• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.6
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• pp.89-96
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• 2021

In this study, a deep-learning image analysis model was established and validated for AI-based monitoring of the tidal flat ecosystem for marine protected creatures Ocypode stimpsoni and their habitat. The data in the study was constructed using an unmanned aerial vehicle, and the U-net model was applied for the deep learning model. The accuracy of deep learning model learning results was about 0.76 and about 0.8 each for the Ocypode stimpsoni and their burrow whose accuracy was higher. Analyzing the distribution of crabs and burrows by putting orthomosaic images of the entire study area to the learned deep learning model, it was confirmed that 1,943 Ocypode stimpsoni and 2,807 burrow were distributed in the study area. Through this study, the possibility of using the deep learning image analysis technology for monitoring the tidal ecosystem was confirmed. And it is expected that it can be used in the tidal ecosystem monitoring field by expanding the monitoring sites and target species in the future.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.35-43
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• 2021

This study aims to investigate factors affecting eBook acceptance and learning outcomes among students experiencing online distance learning. As conventional textbooks are now switched into eBooks, the effects of contextual factors including lecturer, student computer competency, content and design of the course, access ability, infrastructure, and university support on eBook acceptance and learning outcome needs to be evaluated. The sample of this study is represented by students at the Universiti Teknologi MARA, City Campus Melaka, undertaking 'strategic management course'. Non-probability random sampling was selected as the sampling technique and a purposive sampling method was chosen to select the samples. The samples comprised 171 students randomly selected through Google Form. The questionnaire data was analyzed by using PLS-SEM. The results indicated that these factors contributed 62.3% variations in the eBook acceptance and 67.1% variations in the learning outcomes. The strongest factor affecting both dependent variables was content and design of course. Managerial implication suggested that the content for all courses taught through the eBook platform needs to be revisited and improved in accordance with the mode of online deliverance. Tutorial on how to navigate the eBook platform is important to all users as this would enhance acceptance and produce better learning outcomes among students.

• Genomics & Informatics
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• v.18 no.1
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• pp.7.1-7.7
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• 2020

In this paper, we present few technical notes about the distance distribution paradigm for Mosaab-metric using 1, 2, and 3 grams feature extraction techniques to analyze composite data points in high dimensional feature spaces. This technical analysis will help the specialist in bioinformatics and biotechnology to deeply explore the biodiversity of influenza virus genome as a composite data point. Various technical examples are presented in this paper, in addition, the integrated statistical learning pipeline to process segmented genomes of influenza virus is illustrated as sequential-parallel computational pipeline.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.769-779
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• 2020

Self-efficacy has been extensively evaluated, but no studies have investigated the effect of self-efficacy on the self-reliance of women in poor-households economic productivity. This study analyzes self-efficacy as a personal factor, learning processes, and social support as an environmental factor towards the achievement of self-reliance in women from poor-households in productive economy businesses. Despite the dominant logic of this scheme, there is a need for field-based data regarding whether the variable really supports the sustainable empowerment of poor-households women. This study used the quantitative method through the survey technique. The samples of this study included 250 people collected from five regencies in Indonesia by using a multiple-stage random sampling. The data were analyzed with structural equation modeling. The results show that social support has a significant positive impact on the learning process; social support has a direct negative impact on self-efficacy. The learning process has a direct positive influence on self-efficacy, while social support has a non-significant impact on self-reliance. The learning process has a direct influence on self-reliance. Social support and the learning process both have significant positive impact on self-efficacy. Social support, learning process, and self-efficacy simultaneously have a positive impact on self-reliance in productive economic activities.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.625-633
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• 2020

This study aims to empirically investigate the influence of organizational capability and organizational learning on the financial performance of family-business type small- and medium-sized enterprises (SMEs). In addition, this study examines the moderating role of SMEs' ages and the managers' experiences in the relationship between organizational capability and organizational learning on the SMEs financial performance. This study is a basic exploratory research conducted by using an empirical survey, i.e., sampling of the businessman (the owner) of family-business type SMEs cross-functional in the area of DIY. The study uses purposive sampling. The respondents are the SME businessmen from the various business sectors in Yogyakarta, Indonesia. The number of respondents is 150. Hypothesis testing used SPSS program's moderation regression approach; validity and reliability testing used confirmatory factor analysis and Cronbach's alpha. The result of this study shows that organizational capability positively and significantly affects the financial performance. Also, organizational learning significantly affects the financial performance. The organization's age factor does not moderate the relationship between organizational capability and the financial performance, but it is significant on the organizational learning. The factor of manager's experience moderates insignificantly on the relationship between organizational capability and financial performance. However, it is significant to the organizational learning.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.591-601
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• 2021

This study examined the effect of branding capability on business performance moderated by learning capability. This study was conducted with small- and medium-sized enterprises (SMEs) of coffee cafes in the ex-Besuki region, East Java, Indonesia, covering four regencies located around coffee-producing areas with geographical indication (GI) certification. 150 managers of coffee cafe were sampled using the census technique. Data were collected by questionnaires distributed to the coffee cafe managers. The data were then analyzed by using simple regression analysis, Moderation Regression Analysis (MRA) and Moderated MultiGroup Analysis (MMA). The results showed that learning capability positively and significantly affect business performance, and learning capability moderated/enhanced the effect of branding capability on business performance. The findings of this study suggest that branding capability and learning capability play a crucial role in the performance of coffee cafe business especially in the dynamic environment. Coffee cafe managers need to take concrete steps to improve their branding capability and learning capability and they also need to improve their ability to interact with their environment and be committed in managing the coffee cafe. Therefore, it is imperative that the role of branding capability and learning capability be optimized in order to improve the business performance of the coffee cafe.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.300-305
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• 2023

Audience reactions in response to remote virtual performances must be compressed before being transmitted to the server. The server, which aggregates these data for group insights, requires a distribution code for the transfer. Recently, distributed learning algorithms such as federated learning have gained attention as alternatives that satisfy both the information security and efficiency requirements. In distributed learning, no individual user has access to complete information, and the objective is to achieve a learning effect similar to that achieved with the entire information. It is therefore important to distribute interdependent information among users and subsequently aggregate this information following training. In this paper, we present a new extension technique for minimal code that allows a new minimal code with a different length and Hamming weight to be generated through the product of any vector and a given minimal code. Thus, the proposed technique can generate minimal codes with previously unknown parameters. We also present a scenario wherein these combined methods can be applied.

• Journal of Korea Artificial Intelligence Association
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• v.2 no.1
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• pp.25-30
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• 2024

Kodály hand signs are symbols that intuitively represent pitch and note names based on the shape and height of the hand. They are an excellent tool that can be easily expressed using the human body, making them highly engaging for children who are new to music. Traditional hand signs help beginners easily understand pitch and significantly aid in music learning and performance. However, Kodály hand signs have distinctive features, such as the ability to indicate key changes or chords using both hands and to clearly represent accidentals. These features enable the effective use of Kodály hand signs. In this paper, we aim to investigate the changes in recognition rates according to the complexity of scales by creating a device for learning Kodály hand signs, teaching simple Do-Re-Mi scales, and then gradually increasing the complexity of the scales and teaching complex scales and children's songs (such as "May Had A Little Lamb"). The learning device utilizes accelerometer and bending sensors. The accelerometer detects the tilt of the hand, while the bending sensor detects the degree of bending in the fingers. The utilized accelerometer is a 6-axis accelerometer that can also measure angular velocity, ensuring accurate data collection. The learning and performance evaluation of the Kodály learning device were conducted using Python.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.203-208
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• 2024

The convergence of deep learning and smart factory is drawing a lot of attentions from not only industrial but also academic circles. The objective of this article is to quantitatively review on deep learning and smart factory from 2010 to 2023. This research analyzed the 138 articles, extracted from the Core Collection of Web of Science, in terms of four dimensions such as the main trend in article publications, the main trend in article citations, the distribution of article publications by research area, and the keywords representing the main contents of published articles. The quantitative review results reveal the following four points: First, the article publications drastically grew from 2019 to 2022 in its annual trend. Second, the article citations have rapidly grown since 2018. Third, Engineering, Computer Science, and Telecommunications are the top 3 research areas composing the 138 articles. Fourth, it is the top 10 keywords such as 'deep', 'learning', 'smart', 'detection', factory', 'data', 'system', 'manufacturing', 'neural', and 'network' that represent the main contents of the 138 articles published from 2010 to 2023 in deep learning and smart factory. These findings revealed by this quantitative review will be significantly useful for deepening and widening relevant future research on deep learning and smart factory.

• Journal of Distribution Science
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• v.11 no.6
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• pp.51-58
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• 2013

Purpose - Nowadays, more than ever before, fierce competition, deep market segmentation, short product life cycles, and intensifying customer needs are putting increasing pressure on franchise's organizations to satisfy their customers by creating market-oriented relationships with and enhancing their market knowledge of them. One way that this might be achieved is by establishing deep ties (i.e., job commitment and job satisfaction) with their employees. Therefore, the purpose of this study is to examine how two important constructs of franchises' strategic efforts, LO (learning orientation) and RMO (relationship marketing orientation), affect job satisfaction, given the mediating role of job commitment. A franchise system comprises a set of contractual arrangements by which mutual obligations are performed. An organizational learning goal motivates employees to improve their abilities and master the tasks they perform. Relationship marketing, in addition, is to identify, establish, maintain, and enhance relationships with customers and other stakeholders to ensure that the objectives of all parties are met and this is done through the mutual exchange of promises. In a relationship marketing orientation, then, a firm creates, maintains, and enhances a strong relationship with its customers by sustaining long-term ties. This study was designed to examine the evolution of various theoretical approaches to franchise systems in order to determine whether theories about firms have significantly affected the franchise system. To this end, the authors developed a structural model consisting of several constructs. Previous studies have suggested that franchises' learning and relationship marketing orientations are important occupational immersion dimensions driving job satisfaction. Research design, data, methodology - We empirically tested a process of how the learning orientation and the relationship marketing orientation influence job commitment and job satisfaction using survey data drawn from 150 responding franchisees who were interviewed about their individual tendencies. Results - The results of this study provide empirical evidence that learning orientation, relationship marketing orientation, and job commitment all influence franchisees' job satisfaction. The results of this study indicate that, first, learning orientation had a significant effect on job satisfaction; second, relationship marketing orientation was positively related to job commitment; third, job commitment had a significant effect on job satisfaction. We also found that relationship marketing orientation and job satisfaction were mediated by job commitment. Conclusions - The findings of this study confirm the importance of learning orientation and relationship marketing orientation in maintaining a positive marketing relationship between franchiser and franchisee from to the perspective of the market. This indicates that franchiser support such as educational programs provided by the franchiser will help franchisees attain higher business management achievement and satisfaction. Moreover, a positive relationship between franchisees and consumers can be maintained through tie effects. Our findings also suggest that learning orientation plays a critical role in job satisfaction within the franchise system.