• Asia-Pacific Journal of Business
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• v.3 no.1
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• pp.1-9
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• 2012

The Index of Learning Styles (ILS) instrument based on the Felder-Silverman Learning Style Model was used to determine distribution of learning styles of 125 South Korean business students enrolled in a South Korean institution of higher education. Results show that greater proportion of South Korean business students surveyed in this study prefer sensing over intuitive, visual over verbal, reflective over active, and global over sequential learning styles. The majority of business students have a balanced learning style in all four dimensions of the Felder-Silverman model. Among the students that do not have a balanced learning style, students with sensing, visual, reflective, and global learning styles dominate. Gender difference in learning style preference was not statistically significant for any of the four dimensions.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.695-704
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• 2021

This study aims to determine the effect of changes in learning systems and its effects on students' learning outcomes amid the Covid-19 pandemic. The sample of this study are the students who are in Jakarta, Indonesia. "Non-probability random sampling" technique has been used to select the samples while the sampling method used is "purposive sampling", where criteria are used to select samples. The samples in this study are 200 people taken randomly using Google Form. Concentration ability and learning interest can affect learning outcomes with the mediation of learning comfort and a good learning environment. As well as physical distancing can moderate the effect of concentration ability and learning interest on learning outcomes. The ability to concentrate on improving learning outcomes requires psychomotor improvement. Whereas interest in learning with indicators of learning awareness can improve learning outcomes. A clean environment is a strength in the learning comfort and the community environment can be recommended in the learning environment. The implementation of the restriction of gathering becomes an important point of physical distancing. The other novelties are the learning comfort and the learning environment as mediating variables and physical distancing as moderating variables in one study at a time.

• Management & Information Systems Review
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• v.37 no.4
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• pp.237-256
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• 2018

This study focused on the concept of organizational learning as a prior variable of innovation activities, and reviewed the relationship between organizational learning, innovation and management performance. According to prior studies, the ability to perform these activities may be enhanced through organizational learning, as the success of the innovation requires activities to acquire and share knowledge within the organization. In other words, organizational learning is playing a role as a precursor to innovation. Therefore, in this study, the effects of organizational learning on management performance are to be verified through the mediation effect of product and innovation activities. Organizational learning provides various definitions and components for each scholar, but this study consisted of a series of knowledge acquisition, information distribution, information analysis and process memory using the framework of the learning ability analysis by Levitt and March(1988) and Huber(1991), Innovation was also divided into product innovation and process innovation, and measured with sub-variables such as presentation of new products and improvement activities to increase productivity. Management performance was measured as financial and non-financial performance. To verify the effects of the mediation, we used a three-step regression analysis procedure of Baron and Kenny(1986)'s and a sobel-test. Empirical studies show that organizational learning has a positive effect on management performance and that knowledge acquisition and information distribution, which are the early stages of learning activities in the lower variables, affect performance through product innovation. Based on the results of the above empirical study, the implications, limitations of the study and future research directions were presented.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.205-215
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• 2019

Researchers have confirmed the relationship between ambidexterity learning and innovation performance, but according to the resource-based theory, the relationship between ambidexterity learning and innovation performance is also affected by the internal resources of the organization. Internal resources are an important factor affecting the transformation of learning outcomes into performance. In addition, few scholars have pointed out whether different types of learning have different effects on different types of innovation performance. This study collects data from 170 High-tech enterprises in Shandong, china, and discusses the effects of exploitative learning and explorative learning on management innovation performance and technological innovation performance. This study further examines the moderating role of slack resource on the relationship between ambidexterity learning and innovation performance. Results show that ambidexterity learning has positive effect on innovation performance. Compared with exploitative learning, explorative learning has a greater impact on management innovation performance; compared with explorative learning, exploitative learning has a greater impact on technological innovation performances. Slack resource has positive moderating role between the relationship of exploitative learning, explorative learning and technology innovation performance. But Slack resource has no moderating role between the relationship of exploitative learning, explorative learning and management innovation performance.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.433-450
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• 2012

As a worker performs a certain operation repeatedly, he tends to become familiar with the job and complete it in a very short time. That means that the efficiency is improved due to his accumulated knowledge, experience and skill in regards to the operation. Investing time in an output is reduced by repeating any operation. This phenomenon is referred to as the learning curve effect. A learning curve is a graphical representation of the changing rate of learning. According to previous literature, learning curve effects are determined by subjective pre-assigned factors. In this study, we propose a new statistical model to clarify the learning curve effect by means of a basic cumulative distribution function. This work mainly focuses on the statistical modeling of binary data. We employ the Newton-Raphson method for the estimation and Delta method for the construction of confidence intervals. We also perform a real data analysis.

• Journal of Distribution Science
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• v.15 no.1
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• pp.43-49
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• 2017

Purpose - This study is to integrate organizational factors into UCD process. For this research purpose, we investigated the organizational factors which influence people behaviors in the context of user-centred design practice(UCP). And this study presents organizational culture, organizational learning and change management as the organizational factors. Especially, this study is to investigate how change management influences the relationship between the organizational culture/learning and UCD performance. Research design, data, and methodology - Using the survey methodology with a questionnaire, this study distributed the questionnaire to the experienced 112 practitioners of user-centred design practice in 52 Korean small and medium companies. The organizations differed in range and size from medium-scale, which is under 100 of employees, and to small-scale, which is from 100 to 500. Results - Organizational culture and organizational learning have positive effects on user-centred design practice performance as expected. And change management strengthens the positive relationship between organizational learning and user-centred design practice performance but has no effect on the relationship between organizational culture and user-centred design practice performance. Conclusions - This is the first empirical study of investigating and demonstrating some key organizational factors' relationships and UCD performance of an organization, which will support to institutionalize UCD within an organization, providing theoretical foundations.

• Journal of Convergence for Information Technology
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• v.10 no.11
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• pp.23-29
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• 2020

As IoT devices increase exponentially, minimizing MIMO interference and increasing transmission capacity for sending and receiving IoT information through multiple antennas remain the biggest issues. In this paper, secret key-level distribution mechanism using deep learning is proposed to minimize MIMO-based IoT communication noise. The proposed mechanism minimizes resource loss during transmission and reception process by dispersing IoT information sent and received through multiple antennas in batches using deep learning. In addition, the proposed mechanism applied a multidimensional key distribution processing process to maximize capacity through multiple antenna multiple stream transmission at base stations without direct interference between the APs. In addition, the proposed mechanism synchronizes IoT information by deep learning the frequency of use of secret keys according to the number of IoT information by applying the method of distributing secret keys in dimension according to the number of frequency channels of IoT information in order to make the most of the multiple antenna technology.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.169-175
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• 1996

In this paper, a new parallel neural network system that performs dynamic competitive learning is proposed. Conventional learning mehtods utilize the full dimension of the original input patterns. However, a particular attribute or dimension of the input patterns does not necessarily contribute to classification. The proposed system consists of parallel neural networks with the reduced input dimension in order to take advantage of the information in each dimension of the input patterns. Consensus schemes were developed to decide the netowrks performs a competitive learning that dynamically generates output neurons as learning proceeds. Each output neuron has it sown class threshold in the proposed dynamic competitive learning. Because the class threshold in the proposed dynamic learning phase, the proposed neural netowrk adapts properly to the input patterns distribution. Experimental results with remote sensing and speech data indicate the improved performance of the proposed method compared to the conventional learning methods.

• Progress in Medical Physics
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• v.30 no.2
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• pp.39-48
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• 2019

Deep learning has been applied to various medical data. In particular, current deep learning models exhibit remarkable performance at specific tasks, sometimes offering higher accuracy than that of experts for discriminating specific diseases from medical images. The current status of deep learning applications to molecular imaging can be divided into a few subtypes in terms of their purposes: differential diagnostic classification, enhancement of image acquisition, and image-based quantification. As functional and pathophysiologic information is key to molecular imaging, this review will emphasize the need for accurate biomarker acquisition by deep learning in molecular imaging. Furthermore, this review addresses practical issues that include clinical validation, data distribution, labeling issues, and harmonization to achieve clinically feasible deep learning models. Eventually, deep learning will enhance the role of theranostics, which aims at precision targeting of pathophysiology by maximizing molecular imaging functional information.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.4
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• pp.159-176
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• 2023

The conservation of the raccoon dog (Nyctereutes procyonoides) in South Korea requires the protection and preservation of natural habitats while additionally ensuring coexistence with human activities. Applying habitat map modeling techniques provides information regarding the distributional patterns of raccoon dogs and assists in the development of future conservation strategies. The purpose of this study is to generate potential habitat distribution maps for the raccoon dog in South Korea using geospatial technology-based models. These models include the frequency ratio (FR) as a bivariate statistical approach, the group method of data handling (GMDH) as a machine learning algorithm, and convolutional neural network (CNN) and long short-term memory (LSTM) as deep learning algorithms. Moreover, the imperialist competitive algorithm (ICA) is used to fine-tune the hyperparameters of the machine learning and deep learning models. Moreover, there are 14 habitat characteristics used for developing the models: elevation, slope, valley depth, topographic wetness index, terrain roughness index, slope height, surface area, slope length and steepness factor (LS factor), normalized difference vegetation index, normalized difference water index, distance to drainage, distance to roads, drainage density, and morphometric features. The accuracy of prediction is evaluated using the area under the receiver operating characteristic curve. The results indicate comparable performances of all models. However, the CNN demonstrates superior capacity for prediction, achieving accuracies of 76.3% and 75.7% for the training and validation processes, respectively. The maps of potential habitat distribution are generated for five different levels of potentiality: very low, low, moderate, high, and very high.