• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.6
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• pp.661-667
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• 2011

Kinematic contact trigger probes are widely used for feature inspection and measurement on coordinate measurement machines (CMMs) and computer numerically controlled (CNC) machine tools. Recently, the probing accuracy has become one of the most important factors in the improvement of product quality, as the accuracy of such machining centers and measuring machines is increasing. Although high-accuracy probes using strain gauge can achieve this requirement, in this paper we study the universal economic kinematic contact probe to prove its probing mechanism and errors, and to try to make the best use of its performance. Stylus-ball-radius and center-alignment errors are proved, and the probing error mechanism on the 3D measuring coordinate is analyzed using numerical expressions. Macro algorithms are developed for the compensation of these errors, and actual tests and verifications are performed with a kinematic contact trigger probe and reference sphere on a CNC machine tool.

• Journal of the Korean housing association
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• v.20 no.6
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• pp.89-99
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• 2009

The purpose of this research is to determine the deterioration characteristics of high-rise and high-density apartment complexes in 1st period new towns in order to regenerate apartments as sustainable residential environments in Korea. For this purpose, the level of deterioration was evaluated by using 'evaluating indicators of the level of deterioration of high-rise and high-density apartments'. The deterioration characteristics were determined inclusively and concretely based on evaluation results. In addition, the deterioration level according to residents' awareness of the deterioration of their apartment was evaluated. This study was conducted by methods of field data collection, staff interview, field measurement, and resident survey according to the measurement of the evaluating indicators. And the re-organized questionnaire based on the evaluating indicators was utilized for a survey of resident's awareness. The results are as follows: In the physical dimensions of apartments, the deterioration characteristics included deteriorated equipment and a decline in structural performance due to the aging of the apartment, a shortage of parking spaces, and the low flexibility of the bearing wall structure, etc. In terms of the social dimensions, the apartments showed an increase in the number of elderly households, a shortage of community facilities, and a lack of the opportunity for community participation etc. In terms of the economic dimensions, the apartments showed limitations in maintenance & repair and a lack of environmentally friendly features.

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.133-147
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• 1998

Recently, many researchers have been involved in finding deterministic equations which can accurately predict future event, based on chaotic theory, or fractal theory. The theory says that some events which seem very random but internally deterministic can be accurately predicted by fractal equations. In contrast to the conventional methods, such as AR model, MA, model, or ARIMA model, the fractal equation attempts to discover a deterministic order inherent in time series data set. In discovering deterministic order, researchers have found that neural networks are much more effective than the conventional statistical models. Even though prediction accuracy of the network can be different depending on the topological structure and modification of the algorithms, many researchers asserted that the neural network systems outperforms other systems, because of non-linear behaviour of the network models, mechanisms of massive parallel processing, generalization capability based on adaptive learning. However, recent survey shows that prediction accuracy of the forecasting models can be determined by the model structure and data structures. In the experiments based on actual economic data sets, it was found that the prediction accuracy of the neural network model is similar to the performance level of the conventional forecasting model. Especially, for the data set which is deterministically chaotic, the AR model, a conventional statistical model, was not significantly different from the MLP model, a neural network model. This result shows that the forecasting model. This result shows that the forecasting model a, pp.opriate to a prediction task should be selected based on characteristics of the time series data set. Analysis of the characteristics of the data set was performed by fractal analysis, measurement of Hurst index, and measurement of Lyapunov exponents. As a conclusion, a significant difference was not found in forecasting future events for the time series data which is deterministically chaotic, between a conventional forecasting model and a typical neural network model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.357-359
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• 2022

The market for eco-friendly food materials by online distribution is rapidly growing due to major environmental pollution such as air, soil, and water quality, and radical changes in living patterns caused by COVID-19. In addition, because of the aging population and the decrease in agricultural-related population due to social structural changes, aquaponics is emerging as a system that can solve problems such as independence of old economic activities, environmental protection, and securing healthy and safe food. This paper aims to design an intelligent plant growth measurement system among intelligent aquaponics production management modules for optimal growth environment derivation and quantitative production prediction by converging various ICT technologies into existing aquaponics systems. In particular, the focus is on designing systems suitable for production sites that do not have high-performance processing resources, and we propose a module configuration plan for production environments and training data and prediction systems.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.71-81
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• 2020

Enclosed pig house are creating an environment with high concentrations of gas and dust. Poor conditions in pig farms reduce pig weight and increase disease and accidents for livestock workers. In the pig house, the high concentration of harmful gas may cause asphyxiation accidents to workers and chronic respiratory disease by long-term exposure. As pig farm workers have been aging and feminized, the damage to the health of the harsh environment is getting serious, and real-time monitoring is needed to prevent the damage. However, most of the measuring devices related to humidity, harmful gas, and fine dust except temperature sensors are exposed to high concentrations of gas and dust inside pig house and are difficult to withstand for a long time. The purpose of this study is to develop an wearable based device to monitor the hazardous environment exposed to workers working in pig farms. Based on the field monitoring and previous researches, the measurement range and basic specifications of the equipment were selected, and wearable based device was designed in terms of utilization, economic efficiency, size and communication performance. Selected H₂S and NH₃ sensors showed the average error of 5.3% comparing to standard gas concentrations. The measured data can be used to manage the working environment according to the worker's location and to obtain basic data for work safety warning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.503-504
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• 2017

Recently, economic growth in the world has increased interest in healthy life, and the smart health care industry is growing. In the field of smart healthcare, wearable-type biometric information measurement technology has been highlighted due to the importance of IoT technology. The purpose of this study is to develop a wearable heart - rate monitoring system that can be applied to wearable health care and glove - type monitoring that enables convenient monitoring of heart rate during activity. For this purpose, a glove - type wearable health care system was developed and its performance was evaluated. Experimental results showed that the heartbeat monitoring was possible even in the presence of actual daily activities.

• Journal of Drive and Control
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• v.21 no.3
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• pp.28-35
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• 2024

This study compared performances of PID (Proportional Integral Derivative), SMC (Sliding Mode Control), and MPC (Model Predictive Control) strategies applied to a 2DOF (Degree Of Freedom) drone tracking robot. The developed 2DOF robot utilized a depth camera with an IMU (Inertial Measurement Unit), laser pointers, and servo motors to rapidly detect and track objects. Image processing was conducted using the YOLO deep learning model. Through this setup, controllers were attached to the robot to track random drone movements, comparing performances in terms of accuracy and energy consumption. This study revealed that while SMC demonstrated precise tracking without deviating from the path, both PID and MPC controllers showed deviations. Performance-wise, SMC is superior. However, considering economic aspects, PID is more advantageous due to its lower power consumption and relatively minor tracking errors.

• Journal of Korea Port Economic Association
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• v.24 no.4
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• pp.313-327
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• 2008

The purpose of this paper is to show the empirical measurement way for predicting the seaport efficiency by using SBM with Wilcoxson signed-rank test under CRS(constant returns to scale) condition for 20 Korean ports during 1994-2003 for 2 inputs(birthing capacity, cargo handling capacity) and 3 outputs(Export and Import Quantity, Number of Ship Calls, Port Revenue). The main empirical results of this paper are as follows. First, forecasting data have well reflected the real data according to the Wilcoxon signed rank test, because p values have exceeded the 0.05 significance level. Second, SBM has shown the effectiveness for predicting the ports efficiency even though the predicting powers are different according to the levels of p values. The policy implication to the Korean seaports and planner is that Korean seaports should introduce the new methods like SBM method with Wilcoxon signed rank test for predicting the port performance and enhancing the efficiency.

• 한국체육학회지인문사회과학편
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• v.54 no.3
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• pp.31-43
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• 2015

The purpose of this study was to find out the dance sports athlete's factor that presents performance problems and performance enhancing for competitions. To achieve purpose of study carried out open-ended question and structural inquiry of succession in the dance sports athlete of 25 people, the open-ended questions data were examined through inductive content analysis procedure, conducted preliminary investigation to 100 people. Preliminary investigation and main survey were verified to the dance sports athlete of 137 people through exploratory factor analysis, and confirmatory factor analysis was conducted. On the basis of the results, the conclusions were drawn as follows; First, hinders factors to athletic performance is discord with partner, condition, contest environment, limit of physical strength, limit of economic strength. Second, the measurement scale of dance sports athlete's performance enhancing to competition with 23 items which are consisted of 7 main factors. The determination factors of dance sports athlete performance were partnership, ability to invest, spiritual factors, training factors, ability of physical factors, the leader, environment of competition.

• International Journal of Quality Innovation
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• v.8 no.3
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• pp.156-172
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• 2007

The high-tech industry is the economic lifeline for Taiwan. Its characteristics are short product life cycle, rapid changes in the market, and a high obsolescence rate for new products. Under globalization, the high-tech industry has adopted Information Technology (IT) to shorten the manufacturing process, reduce costs and conduct product research and development (R&D) to increase the core competence of enterprises and achieve the goal of sustainable operations. Enterprises should actively strengthen their integration with internal and external resources and lead in R&D management to increase industrial operating performance. Effectively managing operations and R&D management evaluation in Taiwan's High-tech Industry has become a critical subject. This study adopted 4 major Balanced Scorecard (BSC) perspectives to establish the Total Performance Evaluation Indicators for the R&D management department in Taiwan's High-tech Industry. The Analytic Network Process (ANP) was applied to evaluate the overall performance of the R&D management department. The research framework is divided into 2 phases. The first phase is combined with the 4 major perspectives, Financial, Customer, Internal Business Process and Learning and Growth, as the related indicators for each measurement perspective. The Key Performance Indicators (KPI) were selected using Factor Analysis to identify the key factor from the complicated indicators. The relationship between the characteristics of each BSC's evaluation perspective is dependence and feedback. This study applied ANP to conduct the calculation and adjustment of correlation between each KPI, and determine on their relative weights for the objective KPI. The "Financial Perspective" for R&D management department in Taiwan's High-tech Industry focused on the budget achievement rate of R&D management. The weight indicator value is (0.05863). The "Customer Perspective" focused on problem-solving satisfaction. The weight value of this indicator is (0.17549). The "Internal Business Process Perspective" focused on the quantity and quality of R&D. The weight value of this indicator is (0.13506). The "Learning and Growth Perspective" focused on improving competence in the research personnel's professional techniques. The weight value of this indicator is (0.02789). From the total weighting indicators, the order of the Performance Indicators for the R&D management department in Taiwan's High-tech Industry is: (1) Customer Perspective; (2) Internal Business Process Perspective; (3) Financial Perspective; and (4) Learning and Growth Perspective.