• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.2
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• pp.95-104
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• 2019

This study is aimed to take a stock assessment of blackthroat seaperch Doederleinia seaperch regarding the fishing effort of large-powered Danish Seine Fishery and Southwest Sea Danish Seine Fishery. For the assessment, the state-space model was implemented and the standardized catch per unit effort (CPUE) of large powered Danish Seine Fishery and Southwest Sea Danish Seine Fishery which is necessary for the model was estimated with generalized linear model (GLM). The model was adequate for stock assessment because its r-square value was 0.99 and root mean square error (RMSE) value was 0.003. According to the model with 95% confidence interval, maximum sustainable yield (MSY) of Blackthroat seaperch is from 2,634 to 6,765 ton and carrying capacity (K) is between 33,180 and 62,820. Also, the catchability coefficient (q) is between 2.14E-06 and 3.95E-06 and intrinsic growth rate (r) is between 0.31 and 0.72.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.2
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• pp.183-188
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• 2022

It is a difficult task to estimate parameters in even a simple stock assessment model such as a surplus production model, using only data about temporal catch-per-unit-effort (CPUE) (or survey index) and fishery yields. Such difficulty is exacerbated when time-varying parameters are treated as random effects (aka state variables). To overcome the difficulty, previous studies incorporated somewhat subjective assumptions (e.g., B₁=K) or informative priors of parameters. A key is how to build an objective joint prior of parameters, reducing subjectivity. Given the limited data on temporal CPUEs and fishery yields from 1999-2020 for common squid Todarodes pacificus, we built a joint prior of only two parameters, intrinsic growth rate (r) and carrying capacity (K), based on the resilience level of the population (Froese et al., 2017), and used a Bayesian state-space production assessment model. We used template model builder (TMB), a R package for implementing the assessment model, and estimating all parameters in the model. The predicted annual biomass was in the range of 0.76×10⁶ to 4.06×10⁶ MT, the estimated MSY was 0.13×10⁶ MT, the estimated r was 0.24, and the estimated K was 2.10×10⁶ MT.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2017-2025
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• 2021

Objective: To evaluate the accuracy and clinical efficacy of a hybrid Greulich-Pyle (GP) and modified Tanner-Whitehouse (TW) artificial intelligence (AI) model for bone age assessment. Materials and Methods: A deep learning-based model was trained on an open dataset of multiple ethnicities. A total of 102 hand radiographs (51 male and 51 female; mean age ± standard deviation = 10.95 ± 2.37 years) from a single institution were selected for external validation. Three human experts performed bone age assessments based on the GP atlas to develop a reference standard. Two study radiologists performed bone age assessments with and without AI model assistance in two separate sessions, for which the reading time was recorded. The performance of the AI software was assessed by comparing the mean absolute difference between the AI-calculated bone age and the reference standard. The reading time was compared between reading with and without AI using a paired t test. Furthermore, the reliability between the two study radiologists' bone age assessments was assessed using intraclass correlation coefficients (ICCs), and the results were compared between reading with and without AI. Results: The bone ages assessed by the experts and the AI model were not significantly different (11.39 ± 2.74 years and 11.35 ± 2.76 years, respectively, p = 0.31). The mean absolute difference was 0.39 years (95% confidence interval, 0.33-0.45 years) between the automated AI assessment and the reference standard. The mean reading time of the two study radiologists was reduced from 54.29 to 35.37 seconds with AI model assistance (p < 0.001). The ICC of the two study radiologists slightly increased with AI model assistance (from 0.945 to 0.990). Conclusion: The proposed AI model was accurate for assessing bone age. Furthermore, this model appeared to enhance the clinical efficacy by reducing the reading time and improving the inter-observer reliability.

• Journal of the Korean Society of Earth Science Education
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• v.1 no.1
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• pp.1-13
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• 2008

The purpose of this research is to accomplish the goal of science education based in the seventh science course of study by suggesting the plan for development of executable method in the learning process of Earth Science education and establishing a practical model to evaluate its achievement. Furthermore, the idea of this research is to recognize a way of using and consideration at practical use of the model. Since the purpose of the educational evaluation is to maximize the efficiency of school studying, there are some negative aspects in our current method of evaluation to achieve the purpose. New system has been introduced into the educational evaluation to resolve such a critical issue. Despite some positive aspects in the system, it could not be escaped from the multiple choice and pens examination. This could be caused by in various limitations, especially the insufficiency of teachers' awareness and the data about the Performance assessment. This research is to develop and use the practical model for the Performance assessment in consideration of current educational circumstances of Junior and High school. The model of the Performance assessment in this research is to sufficiently evaluate student's ability and skill in the learning process of Earth Science education. Hence, it is dedicated to the education for human being and improve quality in the learning process of the Earth Science education among the modern society, which is characterized globalization and information. Furthermore, it may promote the growth of various character of students and increase creativity and skill for the problem solving.

• Korean Journal of Comparative Education
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• v.28 no.5
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• pp.1-19
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• 2018

The purpose of educational assessments such as the Trends in International Mathematics and Science Study (TIMSS) is to compare groups such as countries. When the unit of measurement is above the student level, group-level diagnostic assessment based on multilevel item response theory (ML-IRT) can be considered just as cognitive diagnosis models are developed from item response theory. This study suggests an ML-IRT-based group-level diagnostic assessment model by modifying an item feature model by Park and bolt (2008). The model is illustrated on the recently released TIMSS 2015 Grade 8 mathematics assessment. The results provide skill profiles for the studied countries and the nine cognitive attributes; that is, the attribute effects can be compared across the countries and also across the attributes. By controlling unexplained variance, the suggested model may provide more reliable and more informative group-level comparisons. The results are interpreted using an example. Limitations and directions for future research are also discussed.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.621-635
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• 2023

The assessment of structural condition is a crucial process for evaluating its usability and determining the diagnostic cycle. The currently employed manpower-based methods suffer from issues related to safety, efficiency, and objectivity. To address these concerns, research based on deep learning using images is being conducted. However, acquiring structural damage data is challenging, making it difficult to construct a substantial amount of training data, thus limiting the effectiveness of deep learning-based condition assessment. In this study, we propose a foundation model-based 2-step structural damage analysis to overcome the lack of training data in image-based structural condition assessments. We subdivided the elements of structural condition assessment into instantiation and quantification. In the quantification step, we applied a foundation model for image segmentation. Our method demonstrated a 10%-point increase in mean intersection over union compared to conventional image segmentation techniques, with a notable 40%-point improvement in the case of rebar exposure. We anticipate that our proposed approach will enhance performance in domains where acquiring training data is challenging.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.643-645
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• 2015

This study is designating the scope, in order to establish the information management system of performance assessment for remodeling buildings, to analyze the current status of performance assessment, and to identify technologies and concepts applicable to performance assessment model.

• Journal of Environmental Impact Assessment
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• v.24 no.1
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• pp.35-50
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• 2015

The purposes of this study are to apply species distribution modeling in urban management planning for habitat conservation in non-urban area and to provide a detailed classification method for management zone. To achieve these objectives, Species Distribution Model was used to generate species richness and then to compare with the results from land suitability assessment. 59 species distribution models were developed by Maxent. This study used 15 model variables (5 topographical variables, 4 vegetation variables, and 6 distance variables) for Maxent models. Then species richness was created by sum of predicted species distributions. Land suitability assessment was conducted with criteria from type I of "Guidelines for land suitability assessment". After acquiring evaluation values from species richness and land suitability assessment, the results from these two models were compared according to the five grades of classification. The areas with the identical grade in Species richness and land suitability assessment are categorized and then compared each other. The comparison results are Grade1 10.92%, Grade2 37.10%, Grade3 34.56%, Grade4 20.89% and Grade5 1.73%. Grade1 and Grade5 showed the lowest agreement rate. Namely, development or conservation grade showed high disagreement between two assessment system. Therefore, the areas located between urban, agriculture, forest, and reserve have a tendency to change easily by development plans. Even though management areas are not the core area of reserve, it is important to provide a venue for species habitat and eco-corridor to protect and improve biodiversity in terms of landscape ecology. Consequently, adoption of species richness in three levels of management area classification such as conservation, production, planning should be considered in urban management plan.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.117-129
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• 2022

The ability to creatively pursue new knowledge and perspectives across various disciplines has established itself as a basic literacy for living in the 21st-century convergence era. With the development of various creative education programs, assessment tools that can objectively and systematically evaluate learners' academic achievement are also required. Therefore, this paper proposed the self assessment, peer assessment, creativity assessment, and reflection tool based on the hyper blended practical model as assessment tools for creative convergence education programs for elementary and secondary school students. The developed assessment tools attempted to develop more completed evaluation methods by modifying two items and deleting four items through validity tests. In addition, the evaluation tool was applied to 596 elementary and secondary school students nationwide, and the application results were analyzed through one-way ANOVA and Wordcloud system. As a result of the analysis, it was found that the self assessment and the reflection tool need to develop questions according to the grade group. In addition, we proposed to use these assessment tools in blended classes or various educational activities in the changing classroom environment. We hope that this paper provides implications for developing evaluation systems and tools for creative convergence education.

• Journal of Korean Library and Information Science Society
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• v.39 no.4
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• pp.305-329
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• 2008

This study is to develop quality assessment module to apply database system quality assessment thus, recognizing necessity of database system quality improvement maturity model. To manage and improve of database system quality, assessment module is needed to assess database system quality systematically. This study is to perform for the purpose of follows. First, this study is to select quality characteristics and sub characteristics on based on ISO/IEC 9126 series and to develop assessment module for database system quality assessment. Second, this study is to compare and to analysis about quality assessment characteristics of two groups. This study is to have significance to apply quantitative assessment in theoretical and practical basis and is to applicate basic materials of study in database system quality assessment. Also, in succeeding study, it will be to develop of database system quality improvement maturity model.