• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.792-798
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• 2021

In this paper, an algorithm for determining the coagulant input rate in the drug-injection tank during the process of the water purification plant was derived through big data analysis and prediction based on artificial intelligence. In addition, analysis of big data technology and AI algorithm application methods and existing academic and technical data were reviewed to analyze and review application cases in similar fields. Through this, the goal was to develop an algorithm for determining the coagulant input rate and to present the optimal input rate through autonomous driving simulator and pilot operation of the coagulant input process. Through this study, the coagulant injection rate, which is an output variable, is determined based on various input variables, and it is developed to simulate the relationship pattern between the input variable and the output variable and apply the learned pattern to the decision-making pattern of water plant operating workers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.20-29
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• 2021

In the Industry 4.0 era, artificial intelligence has attracted considerable interest for learning mass data to improve the accuracy of forecasting and classification. On the other hand, the current method of detecting anomalies relies on traditional statistical methods for a limited amount of data, making it difficult to detect accurate anomalies. Therefore, this paper proposes an artificial intelligence-based anomaly detection methodology to improve the prediction accuracy and identify new data patterns. In particular, data were collected and analyzed from the point of view that sensor data collected at vehicle idle could be used to detect abnormalities. To this end, a sensor was designed to determine the appropriate time length of the data entered into the forecast model, compare the results of idling data with the overall driving data utilization, and make optimal predictions through a combination of various sensor data. In addition, the predictive accuracy of artificial intelligence techniques was presented by comparing Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM) as the predictive methodologies. According to the analysis, using idle data, using 1.5 times of the data for the idling periods, and using CNN over LSTM showed better prediction results.

• Journal of Drive and Control
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• v.17 no.4
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• pp.141-151
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• 2020

The aim of this study was to analyze the safety factor of range-shift gear pairs on multi-purpose agricultural implement machinery for an optimal design of a transmission system. Gear-strengths such as bending and contact stress and safety factors were analyzed under three load conditions: an equivalent engine torque at plow tillage, a rated engine torque, and the maximum engine torque. Root and contact safety factor were calculated to be 3.88, 5.14, 2.24, 2.11, 2.21, 0.99 and 0.78, 0.94, 0.65, 0.68, 0.84, 0.85, respectively, under equivalent engine torque condition at the plow tillage. The root and contact safety factor were calculated to be 1.91, 2.53, 1.10, 1.04, 1.07, 0.48 and 0.55, 0.66, 0.46, 0.48, 0.59, 0.59, respectively, under rated engine torque condition. The root and contact safety factor were calculated to be 1.60, 2.11, 0.92, 0.87, 0.90, 0.40 and 0.51, 0.61, 0.42, 0.44, 0.54, 0.54, respectively, under the maximum engine torque condition. The multi-purpose agricultural implement machinery could be conducted under plow tillage operation. However, gear specifications for tooth surface need modification because the gear surface would be broken at all driving conditions as safety factors are lower than 1.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.1
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• pp.26-32
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• 2022

This paper proposes a power system that includes a 120k W fuel cell DC-DC converter (FDC) and 30 kW bidirectional DC-DC converter (BHDC) for a 150 kW fuel-cell vehicle. With a high DC link voltage of 800 V, the efficiency and power density of the power electronic components are improved. Through the modular design of FDC and BHDC, electric components are shared, resulting in reduced mass production costs. The switching frequency of 30 kHz of full SiC devices and optimal design of coupled inductor reduce the volume, achieving a power density of 8.3 kW/L. Furthermore, a synergetic operation strategy using variable limiter control of FDC and BHDC was proposed to efficiently operate the fuel cell vehicle considering the fuel cell stack efficiency according to the load. Finally, the performance of the prototype was verified by Highway Fuel Economy Driving Schedule testing, EMI test, and the linked operation between FDC and BHDC. The full load efficiencies of the FDC and BHDC prototypes are 98.47% and 98.74%, respectively.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.29-37
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• 2021

A 7 nm technology node using extreme ultraviolet lithography with a wavelength of 13.5 nm has been recently developed and applied to the semiconductor manufacturing process. Furthermore, the development of sub-3 nm technology nodes continues to be required. In this study, design factors of an electrostatic deflector for an ultra-miniaturized microcolumn system that can realize an electron wavelength of below 1.23 nm with an acceleration voltage of above 1 eV were investigated using a three-dimensional simulator. Particularly, the optimal design of the electrostatic octupole floating deflector was derived by optimizing the design elements and improving the driving method of the 1 keV low energy ultra-miniaturized microcolumn deflector. As a result, the entire wide field of view greater than 330 ㎛ at a working distance of 4 mm was realized with an ultra-high-resolution electron beam spot smaller than 10 nm. The results of this study are expected to be a basis technology for realizing a wafer-scale multi-array microcolumn system, which is expected to innovatively improve the throughput per unit time, which is the biggest drawback of electron beam lithography.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.953-965
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• 2023

The stratospheric drones are developed to perform missions such as weather observation, communication relay, surveillance, and reconnaissance at 18km to 20km, where climate change is minimal and there is no worry about a collision with aircraft. It uses solar panels for daytime flights and energy stored in batteries for night flights, providing many advantages over existing satellites. The electrical and power systems essential for stratospheric drone flight must ensure reliability, efficiency, and lightness by selecting the optimal circuit topology. Therefore, it is necessary to analyze the circuit topology of various types of multi-level inverters with high redundancy that can ensure the reliability and efficiency of the motor driving power required for stable long-term flight of stratospheric drones. By quantifying the switch element voltage drop and the number and weight of inverter components for each topology, we evaluate efficiency and lightness and propose the most suitable circuit topology for stratospheric drones.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.11-16
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• 2023

The technology of 3D reconstruction, primarily relying on point cloud data, is essential for digitizing objects or spaces. This paper aims to utilize reinforcement learning to achieve the acquisition of point clouds in a given environment. To accomplish this, a simulation environment is constructed using Unity, and reinforcement learning is implemented using the Unity package known as ML-Agents. The process of point cloud acquisition involves initially setting a goal and calculating a traversable path around the goal. The traversal path is segmented at regular intervals, with rewards assigned at each step. To prevent the agent from deviating from the path, rewards are increased. Additionally, rewards are granted each time the agent fixates on the goal during traversal, facilitating the learning of optimal points for point cloud acquisition at each traversal step. Experimental results demonstrate that despite the variability in traversal paths, the approach enables the acquisition of relatively accurate point clouds.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.465-470
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• 2024

Kitchen cabinets are widely used for their spacious storage and efficient use of space, but their high installed location makes it difficult for the elderly and disabled to access. Therefore, in this paper, we propose a new height-adjustable kitchen cabinet that can be used more easily and safely. The lift-down range of cabinet was set considering the installation location of cabinet for efficient use of kitchen space and the maximum height accessible to the elderly and disabled, and the link geometry and driving method of the complex link mechanism were determined through the mechanism design procedure to ensure that the selected floor come down safely along the optimal descend path. In addition, the appropriate motor and control algorithm were added to allow the user to descend to the desired height with a simple button operation. It was confirmed through actual production that the proposed linkage mechanism performs the desired lift-down motion.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.1
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• pp.203-211
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• 2014

Tunnel reduces travel time as and it is essential facilities for the eco-friendly road construction. In recent years, It has been accelerating the tunnel construction to provide a higher level of traffic service but a driver driving in the narrow and dark tunnel takes characteristically psychological anxiety and the restriction of the sight. Moreover, A driver passing through more than 1,000m long tunnel, as to pass inside the monotonous form of the tunnel for a long time can cause drowsiness and increase the driver load. This driver load can degrade road-holding of the inside of the long tunnel highly and pose a high risk of accidents. Accordingly, In this study is to present the proper length of the Tunnel, considering the characteristics of traffic accident. For this, this study is that the long tunnel that affects traffic safety traffic safety variables are selected and classified. Traffic safety variables are classified in detail as a variable of the traffic accident and velocity one, the applicable variables the number of the traffic accident, the ratio of the traffic accident, driving velocity, the individual vehicle velocity etc. Traffic safety variables are categorized as more than a pole length of the tunnel in order to examine its impact on correlation analysis. The results indicate significant results in traffic accidents in accordance with traffic accidents, traffic safety, selects the variable was Variable depending on the length of the tunnel traffic safety point of significantly increasing the possibility of an accident can be seen as a high point. And the point of the Distribution of selected variables in order to create a traffic safety was a significant increase in traffic safety variables was set at critical intervals. Before reaching the critical point and the corresponding length of the long tunnel was set at the proper length. In this study, the optimum length of the proposed long tunnel through the long tunnel that occur in the future to contribute to reducing traffic accidents would be able to be determined.

• Korean Chemical Engineering Research
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• v.50 no.5
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• pp.933-937
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• 2012

In the present study, we evaluate the sensitivity and optimal stripping voltammetry (SV) conditions of copper (Cu), which is one of the main trace heavy metals inducing the environmental contamination, using carbon nanotube (CNT) electrode. In addition, the reaction mechanism of stripping reaction of Cu is investigated. The electrochemical analyses such as squarewave stripping voltammetry (SWSV) and linear scan voltammetry (LSV) are used for the evaluations. As a result of that, the best SWSV conditions like squarewave amplitude of 15 mV, frequency of 60 Hz, deposition potential of -1.0V vs. Ag/AgCl and deposition time of 200s are determined with the measured Cu sensitivity of $1.824{\mu}A/{\mu}M$. As a driving force affecting the stripping reaction of Cu, surface reaction is more dominant one than diffusion. These results are compared with other reference results and it is confirmed that our suggested CNT electrode gives rise to better Cu sensitivity result than other references.