• Information Systems Review
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• v.8 no.1
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• pp.287-303
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• 2006

Recently, Investment on HRM, particularly, on training and development, in companies has been increased. Therefore, HR managers pay attention to action learning that has the practical effect on performance. The purpose of this study is to introduce action learning as an efficient training method and simultaneously to raise operational issues from the case study. This study analyses a training and development program applying action learning for team manager candidates in corporate Hyosung from September, 2005 to January, 2006. The findings are as follows: First, inefficient processes are thrown out by the process reengineering applying action learning. Second, the training and development activity is maximized by the integrated use of internal and external facilitators. Third, the steady support of executives and the driving force of HRD managers are considered as main success factors.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_2
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• pp.163-171
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• 2020

The condition of tire tread is a key parameter closely related to the driving safety of a vehicle, which affects the contact force of the tire for braking, accelerating and cornering. The major factor influencing the contact force is tread wear, and the more tire tread wears out, the higher risk of losing control of a vehicle exits. The tire tread condition is generally checked by visual inspection that can be easily forgotten. In this paper, we propose the intelligent tire (iTire) system that consists of an acceleration sensor, a wireless signal transmission unit and a tread classifier. In addition, we also presents classification algorithm that transforms the acceleration signal into the frequency domain and extracts the features of several frequency bands as inputs to an artificial neural network. The artificial neural network for classifying tire wear was designed with an Multiple Layer Perceptron (MLP) model. Experiments showed that tread wear classification accuracy was over 80%.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.113-116
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• 2015

Generally, in the railway vehicle the driving force of gravity happens by the high-speed running and the repetitive impulse cause the degradation and the malfunction phenomenon shows differently because the durability of each component changes according to the internal and external causes. The maintenance of propulsion control device which is played the very important role as to the stable service of the railway vehicle is greatly important among them. Therefore maintenance training propulsion control device simulator is needed to maximize learning through repetition and improve the maintenance practical skills training. This paper designed the railway vehicle running device with a miniature for the railway vehicle maintenance training and developed a propulsion control device simulator equipped the imitation steering wheel.

• Journal of Korea Entertainment Industry Association
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• v.15 no.3
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• pp.183-192
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• 2021

This study was purposed to explore the learning culture through the related literature and research review in Jewish Havruta which has interaction, critical reflection, and the driving force creating a better world. The prior researches on Havruta mainly tend to as ways to increase learners' interest in learning and studies as curriculum or teaching methods such as creativity, understanding, and problem-solving skills. However, Havruta is not just method to study subjects, but rather a process of developing thinking through dialogue and discussion. Therefore, Havruta's essential meaning as a lifelong learning should be explored. Studies showed that Jews embody the thinking process from interpreting, analyzing, setting up logic, questioning, discussing, and debating Talmud with others anytime, anywhere, and anyone throughout their learning culture. It develops basic skills for life, forms an integrated personality in relationships with others, and continuously conducts lifelong learning to shape one's own beings. Therefore, lifelong learning culture would be sharing information that one has in the process of discussion through dialogue between two or more people, and supporting and encouraging the other's failure or fear rather than attacking them. The embodiment of thinking process in which people teach and learn eachother, accept the difference, and expand thought would be significant foundation to create lifelong learning culture.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.429-440
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• 2001

To achieve a computer tutor framework with high learning effects as well as practicality, the goal of this research has been set to developing an intelligent tutor for problem-solving in mathematics domain. The maine feature of the CyberTutor, a computer tutor developed in this research, is the facilitation of a learning environment interacting in accordance with the learners differing inferential capabilities and needs. The pedagogical information, the driving force of such an interactive learning, comprises of tutoring strategies used commonly in various domains such as phvsics and mathematics, in which the main contents of learning is the comprehension and the application of principles. These tutoring strategies are those of testing learners hypotheses test, providing hints, and generating explanations. We illustrate the feasibility and the behavior of our propose framework with a sample problem-solving learning in geometry. The proposed tutorial framework is an advancement from previous works in several aspects. Firstly, it is more practical since it supports handing of a wide range of problem types, including not only proof types but also finding-unkown tpes. Secondly, it is aimed at facilitating a personal tutor environment by adapting to learners of varying capabilities. Finally, learning effects are maximized by its tutorial dialogues which are derived from real-time problem-solving inference instead of from built-in procedures.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.541-546
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• 2005

Tracking control of an automatic pipe cutting robot (APCROMB) is studied. Using magnetic force APCROMB, which is designed and developed in Kyung Hee University, binds itself to the pipe and executes unmanned cutting process. The gravity effect on the movement of APCROMB varies as it rotates around the cylindrical pipe laid in the gravitational field. To maintain a constant velocity and consistent cutting performance against the varying gravitational effect, the authors adopt a multi-rate repetitive learning controller (MRLC), which learns the required effort to cancel the repetitive tracking errors caused by nonlinear effect. In addition to the varying gravity effect other types of nonlinear disturbances including backlash in the driving system and the slip between the wheels of APCROMB and the pipe also cause degradation in the cutting process. In order to identify those nonlinear disturbances the position estimation based on the encoder attached at the motor is not good enough. To identify the absolute angular position of APCROMB the authors propose the angular position estimation based on the signals from a MEMS-type two-axis accelerometer mounted on APCROMB. The tracking performances of APCROMB with a MRLC using the encoder-based position estimation is experimentally measured and results are shown. Also the difference between the encoder-based angular displacement measurement and the accelerometerbased angular displacement measurement is included.

• 한국IT서비스학회:학술대회논문집
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• 2008.11a
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• pp.127-130
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• 2008

Recently, a wide variety of research on the knowledge-based industries, which are considered a key area of social science research, has been conducted. In this light, this study examines a case of knowledge diffusion taken from the IT service field. The IT service industry has been considered difficult to diffuse due to its unique technological regimes and sophisticated market demand. In particular, the established public service systems have limited markets and encompass national characteristics, thereby making their international diffusion difficult. However, despite these limitations, the automated customs system ASYCUDA has been distributed successfully and is now operating in about 100 countries, making the case very unusual. Using various industrial innovation models, and an analysis of lead markets, with regard to ASYCUDA, this research examines patterns of technological learning activities by actors, characteristics of the lead markets, and paths of technology transfer. The findings indicate that when active technology providers attempt to streamline and standardize the technology to make it suitable for the characteristics of the initial technology application areas(lead markets), this helps to diffuse the technology to passive recipients and the surrounding nations. The findings also confirm that south-south cooperation in the acquired technologies was of considerable help in sharing knowledge among the passive technology recipients, and that the active technology providers' programmed, well-organized technology assistance was a key driving force behind technology transfer and diffusion between the surrounding nations.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.1-20
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• 2021

As the Great Reset is discussed at the World Economic Forum due to the COVID-19 pandemic, artificial intelligence, the driving force of the 4th industrial revolution, is also in the spotlight. However, corporate research in the field of artificial intelligence is still scarce. Since 2000, related research has focused on how to create value by applying artificial intelligence to existing companies, and research on how startups seize opportunities and enter among existing businesses to create new value can hardly be found. Therefore, this study analyzed the cases of startups using the comprehensive framework of the multi-level perspective with the research question of how artificial intelligence based startups, a sub-industry of software, have different innovation patterns from the existing software industry. The target firms are gazelle firms that have been certified as venture firms in South Korea, as start-ups within 7 years of age, specializing in machine learning modeling purposively sampled in the medical, finance, marketing/advertising, e-commerce, and manufacturing fields. As a result of the analysis, existing software companies have achieved process innovation from an enterprise-wide integration perspective, in contrast machine learning technology based startups identified unit processes that were difficult to automate or create value by dismantling existing processes, and automate and optimize those processes based on data. The contribution of this study is to analyse the birth of artificial intelligence-based startups and their innovation patterns while validating the framework of an integrated multi-level perspective. In addition, since innovation is driven based on data, the ability to respond to data-related regulations is emphasized even for start-ups, and the government needs to eliminate the uncertainty in related systems to create a predictable and flexible business environment.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1216-1221
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• 2022

Ships tend to be larger to increase the efficiency of cargo transportation. Larger ships lead to increased travel time for ship workers, increased work intensity, and reduced work efficiency. Problems such as increased work intensity are reducing the influx of young people into labor, along with the phenomenon of avoidance of high intensity labor by the younger generation. In addition, the rapid aging of the population and decrease in the young labor force aggravate the labor shortage problem in the maritime industry. To overcome this, the maritime industry has recently introduced technologies such as an intelligent production design platform and a smart production operation management system, and a smart autonomous logistics system in one of these technologies. The smart autonomous logistics system is a technology that delivers various goods using intelligent mobile robots, and enables the robot to drive itself by using sensors such as lidar and camera. Therefore, in this paper, it was checked whether the mobile robot could autonomously drive to the stop sign by detecting the passage way of the ship deck. The autonomous driving was performed by detecting the passage way of the ship deck through the camera mounted on the mobile robot based on the data learned through Nvidia's End-to-end learning. The mobile robot was stopped by checking the stop sign using SSD MobileNetV2. The experiment was repeated five times in which the mobile robot autonomously drives to the stop sign without deviation from the ship deck passage way at a distance of about 70m. As a result of the experiment, it was confirmed that the mobile robot was driven without deviation from passage way. If the smart autonomous logistics system to which this result is applied is used in the marine industry, it is thought that the stability, reduction of labor force, and work efficiency will be improved when workers work.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.157-167
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• 2020

The big data and artificial intelligence technology, which has provided the foundation for the recent 4th industrial revolution, has become a major driving force in business innovation across industries. In the field of information security, we are trying to develop and improve an intelligent security system by applying these techniques to large-scale log data, which has been difficult to find effective utilization methods before. The quality of security log big data, which is the basis of information security AI learning, is an important input factor that determines the performance of intelligent security system. However, the difference and complexity of log data by various product has a problem that requires excessive time and effort in preprocessing big data with poor data quality. In this study, we research and analyze the cases related to log data collection of various firewall. By proposing firewall log data collection format standard, we hope to contribute to the development of intelligent security systems based on security log big data.