• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.3
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• pp.580-594
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• 2015

Liquid sloshing in two-dimensional (2-D) and three-dimensional (3-D) rectangular tanks is simulated by using a level set method based on the finite volume method. In order to examine the effect of natural frequency modes on liquid sloshing, we considered a wide range of frequency ratios ($0.5{\leq}fr{\leq}3.2$). The frequency ratio is defined by the ratio of the excitation frequency to the natural frequency of the fluid, and covers natural frequency modes from 1 to 5. When fr = 1, which corresponds to the first mode of the natural frequency, strong liquid sloshing reveals roof impact, and significant forces are generated by the liquid in the tank. The liquid flows are mainly unidirectional. Thus, the strong bulk motion of the fluid contributes to a higher elevation of the free surface. However, at fr = 2, the sloshing is considerably suppressed, resulting in a calm wave with relatively lower elevation of the free surface, since the waves undergo destructive interference. At fr = 2, the lower peak of the free surface elevation occurs. At higher modes of $fr_3$, $fr_4$, and $fr_5$, the free surface reveals irregular deformation with nonlinear waves in every case. However, the deformation of the free surface becomes weaker at higher natural frequency modes. Finally, 3-D simulations confirm our 2-D results.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.273-284
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• 2018

Purpose: Conventional headland turning typically requires repeated forward and backward movements to move the farming equipment to the next row. This research focuses on developing an upland agricultural robot with an optimized headland turning mechanism that enables a $180^{\circ}$ turning positioning to the next row in one steering motion designed for a two-wheel steering, four-wheel drive agricultural robot named the HADA-bot. The proposed steering mechanism allows for faster turnings at each headland compared to those of the conventional steering system. Methods: The HADA-bot was designed with 1.7-m wide wheel tracks to travel along the furrows of a garlic bed, and a look-ahead path following algorithm was applied using a real-time kinematic global positioning system signal. Pivot turning tests focused primarily on accuracy regarding the turning radius for the next path matching, saving headland turning time, area, and effort. Results: Several test cases were performed by evaluating right and left turns on two different surfaces: concrete and soil, at three speeds: 1, 2, and 3 km/h. From the left and right side pivot turning results, the percentage of lateral deviation is within the acceptable range of 10% even on the soil surface. This U-turn scheme reduces 67% and 54% of the headland turning time, and 36% and 32% of the required headland area compared to a 50 hp tractor (ISEKI, TA5240, Ehime, Japan) and a riding-type cultivator (CFM-1200, Asia Technology, Deagu, Rep. Korea), respectively. Conclusion: The pivot turning trajectory on both soil and concrete surfaces achieved similar results within the typical operating speed range. Overall, these results prove that the pivot turning mechanism is suitable for improving conventional headland turning by reducing both turning radius and turning time.

• Journal of Korea Technology Innovation Society
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• v.22 no.3
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• pp.340-361
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• 2019

This study analyzes the technological structure of artificial intelligence (AI) and technological capabilities of AI companies based on patent information. 2589 AI patents registered in USPTO from 2007 to 2017 were collected and analyzed by the Latent Dirichlet Allocation (LDA) to derive 20 AI technology topics. Analysis of technology development trends by AI technology reveals that visual understanding, data analysis, motion control, and machine learning are growing, while language understanding and speech technology are sluggish. In addition, we also investigated leading companies in each sub-field of AI as well as core competencies of global IT companies. The findings of this study are expected to be fruitfully used for formulation and implementation of technology strategy of AI companies.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• Smart Media Journal
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• v.8 no.3
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• pp.95-103
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• 2019

The global manufacturing industry has reached the limit to growth due to a long-term recession, the rise of labor cost and raw material. As a solution to these difficulties, we promote the 4th Industry Revolution based on ICT and sensor technology. Following this trend, this paper proposes the design of a model using manufacturing data in the protection film process for smart manufacturing innovation. In the protective film process, the manufacturing data of temperature, pressure, humidity, and motion and thermal image are acquired by various sensors for the raw material blending, stirring, extrusion, and inspection processes. While the acquired manufacturing data is stored in mass storage, A.I. platform provides time-series image analysis and its visualization.

• Smart Structures and Systems
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• v.24 no.3
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• pp.303-317
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• 2019

Magneto-rheological fluid (MRF) rotatory dampers are normally used for controlling the constant rotation of machines and engines. In this research, such a device is proposed to act as variable stiffness device to alleviate the rotational oscillation existing in the many engineering applications, such as motor. Under such thought, the main purpose of this work is to characterize the nonlinear torque-angular displacement/angular velocity responses of an MRF based variable stiffness device in oscillatory motion. A rotational hysteresis model, consisting of a rotatory spring, a rotatory viscous damping element and an error function-based hysteresis element, is proposed, which is capable of describing the unique dynamical characteristics of this smart device. To estimate the optimal model parameters, a modified whale optimization algorithm (MWOA) is employed on the captured experimental data of torque, angular displacement and angular velocity under various excitation conditions. In MWOA, a nonlinear algorithm parameter updating mechanism is adopted to replace the traditional linear one, enhancing the global search ability initially and the local search ability at the later stage of the algorithm evolution. Additionally, the immune operation is introduced in the whale individual selection, improving the identification accuracy of solution. Finally, the dynamic testing results are used to validate the performance of the proposed model and the effectiveness of the proposed optimization algorithm.

• Journal of Astronomy and Space Sciences
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• v.36 no.1
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• pp.35-43
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• 2019

The Optical Wide-field patroL-Network (OWL-Net) is a global optical network for Space Situational Awareness in Korea. The primary operational goal of the OWL-Net is to track Low Earth Orbit (LEO) satellites operated by Korea and to monitor the Geostationary Earth Orbit (GEO) region near the Korean peninsula. To obtain dense measurements on LEO tracking, the chopper system was adopted in the OWL-Net's back-end system. Dozens of angle-only measurements can be obtained for a single shot with the observation mode for LEO tracking. In previous work, the reduction process of the LEO tracking data was presented, along with the mechanical specification of the back-end system of the OWL-Net. In this research, we describe an integrity assessment method of time-position matching and verification of results from real observations of LEO satellites. The change rate of the angle of each streak in the shot was checked to assess the results of the matching process. The time error due to the chopper rotation motion was corrected after re-matching of time and position. The corrected measurements were compared with the simulated observation data, which were taken from the Consolidated Prediction File from the International Laser Ranging Service. The comparison results are presented in the In-track and Cross-track frame.

• Journal of Ocean Engineering and Technology
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• v.33 no.2
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• pp.99-105
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• 2019

Unlike typical a dynamic positioning (DP) system, a DP-assisted mooring system must determine a set point (SP) that can ensure a mooring tension safety range to prevent an excessive increase in mooring tension. In this paper, a new algorithm for determining the SP is suggested in order to reduce the tension on all the mooring lines. To determine the SP, a working area around the vessel is represented by a rectangular grid. Thus, the size of the grid area is limited considering the offset of a vessel with a mooring system. At each grid's nodes, the resultant tension from all the mooring lines is estimated using the time history of the tension and vessel's position. The results of static analyses for each grid position are used to estimate the global tension. Consequently, the SP is automatically selected as a position satisfying criterion for minimizing the total tension. In order to validate the suggested algorithm, a motion simulation with the control system in the time domain and a discussion of the results are presented.

• Journal of Korean Medicine Rehabilitation
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• v.32 no.1
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• pp.125-131
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• 2022

This study was to investigate the effectiveness of combined Korean medicine treatment on a patient who was diagnosed on lumbosacral transitional vertebra (LSTV) with localized bone marrow edema. The patient was treated with acupuncture, pharmacopucture, cupping and herbal medicine. We evaluated patient's progress using range of motion (ROM), EuroQol-5 dimensions (EQ-5D), Oswestry disability index (ODI), numerical rating scale (NRS), patient global impression of change, self-walkable distance. NRS of back pain decreased from 7 to 5, at the same time NRS of lower limb decreased from 4 to 3. EQ-5D score increased from 0.24 to 0.646. ODI score improved 80 to 62. Self-walkable distance and lumbar spine ROM also increased. As a result, clinical improvements were found in a patient. In conclusion, this study shows that Korean medicine treatment can be considered as effective conservative care for LSTV with localized bone marrow edema.

• Journal of Ocean Engineering and Technology
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• v.36 no.5
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• pp.340-352
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• 2022

This article presents a modeling method for the uncorrelated measurement error of the ultra-short baseline (USBL) acoustic positioning system for aiding navigation of underwater vehicles. The Mahalanobis distance (MD) and principal component analysis are applied to decorrelate the errors of USBL measurements, which are correlated in the x- and y-directions and vary according to the relative direction and distance between a reference station and the underwater vehicles. The proposed method can decouple the radial-direction error and angular direction error from each USBL measurement, where the former and latter are independent and dependent, respectively, of the distance between the reference station and the vehicle. With the decorrelation of the USBL errors along the trajectory of the vehicles in every time step, the proposed method can reduce the threshold of the outlier decision level. To demonstrate the effectiveness of the proposed method, simulation studies were performed with motion data obtained from a field experiment involving an autonomous underwater vehicle and USBL signals generated numerically by matching the specifications of a specific USBL with the data of a global positioning system. The simulations indicated that the navigation system is more robust in rejecting outliers of the USBL measurements than conventional ones. In addition, it was shown that the erroneous estimation of the navigation system after a long USBL blackout can converge to the true states using the MD of the USBL measurements. The navigation systems using the uncorrelated error model of the USBL, therefore, can effectively eliminate USBL outliers without loss of uncontaminated signals.