• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.489-498
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• 2022

Recently, the textile industry, which is labor-intensive, is attempting to reduce process costs and optimize quality through artificial intelligence. However, the fiber spinning process has a high cost for data collection and lacks a systematic data collection and processing system, so the amount of accumulated data is small. In addition, data imbalance occurs by preferentially collecting only data with changes in specific variables according to the purpose of fiber spinning, and there is an error even between samples collected under the same fiber spinning conditions due to difference in the measurement environment of physical properties. If these data characteristics are not taken into account and used for AI models, problems such as overfitting and performance degradation may occur. Therefore, in this paper, we propose an outlier handling technique and data augmentation technique considering the characteristics of the spinning process data. And, by comparing it with the existing outlier handling technique and data augmentation technique, it is shown that the proposed technique is more suitable for spinning process data. In addition, by comparing the original data and the data processed with the proposed method to various models, it is shown that the performance of the tensile tenacity and elongation prediction model is improved in the models using the proposed methods compared to the models not using the proposed methods.

• The Korean Journal of Franchise Management
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• v.1 no.1
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• pp.19-42
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• 2010

Since circulation market whole surface opening, traditional market is real condition that is looked away more gradually to consumer as reasons of international retail firms and domestic enterprise firms to enter distribution industry, internet mail order rapid increase by information-oriented society, the pursuit of upgradation and normalization by elevation of income level and consumption pattern change that consideration convenience with young consumers as the central figure. Therefore, the purpose of this study is to analyze stagnation cause of traditional market and problem within a change of new distribution environment, and to develop new approaches for dealing with domestic traditional market relationship prompting competition through activation example analysis of foreign traditional market and domestic traditional market. The result of the study indicated that there are a lot of cases that are begun by a few's merchant with leadership that has been will which is strong in activation in beginning in market's occasion that succeed in activation. In particular, software side such as operational efficiency or marketing expertise strengthening of management is that effect is high relatively than hardware side market activation. Also essential to the settlement of credit transactions using credit cards is important for expanding the effort, for the expansion of credit card merchant credit card advantage and raise awareness among traders about the expected effects is needed. Though these study finding submits plan that create market ecosystem so that many consumers may become place that could visit naturally and create pleasure and convenience, and time, monetary, psychological value of shopping to traditional market, there is sense.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.1-20
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• 2022

As the global business environment is rapidly changing due to the 4th industrial revolution, new jobs that did not exist before are emerging. Among them, the job that companies are most interested in is 'Data Scientist'. As information and communication technologies take up most of our lives, data on not only online activities but also offline activities are stored in computers every hour to generate big data. Companies put a lot of effort into discovering new opportunities from such big data. The new job that emerged along with the efforts of these companies is data scientist. The demand for data scientist, a promising job that leads the big data era, is constantly increasing, but its supply is not still enough. Although data analysis technologies and tools that anyone can easily use are introduced, companies still have great difficulty in finding proper experts. One of the main reasons that makes the data scientist's shortage problem serious is the lack of understanding of the data scientist's job. Therefore, in this study, we explore the job competencies of a data scientist by qualitatively analyzing the actual job posting information of the company. This study finds that data scientists need not only the technical and system skills required of software engineers and system analysts in the past, but also business-related and interpersonal skills required of business consultants and project managers. The results of this study are expected to provide basic guidelines to people who are interested in the data scientist profession and to companies that want to hire data scientists.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.7
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• pp.325-332
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• 2023

Currently, the world's population has already entered a super-aging era, and the rate is expected to increase rapidly to about 40% by 2050. However, the rapid development of automation technology and the online service sector, the main technologies of the Fourth Industrial Revolution, are still further isolating them in a world where many inconveniences and development technologies are applied. As such, alienation in daily life is widely expanded in various fields, but the financial service sector is one of the must-use areas regardless of age because of its strong nature in the public service sector, and is a very important factor in the period when branches are rapidly decreasing. However, the current utilization rate of mobile banking services is not around 5%, so users over 60 are rarely able to use them. The UX design of the most frequently used remittance service screen in mobile banking services was proposed, and the difficulty of trying to find the preferred bank among 56 or more banks was solved by analyzing the usage rate of each bank and dividing it into three stages by age group from 50 or older. In addition, it was designed to strengthen customized services by showing their recently used banks as the top priority. The design proposed in this study obtained an average of 4.8 points or more out of 5 points as a result of usability satisfaction through interviews with less than 50 senior groups. This study is believed to help each bank upgrade its different mobile banking designs in a unified manner.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.671-679
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• 2023

This study aims to establish an evaluation model by quantifying the evaluation index as a follow-up study to the development of evaluation index for work-study parallel learning companies. An evaluation model was established by verifying the 2nd level components based on the quantitative factors of the learning company, the qualitative factors, the competency factors of the person in charge, and the competency factors of the learning workers, which are the highest-level components derived from previous study. For the evaluation of a learning company, an AHP survey was conducted with experts in charge of the company consulting to derive important factors that determine the quality of on-site education and training, and the evaluation model of the learning company was completed and grouped by calculating the weight between evaluation items proceeded. Work-study parallel program was promoted as a key policy to resolve the mismatch between industrial sites and school education and realize a competency-centered society, and as of December 2022, 16,664 companies participated in the training. Learning companies play a very important role as education and training supply organizations that conduct field training. It is expected that the support and consulting plan for each level of learning companies according to the evaluation model presented in this study will be used as basic data to improve the quality of work-study parallel program.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.57-68
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• 2023

With the technological development in the era of the 4th Industrial Revolution, technologies using HMD are being applied in various fields. HMD is especially useful in virtual reality fields such as AR/VR, and is very effective in receiving vivid impressions from users located in remote locations. According to these characteristics, the frequency of using HMD is increasing in the field related to collaboration. However, when HMD is applied to collaboration, communication between experts located in remote locations and workers located in the field is not smooth, causing various problems in terms of usability. In this paper, remote experts and workers in the field use HMD to solve various problems arising from collaboration, design/propose new types of HMD structures and functions that enable more efficient collaboration, and verify their usability using SUS evaluation techniques. As a result of the SUS evaluation, the new type of HMD structure and function proposed in this paper was 86.75points, which is believed to have greatly resolved the restrictions on collaboration and inconvenience in use of the existing HMD structure. In the future, when the HMD structure and design proposed in this paper are actually applied, it is expected that the application technology using HMD will expand rapidly.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.105-115
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• 2022

This study aims to investigate the Effect of Money Rush on Entrepreneurial Opportunity Recognition for college students in Busan and Gyeongnam area. We also examine whether Entrepreneurship has a mediating effect between Money Rush and Entrepreneurial Opportunity Recognition. Since the outbreak of COVID-19, digital transformation of the industry have greatly changed the world of work, and job insecurity is becoming more prevalent. As income inequality expands due to the disparity in asset income, the Money Rush phenomenon, which prefers to increase asset income through investment rather than earned income, is becoming common. Money Rush secures an income pipeline and is divided into side hustles and investments that actively utilize Leverage to maximize profits. The findings of this study confirm that Money Rush has a positive effect on Entrepreneurial Opportunity Recognition and a partially positive effect on Entrepreneurship. Entrepreneurship has a partial mediating effect between Money Rush and Entrepreneurial Opportunity Recognition. The study analysis is expected to contribute to strengthening college students' competencies in Entrepreneurial Opportunity Recognition and presenting the policy and practical directions necessary to promote Start-up.

• Journal of Practical Agriculture & Fisheries Research
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• v.26 no.1
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• pp.22-29
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• 2024

In this study, we summarized the definition of smart vegetable seedling production technology, analysis of smart seedling production system, a hardware and software configuration model for smart seedling production system, research and development trends in smart seedling production system, and proposed future research and development plans for smart seedling production technology. Smart vegetable seedling production is a data-based seedling production, management, and distribution system that utilizes 4th Industrial Revolution technology to improve seedling productivity and quality. The production of vegetable seedlings using smart seedling production technology can be efficiently managed by collecting, analyzing, and managing information on seedlings, environment, and tasks at each stage of production by linking with the smart seedling integrated management system. However, there is still a lack of standardization of seedling standards and quality for each vegetable crop to establish smart seeding production technology, as well as development of smart seedling production element technology, which requires national wide R&D support.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.76-81
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• 2024

Recently, agricultural methods are changing from experience-based agriculture to data-based agriculture. Changes in agricultural production due to the 4th Industrial Revolution are largely occurring in three areas: smart sensing and monitoring, smart analysis and planning, and smart control. In order to realize open-field smart agriculture, information on the physical and chemical properties of soil is essential. Conventional physicochemical measurements are conducted in a laboratory after collecting samples, which consumes a lot of cost, labor, and time, so they are quickly measured in the field. Measurement technology that can do this is urgently needed. In addition, a soil analysis system that can be carried and moved by the measurer and used in Korea's rice fields, fields, and facility houses is needed. To solve this problem, our goal is to develop and commercialize software that can collect soil samples and analyze the information. In this study, basic soil composition measurement was conducted using soil composition measurement sensors consisting of hardness measurement and electrode sensors. Through future research, we plan to develop a system that applies soil sampling using a CCD camera, ultrasonic sensor, and sampler. Therefore, we implemented a sensor and soil analysis UI that can measure and analyze the soil condition in real time, such as hardness measurement display using a load cell and moisture, PH, and EC measurement display using conductivity.

• Smart Media Journal
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• v.13 no.4
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• pp.33-48
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• 2024

With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.