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WoS SCOPUS Document Type Document Title Abstract Authors Affiliation ResearcherID (WoS) AuthorsID (SCOPUS) Author Email(s) Journal Name JCR Abbreviation ISSN eISSN Volume Issue WoS Edition WoS Category JCR Year IF JCR (%) FWCI FWCI Update Date WoS Citation SCOPUS Citation Keywords (WoS) KeywordsPlus (WoS) Keywords (SCOPUS) KeywordsPlus (SCOPUS) Language Publication Stage Publication Year Publication Date DOI JCR Link DOI Link WOS Link SCOPUS Link
Article Deep Learning-Based Method to Recognize Line Objects and Flow Arrows from Image-Format Piping and Instrumentation Diagrams for Digitization As part of research on technology for automatic conversion of image-format piping and instrumentation diagram (P&ID) into digital P&ID, the present study proposes a method for recognizing various types of lines and flow arrows in image-format P&ID. The proposed method consists of three steps. In the first step of preprocessing, the outer border and title box in the diagram are removed. In the second step of detection, continuous lines are detected, and then line signs and flow arrows indicating the flow direction are detected. In the third step of post-processing, using the results of line sign detection, continuous lines that require changing of the line type are determined, and the line types are adjusted accordingly. Then, the recognized lines are merged with flow arrows. For verification of the proposed method, a prototype system was used to conduct an experiment of line recognition. For the nine test P&IDs, the average precision and recall were 96.14% and 89.59%, respectively, showing high recognition performance. Moon, Yoochan; Lee, Jinwon; Mun, Duhwan; Lim, Seungeun Korea Univ, Sch Mech Engn, 145 Anam Ro, Seoul 02841, South Korea; Kyungpook Natl Univ, Dept Precis Mech Engn, Sangju Si 37224, Gyeongsangbuk D, South Korea ; Mun, Duhwan/AAC-5360-2020; Lee, Jinwon/JZS-9570-2024 57224533910; 57226003211; 23019305700; 57315285100 ans9173@korea.ac.kr;jinwonlee@korea.ac.kr;dhmun@korea.ac.kr;sea3729@naver.com; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 21 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 1.48 2025-07-30 21 26 deep learning; image processing; line object; object recognition; piping and instrumentation diagram Deep learning; Image processing; Line object; Object recognition; Piping and instrumentation diagram English 2021 2021-11 10.3390/app112110054 바로가기 바로가기 바로가기 바로가기
Article Design and Performance Evaluation of a Cherry Tomato Calyx Remover A prototype for the remover of cherry tomato calyxes was designed and manufactured. The tap remover was designed and manufactured considering the conveyor transport speed, brush length and clearance, and diameter. These were adjusted in three levels to determine the optimal design factor. Performance tests were conducted using Icon 513, a circular-shaped cherry tomato variety, and Minimaru, a jujube-shaped cherry tomato variety. Conveyor transport speeds were set at 210, 280, and 350 mm/s; brush lengths at 70, 80, and 90 mm; brush clearances at 20, 22, and 24 mm; and brush diameters at 0.8, 1.0, and 1.2 mm. The two varieties showed a similar damage rate during calyx removal. However, Minimaru showed a higher calyx removal rate than Icon 513, indicating that it is most suitable for the calyx removal mechanization process. Kim, Yeongsu; Kang, Seokho; Park, Hyunggyu; Woo, Seungmin; Uyeh, Daniel Dooyum; Ha, Yushin Kyungpook Natl Univ, Dept Bioind Machinery Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Upland Field Machinery Res Ctr, Daegu 41566, South Korea 57210594021; 57221791368; 57279183700; 57192074884; 57194449611; 57192072314 mvio9256@naver.com;deshshk@naver.com;pyd7169@naver.com;kooger7571@naver.com;uyehdooyum@gmail.com;yushin72@knu.ac.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 22 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0.07 2025-07-30 1 1 cherry tomato; calyx removal; contribution rate; Taguchi method; robust optimization Calyx removal; Cherry tomato; Contribution rate; Robust optimization; Taguchi method English 2021 2021-11 10.3390/app112211016 바로가기 바로가기 바로가기 바로가기
Article Development of a Virtual Fit Analysis Method for an Ergonomic Design of Pilot Oxygen Mask In the ergonomic design of wearable products such as an oxygen mask, systematic design methods including the analysis of anthropometric information, evaluation of fit, and product design need to utilize 3D human scan data. The present study intends to develop a virtual fit analysis method that generates an ergonomic shape of an oxygen mask for fighter pilots based on 3D facial scans. The proposed virtual fit analysis method enables iteratively to revise the shape of an oxygen mask until an appropriate level of fit between the mask and a group of pilot faces is achieved. The proposed method of virtual fit analysis and design optimization was applied to find ergonomic shapes of oxygen masks for four size categories (small narrow, medium narrow, medium wide, and large wide) to accommodate 336 pilots of the Republic of Korea Air Force. The virtual fit analysis results in the study showed that the revised oxygen mask shapes achieved significantly higher accommodation percentages (4.8 similar to 88.7%) at facial areas (nasal root, nasal side, cheek, and chin) compared to the existing oxygen mask shapes. The proposed method can be applied to develop an ergonomic product design that fits the face and other human body parts. Lee, Wonsup; Jung, Daehan; Park, Seikwon; Kim, Heeeun; You, Heecheon Handong Global Univ, Sch Global Entrepreneurship & Informat Commun Tec, Pohang 37554, South Korea; Korea Air Force Acad, Dept Mech Engn, Cheongju 28187, South Korea; Jungwon Univ, Dept Aviat Maintenance Engn, Goesan 28024, South Korea; Kyungpook Natl Univ, Dept Clothing & Text, Daegu 41566, South Korea; Pohang Univ Sci & Technol, Dept Ind & Management Engn, Pohang 37673, South Korea ; Lee, Wonsup/O-2000-2019; Lee, Wonsup/P-1555-2016 55582098000; 55793116500; 7501830128; 55766543400; 7101663786 wlee@handong.edu;daehanj@yahoo.com;ergoparks@gmail.com;hekim@knu.ac.kr;hcyou@postech.ac.kr;w.lee@handong.edu; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 12 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0.96 2025-07-30 14 16 pilot oxygen mask; design optimization; virtual fit analysis; ergonomic design RESPIRATOR; DIMENSIONS; SIMULATION; FEATURES Design optimization; Ergonomic design; Pilot oxygen mask; Virtual fit analysis English 2021 2021-06 10.3390/app11125332 바로가기 바로가기 바로가기 바로가기
Article Device Modeling of Quantum Dot-Organic Light Emitting Diodes for High Green Color Purity In this study, the optimal structure for obtaining high green color purity was investigated by modeling quantum dot (QD)-organic light-emitting diodes (OLED). It was found that even if the green quantum dot (G-QD) density in the G-QD layer was 30%, the full width at half maximum (FWHM) in the green wavelength band could be minimized to achieve a sharp emission spectrum, but it was difficult to completely block the blue light leakage with the G-QD layer alone. This blue light leakage problem was solved by stacking a green color filter (G-CF) layer on top of the G-QD layer. When G-CF thickness 5 mu m was stacked, blue light leakage was blocked completely, and the FWHM of the emission spectrum in the green wavelength band was minimized, resulting in high green color purity. It is expected that the overall color gamut of QD-OLED can be improved by optimizing the device that shows such excellent green color purity. Jeong, Byoung-Seong Kyungpook Natl Univ, Grad Sch Adv Integrat Sci & Technol, Dept Hydrogen & Renewable Energy, Daegu 41566, South Korea; Kyungpook Natl Univ, KNU Adv Mat Res Inst, Daegu 41566, South Korea 35895071700 gatorever@knu.ac.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 6 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0.22 2025-07-30 5 4 quantum dot; OLED; green color purity; emission spectrum; device modeling Device modeling; Emission spectrum; Green color purity; OLED; Quantum dot English 2021 2021-03 10.3390/app11062828 바로가기 바로가기 바로가기 바로가기
Review Doppler Optical Coherence Tomography for Otology Applications: From Phantom Simulation to In Vivo Experiment In otology, visualization and vibratory analysis have been crucial to enhance the success of diagnosis and surgical operation. Optical coherence tomography (OCT) has been employed in otology to obtain morphological structure of tissues non-invasively, owing to the ability of measuring the entire region of tympanic membrane, which compensates the limitations of conventional methods. As a functional extension of OCT, Doppler OCT, which enables the measurement of the motion information with structural data of tissue, has been applied in otology. Over the years, Doppler OCT systems have been evolved in various forms to enhance the measuring sensitivity of phase difference. In this review, we provide representative algorithms of Doppler OCT and various applications in otology from preclinical analysis to clinical experiments and discuss future developments. Seong, Daewoon; Lee, Changho; Jeon, Mansik; Kim, Jeehyun Kyungpook Natl Univ, Coll IT Engn, Sch Elect & Elect Engn, 80 Daehak Ro, Daegu 41566, South Korea; Chonnam Natl Univ, Dept Nucl Med & Artificial Intelligence Convergen, Med Sch, Hwasun 58128, Jeollanamdo, South Korea; Hwasun Hosp, Hwasun 58128, Jeollanamdo, South Korea 57212512353; 56198394900; 24171094000; 7601373350 smc7095@knu.ac.kr;ch31037@jnu.ac.kr;msjeon@knu.ac.kr;jeehk@knu.ac.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 12 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0.23 2025-07-30 8 9 optical coherence tomography; optical Doppler tomography; optical coherence vibrometry; otology; Doppler effect BLOOD-FLOW VELOCITY; TYMPANIC MEMBRANE; MIDDLE-EAR; REAL-TIME; HIGH-SPEED; HUMAN SKIN; ULTRAHIGH-RESOLUTION; STANDARD-DEVIATION; OTITIS-MEDIA; SWEPT-SOURCE Doppler effect; Optical coherence tomography; Optical coherence vibrometry; Optical doppler tomography; Otology English 2021 2021-06 10.3390/app11125711 바로가기 바로가기 바로가기 바로가기
Article DSCope: Development of Automatic Program for Detecting Fractures and Measuring Dip Angles Changes in underground environments have been predicted by investigating underground bedrock conditions and analyzing the shapes of discontinuities in the rocks. The most commonly used method is to drill a borehole, insert a camera inside and capture the wall of the borehole in a photograph to investigate the discontinuities. However, if the images of the borehole cannot be captured, the characteristics of the discontinuities in the bedrock are analyzed by capturing the drilling cores in photographs. In this case, considerable time is required to analyze the drilling cores with the naked eye and measure the attitudes of the discontinuities developed in the cores in detail. Moreover, the results may vary depending on the researcher's perspective. To overcome these limitations, this study develops a program for analyzing photographs of drilling cores. The program can automatically identify discontinuities in drilling cores and measure the attitudes through linear fitting using only drilling core photographs. In addition, we apply the program to practical field data to verify its applicability. We found that the program could provide more accurate and objective information on drilling cores than the currently used method and could more effectively organize the characteristics of fractures in the study area. Lee, Dongseob; Sung, Sangyoon; Choi, Junghae; Kihm, You-Hong Kyungpook Natl Univ, Dept Earth Sci Educ, Daegu 41566, South Korea; Ahwa Middle Sch, Gyeongsangbukdo Gyeongju Off Educ, Gyeongju 38053, South Korea; Korea Inst Geosci & Mineral Resources, Ctr HLW Geol Disposal, Daejeon 34132, South Korea 57218674853; 57226185565; 55839820300; 6504341152 astrolee@knu.ac.kr;6k5yyo@naver.com;choi.jh@knu.ac.kr;kihmyh@kigam.re.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 14 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0 2025-07-30 0 0 image processing; automated program; drilling core; fracture GRANITE Automated program; Drilling core; Fracture; Image processing English 2021 2021-07 10.3390/app11146423 바로가기 바로가기 바로가기 바로가기
Article Dynamic Nonprehensile Manipulation of a Moving Object Using a Batting Primitive To achieve human-level object manipulation capability, a robot must be able to handle objects not only with prehensile manipulation, such as pick-and-place, but also with nonprehensile manipulation. To study nonprehensile manipulation, we studied robotic batting, a primitive form of nonprehensile manipulation. Batting is a challenging research area because it requires sophisticated and fast manipulation of moving objects and requires considerable improvement. In this paper, we designed a batting system for dynamic manipulation of a moving ball and proposed several algorithms to improve the task performance of batting. To improve the recognition accuracy of the ball, we proposed a circle-fitting method that complements color segmentation. This method enabled robust ball recognition against illumination. To accurately estimate the trajectory of the recognized ball, weighted least-squares regression considering the accuracy according to the distance of a stereo vision sensor was used for trajectory estimation, which enabled more accurate and faster trajectory estimation of the ball. Further, we analyzed the factors influencing the success rate of ball direction control and applied a constant posture control method to improve the success rate. Through the proposed methods, the ball direction control performance is improved. Joe, Hyun-Min; Lee, Joonwoo; Oh, Jun-Ho Kyungpook Natl Univ, Dept Robot & Smart Syst Engn, Humanoid Robot LAB, Daegu 41566, South Korea; Kyungpook Natl Univ, Dept Robot & Smart Syst Engn, Sch Elect & Elect Engn, Robot & Intelligent Syst LAB,Dept Elect Engn, Daegu 41566, South Korea; Korea Adv Inst Sci & Technol, Dept Mech Engn, HUBO LAB, Daejeon 34141, South Korea 57188687051; 57209469100; 7402155481 hmjoe@knu.ac.kr;jwl@knu.ac.kr;jhoh@kaist.ac.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 9 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0.37 2025-07-30 5 5 nonprehensile manipulation; robotic batting; high-speed object manipulation; ball recognition; trajectory estimation; motion control; weighted least square Ball recog-nition; High-speed object manipulation; Motion control; Nonprehensile manipulation; Robotic batting; Trajectory estimation; Weighted least square English 2021 2021-05 10.3390/app11093920 바로가기 바로가기 바로가기 바로가기
Article Effect of Probabilistic Similarity Measure on Metric-Based Few-Shot Classification In developing a few-shot classification model using deep networks, the limited number of samples in each class causes difficulty in utilizing statistical characteristics of the class distributions. In this paper, we propose a method to treat this difficulty by combining a probabilistic similarity based on intra-class statistics with a metric-based few-shot classification model. Noting that the probabilistic similarity estimated from intra-class statistics and the classifier of conventional few-shot classification models have a common assumption on the class distributions, we propose to apply the probabilistic similarity to obtain loss value for episodic learning of embedding network as well as to classify unseen test data. By defining the probabilistic similarity as the probability density of difference vectors between two samples with the same class label, it is possible to obtain a more reliable estimate of the similarity especially for the case of large number of classes. Through experiments on various benchmark data, we confirm that the probabilistic similarity can improve the classification performance, especially when the number of classes is large. Lee, Youngjae; Park, Hyeyoung Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu 41566, South Korea 57218305950; 55713613500 leeyj2711@gmail.com;hypark@knu.ac.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 22 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0.07 2025-07-30 0 1 few-shot classification; metric-learning; probabilistic similarity; intra-class statistics Few-shot classification; Intra-class statistics; Metric-learning; Probabilistic similarity English 2021 2021-11 10.3390/app112210977 바로가기 바로가기 바로가기 바로가기
Article Effect of Wetting Conditions on the In Situ Density of Soil Using the Sand-Cone Method The sand-cone method is commonly used to measure the in situ density of compacted soils. While determining field density with this method, differences in the sand-filling process between the test hole and the calibration container can cause errors. The differences can result from various in situ conditions such as the shape and size of the test hole and the moisture conditions of the filling sand and test ground. Temporary rainfall can increase the moisture content of both in situ soils and filling sand. This study examined the effect of wetting conditions on the accuracy of the sand-cone method in a laboratory. Compacted soils with different water contents (2-16%) were prepared in a small circular container in the laboratory, and the sand-filling process was simulated for cylindrical, conical, and roof-shaped test holes with depths of 10 and 15 cm. As the water content of the compacted soils increased, the sand-cone method underestimated the volume of sand accumulated in the test holes by up to 20%, resulting in the calculated density being overestimated by an identical amount. Slightly moist sand was poured into artificial test holes. When the water content of the filling sand was below 1%, no significant error was observed in the calculated volume. Park, Sung-Sik; Ogunjinmi, Peter D.; Lee, Hyun-Il; Woo, Seung-Wook; Lee, Dong-Eun Kyungpook Natl Univ, Dept Civil Engn, 80 Daehakro, Daegu 41566, South Korea; Daelim Construct Co, Dept Civil Engn, 14 Mirae Ro, Incheon 21556, South Korea; Kyungpook Natl Univ, Sch Architecture Civil Environm & Energy Engn, 80 Daehakro, Daegu 41566, South Korea Ogunjinmi, Peter/IWL-9239-2023 36241850300; 57217171969; 57221532018; 57212917862; 56605563300 sungpark@knu.ac.kr;peterogunjinmi@knu.ac.kr;h1901561@daelim.co.kr;geowsw@knu.ac.kr;dolee@knu.ac.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 2 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0 2025-07-30 0 0 sand-cone method; in situ density; sand; compaction; moisture Compaction; In situ density; Moisture; Sand; Sand-cone method English 2021 2021-01 10.3390/app11020718 바로가기 바로가기 바로가기 바로가기
Article Enhanced Potential Field-Based Collision Avoidance in Cluttered Three-Dimensional Urban Environments With the various applications of unmanned aerial vehicles (UAVs), the number of UAVs will increase in limited airspace, leading to an increased risk collision. To reduce such potential risk, this work proposes a collision avoidance strategy for UAVs using an enhanced potential field (EPF) approach in cluttered three-dimensional urban environments. Using the EPF formulated in a two-dimensional environment, the avoidance maneuvers for both horizontal and vertical planes are generated by introducing rotation matrices, and these maneuvers are combined by applying a weighting factor. The numerical simulations with various meaningful scenarios are conducted to validate the performance of the proposed approach. To mimic practical situations, UAV dynamics and sensor limitations were considered. The simulation results show that the proposed approach provides an efficient, reliable, and collision-free path without local minima and unreachable goal issues. Choi, Daegyun; Kim, Donghoon; Lee, Kyuman Univ Cincinnati, Dept Aerosp Engn & Engn Mech, Cincinnati, OH 45221 USA; Kyungpook Natl Univ, Dept Robot & Smart Syst Engn, Daegu 41566, South Korea lee, kyuman/AAM-6979-2020 57219363030; 57223664471; 57193932345 choidg@mail.uc.edu;Donghoon.Kim@uc.edu;klee400@knu.ac.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 22 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0.37 2025-07-30 3 7 enhanced potential field; collision avoidance; unmanned aerial vehicles Collision avoidance; Enhanced potential field; Unmanned aerial vehicles English 2021 2021-11 10.3390/app112211003 바로가기 바로가기 바로가기 바로가기
Article Enhanced Tone Mapping Using Regional Fused GAN Training with a Gamma-Shift Dataset High-dynamic-range (HDR) imaging is a digital image processing technique that enhances an image's visibility by modifying its color and contrast ranges. Generative adversarial networks (GANs) have proven to be potent deep learning models for HDR imaging. However, obtaining a sufficient volume of training image pairs is difficult. This problem has been solved using CycleGAN, but the result of the use of CycleGAN for converting a low-dynamic-range (LDR) image to an HDR image exhibits problematic color distortion, and the intensity of the output image only slightly changes. Therefore, we propose a GAN training optimization model for converting LDR images into HDR images. First, a gamma shift method is proposed for training the GAN model with an extended luminance range. Next, a weighted loss map trains the GAN model for tone compression in the local area of images. Then, a regional fusion training model is used to balance the training method with the regional weight map and the restoring speed of local tone training. Finally, because the generated module tends to show a good performance in bright images, mean gamma tuning is used to evaluate image luminance channels, which are then fed into modules. Tests are conducted on foggy, dark surrounding, bright surrounding, and high-contrast images. The proposed model outperforms conventional models in a comparison test. The proposed model complements the performance of an object detection model even in a real night environment. The model can be used in commercial closed-circuit television surveillance systems and the security industry. Jung, Sung-Woon; Kwon, Hyuk-Ju; Lee, Sung-Hak Kyungpook Natl Univ, Sch Elect & Elect Engn, 80 Deahakro, Daegu 702701, South Korea 57216623303; 55169908300; 7601395661 iymo@knu.ac.kr;olin1223@ee.knu.ac.kr;shak2@ee.knu.ac.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 16 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0.22 2025-07-30 4 4 gamma shift; generative adversarial network (GAN); tone mapping; regional fusion training (RFT); regional weighted loss (RWL) Gamma shift; Generative adversarial network (GAN); Regional fusion training (RFT); Regional weighted loss (RWL); Tone mapping English 2021 2021-08 10.3390/app11167754 바로가기 바로가기 바로가기 바로가기
Article Evaluation of Reinforcement and Deep Learning Algorithms in Controlling Unmanned Aerial Vehicles Unmanned Aerial Vehicles (UAVs) are abundantly becoming a part of society, which is a trend that is expected to grow even further. The quadrotor is one of the drone technologies that is applicable in many sectors and in both military and civilian activities, with some applications requiring autonomous flight. However, stability, path planning, and control remain significant challenges in autonomous quadrotor flights. Traditional control algorithms, such as proportional-integral-derivative (PID), have deficiencies, especially in tuning. Recently, machine learning has received great attention in flying UAVs to desired positions autonomously. In this work, we configure the quadrotor to fly autonomously by using agents (the machine learning schemes being used to fly the quadrotor autonomously) to learn about the virtual physical environment. The quadrotor will fly from an initial to a desired position. When the agent brings the quadrotor closer to the desired position, it is rewarded; otherwise, it is punished. Two reinforcement learning models, Q-learning and SARSA, and a deep learning deep Q-network network are used as agents. The simulation is conducted by integrating the robot operating system (ROS) and Gazebo, which allowed for the implementation of the learning algorithms and the physical environment, respectively. The result has shown that the Deep Q-network network with Adadelta optimizer is the best setting to fly the quadrotor from the initial to desired position. Jembre, Yalew Zelalem; Nugroho, Yuniarto Wimbo; Khan, Muhammad Toaha Raza; Attique, Muhammad; Paul, Rajib; Shah, Syed Hassan Ahmed; Kim, Beomjoon Keimyung Univ, Dept Elect Engn, Daegu 42601, South Korea; Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu 41566, South Korea; Sejong Univ, Dept Software, Seoul 05006, South Korea; Ajou Univ, Dept Software & Comp Engn, Suwon 16499, South Korea; JMA Wireless, Corona, CA 92881 USA ; Khan, Turyalai/HPH-0061-2023; Yalew, Zelalem/AAS-3299-2021; Shah, Syed Hassan/E-5058-2014; Khan, Muhammad Toaha Raza/KXR-8209-2024; Paul, Rajib/H-3830-2017 36835873800; 57226679492; 57202044597; 55755354900; 55360116500; 55389144500; 55726527400 zizutg@kmu.ac.kr;wimboyt@kmu.ac.kr;toaha@knu.ac.kr;attique@sejong.ac.kr;rajib@ajou.ac.kr;sh.ahmed@ieee.org;bkim@kmu.ac.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 16 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0.81 2025-07-30 11 14 reinforcement learning; UAV; quadrotor; flight control; intelligent control QUADROTOR; FLIGHT Flight control; Intelligent control; Quadrotor; Reinforcement learning; UAV English 2021 2021-08 10.3390/app11167240 바로가기 바로가기 바로가기 바로가기
Article Fast Drivable Areas Estimation with Multi-Task Learning for Real-Time Autonomous Driving Assistant Autonomous driving is a safety-critical application that requires a high-level understanding of computer vision with real-time inference. In this study, we focus on the computational efficiency of an important factor by improving the running time and performing multiple tasks simultaneously for practical applications. We propose a fast and accurate multi-task learning-based architecture for joint segmentation of drivable area, lane line, and classification of the scene. An encoder-decoder architecture efficiently handles input frames through shared representation. A comprehensive understanding of the driving environment is improved by generalization and regularization from different tasks. The proposed method learns end-to-end through multi-task learning on a very challenging Berkeley Deep Drive dataset and shows its robustness for three tasks in autonomous driving. Experimental results show that the proposed method outperforms other multi-task learning approaches in both speed and accuracy. The computational efficiency of the method was over 93.81 fps at inference, enabling execution in real-time. Lee, Dong-Gyu Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 700010, South Korea 57169003900 glee@knu.ac.kr;dglee@knu.ac.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 22 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 1.33 2025-07-30 17 23 drivable area estimation; autonomous driving; multi-task learning; lane line detection; scene classification; real-time processing Autonomous driving; Drivable area estimation; Lane line detection; Multi-task learning; Real-time processing; Scene classification English 2021 2021-11 10.3390/app112210713 바로가기 바로가기 바로가기 바로가기
Article Fermented Rice Germ Extract Ameliorates Abnormal Glucose Metabolism via Antioxidant Activity in Type 2 Diabetes Mellitus Mice Rice germ is an abundant source of ferulic acid, which is known for its anti-oxidant activity. This study aimed to evaluate the regulatory effects of fermented rice germ extracts on hepatic glucose metabolism in C57BL/KsJ-db/db mice. Rice germ was fermented with Lactobacillus plantarum and extracted with 30% ethanol (RG₃₀E) or 50% ethanol (RG₅₀E). Mice were fed modified AIN-93 diets containing fermented rice germ extracts and ferulic acid for 8 weeks. RG₅₀E significantly reduced food intake as well as liver weight and RG₃₀E and RG₅₀E improved glucose homeostasis, as indicated by fasting blood glucose levels and glucose tolerance. Hepatic triglyceride and total cholesterol levels were significantly decreased in db/db mice fed RG₃₀E and RG₅₀E. The antioxidant capacity of RG₃₀E and RG₅₀E was confirmed by a decrease in malondialdehyde levels and an increase in hepatic superoxide dismutase activity. The expression of genes related to glycolysis and gluconeogenesis was significantly regulated by RG₃₀E and RG₅₀E. These results suggest that fermented rice germ extracts have the potential to regulate hypoglycemia and hepatic glucose metabolism in type 2 diabetes db/db mice. Hyun, Ye Ji; Kim, Ju Gyeong; Jung, Sung Keun; Kim, Ji Yeon Seoul Natl Univ Sci & Technol, Dept Food Sci & Technol, 232 Gongneung Ro, Seoul 01811, South Korea; Kyungpook Natl Univ, Sch Food Sci & Biotechnol, Daegu 41566, South Korea; Kyungpook Natl Univ, Inst Agr Sci & Technol, Daegu 41566, South Korea ; Jung, SUNG KEUN/AGR-2623-2022; Kim, Joo/X-7562-2019 57221908866; 57216640718; 35310491400; 55873676800 yj0706hyun@naver.com;jgrla23@naver.com;skjung04@knu.ac.kr;jiyeonk@seoultech.ac.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 7 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0.52 2025-07-30 7 8 rice germ; ferulic acid; type 2 diabetes mellitus; hypoglycemia effect; hepatic glucose metabolism Ferulic acid; Hepatic glucose metabolism; Hypoglycemia effect; Rice germ; Type 2 diabetes mellitus English 2021 2021-04 10.3390/app11073091 바로가기 바로가기 바로가기 바로가기
Article GA-Based Optimization Method for Mobile Crane Repositioning Route Planning Mobile cranes have been used extensively as essential equipment at construction sites. The productivity improvement of the mobile crane affects the overall productivity of the construction project. Hence, various studies have been conducted regarding mobile crane operation planning. However, studies on solving RCP (the repositioning mobile crane problem) are insufficient. This article presents a mobile crane reposition route planning optimization method (RPOS) that minimizes the total operating time of mobile crane. It converts the construction site into a mathematical model, determines feasible locations of the mobile crane, and identifies near-global optimal solution (s) (i.e., the placement point sequences of mobile crane) by implementing genetic algorithm and dijkstra's algorithm. The study is of value to practitioners because RPOS provides an easy-to-use computerized tool that reduces the lengthy computations relative to data processing and Genetic Algorithms (GAs). Test cases verify the validity of the computational method. Gwak, Han-Seong; Lee, Hong-Chul; Choi, Byoung-Yoon; Mi, Yirong Construct Engn Policy Inst Korea, Seoul 06098, South Korea; Kyungpook Natl Univ, Intelligent Construct Automat Ctr, Daegu 41566, South Korea; Kyungpook Natl Univ, Sch Architecture Environm Energy & Civil Engn, Daegu 41566, South Korea Gwak, Hanseong/AAW-6131-2021 56800359900; 57060948100; 57218326140; 57225181327 hsgwak@cepik.re.kr;colf@knu.ac.kr;jr1381@knu.ac.kr;2021320938@knu.ac.kr; APPLIED SCIENCES-BASEL APPL SCI-BASEL 2076-3417 11 13 SCIE CHEMISTRY, MULTIDISCIPLINARY;ENGINEERING, MULTIDISCIPLINARY;MATERIALS SCIENCE, MULTIDISCIPLINARY;PHYSICS, APPLIED 2021 2.838 41.9 0.37 2025-07-30 5 7 mobile crane; reposition; genetic algorithm; optimization; data modeling GENETIC ALGORITHM; SELECTION Data modeling; Genetic algorithm; Mobile crane; Optimization; Reposition English 2021 2021-07 10.3390/app11136010 바로가기 바로가기 바로가기 바로가기
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Title 논문의 제목입니다.
Abstract 논문의 초록(요약)입니다. 연구의 목적, 방법, 결과, 결론을 간략히 요약한 내용입니다.
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Journal 논문이 게재된 학술지의 정식 명칭입니다.
JCR Abbreviation Journal Citation Reports에서 사용하는 저널의 공식 약어입니다. 저널을 간략하게 표기할 때 사용됩니다.
ISSN International Standard Serial Number. 국제표준연속간행물번호로, 인쇄본 저널에 부여되는 고유 식별번호입니다.
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Volume 저널의 권(Volume) 번호입니다. 보통 연도별로 하나의 권이 부여됩니다.
Issue 저널의 호(Issue) 번호입니다. 한 권 내에서 여러 호로 나누어 출판되는 경우가 많습니다.
WoS Edition Web of Science의 에디션입니다. SCIE(Science Citation Index Expanded), SSCI(Social Sciences Citation Index), AHCI(Arts & Humanities Citation Index) 등으로 구분됩니다.
WoS Category Web of Science의 주제 분류 카테고리입니다. 저널과 논문이 속한 학문 분야를 나타냅니다.
JCR Year 해당 저널의 JCR(Journal Citation Reports) 지표가 산출된 연도입니다.
IF (Impact Factor) 저널 영향력 지수. 최근 2년간 발표된 논문이 해당 연도에 평균적으로 인용된 횟수를 나타냅니다. 저널의 학술적 영향력을 나타내는 대표적인 지표입니다.
JCR (%) 해당 카테고리에서 저널이 위치하는 상위 백분율입니다. 값이 낮을수록 우수한 저널임을 의미합니다 (예: 5%는 상위 5%를 의미).
FWCI Field-Weighted Citation Impact. 분야별 가중 인용 영향력 지수입니다. 논문이 받은 인용을 동일 분야, 동일 연도, 동일 문헌 유형의 평균과 비교한 값입니다. 1.0이 평균이며, 1.0보다 높으면 평균 이상의 인용을 받았음을 의미합니다.
FWCI UpdateDate FWCI 값이 마지막으로 업데이트된 날짜입니다. FWCI는 인용이 누적됨에 따라 주기적으로 업데이트됩니다.
WOS Citation Web of Science에서 집계된 해당 논문의 총 인용 횟수입니다.
SCOPUS Citation SCOPUS에서 집계된 해당 논문의 총 인용 횟수입니다.
Keywords (WoS) 저자가 논문에서 직접 지정한 키워드입니다. Web of Science에 등록된 저자 키워드 목록입니다.
KeywordsPlus (WoS) Web of Science에서 자동으로 추출한 추가 키워드입니다. 논문의 참고문헌 제목에서 자주 등장하는 단어들로 생성됩니다.
Keywords (SCOPUS) 저자가 논문에서 직접 지정한 키워드입니다. SCOPUS에 등록된 저자 키워드 목록입니다.
KeywordsPlus (SCOPUS) SCOPUS에서 자동으로 추출하거나 추가한 색인 키워드입니다.
Language 논문이 작성된 언어입니다. 대부분 English이며, 그 외 다양한 언어로 작성된 논문이 포함될 수 있습니다.
Publication Year 논문이 출판된 연도입니다.
Publication Date 논문의 정확한 출판 날짜입니다 (년-월-일 형식).
DOI Digital Object Identifier. 디지털 객체 식별자로, 논문을 고유하게 식별하는 영구적인 식별번호입니다. 이를 통해 논문의 온라인 위치를 찾을 수 있습니다.