• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.4
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• pp.175-189
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• 2017

Science and technologies develop rapidly and in conditions where it is difficult to predict both domestically and abroad, the rapidly changing business environment demands innovation. To strengthen the businesses' competitive edge, the key challenge is not to control but rather grant autonomy, allowing it to anticipate the future and actively deal with. This will allow to train and manage talented people with competence and abilities, which all links to the concept of the Super Leadership. Currently, our society is in the change due to the Fourth Industrial Revolution wave and paradigm related with high-tech industry, hence is in desperate need for creativeness and speed management. It is a time where risk and challenges coexist and is not a standardized environment. Businesses must make efforts in managing human resources and allow them to have leaderships compatible with the current era, giving them opportunities to face challenges. The necessity for Super Leadership is emphasized especially in the industry-orientated era, where new revolutionary technologies are emerging and existing technologies are being advanced and maximized, to cultivate the potentials of the members and secure competitive superiority for the best management and creation. Therefore, in this research, the empirical analysis of the relationship between Super Leadership of small and medium enterprises and the business outcome was conducted. Research outcome states that, in order to create a sustainable business outcome, enterprises need to invest more in developing leaderships and in accordance with it, promote talent. In order to survive and sustain growth in the period of endless competition like today, it is concluded that it is imperative to establish a powerful Super Leadership that will endeavor to engage and maximize the competence of members of the organization.

• Journal of the Korean Society for Railway
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• v.20 no.5
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• pp.625-636
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• 2017

This study looked into the behavior of precast concrete track due to temperature variation and initial track deformation and examined the effect of initial deformation and deformation caused by temperature gradient on the stress distribution of slab under train load. In this paper, one of two papers in a series, a finite element analysis model for calculating deformation and stress of precast concrete track was proposed; the temperature distribution and displacements measured at the precast concrete track in the field were compared with the analytical results. The results show that the slab always curled up due to initial deformation; by comparing the measured displacements with the displacements calculated by taking measured temperatures at each depth as input, the effective built-in temperature (EBITD), the temperature difference between the top and bottom of the slab corresponding to the initial deformation, can be estimated. If EBITD is relevantly assumed, the calculated displacements correlate well with the measured ones.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.173-178
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• 2016

When a ballast track of a high-speed train is constructed on a bridge, the displacement of the bridge decks can occur because they are not fixed to the rails. Moreover, relative displacements occur between the bridge and rails caused by temperature changes and external loads. The current longitudinal resistance criteria (UIC Code 774-3, KR C-08080) on ballast tracks with continuous welded rails (CWRs) do not take into account the longitudinal movement of the bridge and the frictional force between the ballast and slabs. In addition, the magnitude of the longitudinal resistance, k, is calculated somewhat conservatively and, (therefore?) it acts as an unfavorable element in the design of long span and continuous railway bridges. Thus, in order to replicate the actual behavior more effectively, the longitudinal resistance of CWRs should take into account the additional rigidity between the slab and track. In this study, the longitudinal resistances of the ballasted track on the bridge were analyzed by carrying out an experimental study with a test setup designed to simulate the deck and bed track. In the test results, the maximum longitudinal resistances of the tests were similar to the resistances of the current codes, however, the measured longitudinal stiffness designed to limit the displacement of the tests were much smaller in comparison with the longitudinal stiffness on the codes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.471-479
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• 2018

Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.637-644
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• 2016

This paper is a follow-up to previous papers entitled, "Development of Tunnel-Environment Monitoring System and Its Installation" I [1] and II [2]. The target tunnel of these studies is the Solan Tunnel, which is a loop-type, single-track, 16.7-km-long tunnel located in mountainous terrain and passing through the Baekdudaegan mountain range. It is an ordinary railway tunnel designed for both freight and passenger trains. We analyzed the environmental conditions of the tunnel using temperature and humidity data recorded over approximately one year. The data were recorded using the Tunnel Rough Environment Measuring System (TREMS), which measures environmental data in subway and high-speed train tunnels and is installed in three locations inside the tunnel. Previous studies analyzed environmental conditions inside tunnels located in or near a city, whereas the tunnel in this study is located in a mountainous area. The tunnel conditions were compared with those measured outside the tunnel for each month. Hourly changes during summer and winter periods were also analyzed, and the environmental conditions at different locations inside the tunnel were compared. The results are widely applicable in studies on the thermal environment and air quality of tunnels, as well as for computer analysis of tunnel airflow such as tunnel ventilation and fire simulations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.141-148
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• 2021

In some intersections or busy traffic roads, there are more pedestrians in a specific period of time, and there are many traffic accidents caused by road congestion. Especially at the intersection where there are schools nearby, it is particularly important to protect the traffic safety of students in busy hours. In the past, when designing traffic lights, the safety of pedestrians was seldom taken into account, and the identification of motor vehicles and traffic optimization were mostly studied. How to keep the road smooth as far as possible under the premise of ensuring the safety of pedestrians, especially students, will be the key research direction of this paper. This paper will focus on person, motorcycle, bicycle, car and bus recognition research. Through investigation and comparison, this paper proposes to use YOLO v4 network to identify the location and quantity of objects. YOLO v4 has the characteristics of strong ability of small target recognition, high precision and fast processing speed, and sets the data acquisition object to train and test the image set. Using the statistics of the accuracy rate, error rate and omission rate of the target in the video, the network trained in this paper can accurately and effectively identify persons, motorcycles, bicycles, cars and buses in the moving images.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.1
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• pp.29-34
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• 2024

The heating element utilizing the Joule heating generated when current flows through a conductor is widely researched and developed for various industrial applications such as moisture removal in automotive windshield, high-speed train windows, and solar panels. Recently, research utilizing heating elements with various nanostructures has been actively conducted to develop flexible heating elements capable of maintaining stable heating even under mechanical deformation conditions. In this study, flexible polyurethane possessing excellent flexibility was selected as the substrate, and silver (Ag) thin films with low electrical resistivity (1.6 μΩ-cm) were fabricated as the heating layer using magnetron sputtering. The 2D heating structure of the Ag thin films demonstrated excellent heating reproducibility, reaching 95% of the target temperature within 20 seconds. Furthermore, excellent heating characteristics were maintained even under mechanically deforming environments, exhibiting outstanding flexibility with less than a 3% increase in electrical resistance observed in repetitive bending tests (10,000 cycles, based on a curvature radius of 5 mm). This demonstrates that polyurethane/Ag planar heating structure bears promising potential as a flexible/wearable heating element for curved-shaped appliances and objects subjected to diverse stresses such as human body parts.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.