• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.398-403
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• 2023

Process-based K-cabbage model is based on physiological processes such as photosynthesis and phenology, making it possible to predict crop growth under different climate conditions that have never been experienced before. Current first-stage process-based models can be used to assess climate impact through yield prediction based on climate change scenarios, but no comparison has been performed between big data obtained from the main production area and model prediction so far. The aim of this study was to find out the direction of model improvement when using the current model for yield prediction. For this purpose, model performance evaluation was conducted based on data collected from farmers growing 'Chungwang' cabbage in Taebaek and Samcheok, the main producing areas of Chinese cabbage in highland region. The farms surveyed in this study had different cultivation methods in terms of planting date and soil water and nutrient management. The results showed that the potential biomass estimated using the K-cabbage model exceeded the observed values in all cases. Although predictions and observations at the time of harvest did not show a complete positive correlation due to limitations caused by the use of fresh weight in the model evaluation process (R²=0.74, RMSE=866.4), when fitting the model based on the values 2 weeks before harvest, the growth suitability index was different for each farm. These results are suggested to be due to differences in soil properties and management practices between farms. Therefore, to predict attainable yields taking into account differences in soil and management practices between farms, it is necessary to integrate dynamic soil nutrient and moisture modules into crop models, rather than using arbitrary growth suitability indices in current K-cabbage model.

• Journal of the Korean Institute of Landscape Architecture
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• v.34 no.4 s.117
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• pp.69-83
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• 2006

Nature rehabilitation has become a major theme in river management in South Korea. An analysis and evaluation of the landscape is a crucial step to select the suitable tracts for developing or conserving land use in the process of landscape planning. The purpose of this paper is to establish a hierarchical procedure for the setting of the landscape units on the various scales at which field biologists performed their observations and to select the preserves through by a suitability model for synthesizing the ecological empirical, and biophysical data. An evaluation process needs to be performed according to the landscape scales: site, local, and regional scales, at which the environmental data were collected, analyzed, and synthesized. Introducing of three level scales was crucially necessary for evaluating the various multi level ecological data for zoning of preserves in river corridors. The evaluation level at different scales are hierarchically established into three phases. The first evaluation phase can be performed by the long length units defined by the ranges of stream widths at regional scale. Secondly, each of these long units can be divided into two or more segments according to its landscape homogeneity at local level. Finally the segments at the last phase can be designated according to the location of the reservoir weirs and bridges at site level. The conceptual model components are adopted for collecting, evaluating, and interpreting the biological and abiotic data at site level. Three preserves are selected, having high potentials for being intensely managed as the Ecological Education Areas in the river. Despite a lot of assumption the results are expected to facilitate discussion and decision making about which frameworks of evaluation are desirable and adaptable for integrating the ecological data into the rehabilitation design process in South Korea.

• Journal of Digital Convergence
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• v.13 no.7
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• pp.183-196
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• 2015

In order to perform a successful outsourcing, we needs the SLA through improving the quality of IT services. In particular SLA metrics and evaluation criteria is an important factor as to substitute the IT viability of the company to promote IT Outsourcing. SLA metrics consist of technical, managerial, user perspective items, and has been managed to aim to provide reliable and continuous quality improvement of IT services. This study focuses on the HW availability metrics of SLA indicators of IT outsourcing. We propose the Infra availability criteria for the HW configuration level to meet the SLA contract and evaluation. We offer the Infra configuration standards of SLA contract, and propose criteria to determine the suitability of the target levels in IT operations audit environment. The proposed model was verified the necessity and effectiveness of the Infra configuration standards and operation audit check items through the surveys of experts and users.

• Journal of The Korean Association of Information Education
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• v.14 no.2
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• pp.189-197
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• 2010

This paper proposes elementary robot programming problems using the algorithmic thinking-based problem model with material factors in the elementary robot programming. And this paper proves the validity of developed robot programming problems in defining them as algorithmic thinking-based problems through experiments. The experimental results are analyzed in views of variety and effectiveness evaluation of answer algorithms and suitability of allocating degrees of difficulties to the developed robot programming problems. As a result of the experiment, we find that the developed problems has various answer algorithms and suitable degrees of difficulties for elementary school students.

• Journal of the Korean Solar Energy Society
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• v.34 no.6
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• pp.39-47
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• 2014

Daylighting has a great effect on people inside the room. It is also closely related to the lighting energy consumption. Daylight factor(DF) is a very important index for evaluation of the daylighting in overcast sky. The objective of this study is to verify the suitability of the Tregenza's Modified Split Flux formula for the calculation of the daylight factor. We compared the daylight factors calculated by two methods; one by a measurement with 1/5 scale model and the other by the Daysim program. We used variables for verification as window wall ratios(WWR) and angles of the sky visible. As a result, daylight factor calculated by Modified Split Flux is similar to the measurement when more daylight enters the inside. And error is significantly increased when the angle of the sky visible is $50^{\circ}$.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.249-277
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• 2023

The purpose of this study is to explore the potential contribution of citation metrics to improving the search performance of citation index databases. To this end, the study generated ten queries in the field of library and information science and conducted experiments based on the relevance assessment using 3,467 documents retrieved from the Web of Science and 60,734 documents published in 85 SSCI journals in the field of library and information science from 2000 to 2021. The experiments included re-ranking of the top 100 search results using citation metrics and search methods, query expansion experiments using vector space model retrieval systems, and the construction of a citation-based re-ranking system. The results are as follows: 1) Re-ranking using citation metrics differed from Web of Science's performance, acting as independent metrics. 2) Combining query term frequencies and citation counts positively affected performance. 3) Query expansion generally improved performance compared to the vector space model baseline. 4) User-based query expansion outperformed system-based. 5) Combining citation counts with suitability documents affected ranking within top suitability documents.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.121-133
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• 2020

This study examines the most recent successful venture development practices in the United States, Israel, Germany, Finland, and China. The purpose of this study was to find out which foreign country's venture promotion policy is appropriate to korea, why foreign country's venture policy is appropriate to korea and why it is not appropriate, and to draw policy implications for domestic venture promotion and development. The research method was conducted by 50 panel of venture experts using Delphi research technique called 'expert consensus'. As a result of the Delphi research, Finland's venture promotion policy has received the highest evaluation in the usefulness, ease and suitability. Like Finland, the establishment of venture ecosystem through organic activities of private, government, industry, academia, and research was analyzed as the first priority for domestic venture policy. Analyzed. In addition, it was analyzed that the venture policy followed by the private sector under the government's strong promotion policy was no longer appropriate.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.265-274
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• 2021

This study empirically analyzed the users' experiences with the Netflix thumbnail curation based on the Technology Acceptance Model(TAM). According to the correlation analysis results, the higher the dependence on the thumbnails, the higher the satisfaction with the thumbnail curation. Both Perceived Informational Usefulness(PIU) and Perceived Ease of Use(PEOU) had correlations with the degree of satisfaction with the thumbnail curation. In particular, the factors of relevance in PEOU had the greatest impact on the degree of satisfaction and this result proved that the suitability factors of the thumbnails had significant correlations with the degree of satisfaction. The degree of satisfaction with the thumbnail curation also positively correlated with Netflix's overall degree of satisfaction and behavioral intention to use the Netflix. This study demonstrated the suitability of the TAM as a UX evaluation tool for the Netflix thumbnail curation.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.5
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• pp.221-230
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• 2016

With emerging the Internet of Things (IoT) paradigm, the sensor network and sensor platform technologies have been changed according to exploding amount of sensors. Sensor Registry System (SRS) as a sensor platform is a system that registers and manages sensor metadata for consistent semantic interpretation in heterogeneous sensor networks. However, the SRS is unsuitable for the IoT environment. Therefore, this paper proposes sensor registry data model to register and manager sensor information in the IoT environment. We analyze Semantic Sensor Network Ontology (SSNO) for improving the existed SRS, and design metamodel based on the analysis result. We also build tables in a relational database using the designed metamodel, then implement SRS as a web application. This paper applies the SSNO and sensor ontology examples with translating into the proposed model in order to verify the suitability of the proposed sensor registry data model. As the evaluation result, the proposed model shows abundant expression of semantics by comparison with existed models.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.6
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• pp.19-30
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• 2016

The projection of climate-related range shift is critical information for conservation planning of Korean fir (Abies koreana E. H. Wilson). We first modeled the distribution of Korean fir under current climate condition using five single-model species distribution models (SDMs) and the pre-evaluation weighted ensemble method and then predicted the distributions under future climate conditions projected with HadGEM2-AO under four $CO_2$ emission scenarios, the Representative Concentration Pathways (RCP) 2.6, 4.5, 6.0 and 8.5. We also investigated the predictive uncertainty stemming from five individual algorithms and four $CO_2$ emission scenarios for better interpretation of SDM projections. Five individual algorithms were Generalized linear model (GLM), Generalized additive model (GAM), Multivariate adaptive regression splines (MARS), Generalized boosted model (GBM) and Random forest (RF). The results showed high variations of model performances among individual SDMs and the wide range of diverging predictions of future distributions of Korean fir in response to RCPs. The ensemble model presented the highest predictive accuracy (TSS = 0.97, AUC = 0.99) and predicted that the climate habitat suitability of Korean fir would increase under climate changes. Accordingly, the fir distribution could expand under future climate conditions. Increasing precipitation may account for increases in the distribution of Korean fir. Increasing precipitation compensates the negative effects of increasing temperature. However, the future distribution of Korean fir is also affected by other ecological processes, such as interactions with co-existing species, adaptation and dispersal limitation, and other environmental factors, such as extreme weather events and land-use changes. Therefore, we need further ecological research and to develop mechanistic and process-based distribution models for improving the predictive accuracy.