• Journal of East Asia Management
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• v.1 no.1
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• pp.29-49
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• 2020

In an intensively competitive global market, small-and medium-sized firms are puzzled about how to develop sustainable competitive advantages against global rivalries, thus leading satisfactory economic performance. However, despite the roles and contributions of such small-and medium-sized firms in the local community and national economies in Japan, little guidance has been offered to the practical issues related to their strategic behaviors toward global management. To fill this notable knowledge gap, this study aims to investigate the conditions in which how Japanese small-and medium-sized could dominates global market, which is one of key challenges in the literature of small business and entrepreneurship. To obtain better insights to this research area, this study undertakes an in-depth interview survey with I.S.T (Industrial Summit Technology) Corporation that shows off the highest global market share (40 per cent) with seamless polyimide tube product widely used in office automation equipment (e.g., copiers and printers). This method of survey is designed to deeply understand historical considerations about how I.S.T Corporation could dominate in the global market of such seamless polyimide tube product. Based on findings drawn from an interview, this study identifies five major factors enabling I.S.T Corporation to be a competitive global hidden company: vision sharing through founder's entrepreneurship, core competence, strategic network, risk management, and employee engagement. Specifically, to become a global hidden champion, sharing the vision motivating employees to partake in shaping company's future will be the first step on the road to global success through founder's entrepreneurship. However, in order to achieve such a vision, the importance of company's core competence cannot be overemphasized, which differentiates your customer solution with those of competitors. As such, a group of experts will be naturally formed and demonstrates your expertise in the global market, thereby building sustainable competitiveness. On the other hand, to maintain sustainable competitiveness, it is necessary to make up for the weaknesses small-and medium-sized firms suffer from competitive resources while strengthening their own strengths through strategic networks with external organizations. Here, every company has to understand the critical role of risk management, which is essential in this process of being global company so as not to lose your own strengths. Last but not least, do not forget the significant effects of employee engagement in firm performance. To enhance employees' engagement, a company has to create an ideal organization culture which fits into company's history and personality. In doing so, such organization culture can allow the vision and strategy to be implemented into detailed business tactics while facilitating employees to challenge the status quo by experimenting with creative ideas.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.1
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• pp.15-26
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• 2013

IP-based Wireless Sensor Networks (IP-WSNs) are gaining importance for their broad range of applications in health-care, home automation, environmental monitoring, industrial control, vehicle telematics and agricultural monitoring. In all these applications, mobility in the sensor network with special attention to energy efficiency is a major issue to be addressed. Because of the energy inefficiency of networks-based mobility management protocols can be supported in IP-WSN. In this paper we propose a network based mobility supported IP-WSN protocol called Multicasting-based inter-Domain Mobility Management Scheme in Sensor-based Fast Proxy Mobile IPv6 Networks (mSFP). Based on [8,20], We present its network architecture and evaluate its performance by considering the signaling and mobility cost. Our analysis shows that the proposed scheme reduces the signaling cost, total cost, and mobility cost. With respect to the number of IP-WSN nodes, the proposed scheme reduces the signaling cost by 7% and the total cost by 3%. With respect to the number of hops, the proposed scheme reduces the signaling cost by 6.9%, the total cost by 2.5%, and the mobility cost by 1.5%. With respect to the number of IP-WSN nodes, the proposed scheme reduces the mobility cost by 1.6%.

• Journal of Fashion Business
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• v.1 no.2
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• pp.46-54
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• 1997

The purpose of this study is to understand women's wear manufacturing industries. First, the study was to investigate the present production systems and how much the automatic facility are by comparing them. This study enhanced more efficient, stable, and suitable work line. This intern will direct the way in which automatic facilities will be created. Second, through this study on the general character of the inspectors, the ratio of impaired goods, and the reasons for unsatisfactory goods, I intended to find out a way to decrease the impaired goods and to produce competitive and high quality goods. The results of the survey can be summarized as follows; 1. The result of the research on the automatic industrial facilities shows that the majority of the factories (77.4%) are 40% below the automatic facility rate. The reasons for this according to order are that was a deficit in money, no reason for expensive machines, and lack of the technique and the number of workers required to handle the machines. 2. At this time, the most required equipments are shown according to its importance; automatic sewing machine, automatic cutting machine, automatic spreading machine, and finishing & pressing machine. So in the women's wear manufacturing industries, they think that they need more automatic cutting machine, automatic spreading machine in the cutting field rather than high price automatic machine in the sewing field such as pattern former, pocket welting, automatic sleeve connecting machine and automatic label connecting machine. 3. The result of the research in the goods quality shows that the average impaired rate is 12.7% at the first inspection. In addition the average rate for complete impaired rate is 1.52%. The line system shows that it has a impaired rate that is double the rate of the pair system. Because of this, the industries plan to combine the line system and pair system to create an improved and suitable production system which can boost the quality and productivity of the goods. 4. The fabric is the main point of the impaired goods. The factors of the impaired goods in manufacturing are the lack of mental abilities of the worker, impaired fabrics and a lack of cooperation in the working system. Furthermore, there is a lack of technique for new material. 5. To prohibit impaired goods in manufacturing, there need to be a way to educate the workers and to enhance the workers' mind on the productive goods. Also there need to increase in the investments of automatic production machines. Finally there need to be a standardized working line. Therefore, there need to be an improvement on the management of the production of goods, the development of technique and an increase in the education for the workers, with this there will be a decrease in impaired goods, and an increase in better quality of goods to enforce the domestic apparel industries.

• Journal of Preventive Medicine and Public Health
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• v.27 no.2 s.46
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• pp.230-241
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• 1994

Though people occupationally exposed to machineries and automation in the industrialized society desire work involving decreased strength, due to the continuous and repetitive activities, a new industrial stress is present. Studies on prevalence of musculoskeletal disease and their related risk factors have evolved. In this study in relation to work tasks, we investigated the differences in musculoskeletal symptoms occurring In each body region. The results of the survey were as follows. 1. When comparing age, level of education, work duration, job satisfaction and leisure time activities according to work task, age in control group was $38.83{\pm}5.5$, in comparison to the other 2 groups was smaller(p<0.05), and level of education in control group was higher (p<0.05). Work duration in the cutting department was $8.04{\pm}4.99$ years longer than the other 2 groups (p<0.05), but there was no difference in the job satisfaction and leisure time activities. 2. The mean of symptom scores of each work task was 1.54 in the cutting department, 1.57 in the press department and 1.59 in the control group, and there was no significant differnce in the 3 groups. The mean of symptom scores for upper extremities in the control group was low but no statistically significant diffrence was shown. 3. When comparing the mean of symptom score according to work task in the each body region, in the shoulder region, the symptom score in the press department which desired strength was higher than the other 2 groups but no significant difference was shown. In the wrist region the cutting department scored 1.01 and in comparison to the other 2 groups was significantly increased (p<0.05). 4. The results of the univariate regression analysis on the major individual risk factors associated with musculoskeletal symptom relating work showed that previous symptom complaints in the same body region was significant risk factor(p<0.001) in the whole body Besides wrist, hip, and knee, psychological problem was shown to be a significant factor(p<0.05). And the body regions which work task was significant risk factor were wrist and neck region (p<0.05). 5. The results of the multiple regression analysis involving significant factors of each body region from the univariate regression analysis showed that previous symptom complaint in whole body region(p<0.001) and psychological problem in the shoulder, elbow and lumbar region (p<0.05) were significant factors, and work task was significant factor in the wrist (p<0.05).

• Journal of Navigation and Port Research
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• v.29 no.5 s.101
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• pp.395-402
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• 2005

The most important point when we engage on waterway dredging work is supplying safe navigational passage to the vessels underway by narrowing dredge work area and removing submerged dangers. In order to meet this end it is necessary to use auxiliary equipment for shifting actively and mooring and adopt automation of dredging work by integrating information on real time position, dredging depth, and work information. The dredger with a spud control system in this study, by the way, is able to employed on continuous dredging work with the narrowest working area allowing wide and safe passages to vessels underway, by moving the dredger to the working zone with the spud controlled automatically. Furthermore, it has been improved definitely compared with the existing dredging process management system such that it shows the track of spud and working depth on the electronic navigation chart of window, together with the final outcome of dredging work. The test dredging work at the entrance of Busan North Port for system evaluation showed that actual working time available was twice of the one by the existing anchor system, and that it reduced $38\%$ of time for preparation work and one man power.

• The Journal of Bigdata
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• v.6 no.1
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• pp.23-35
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• 2021

In the era of the 4th industrial revolution, smart factories have received great attention, where production and manufacturing technology and ICT converge. With the development of IoT technology and big data, automation of production systems has become possible. In the advanced manufacturing industry, production systems are subject to unscheduled performance degradation and downtime, and there is a demand to reduce safety risks by detecting and reparing potential errors as soon as possible. This study designs a model based on supervised and unsupervised learning for detecting anomalies. The accuracy of XGBoost, LightGBM, and CNN models was compared as a supervised learning analysis method. Through the evaluation index based on the confusion matrix, it was confirmed that LightGBM is most predictive (97%). In addition, as an unsupervised learning analysis method, MD, AE, and LSTM-AE models were constructed. Comparing three unsupervised learning analysis methods, the LSTM-AE model detected 75% of anomalies and showed the best performance. This study aims to contribute to the advancement of the smart factory by combining supervised and unsupervised learning techniques to accurately diagnose equipment failures and predict when abnormal situations occur, thereby laying the foundation for preemptive responses to abnormal situations. do.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.241-262
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• 2021

This paper reviewed the necessity of a information and communication technology (ICT)-based smart livestock system as a development strategy for the animal life industry in the future. It also predicted the trends of livestock and animal food until 2050, 30 years later. Worldwide, livestock raising and consumption of animal food are rapidly changing in response to population growth, aging, reduction of agriculture population, urbanization, and income growth. Climate change can change the environment and livestock's productivity and reproductive efficiencies. Livestock production can lead to increased greenhouse gas emissions, land degradation, water pollution, animal welfare, and human health problems. To solve these issues, there is a need for a preemptive future response strategy to respond to climate change, improve productivity, animal welfare, and nutritional quality of animal foods, and prevent animal diseases using ICT-based smart livestock system fused with the 4th industrial revolution in various aspects of the animal life industry. The animal life industry of the future needs to integrate automation to improve sustainability and production efficiency. In the digital age, intelligent precision animal feeding with IoT (internet of things) and big data, ICT-based smart livestock system can collect, process, and analyze data from various sources in the animal life industry. It is composed of a digital system that can precisely remote control environmental parameters inside and outside the animal husbandry. The ICT-based smart livestock system can also be used for monitoring animal behavior and welfare, and feeding management of livestock using sensing technology for remote control through the Internet and mobile phones. It can be helpful in the collection, storage, retrieval, and dissemination of a wide range of information that farmers need. It can provide new information services to farmers.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.1
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• pp.28-36
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• 2022

Currently, the automation and intelligence of the shipbuilding industry have improved its work production capacity and cost competitiveness, but the reduction rate of safety accidents among industrial site workers is still low and the damage caused by safety accidents is very serious, so there is a need for improvement according to the workplace. This research aims to demonstrate the connectivity between smart safety helmets in the demonstration area to verify the effectiveness along with the development of smart helmets for worker protection and environmental safety in shipyards. For efficient communication between workers, impact noise of over 95dB was confirmed in the workplace, and noise reduction was required. To solve this problem, the filtering performance was compared and analyzed using the Butterworth, Chebyshev, and elliptic algorithms. The connectivity test and noise reduction method between smart helmets proposed in this study will increase the usability and safety of the field through the development of advanced smart helmets tailored to the shipbuilding workplace in the future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.1019-1034
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• 2022

Malware attacks become more prevalent in the hyper-connected society of the 4th industrial revolution. To respond to such malware, automation of malware detection using artificial intelligence technology is attracting attention as a new alternative. However, using artificial intelligence without collateral for its reliability poses greater risks and side effects. The EU and the United States are seeking ways to secure the reliability of artificial intelligence, and the government announced a reliable strategy for realizing artificial intelligence in 2021. The government's AI reliability has five attributes: Safety, Explainability, Transparency, Robustness and Fairness. We develop four elements of safety, explainable, transparent, and fairness, excluding robustness in the malware detection model. In particular, we demonstrated stable generalization performance, which is model accuracy, through the verification of external agencies, and developed focusing on explainability including transparency. The artificial intelligence model, of which learning is determined by changing data, requires life cycle management. As a result, demand for the MLops framework is increasing, which integrates data, model development, and service operations. EXE-executable malware and documented malware response services become data collector as well as service operation at the same time, and connect with data pipelines which obtain information for labeling and purification through external APIs. We have facilitated other security service associations or infrastructure scaling using cloud SaaS and standard APIs.

• The Journal of Bigdata
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• v.6 no.2
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• pp.17-28
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• 2021

Current development of technologies related to 4^th industrial revolution and the pandemic of COVID-19 lead the rapid expansion of e-marketplace. The level of competition among several companies gets increased by introducing different strategies. To cope with the current change in the market and satisfy the customers who request the better delivery service, the new concept, fulfillment, has been introduced. It makes the leadtime of process from order picking to delivery reduced and the efficiency improved. Still, the efficiency of operation in fulfillment centers constrains the service level of the entire delivery process. In order to solve this problem, several different approaches for demand forecasting and coordinating supplies using Bigdata, IoT and AI, which there exists the trivial limitations. Because it requires the most lead time for operation and leads the inefficiency the process from picking to packing the ordered items, the logistics service providers should try to automate this procedure. In this research, it has been proposed to develop the efficient plans to automate the process to move the ordered items from the location where it stores to stage for packing using AGV and AMR. The efficiency of automated devices depends on the number of items and total number of devices based on the demand. Therefore, the result of simulation based on several different scenarios has been analyzed. From the result of simulation, it is possible to identify the several factors which should be concerned for introducing the automated devices in the fulfillment centers. Also, it can be referred to make the optimal decisions based on the efficiency metrics.