• Journal of Distribution Science
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• v.20 no.4
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• pp.111-119
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• 2022

Purpose: This study seeks to address the omission through examining the manner in which demographic similarity affects the responses of employees in the retail sector towards horizontal pay dispersion. Through doing so the study will be effective in bolstering the recent efforts of more careful exploration of conditions. Research design, data, and methodology: Scant past studies are available to guide for practitioners in retail sector which compensation strategy might lead adequate job performance for retail sales workers. To suggest possible solution, the present authors used variables of pay dispersion and obtained 317 US retail sale workers in distribution channels to measure the association between pay dispersion and employee job performance. Results: The statistical findings indicated both first and second hypothesis could be acceptable with favorable Beta and T values, resulting high degree of pay dispersion leads a low level of job performance, while a low degree of pay dispersion can motivate retail sales workers to improve their performance. Conclusions: The findings of this study raises an argument that processes of social comparison work in a more vigorous manner. This is thus a representation of the propensity of a retail sales worker to voluntarily resign from an organization when dispersion rates are higher.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.264-264
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• 2021

해수면 상승 및 인간의 활동으로 인한 해수 침투 영향 반경의 예측 및 모의에 대한 연구는 활발히 진행되고 있으며, 해수 침투 피해를 완화하기 위한 다양한 대응 방안이 시도되고 있다. 하지만 해수 침투 피해 대응 방안 등을 효율적으로 사용하기 위해서는 해수 침투 피해가 가장 활발히 일어나는 지역을 선정하고, 지역 특성에 맞는 대응 방안을 선정하는 과정이 필요하다. 기존의 해수침투 취약성 평가의 방법은 대수층 매개변수의 불확실성, 자료의 결측이 빈번하게 발생하고 있다. 또한, 평가 인자에 대한 자료 수집이 어렵고, 대수층에 대한 매개변수의 불확실성으로 직관적인 평가가 어렵다. 본 연구에서는 서해안의 도서지역을 제외한 연안지역을 대상으로 해수침투 취약성 평가 기법을 개발하였다. 해수침투에 대한 직관적인 해석을 위해 직접적인 영향을 미치는 수문 성분 중 해수면, 지하수위, 함양량, 지하수 이용량을 지표로 선정하고, 행정구역 단위로 자료를 수집하였다. 각각의 자료에 대한 평균, 기울기를 이용하였다. 각각의 인자에 대해서 객관적 가중치 산정 방법인 엔트로피 방법을 이용하여 가중치를 결정하였다. Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)를 이용하여 가장 취약한 지역을 선정하였다. 객관적 가중치 산정 방법을 이용하여 자료를 통해 직접적인 평가 가능하며, 추세 분석을 통해 앞으로의 해수침투 취약성에 대한 전망도 가능하다. 평가 결과를 이용하여 해안의 지하수자원의 지속가능한 운영 관리를 위한 자료로 활용할 수 있을 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.385-385
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• 2020

본 연구에서는 가뭄과 연관되는 다양한 관련 요인을 포함한 가뭄취약성 평가방안을 수립하고 이를 적용하는 것을 목표로 하였다. 평가기법은 평가인자와 가중치 선정, 평가자료 데이터베이스 구축, 평가자료와 가중치를 조합한 평가의 세 단계로 구성되었으며 평가인자 및 가중치 선정에는 Delphi 조사기법을 적용하고 평가기법으로는 최근 널리 적용되고 있는 MCDM (Multi-Criteria Decision Making) 방법인 TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) 기법을 활용하였다. 평가인자는 기상분야(Meteorological factors), 농업분야(Agricultural factors), 사회경제분야(Socioeconomic factors), 환경분야(Natural System)로 구성하였으며 선정된 인자에 대한 데이터베이스를 구성하기 위하여 기상청, 농어촌공사, 수자원공사 등의 관계기관이 관리하는 자료를 수집하였다. 수립한 가뭄취약성 평가방안을 2016년 3월부터 2019년 9월까지 우리나라 시군구 행정구역 단위, 총 167개 지역이며 순위법, 비율법, fuzzy 등 가중치 선정방법에 따라 결과에 약간의 차이가 나타난다. 가뭄예보결과와 취약성 평가결과를 비교해 보면 충청남도 홍성군이 동기간 동안 가뭄예경보 발령 횟수가 가장 많았으며, 충청남도 보령시와 서산시도 매우 높은 빈도로 확인되었다. 평가 결과, 충청북도, 경상남도, 전라남도에 가뭄 취약지역이 다수 도출 되어 이들 지역에 대한 가뭄 대응 방안 수립이 필요한 것으로 분석되었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.195-195
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• 2020

이 연구는 기후변화 위험에 노출되어 있는 북한에 대한 잠재증발산량의 미래 변화를 전망하였다. 이를 위해 IPCC AR5의 RCP 기후변화 시나리오로부터 모의된 미래 기온자료를 APCC (APEC Climate Center) Integrated Modeling (AIMS)를 사용하여 25개 관측 지점에 대해서 상세화하여, McGuinness-Borne 방법으로 잠재증발산량을 추정하였다. 6개의 성능 지표와 TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution)로 27개 GCMs 간의 과거 기후 재현성을 비교하여, 관측 지점 규모에서 적정 GCM을 선정하였다. 마지막으로 각 지점에서 선정된 대표 시나리오(representative climate change scenarios, RCCS)로 북한 지역의 잠재증발산량의 미래 변화를 3개의 구간(F1: 2011-2040; F2: 2041-2070; F3: 2071-2100)에서 all CCS(climate change scenario)와 비교하고, 미래 변화를 정량적으로 제시하였다. 그 결과 공간 해상도가 더 높은 GCM이 RCCS로 선정되었으며, 미래로 갈수록 잠재증발산량이 증가하리라 전망되었다. 또한, 여름철 잠재증발산량의 모델 간 변동성은 미래 구간에 따라 점진적으로 증가되었고, 연 평균 증발산량은 과거 기후대비 1.4배(F1), 2.0배(F2) 및 2.6배(F3) 증가하였다.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.697-705
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• 2023

Along with other heavy metals, arsenic (As) is one among the substances most harmful to living organisms including humans. Owing to its morphological similarity to phosphorus, the uptake of As is influenced by photosynthesis and the phosphorus uptake pathway. In this study, we varied arsenic exposure and light intensity during nutrient solution cultivation of lettuce (Lactuca sativa L.) to determine the effect of these two factors on arsenic uptake, lettuce growth, and electron transfer in photosystem II. In the treatment exposed to 30 μmol L^-1 of arsenic, the shoot arsenic concentration increased from 4.73 mg kg^-1 to 18.97 mg kg^-1 as the light intensity increased from 22 to 122 μmol m^-2 s^-1. The water content and ET2o/RC of the shoots were not affected by arsenic at low light intensity; however, at optimal light intensity, they decreased progressively with arsenic exposure. Increased light intensity stimulated the growth of plant roots and shoots; contrarily, the difference in growth decreased as the concentration of As exposure increased. The results of this study suggest that the effect of As on plant growth is dependent on light intensity; in particular, an increase in light intensity can increase the uptake of As, thereby affecting plant growth and As toxicity.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.131-146
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• 2011

It is becoming more essential than ever for office professionals to become competent in information collection/gathering and problem solving in today's global business society. In particular, office professionals do not only assist simple chores but are also forced to make decisions as quickly and efficiently as possible in problematic situations that can end in either profit or loss to their company. Since office professionals rely heavily on their tacit knowledge to solve problems that arise in everyday business situations, it is truly helpful and efficient to refer to similar business cases from the past and share or reuse such previous business knowledge for better performance results. Case-based reasoning(CBR) is a problem-solving method which utilizes previous similar cases to solve problems. Through CBR, the closest case to the current business situation can be searched and retrieved from the case or knowledge base and can be referred to for a new solution. This reduces the time and resources needed and increase success probability. The main purpose of this study is to design a system called COKRS(Case-based reasoning Office Knowledge Recommender System) and develop a prototype for it. COKRS manages cases and their meta data, accepts key words from the user and searches the casebase for the most similar past case to the input keyword, and communicates with users to collect information about the quality of the case provided and continuously apply the information to update values on the similarity table. Core concepts like system architecture, definition of a case, meta database, similarity table have been introduced, and also an algorithm to retrieve all similar cases from past work history has also been proposed. In this research, a case is best defined as a work experience in office administration. However, defining a case in office administration was not an easy task in reality. We surveyed 10 office professionals in order to get an idea of how to define a case in office administration and found out that in most cases any type of office work is to be recorded digitally and/or non-digitally. Therefore, we have defined a record or document case as for COKRS. Similarity table was composed of items of the result of job analysis for office professionals conducted in a previous research. Values between items of the similarity table were initially set to those from researchers' experiences and literature review. The results of this study could also be utilized in other areas of business for knowledge sharing wherever it is necessary and beneficial to share and learn from past experiences. We expect this research to be a reference for researchers and developers who are in this area or interested in office knowledge recommendation system based on CBR. Focus group interview(FGI) was conducted with ten administrative assistants carefully selected from various areas of business. They were given a chance to try out COKRS in an actual work setting and make some suggestions for future improvement. FGI has identified the user-interface for saving and searching cases for keywords as the most positive aspect of COKRS, and has identified the most urgently needed improvement as transforming tacit knowledge and knowhow into recorded documents more efficiently. Also, the focus group has mentioned that it is essential to secure enough support, encouragement, and reward from the company and promote positive attitude and atmosphere for knowledge sharing for everybody's benefit in the company.

• Journal of KIISE
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• v.42 no.2
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• pp.242-254
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• 2015

In this paper, we address the problem of improving the performance of multi-step k-NN search using multi-dimensional indexes. Due to information loss by lower-dimensional transformations, existing multi-step k-NN search solutions produce a large tolerance (i.e., a large search range), and thus, incur a large number of candidates, which are retrieved by a range query. Those many candidates lead to overwhelming I/O and CPU overheads in the postprocessing step. To overcome this problem, we propose two efficient solutions that improve the search performance by reducing the tolerance of a range query, and accordingly, reducing the number of candidates. First, we propose a tolerance reduction-based (approximate) solution that forcibly decreases the tolerance, which is determined by a k-NN query on the index, by the average ratio of high- and low-dimensional distances. Second, we propose a coefficient control-based (exact) solution that uses c k instead of k in a k-NN query to obtain a tigher tolerance and performs a range query using this tigher tolerance. Experimental results show that the proposed solutions significantly reduce the number of candidates, and accordingly, improve the search performance in comparison with the existing multi-step k-NN solution.

• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.1-14
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• 2004

Visualization of documents will help users when they do search similar documents. and all research in information retrieval addresses itself to the problem of a user with an information need facing a data source containing an acceptable solution to that need. In various contexts. adequate solutions to this problem have included alphabetized cubbyholes housing papyrus rolls. microfilm registers. card catalogs and inverted files coded onto discs. Many information retrieval systems rely on the use of a document surrogate. Though they might be surprise to discover it. nearly every information seeker uses an array of document surrogates. Summaries. tables of contents. abstracts. reviews, and MARC recordsthese are all document surrogates. That is, they stand infor a document allowing a user to make some decision regarding it. whether to retrieve a book from the stacks, whether to read an entire article, etc. In this paper another type of document surrogate is investigated using a grouping method of term list. lising Multidimensional Scaling Method (MDS) those surrogates are visualized on two-dimensional graph. The distances between dots on the two-dimensional graph can be represented as the similarity of the documents. More close the distance. more similar the documents.

• Journal of Science Education
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• v.46 no.1
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• pp.17-29
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• 2022

The purpose of this study is to look qualitatively into how efficiently and reasonably a computer can learn themes related to the Nature of Science (NOS). In this regard, a corpus has been constructed focusing on literature (920 abstracts) related to NOS, and factors of the optimized Word2Vec (CBOW, Skip-gram) were confirmed. According to the four dimensions (Inquiry, Thinking, Knowledge and STS) of NOS, the comparative evaluation on the word-level word embedding was conducted. As a result of the study, according to the previous studies and the pre-evaluation on performance, the CBOW model was determined to be 200 for the dimension, five for the number of threads, ten for the minimum frequency, 100 for the number of repetition and one for the context range. And the Skip-gram model was determined to be 200 for the number of dimension, five for the number of threads, ten for the minimum frequency, 200 for the number of repetition and three for the context range. The Skip-gram had better performance in the dimension of Inquiry in terms of types of words with high similarity by model, which was checked by applying it to the four dimensions of NOS. In the dimensions of Thinking and Knowledge, there was no difference in the embedding performance of both models, but in case of words with high similarity for each model, they are sharing the name of a reciprocal domain so it seems that it is required to apply other models additionally in order to learn properly. It was evaluated that the dimension of STS also had the embedding performance that was not sufficient to look into comprehensive STS elements, while listing words related to solution of problems excessively. It is expected that overall implications on models available for science education and utilization of artificial intelligence could be given by making a computer learn themes related to NOS through this study.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2412-2420
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• 1997

An algorithm for detecting dominant points on a digital contour is proposed. The algorithm detects the dominant points from the given contour with the given number of points as a constraint condition. on the basis of the principle of the top-down approach. The dominant points are detected by minimizing the object function that presents the similarity between the given contour and the approximated polygon drawn by connecting the dominant points of candicate. The penalty multiplier method is applied to minimize the augmented Lagrangean function which is made by adding the penalty of the constraint condition to the object function. On the minimization, a local searching method by the partial problem division is considered, and it is clarified that the reasonable solution is obtained by the method. The proposed algorithm has a merit that the dominant points can be detected exactly and stably even for the digital contour composed of multiple-scale features and the similar contours, because it detects them on considering the property of a whole figure of the given contour. It is confirmed that the proposed algorithm is more excellent than other previously proposed algorithms by the comparison and the evaluation through the experiment on suing typical digital curves.