• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.97-104
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• 2015

A fuzzy controller and a 2-dimensional wire-driven heavy material lifting system helping human operator are proposed in this paper. The 2-dimensional wire-driven heavy material lifting system is a kind of human-assistive systems in which a human is involved in the control loop. Most of the existing human-assistive control systems cannot consider human operator's characteristic. To consider human operator's characteristic, human's operating motion and requirement of reducing operator's force to lift a heavy material are considered in the design process of the proposed fuzzy controller. The performance of the proposed system is verified by experiments.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1999.10a
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• pp.52-57
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• 1999

Korea Earthquake Monitoring System(KEMS) in the Korea Institute of Geology Mining and Materials(KIGAM) as detected more than 1000 events since the end of 1998. But not all events are interpreted as earthquakes because many events are concentrated on daytime. It strongly implies that in addition to earthquake these events include artificial effects such as industrial blasting. Before the determination of eathquake charactertistics in the korean peninsula it is necessary to discriminate the detected events as earthquakes or artificial events. For the discriminant study KIGAM and SMU(Southern Methodist University) installed a triangular four-element 1-km aperture seismo-acoustic array at Chul-Won area northeast of Seoul Korea. Each array element includes a GS-13 seismometer in the bottom of borehole and a Validyne DP250-14 microbarometer sensor mounted inside of the borehole 1,2 meter deep connected to a 11 arm radial array of 10m porous soaker hoses. This array introduce the use of 2.4-GHz radios for inter-array self-contained solar-charged power system and GPS time-keeping system. A 24-bit digital data acquisition system performs 40 SPS in the infrasound and seismometer data. Velocity and direction of wind and temperature are also measured at hub site and included to the data stresam. This seismo-acoustic array will be used to identify and locate associated with industrial blasting and these identified and located events will be applied to form a ground truth database useful to assist the other development of discriminant studies.

• Journal of Information Science Theory and Practice
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• v.7 no.3
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• pp.6-20
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• 2019

Learning analytics, or educational data mining, is an emerging field that applies data mining methods and tools for the exploitation of data coming from educational environments. Learning management systems, like Moodle, offer large amounts of data concerning students' activity, performance, behavior, and interaction with their peers and their tutors. The analysis of these data can be elaborated to make decisions that will assist stakeholders (students, faculty, and administration) to elevate the learning process in higher education. In this work, the power of Excel is exploited to analyze data in Moodle, utilizing an e-learning course developed for enhancing the information computer technology skills of school teachers in primary and secondary education in Greece. Moodle log files are appropriately manipulated in order to trace daily and weekly activity of the learners concerning distribution of access to resources, forum participation, and quizzes and assignments submission. Learners' activity was visualized for every hour of the day and for every day of the week. The visualization of access to every activity or resource during the course is also obtained. In this fashion teachers can schedule online synchronous lectures or discussions more effectively in order to maximize the learners' participation. Results depict the interest of learners for each structural component, their dedication to the course, their participation in the fora, and how it affects the submission of quizzes and assignments. Instructional designers may take advice and redesign the course according to the popularity of the educational material and learners' dedication. Moreover, the final grade of the learners is predicted according to their previous grades using multiple linear regression and sensitivity analysis. These outcomes can be suitably exploited in order for instructors to improve the design of their courses, faculty to alter their educational methodology, and administration to make decisions that will improve the educational services provided.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3423-3440
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• 2023

In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. To address the uncertainty inherent in such predictions, a Bayesian Neural Network (BNN) was implemented. The models were trained using a database generated by the Best Estimate Plus Uncertainty (BEPU) methodology; coupling the thermal hydraulics code, RELAP5/SCDAP/MOD3.4 to the statistical tool, DAKOTA, to predict the variation in system response under various operational and phenomenological uncertainties. The RNN models successfully captures the underlying characteristics of the data with reasonable accuracy, and the BNN-LSTM approach offers an additional layer of insight into the level of uncertainty associated with the predictions. The results demonstrate that LSTM outperforms GRU, while the hybrid CNN-LSTM model is computationally the most efficient. This study aims to gain a better understanding of the capabilities and limitations of machine learning models in the context of nuclear safety. By expanding the application of ML models to more severe accident scenarios, where operators are under extreme stress and prone to errors, ML models can provide valuable support and act as expert systems to assist in decision-making while minimizing the chances of human error.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.72-81
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• 2023

This research proposes a novel approach to tackle the challenge of categorizing unstructured customer complaints in the automotive industry. The goal is to identify potential vehicle defects based on the findings of our algorithm, which can assist automakers in mitigating significant losses and reputational damage caused by mass claims. To achieve this goal, our model uses the Word2Vec method to analyze large volumes of unstructured customer complaint data from the National Highway Traffic Safety Administration (NHTSA). By developing a score dictionary for eight pre-selected criteria, our algorithm can efficiently categorize complaints and detect potential vehicle defects. By calculating the score of each complaint, our algorithm can identify patterns and correlations that can indicate potential defects in the vehicle. One of the key benefits of this approach is its ability to handle a large volume of unstructured data, which can be challenging for traditional methods. By using machine learning techniques, we can extract meaningful insights from customer complaints, which can help automakers prioritize and address potential defects before they become widespread issues. In conclusion, this research provides a promising approach to categorize unstructured customer complaints in the automotive industry and identify potential vehicle defects. By leveraging the power of machine learning, we can help automakers improve the quality of their products and enhance customer satisfaction. Further studies can build upon this approach to explore other potential applications and expand its scope to other industries.

• Animal Bioscience
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• v.37 no.5
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• pp.817-825
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• 2024

Objective: The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls. Methods: A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied. Results: Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture. Conclusion: Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance.

• Journal of Environmental Policy
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• v.8 no.2
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• pp.83-118
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• 2009

Clean Development Mechanism(CDM) projects under the Kyoto Protocol have two objectives. One is to assist the Parties included in Annex I in achieving compliance with their quantified emission limitation and reduction commitments in cost-effective ways by allowing them to implement emission reduction projects in Non-Annex I countries and receive CERs, which will offset their reduction commitments. The other is to assist Parties not included in Annex I in achieving sustainable development and technology transfers through investments by Annex I countries. However, in reality, it is said that the former objective is achievable but the latter is not. In this light, this article suggests sustainability appraisal criteria applicable for Korea. Among various methodologies, we used the 'multi-attributes utility theory(MAUT)'; one of the 'multi-criteria analysis (MCA)' methodologies judged to be the most practical and relevant. Based on the guidelines of the MAUT methodology, we identified sustainability criteria that meet the guidelines. We took two tracks, the first to find the preferences of Korean experts, and the other to check foreign cases. In all, 37 preliminary criteria were suggested to Korean experts and each criterion was scored, from between 1 and 3, in terms of relevance, possibility of real improvement, easiness of data collection, and preferences. We combined foreign cases and the results of a survey conducted in Korea and selected 12 core criteria and 10 additional criteria. After that, all the criteria were converted into indicators. The indicators were applied to a CDM project for case study. We chose the "Sihwa Tidal Power Project", which is currently the biggest tidal power plant in the world. Twelve core indicators and 3 additional indicators were applied. In order to weight each indicator, the 'analytical hierarchy process (AHP)' was used. A total of 30 experts were asked to suggest weights and 21 answered. Among them, only 14 respondents were proven to meet the consistency ratio. We analyzed the 14 responses through Expert Choice and the CDM project was scored (+)53.082. In addition, sensitivity analysis was undertaken with the result of (+)44.667 to (+)65.522. As a result of this study, it was proven that this project would contribute to the sustainable development of Korea.

• Korean Journal of Applied Biomechanics
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• v.15 no.2
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• pp.11-20
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• 2005

This study has a purpose on contributing to apprehend safe and right way to stop to the inline skate beginners and to the instructors who teaches line skating on the basis for the result of the kinematical analysis on Heel brake stop movement of the inline skate, focusing on the displacement on COG, angle displacement of ankle joint, angle displacement of knee joint, angle displacement of hip joint, using a 3D image method by DLT. To achieve this goal, we analysed the kinematical factor of the 3 well-trained inline skating instructors and obtained the following results. 1. During the movement of heel-brake stop, when strong power was given to a stable and balanced stop and the lower limbs, if the physical centroid is lowered the stability increases, and if it is placed high from the base surface, as the stability decreases compared to the case of low physical centroid, we should make a stop by placing a physical centroid in the base surface and lowering the hight of physical centroid. 2. To make a stable and balanced stop and to provide a strong power to the lower limbs, it is advisable to make a stop by decreasing an angle displacement of ankle joint during a "down" movement. In case of the left ankle joint, in all events and phases the dorsiflexion angle showed a decrease. Nevertheless, in the case of the right ankle joint, the dorsiflexion angle shows an increase after a slight decrease. The dorsiflexion angle displacement of ankle joint can be diminished because of the brake pad of the rear axis frame of the right side inline skate by raising a toe, but cannot be more decreased if certain degree of an angle is made by a brake pad touching a ground surface. To provide a power to a brake pad, it is recommended to place a power by lowering a posture making the dorsiflexion angle of the left ankle joint relatively smaller than that of the right ankle. 3. To make a stable and balanced stop and to add a power to a brake pad, the power must be given to the lower limbs in lowering the hight of physical centroid. For this, it is recommended to make a down movement by decreasing the flexion angle of a knee joint and it is necessary to make a down movement by a regular decrease of the angle displacement of knee joint rather than a swift down movement in every event and phase. 4. The right angle displacement of hip joint is made by lowering vertically the hight of physical centroid as leaning slightly forward. If too narrow angle displacement of hip joint is made by leaning forward too much, the balance is lost during the stop by placing the center in front. To make a stable and balance stop and to place a strong power to the lower limbs, it is recommendable to make a narrow angle by lower the hip joint angle. However, excessive leaning of the upper body to make the angle too narrow, can cause an instable stop and loss of physical centroid. After this study, it is considered to assist the kinematical understanding during the heel brake stop movement of the inline skate, and, to present basic data in learning a method of stable and balanced stop for the inline skating beginners or for the inline skate instructors in the present situation of the complete absence of the study in inline skating.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.3 no.1
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• pp.7-13
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• 2009

Recently, the interest on walking assistances in order to assist aged people has increased due to the increase of the aged. However, most walking aid systems have a weakness for a slope because they don't have power. So, they have a weak point which makes users difficult to move when they are weak in the legs. That is why the interest on walking assistances with power has increased. The use of the walking aid systems should be easy because most users are old people. Thus, we produce module to grasp walking intent of users by using various sensors such as potentiometer, FSR(Force Sensing Resistance) Sensor and Stretch Sensor and calculate the response time to the module. Firstly, the response time of handlebar which is a kind of potentiometer is 420ms and Resilience of it is 140ms. Secondly, the response time of handlebar which use FSR Sensor is 320ms and Resilience of it is 220ms. Finally, the response time of the Stretch Sensor is 160ms and Resilience of it is 140ms. The performance of Stretch Sensor is the best among the three kind of sensors.

• Journal of Korea Water Resources Association
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• v.37 no.8
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• pp.653-662
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• 2004

In this study, the method of Increasing the flood control as well as conservation effects is studied by joint operation of Hwacheon and Peace Dam. After completing the second phase of the construction of the Peace Dam, the dam crest height will be increased from 225m and the storage capacity will also be increased. If storage capacity is increased and gates are installed, it will assist not only flood control but also conservation of the entire Han river basin. Considering the change of conservation levels, the change of the restricted water level of the Hwacheon Dam in flood season, and the inflow change into the Peace Dam through the simulated reservoir operation, the annual average power of Hwacheon Dam with 95% reliability, annual firm power, the volume of water supply is calculated. As a result, when the conservation level of the Peace Dam and the restricted water level of the Hwacheon Dam are increased, the generation capacity will be improved. However, even though the inflow decrease, the generation capacity will not be affected. If the inflow decrease under the same conditions, the water supply capability will be reduced to the range from 35% to 40%. It is necessary to increase conservation level to keep the same water supply capability.