• Journal of Distribution Science
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• v.15 no.1
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• pp.123-130
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• 2017

Purpose - This research aims to examine the effect of e-business adoption on firm's growth and profitability in the distribution industry. The value added from the distribution industry acts as the cost of other industries. As the distribution industry develops, its stage becomes shorter and the distribution margin becomes smaller. Therefore, e-business is expected to have a different effect on the distribution industry than other industries. Research design, data and methodology - The previous research generally used e-business adoption as an independent variable and firm's performance as a dependent variable. This study elaborated the model using a dynamic panel model that includes the performance variable of the previous year as an independent variable. By employing system GMM (Generalized Method of Moments), the endogeneity problem in the dynamic panel model can be solved. For the analysis, I extracted the distribution companies as the raw data in the National Statistical Office's Business Activity Survey over the period 2006 to 2012. Results - The growth rate of firms adopting e-business was 0.299%p higher than that of the non-adopter. However, only ERP (Enterprise Resource Planning), KMS (Knowledge Management System) and SCM (Supply Chain Management) contributed positively to the growth rate. In the case of profitability, it was 0.04%p higher than the distribution companies that did not adopt e-business. ERP and LMS (Learning Management System) improve profitability, while SCM reduces profitability. Consequently, while ERP improves both growth and profitability, SCM improves growth but reduces profitability. In addition, KMS improves firm's growth only, and LMS does only profitability, showing that each e-business has a differentiated effect. Conclusions - Since the distribution industry has different characteristics from manufacturing and other service industries, the introduction of e-business may not guarantee the growth and profitability of distribution companies. Careful introduction considering the characteristics of the distribution industry is required. In particular, it is necessary to select an e-business meeting the characteristics and needs of a distribution company, and thereafter, it is required for the company's own efforts to internalize it within the system.

• Communications of Mathematical Education
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• v.31 no.2
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• pp.187-201
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• 2017

The study in this paper, which is part of a bigger study investigating non-cognitive characteristics of Korean students at the 4-12 grade levels, aims to identify the influential characteristics that explain students' decision to give up on mathematics learning. We consider seven non-cognitive student characteristics: value, interest, attitudes, external motivation, internal motivation, learning conation and efficacy. Data were collected from 21,485 Korean students, and were analyzed with a logistic regression method using SPSS. The findings show that efficacy was the most significant indicator of students' decision to give up on mathematics learning in all three grade level bands: elementary (4th-6th), middle (7th-9th) and high (10th-12th). In particular, the causal model analysis shows that students who highly value mathematics tend to have stronger internal and external motivation, which bring about stronger interest and learning conation, which in turn lead to positive attitudes and strong efficacy regarding the learning of mathematics. It was further found that while external motivation was a significant indicator of upper grade level students' decision to give up on mathematics learning, it was only a moderate indicator for lower grade level students. The findings of this study provide useful information about which non-cognitive areas need to be focused on, in what grade levels, to help students stay on track and not fall behind in learning mathematics.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.119-130
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• 2022

Crime is a common social problem that affects the quality of life. As the number of crimes increases, it is necessary to build a model to predict the number of crimes that may occur in a given period, identify the characteristics of a person who may commit a particular crime, and identify places where a particular crime may occur. Data privacy is the main challenge that organizations face when building this type of predictive models. Federated learning (FL) is a promising approach that overcomes data security and privacy challenges, as it enables organizations to build a machine learning model based on distributed datasets without sharing raw data or violating data privacy. In this paper, a federated long short- term memory (LSTM) model is proposed and compared with a traditional LSTM model. Proposed model is developed using TensorFlow Federated (TFF) and the Keras API to predict the number of crimes. The proposed model is applied on the Boston crime dataset. The proposed model's parameters are fine tuned to obtain minimum loss and maximum accuracy. The proposed federated LSTM model is compared with the traditional LSTM model and found that the federated LSTM model achieved lower loss, better accuracy, and higher training time than the traditional LSTM model.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• Communications of Mathematical Education
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• v.36 no.4
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• pp.511-533
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• 2022

The purpose of this study is to develop a learning coaching model suitable for the mathematics subject by reflecting the characteristics of the mathematics subject and the mathematics teaching/learning process in the CARE learning coaching model that supports students' self-directed learning. The mathematics learning coaching model developed in this study is a 'step' and 'element' to apply coaching, and a 'strategy' for carrying out it. Mathematics learning coaching model evaluated rapport, trust, state management, and math pre-test as elements of 'creating a comfortable atmosphere', and problem recognition, hypercognition, restructuring, initiative, and math learning ability as elements of 'improving perception'. Self-efficacy, learning readiness, confirmation (feedback) as elements of the 'reawakening of learning immersion' stage, voluntary motivation and success experiences as elements of the 'empowerment' stage, and various math learning strategies to perform each element presented. The math learning coaching model can be used to help math teachers motivate students to learn and help students solve their own problems.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.4
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• pp.53-82
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• 2020

With the increase in smartphone ownership and Internet usage using smartphones, the information environment is shifting from the existing PC to the smart mobile. The current undergraduate students are called Generation Z who prefer smartphones to PCs and video contents to texts. This study attempted to understand their usage behaviors of electronic resources in an academic library in a smart mobile environment. This study conducted a usage statistics analysis with 61,433 usage records of e-books, audiobooks, and e-learning contents and 1,595 records of users in the A academic library during 3 years from 2016 to 2018. The scope of the data includes the date of use, the subject, the year of publication, the channel of use, and each user's gender, affiliation, status, admission date, and graduation date. This study investigated not only the general characteristics of electronic resource use, but also the usage behaviors according to the user's demographic characteristics. Based on the findings, this study suggested practical service plans that are applicable in the near future and reflect changing circumstances.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.3
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• pp.8-16
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• 2013

Determining relative importance among many quality attributes under financial constraints is an important task. The weighted value of an attribute particularly in QFD, will influence on engineering characteristics and this will eventually influence the whole manufacturing process such as parts deployment, process planning, and production planning. Several scholars have suggested weighting formulas using CSC (Customer Satisfaction Coefficient) in the Kano model. However, previous research shows that the validity of the CSC approaches has not been proved systematically. The aim of the present study is to address drawbacks of CSC and to develop APC (Average Potential Coefficient), a new approach for weighting of quality attributes. For this, the current study investigated 33 quality attributes of e-learning and conducted a survey of 375 university students for the results of APC, the Kano model, and the direct importance of the quality attributes. The results show that the proposed APC is better than other approaches based on the correlation analysis with the results of direct importance. An analysis of e-leaning's quality perceptions using the Kano model and suggestions for improving e-learning's service quality are also included in this study.

• Journal of Korean Home Economics Education Association
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• v.8 no.2
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• pp.29-41
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• 1996

In this research, researcher will examined the theoretical background of open education. Based on the result of the development of the suggested guidelines for a home economics teaching/learning program, researcher concludes that in order for the teaching/learning programs based on open education to be efficiently acieved in the classroom environment-organization at the middle school the following reform measures must accompany these programs. First, in order for the special characteristics of open education, i.e., individualized and small group study, to be effectively achieved, it is necessary to improve the physical classroom environment-organization. Second, the two class hours per week currently allotted for home economics are not sufficient to convey the information in the textbook. In order to reach objectives of teaching home economics according to open education a guarantee of a few more class hours is demanded. Third, in order to successfully achieve teaching/learning programs following open education, it is necessary for home economics teachers to make efforts to develop educational materials, and to engage in ongoing research and inservice training. For this to occur, measures must be taken to reduce the workload of teachers.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.173-178
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• 2023

As Korean literature spreads around the world, its position in the overseas publishing market has become important. As demand in the overseas publishing market continues to grow, it is essential to predict future book sales and analyze the characteristics of books that have been highly favored by overseas readers in the past. In this study, we proposed ensemble learning based prediction model and analyzed characteristics of the cumulative sales of more than 5,000 copies classified as good sellers published overseas over the past 5 years. We applied the five ensemble learning models, i.e., XGBoost, Gradient Boosting, Adaboost, LightGBM, and Random Forest, and compared them with other machine learning algorithms, i.e., Support Vector Machine, Logistic Regression, and Deep Learning. Our experimental results showed that the ensemble algorithm outperforms other approaches in troubleshooting imbalanced data. In particular, the LightGBM model obtained an AUC value of 99.86% which is the best prediction performance. Among the features used for prediction, the most important feature is the author's number of overseas publications, and the second important feature is publication in countries with the largest publication market size. The number of evaluation participants is also an important feature. In addition, text mining was performed on the four book reviews that sold the most among good-selling books. Many reviews were interested in stories, characters, and writers and it seems that support for translation is needed as many of the keywords of "translation" appear in low-rated reviews.

• Journal of The Korean Association of Information Education
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• v.10 no.2
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• pp.241-248
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• 2006

Recently, as the importance of the information communication ethics education has increased, the research about new instructional method or contents have been progressed actively. On the other hand, due to the advance of e-learning technology, instead of teacher-centered instruction, the development of learning contents and learning method for satisfying students' requirements is proceeded actively. In this paper, in order to increase the learning effect for information communication ethics education for primary school students, we propose a new way to design an instruction which considers the characteristics and the requirements of students. We decompose instructional design features into 4 components such as goal, model, contents, and media, and then we pose questionnaire to the 5th grade students of a primary school. After that, we analyze data by using the conjoint analysis. Based on the result of the conjoint analysis, we give instructions to two classes in order to compare the learning achievement of the two classes. Finally, by evaluating the students and analyzing their satisfaction levels, we diagnose the effectiveness of the proposed method.