• Title/Summary/Keyword: validation of a scale

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Very short-term rainfall prediction based on radar image learning using deep neural network (심층신경망을 이용한 레이더 영상 학습 기반 초단시간 강우예측)

  • Yoon, Seongsim;Park, Heeseong;Shin, Hongjoon
    • Journal of Korea Water Resources Association
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    • v.53 no.12
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    • pp.1159-1172
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    • 2020
  • This study applied deep convolution neural network based on U-Net and SegNet using long period weather radar data to very short-term rainfall prediction. And the results were compared and evaluated with the translation model. For training and validation of deep neural network, Mt. Gwanak and Mt. Gwangdeoksan radar data were collected from 2010 to 2016 and converted to a gray-scale image file in an HDF5 format with a 1km spatial resolution. The deep neural network model was trained to predict precipitation after 10 minutes by using the four consecutive radar image data, and the recursive method of repeating forecasts was applied to carry out lead time 60 minutes with the pretrained deep neural network model. To evaluate the performance of deep neural network prediction model, 24 rain cases in 2017 were forecast for rainfall up to 60 minutes in advance. As a result of evaluating the predicted performance by calculating the mean absolute error (MAE) and critical success index (CSI) at the threshold of 0.1, 1, and 5 mm/hr, the deep neural network model showed better performance in the case of rainfall threshold of 0.1, 1 mm/hr in terms of MAE, and showed better performance than the translation model for lead time 50 minutes in terms of CSI. In particular, although the deep neural network prediction model performed generally better than the translation model for weak rainfall of 5 mm/hr or less, the deep neural network prediction model had limitations in predicting distinct precipitation characteristics of high intensity as a result of the evaluation of threshold of 5 mm/hr. The longer lead time, the spatial smoothness increase with lead time thereby reducing the accuracy of rainfall prediction The translation model turned out to be superior in predicting the exceedance of higher intensity thresholds (> 5 mm/hr) because it preserves distinct precipitation characteristics, but the rainfall position tends to shift incorrectly. This study are expected to be helpful for the improvement of radar rainfall prediction model using deep neural networks in the future. In addition, the massive weather radar data established in this study will be provided through open repositories for future use in subsequent studies.

The Validation Study of Beck Depression Scale 2 in Korean Version (한국판 벡 우울 척도 2판의 타당화 연구)

  • Lim, Sun-Young;Lee, Eun-Jeong;Jeong, Seong-Won;Kim, Hee-Chul;Jeong, Cheol-Ho;Jeon, Tae-Yeon;Yi, Min-Soo;Kim, Jae-Min;Jo, Hyeon-Ju;Kim, Jeong-Beom
    • Anxiety and mood
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    • v.7 no.1
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    • pp.48-53
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    • 2011
  • Objective : Korean Version of Beck-II Depression Inventory to verify the reliability and validity of the proposed standards are practical and standardized, cut-off score by establishing a baseline indicating the presence of depression and depression On in the evaluation was to evaluate the clinical usefulness. Methods : 739 patients with major depression using the SCID and normal controls were 302 study subjects. Of patients with clinically significant medical condition, or psychotic disorders, organic mental disorder, epilepsy or seizure disorder, eating disorders are associated with patients taking anti-convulsants experienced in the past, patients were excluded from the study. Results : The main findings of this study were as follows. First, with respect to the KBDI-II items, the correlation between them ranged from 0.51 to 0.74, and was 0.60 over all questions. Further, the overall correlation of the KBDI-II plates showing confidence 'normal' than it was verified that. Second, the BDIII was used in each group to examine internal consistency and thus, whether Cronbach's alpha values were greater than 0.94. Third, the principal component analysis sought to extract factors in a way consistent with the results inspected last 3 factors were extracted and the total variance explained was 47.3%. Fourth, the Cutting calculated the score on the KBDI-II for ROC (Receiver operator characteristic) analysis yielding 18 dot, with the highest sensitivity and specificity was seen. Conclusion : Based on the results of this Study, the KBDI-II cut-off point should be valid as prescribed in 18 is considered.

The Effects of Environmental Dynamism on Supply Chain Commitment in the High-tech Industry: The Roles of Flexibility and Dependence (첨단산업의 환경동태성이 공급체인의 결속에 미치는 영향: 유연성과 의존성의 역할)

  • Kim, Sang-Deok;Ji, Seong-Goo
    • Journal of Global Scholars of Marketing Science
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    • v.17 no.2
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    • pp.31-54
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    • 2007
  • The exchange between buyers and sellers in the industrial market is changing from short-term to long-term relationships. Long-term relationships are governed mainly by formal contracts or informal agreements, but many scholars are now asserting that controlling relationship by using formal contracts under environmental dynamism is inappropriate. In this case, partners will depend on each other's flexibility or interdependence. The former, flexibility, provides a general frame of reference, order, and standards against which to guide and assess appropriate behavior in dynamic and ambiguous situations, thus motivating the value-oriented performance goals shared between partners. It is based on social sacrifices, which can potentially minimize any opportunistic behaviors. The later, interdependence, means that each firm possesses a high level of dependence in an dynamic channel relationship. When interdependence is high in magnitude and symmetric, each firm enjoys a high level of power and the bonds between the firms should be reasonably strong. Strong shared power is likely to promote commitment because of the common interests, attention, and support found in such channel relationships. This study deals with environmental dynamism in high-tech industry. Firms in the high-tech industry regard it as a key success factor to successfully cope with environmental changes. However, due to the lack of studies dealing with environmental dynamism and supply chain commitment in the high-tech industry, it is very difficult to find effective strategies to cope with them. This paper presents the results of an empirical study on the relationship between environmental dynamism and supply chain commitment in the high-tech industry. We examined the effects of consumer, competitor, and technological dynamism on supply chain commitment. Additionally, we examined the moderating effects of flexibility and dependence of supply chains. This study was confined to the type of high-tech industry which has the characteristics of rapid technology change and short product lifecycle. Flexibility among the firms of this industry, having the characteristic of hard and fast growth, is more important here than among any other industry. Thus, a variety of environmental dynamism can affect a supply chain relationship. The industries targeted industries were electronic parts, metal product, computer, electric machine, automobile, and medical precision manufacturing industries. Data was collected as follows. During the survey, the researchers managed to obtain the list of parts suppliers of 2 companies, N and L, with an international competitiveness in the mobile phone manufacturing industry; and of the suppliers in a business relationship with S company, a semiconductor manufacturing company. They were asked to respond to the survey via telephone and e-mail. During the two month period of February-April 2006, we were able to collect data from 44 companies. The respondents were restricted to direct dealing authorities and subcontractor company (the supplier) staff with at least three months of dealing experience with a manufacture (an industrial material buyer). The measurement validation procedures included scale reliability; discriminant and convergent validity were used to validate measures. Also, the reliability measurements traditionally employed, such as the Cronbach's alpha, were used. All the reliabilities were greater than.70. A series of exploratory factor analyses was conducted. We conducted confirmatory factor analyses to assess the validity of our measurements. A series of chi-square difference tests were conducted so that the discriminant validity could be ensured. For each pair, we estimated two models-an unconstrained model and a constrained model-and compared the two model fits. All these tests supported discriminant validity. Also, all items loaded significantly on their respective constructs, providing support for convergent validity. We then examined composite reliability and average variance extracted (AVE). The composite reliability of each construct was greater than.70. The AVE of each construct was greater than.50. According to the multiple regression analysis, customer dynamism had a negative effect and competitor dynamism had a positive effect on a supplier's commitment. In addition, flexibility and dependence had significant moderating effects on customer and competitor dynamism. On the other hand, all hypotheses about technological dynamism had no significant effects on commitment. In other words, technological dynamism had no direct effect on supplier's commitment and was not moderated by the flexibility and dependence of the supply chain. This study makes its contribution in the point of view that this is a rare study on environmental dynamism and supply chain commitment in the field of high-tech industry. Especially, this study verified the effects of three sectors of environmental dynamism on supplier's commitment. Also, it empirically tested how the effects were moderated by flexibility and dependence. The results showed that flexibility and interdependence had a role to strengthen supplier's commitment under environmental dynamism in high-tech industry. Thus relationship managers in high-tech industry should make supply chain relationship flexible and interdependent. The limitations of the study are as follows; First, about the research setting, the study was conducted with high-tech industry, in which the direction of the change in the power balance of supply chain dyads is usually determined by manufacturers. So we have a difficulty with generalization. We need to control the power structure between partners in a future study. Secondly, about flexibility, we treated it throughout the paper as positive, but it can also be negative, i.e. violating an agreement or moving, but in the wrong direction, etc. Therefore we need to investigate the multi-dimensionality of flexibility in future research.

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