• The Journal of Korean Academic Society of Nursing Education
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• v.9 no.2
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• pp.199-211
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• 2003

Purpose: The purpose of this study was to review and summarize the trend of nursing research on image of nurses performed in Korea and to get the preliminary data for future research. Method: This study queried 18 Korean studies performed from 1990 to 2002, selected by two online databases surfing. The studies were analyzed in terms of several standards Lee, Myung Ha(1996) suggested in her study. Result: (1) The first study on image of nursing performed at 1992. (2) 33.4% of the studies included in this analysis were performed for a thesis for a degree, 61.2% hired non-experimental research design, and only 5.6% selected study sample by simple random sampling. (3) Almost studies used the research instruments developed by Korean nursing scientist and collected research data with questionnaires. (4) The variety variables were analyzed to identify the relationship between image of nurses and the variables. (5) 88.9% of the studies included in this analysis included the suggestions for future study. Conclusion: The research findings were summarized and strategic planning for future study on image of nurses were discussed.

• Agricultural and Biosystems Engineering
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• v.6 no.1
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• pp.1-7
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• 2005

Assessing health condition of crop in the field is one of core operation in precision fanning. A sensing system was proposed to remotely detect the crop health condition in terms of SP AD readings directly related to chlorophyll contents of crop using a multispectral camera equipped on ground-based platform. Since the image taken by a camera was sensitive to changes in ambient light intensity, it was needed to convert gray scale image data into reflectance, an index to indicate the reflection characteristics of target crop. A reference reflectance panel consisting of four pieces of sub-panels with different reflectance was developed for a dynamic calibration, by which a calibration equation was updated for every crop image captured by the camera. The system performance was evaluated in a field by investigating the relationship between com canopy reflectance and SP AD values. The validation tests revealed that the com canopy reflectance induced from Green band in the multispectral camera had the most significant correlation with SPAD values $(r^2=0.75)$ and NIR band could be used to filter out unwanted non-crop features such as soil background and empty space in a crop canopy. This research confirmed that it was technically feasible to develop a ground-based remote sensing system for assessing crop health condition.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.1
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• pp.313-330
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• 2016

A coalition of information schools, called the iSchools Organization, was established to increase the visibility of library and information science and to cope with the new demands of the digital age. As of 2015, sixty-five schools from many different countries have joined the iSchools Organization. While some other schools are interested in adopting iSchools, there are still some issues that need to be considered before adopting the iSchool charter. This paper presents those issues from the perspectives of the 5C groups: curriculum, competencies, convergence, collaboration, and consensus. A survey was conducted to investigate some aspects of the 5Cs. This study identifies five iSchool-related issues - 5Cs. Providing perspectives in the areas of the 5Cs will be useful to establish stronger iSchools. These five Cs will resolve information problems that we are facing, prepare students or any organizations for the digital age, give students digital service skills, and train future data scientists. This paper represents practical guidelines to build a strong iSchool. With the success of iSchools, societies see us as more than the traditional librarian.

• Genomics & Informatics
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• v.17 no.4
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• pp.39.1-39.20
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• 2019

Analyzing patterns in data points embedded in linear and non-linear feature spaces is considered as one of the common research problems among different research areas, for example: data mining, machine learning, pattern recognition, and multivariate analysis. In this paper, data points are heterogeneous sets of biosequences (composite data points). A composite data point is a set of ordinary data points (e.g., set of feature vectors). We theoretically extend the derivation of the largest generalized eigenvalue-based distance metric D_ij(γ₁) in any linear and non-linear feature spaces. We prove that D_ij(γ₁) is a metric under any linear and non-linear feature transformation function. We show the sufficiency and efficiency of using the decision rule $\bar{{\delta}}_{{\Xi}i}$(i.e., mean of D_ij(γ₁)) in classification of heterogeneous sets of biosequences compared with the decision rules min_𝚵iand median_𝚵i. We analyze the impact of linear and non-linear transformation functions on classifying/clustering collections of heterogeneous sets of biosequences. The impact of the length of a sequence in a heterogeneous sequence-set generated by simulation on the classification and clustering results in linear and non-linear feature spaces is empirically shown in this paper. We propose a new concept: the limiting dispersion map of the existing clusters in heterogeneous sets of biosequences embedded in linear and nonlinear feature spaces, which is based on the limiting distribution of nucleotide compositions estimated from real data sets. Finally, the empirical conclusions and the scientific evidences are deduced from the experiments to support the theoretical side stated in this paper.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.4
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• pp.508-516
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• 2021

Although scientist have been reporting recently that changes in ocean environment influence the species composition, movements, and growth of fish in Korea waters. Previous studies on fish vulnerability owing to climate changes are insufficient to explain the effect of fluctuating ocean environments on fisheries ground. In this study, we suggested a method for the assessment of fisheries sensitivity to various factors in ocean environments in Korean waters. To evaluate the fisheries sensitivity, catch data (Chub mackerel, Hairtail, Common squid, small yellow croaker) from National federation of fisheries cooperatives in Korea (1991-2017) and oceanographic data from Korea Ocean Data Center (KODC; 1960-2017) were normalized using the z-score method. Thereafter, the fisheries sensitivity was calculated using the difference between the catch data and the oceanographic data. Finally, the fisheries sensitivity was evaluated based on evaluation grade ratings. Result revealed that in the south sea, variability in catch data was obviously higher than environmental fluctuation (evaluation grade 1), indicating that catch variability in response to environmental change is most sensitive in the south sea among Korean waters in 2017. These results would be helpful for fishery management and policy for sustainable yield in Korean waters.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.47-69
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• 2021

Data scientists are new knowledge workers representing the knowledge economy era. Knowledge workers perform unstandardized works that solve ambiguity-intensive problems. Therefore, self-leadership, which emphasizes self-motivated, autonomous judgment and execution, significantly influences their work-related outcomes. Even knowledge workers have high occupational commitment, they usually show low organizational commitment. Knowledge workers' intention to leave is also relatively high due to this reason. This study focused on data scientists' self-leadership, predicted that self-leadership would increase an organization's commitment and intention to leave. Based on the trait activation theory(TAT), the author also confirmed how perceived job autonomy enhances self-leadership influences. Results showed that data scientists' self-leadership significantly lowered intention to leave through organizational commitment and this mediating effect was moderated by perceived job autonomy. This study broadened the theoretical understanding the effects of knowledge workers' self-leadership and presented practical implications for managing data scientists.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.543-549
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• 2018

The importance of prediction is becoming more emphasized, due to the uncertain business environment. In order to implement the predictive model, a number of data engineers and scientists are involved in the project and various prediction ideas are suggested to enhance the model. it takes a long time to validate the model's accuracy. Also It's hard to redesign and develop the code. In this study, development method such as Lego is suggested to find the most efficient idea to integrate various prediction methodologies into one model. This development methodology is possible by setting the same data layout for the development code for each idea. Therefore, it can be validated by each idea and it is easy to add and delete ideas as it is developed in Lego form, which can shorten the entire development process time. Finally, result of test is shown to confirm whether the proposed method is easy to add and delete ideas.

• Journal of The Korean Association For Science Education
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• v.34 no.5
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• pp.469-478
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• 2014

To provide students an alternative image of science and scientist, we developed five lesson plans that include scientists' joy, anger, sorrow, and pleasure in their life. Through the 10 hour lessons with the five topics, we investigated the effect of our program on students' image change toward scientists, their science learning, and their career development in science field. Twenty high school students participated in our program and five of them were analyzed. The qualitative data included opinionnaire survey before and after the program, field note, video recording, students' worksheets, and interview. The science episode lessons that reflect the human side of scientists were designed in five steps. The first step is the one about imaging of scientists, the second step is the one about reading scientists' episode in their life, the third step is the one about investigating human side of scientists, the fourth step is the one about feeling sympathy in scientists' context, and the last step is the one about judging human side of scientists. Students participated in this program got to feel familiarity in scientists as well as confidence in science. By obtaining the alternative image of scientists after the class, it is expected that students will play roles of well-prepared supporters with scientific literacy.

• Journal of The Korean Association For Science Education
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• v.39 no.4
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• pp.511-523
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• 2019

In this age of the $4^{th}$ industrial revolution, we, science educators, are giving more light on students' agentic behavior in the process of educating future scientist. This study, with the analytic lens of epistemic agency, explores the key stages of a student-driven R&E program rather than the scientist-led R&E program. It also examines to understand the emergence of students' epistemic agency in each stage of R&E. Data from participant observation for 18 months and in-depth interviews were collected and analyzed with the constant comparative method of grounded theory. This study identifies and describes five key stages of student-driven R&E: The stage of exploring research theme, designing research, performing lab activity, interpreting results, and communicating research. It also finds that (a) students' epistemic agency emerged with the constant interactions with the R&E structure; (b) students' epistemic agency has deep relations with the epistemic beliefs of the students; (c) students positioned themselves as decision-makers in the R&E practice; (d) the redistributed power and authority of the R&E contributed to the emergence of students' epistemic agency.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.4
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• pp.511-514
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• 1999

Data pertaining to 1111 first lactation performance record of Karan Fries (Holstein-Friesian $\times$ Zebu) cows spread over a period of 21 years and sired by 72 bulls were used to examine the efficiency of sire indices for lactation milk production using auxiliary traits. First lactation length, first service period, first calving interval, first dry period and age at first calving were considered as auxiliary traits. The efficiency of this method was compared with simple daughter average index (D), contemporary comparison method (CC), least-square method (LSQ), simplified regressed least-squares method (SRLS) and best linear unbiased prediction (BLUP) for lactation milk production. The relative efficiency of sire evaluation methods using one auxiliary trait was lower (24.2-32.8%) in comparison to CC method, the most efficient method observed in this study. Use of two auxiliary traits at a time did not further improve the efficiency. The auxiliary sire indices discriminate better among bulls as the range of breeding values were higher in these methods in comparison to conventional sire evaluation methods. The rank correlation between breeding values estimated using auxiliary traits were high (0.77-0.78) with CC method. The rank correlation among auxiliary sire indices ranged from 0.98 to 0.99, indicating similar ranking of sire for breeding values of milk production in all the auxiliary sire indices.