.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.65-78
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• 2023

Investigations on information security factors re- main elusive at small and medium enterprises (SMEs), es- specially for custom-made software solutions. This article aims to investigate, classify, adopt factors from recent literature addressing information security resources. SMEs al- ready have information security in place, but they are not easy to adopt through the negotiation processes between the in-house software development companies and custom-made software clients at SMEs. This article proposes a strategic framework for implementing the process of adoption of the information security factors at SMEs after conducting a systematic snapshot approach for investigating and classifying the resources. The systematic snapshot was conducted using a search strategy with inclusion and exclusion criteria to retain 128 final reviewed papers from a large number of papers within the period of 2001-2022. These papers were analyzed based on a classification schema including management, organizational, development, and environmental categories in software development lifecycle (SDLC) phases in order to define new security factors. The reviewed articles addressed research gaps, trends, and common covered evidence-based decisions based on the findings of the systematic mapping. Hence, this paper boosts the broader cooperation between in-house software development companies and their clients to elicit, customize, and adopt the factors based on clients' demands.

• Journal of The Korean Association For Science Education
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• v.20 no.2
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• pp.288-296
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• 2000

In this study, the types and the characteristics of students' responses to anomalous data were investigated. The criteria for classifying students' responses were 'acceptance of validity of anomalous data', 'acceptance of inconsistency between anomalous data and initial theory', and 'change of belief in initial theory'. Seven types of responses were identified as follows: Rejection, reinterpretation, exclusion, uncertainty, peripheral theory change, partial belief change, and theory change. Absolute belief in the intial theory and doubts about methodological accuracy were found to be the major reasons for rejecting anomalous data. The students did not accept the inconsistency between anomalous data and initial theory because they ignored the experimental procedures and focused on the similarity of the experimental results.

• The Research Journal of the Costume Culture
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• v.18 no.5
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• pp.942-959
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• 2010

The Realization of Ubiquitous is achieved by magic mirror and it is required more concrete study to realize it's functionality. Especially its function of professional fashion co-ordinator for managing the appearance could be of further use. The Objective of this Study is to establish RFID chip data base to put into a computer for making use of the functionality of the magic mirror aiming at suggesting the available information on the total fashion co-ordination. I sought firstly the code with binary system determining the criteria of accessories to be input in a RFID chip. Secondly, as the image with cloth is an important element for the total fashion co-ordination, desired co-ordination among the emphasis, harmony, character, season and accent can be made selectable classifying into a limit element and a common element to extract the codes. Thirdly, necessary conditions were given to the generated codes using Visual C++ program of Microsoft and the extracted codes as per groups were compared and analyzed.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.61-69
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• 2014

Various Time Synchronization protocols considering for the characteristics of WSN(Wireless Sensor Network) have been developed, because a time relationship plays an important role in many WSN applications, as well. Synchronization accuracy as well as constraints of energy should be considered for WSN Time Synchronization protocols, especially. In this paper, I analyze Time Synchronization protocols for WSN after classifying these protocols with a new criteria (i.e. power consumption). So, this method will contribute to evaluating and comparing WSN Time Synchronization protocols in respect of power consumption.

• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.128-135
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• 2018

Currently, the government selects products that are likely to cause harm to consumers as safety management targets and classifies them into three types: safety certification, safety confirmation, and supplier conformity verification. In addition, the government conducts safety surveys on products in circulation or accident products, and recalls products that are of great concern to consumer risks. In this paper, we have developed RAP (Risk Assessment method based on Probability), which is a probability based product risk assessment method, for the classification of safety management type of product and safety investigation, and have shown an application example. In this process, information is used for the CISS (Consumer Injury Surveillance System) of the Korean Consumer Agency. In addition, we apply the cluster analysis to classify the current supervised children products into three groups. Then, we confirm the effectiveness of RAP by comparing the result of RAP application, cluster analysis result and current safety management classification type. Also, we recognize the need to review the current safety management classification criteria for classifying products into three types.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.17 no.4
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• pp.1-14
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• 2021

Recently, various renewable systems have been developed and applied in Korea. However, there are many systems which were not utilized in real buildings or not widely spread in the market. Furthermore, the attention of most users focused on several certain system such as PV or solar system. Therefore, this research aims to find user's needs for renewable energy based on perception surveys to improve the acceptance of technology in line with the world's energy flow. The survey was conducted by classifying respondents by various criteria, and the results were analyzed using AHP technique and CVM technique, focusing on preference and acceptance. According to the results of the survey, it was found that the people felt the need for renewable energy but lacked knowledge about renewable energy compared to the various government-implemented renewable energy supply policies. Therefore, a government-level policy is needed so that the people can have universal knowledge about renewable energy system.