• Journal of Technology Innovation
• /
• v.27 no.1
• /
• pp.45-77
• /
• 2019

The balance between exploration for new possibility and exploitation for existing certainty is an important issue in strategy, innovation, R&D as well as organization learning. Among the convergence trends of technologies, many firms seek to have the wider technological knowledge assets and the deeper technology capabilities for the sustainable competitive advantage at the same time. While firms plan technology portfolio strategies, they should consider the attribute of the technology. Nanotechnology, a cutting-edge technology, is a general purpose technology, unlike conventional product-oriented technologies. This empirical study was focused on how multi-national firms' exploration and exploitation strategies for nanotechnology affect their innovative and financial performance. It uses multiple regression analysis on panel data. This result shows that the more diversified and specialized nanotechnology as platform technology is positively related to their innovative and financial performance, unlike the research results for product-oriented technologies. In addition, exploratory innovation is more effective to firm performance than exploitation. This implies how global firms can manage effectively platform technology strategies under the constraints of resources.

• The Korean Journal of Applied Statistics
• /
• v.32 no.2
• /
• pp.173-185
• /
• 2019

Causal questions are prevalent in scientific research, for example, how effective a treatment was for preventing an infectious disease, how much a policy increased utility, or which advertisement would give the highest click rate for a given customer. Causal inference theory in statistics interprets those questions as inferring the effect of a given intervention (treatment or policy) in the data generating process. Causal inference has been used in medicine, public health, and economics; in addition, it has received recent attention as a tool for data-driven decision making processes. Many recent datasets are observational, rather than experimental, which makes the causal inference theory more complex. This review introduces key concepts and recent trends of statistical causal inference in observational studies. We first introduce the Neyman-Rubin's potential outcome framework to formularize from causal questions to average treatment effects as well as discuss popular methods to estimate treatment effects such as propensity score approaches and regression approaches. For recent trends, we briefly discuss (1) conditional (heterogeneous) treatment effects and machine learning-based approaches, (2) curse of dimensionality on the estimation of treatment effect and its remedies, and (3) Pearl's structural causal model to deal with more complex causal relationships and its connection to the Neyman-Rubin's potential outcome model.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.32 no.6
• /
• pp.561-568
• /
• 2020

Wave measurements using X-band radar have many advantages compared to other wave gauges including wave-rider buoy, P-u-v gauge and Acoustic Doppler Current Profiler (ADCP), etc.. For example, radar system has no risk of loss/damage in bad weather conditions, low maintenance cost, and provides spatial distribution of waves from deep to shallow water. This paper presents new methods for estimating significant wave heights of X-band marine radar images using Artificial Neural Network (ANN). We compared the time series of estimated significant wave heights (Hs) using various estimation methods, such as signal-to-noise ratio (${\sqrt{SNR}}$), both and ${\sqrt{SNR}}$ the peak period (TP), and ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k). The estimated significant wave heights of the X-band images were compared with wave measurement using ADCP(AWC: Acoustic Wave and Current Profiler) at Hujeong Beach, Uljin, Korea. Estimation of Hs using ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k) yields best result.

• Journal of Industrial Convergence
• /
• v.19 no.1
• /
• pp.99-108
• /
• 2021

To determine clinical nursing instructors' teaching efficacy, students' clinical practice satisfaction, and confirm between correlation, and develop a plan for operating nursing education efficiently for clinical practice. Clinical practice could create an optimal learning situation. We applied CNITEs and CPS to measure clinical nursing instructor teaching efficacy and clinical practice satisfaction. The differences in teaching efficacy by the general characteristics were measured and analyzed; the higher the level of the participants' education, position, clinical career, and clinical teaching career, the higher their teaching efficacy. The higher the age at clinical practice, the higher the clinical efficacy of clinical practitioners with clinical career and higher education level students were more satisfied with the practice subject and nursing instruction than other categories. Therefore, in order to increase the satisfaction of nursing students' practice in the clinical field, we hope to improve various things that can be used not only teaching efficacy but also in clinical practice satisfaction.

• The Journal of Korean Society for School & Community Health Education
• /
• v.22 no.4
• /
• pp.49-60
• /
• 2021

Objectives: Laboratories have various latent physical, chemical, biological, and ergonomical factors according to the diversification and fusion of research and development activities. This study aims to investigate the chemical exposure concentrations of college laboratories and evaluate their health risks, and use them as basic data to promote the health of college students. Methods: The sampling and analysis of harmful chemicals in the air in laboratories were performed using Method 1500 of the U.S. National Institute for Occupational Safety and Health (NIOSH)의 Method 1500. The harmful chemicals in the laboratories were divided into carcinogenic and non-carcinogenic chemicals. Risk assessment was performed using the cancer risk (CR) for carcinogenic chemicals and using the hazard index (HI) for non-carcinogenic chemicals. Results: The harmful chemicals in college laboratories consisted of acetone, diethyl ether, methylene chloride, n-hexane, ethyl acetate, chloroform, tetrahydrofuran, toluene, and xylenes. They showed the highest concentrations in laboratories A (acetone 0.001~2.34ppm), B (chloroform 0.95~6.35ppm), C (diethyl ether 0.08~8.68ppm), and D (acetone 0.07~14.96ppm). The risk assessment result for non-carcinogenic chemicals showed that the HI of methylene chloride was 2.052 for men and 2.333 for women, the HI of N-hexane was 4.442 for men and 5.05 for women. Thus, the HI values were higher than 1. The risk of carcinogenic chemicals is determined by an excess cancer risk (ECR) value of 1.0×10^-5, which means that one in 100,000 people has a cancer risk. The ECRs of chloroform exceeded 1.0×10^-5 for both men and women, indicating the possibility of cancer risk. Conclusion: College laboratories showed the possibility of non-carcinogenic health risks for methylene chloride, n-hexane, tetrahydrofuran (THF), toluene, and xylenes, and carcinogenic health risks for chloroform, methylene chloride. However, this study used the maximum values of measurements to determine the worst case, and assumed that the subjects were exposed to the corresponding concentrations continuously for 8 hours per day for 300 days per year. In consideration of the nature of laboratory environment in which people are intermittently exposed, rather than continuously, to the chemicals, the results of this study has an element of overestimation.

• Journal of Life Science
• /
• v.32 no.5
• /
• pp.362-367
• /
• 2022

Hempseed, a dehulled Cannabis fructus, has high nutraceutical potential. It has plenty of essential amino acids, vitamins, and essential polyunsaturated fatty acids, including α- and γ-linolenic acid. Increased exercise capacity, cognitive function, and ameliorative effects against hypercholesterolemia, neuro-inflammation, thrombus formation, and learning and memory impairment were reported in hemp-seed oil-administered models. Therefore, the market prices of hempseed oil are 45~140-fold higher than the other plant-derived oils, such as soy, corn, olive, canola, or linseed oil. In this study, instead of FTIR (Fourier Transform Infrared Spectroscopy) or FTIR-Raman spectroscopy, a simple UV-Vis spectrophotometry method was developed to authenticate the hempseed oil. Measurements of absorbance at 245, 305, and 415 nm of oils and calculations of 245/415 and 315/415 nm provided that the ratios of 245/415 and 315/415 nm of authentic hempseed oils were 12.9 and 9.6, respectively. The 245/415 and 315/415 nm of soy oil, corn oil, canola oil, and linseed oil were 35.4~61.8 and 29.7~50.8, respectively. This simple UV-Vis spectrophotometry method could also be applied to differentiate hempseed oil from blended oil products in markets.

• Korean Journal of Remote Sensing
• /
• v.39 no.1
• /
• pp.77-86
• /
• 2023

Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.

• Journal of the Korean Applied Science and Technology
• /
• v.40 no.3
• /
• pp.476-483
• /
• 2023

This study aimed to analyze the effects of athletic career and competition participation frequency on exercise commitment of women university taekwondo athletes. Study subjects were 20 women university taekwondo athletes. Athletic career and competition participation frequency was assessed by 4-points scale and the higher points indicate the higher level of each variables. Exercise commitment was assessed by Exercise Commitment Scale. The assessment consists of a total of 8 questions, 4 of which are action immersion and 4 of cognitive immersion, and is evaluated using a 5-point Likert scale. The higher the score, the higher the level of exercise commitment. As the results, positive relationship showed both correlation and casual relationship analysis between competition participation frequency and exercise commitment. Negative casual relationship (-) showed between athletic career and exercise commitment. These results indicated that the increase of competition participation frequency affects the exercise commitment and the longer of athletic career indicates the decrease the level of exercise commitment. Thus, to improve the exercise commitment of women university taekwondo athletes, the competition participation frequency and athletic career should be considered.

• Journal of Internet Computing and Services
• /
• v.24 no.4
• /
• pp.57-64
• /
• 2023

The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.5
• /
• pp.667-674
• /
• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.