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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 |
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| ○ | Conference paper | Characterization of AlGaN/GaN HEMTs on 4-inch SiC substrate at Cryogenic temperature | We present the systematic analysis of DC and carrier transport behavior of AlGaN/GaN HEMTs in room-temperature and Cryogenic temperature. The fabricated Lg = 2 μm devices shows maximum-transconductance (gmₘₐₓ) of 175 mS/mm and off-current (Ioff) of 10 μA/mm in comprision to gmₘₐₓ of 298 mS/mm and Ioff of 1 nA/mm. Also, series resistance (RS) is improved from 1.8 Ω∙mm at 300 K to 0.44 Ω∙mm at 4 K due to reduction of sheet resistance of access region. Carrier transport at 300 K and 4 K were evaluated through gm modeling, indicating that improvement of effective mobility (μnₑff) and slightly improvement of saturation velocity (vsat). Here, we investigate AlGaN/GaN HEMTs behavior in Cryogenic temperature applications such as deep space reception, radio astronomy, and quantum computing. © 2024 International Conference on Compound Semiconductor Manufacturing Technology. All Rights Reserved. | Park, Wan-Soo; Lee, Hyeok-Jun; Kim, Hyo-Jin; Lee, Jae-Hak; Yang, Kyounghoon; Kim, Dae-Hyun | School of Electronic and Electrical Engineering, Kyungpook National University (KNU), Daegu, South Korea; School of Electronic and Electrical Engineering, Kyungpook National University (KNU), Daegu, South Korea; School of Electronic and Electrical Engineering, Kyungpook National University (KNU), Daegu, South Korea; School of Electronic and Electrical Engineering, Kyungpook National University (KNU), Daegu, South Korea; School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea; School of Electronic and Electrical Engineering, Kyungpook National University (KNU), Daegu, South Korea | 57222957219; 59106441600; 57202516002; 55690077600; 7404291550; 57212363794 | dae-hyun.kim@ee.knu.ac.kr; | CS MANTECH 2024 - 2024 International Conference on Compound Semiconductor Manufacturing Technology | 0 | AlGaN/GaN; Carrier transport; Cryogenic; GaN; HEMTs | Aluminum gallium nitride; Carrier mobility; Electric resistance; Gallium nitride; Quantum chemistry; Radio astronomy; Semiconductor device manufacture; Silicon carbide; Superconducting films; Wide band gap semiconductors; AlGaN; AlGaN/GaN; AlGaN/GaN HEMTs; AlGaN/GaN-HEMT; Carriers transport; Cryogenic temperatures; Maximum transconductance; SiC substrates; Systematic analysis; Transport behavior; Carrier transport; Cryogenics; III-V semiconductors | English | Final | 2024 | 바로가기 | ||||||||||||||||||||||
| ○ | Article | Choosing allowability boundaries for describing objects in subject areas | Anomaly detection is one of the most promising problems for study and can be used as independent units and preprocessing tools before solving any fundamental data mining problems. This article proposes a method for detecting specific errors with the involvement of experts from subject areas to fill knowledge. The proposed method about outliers hypothesizes that they locate closer to logical boundaries of intervals derived from pair features, and the interval ranges vary in different domains. We construct intervals leveraging pair feature values. While forming knowledge in a specific field, a domain specialist checks the logical al-lowability of objects based on the range of the intervals. If the objects are logical outliers, the specialist ignores or corrects them. We offer the general algorithm for the formation of the database based on the proposed method in the form of a pseudo-code, and we provide comparison results with existing methods. © 2024, Institute of Advanced Engineering and Science. All rights reserved. | Lolaev, Musulmon; Madrakhimov, Shavkat; Makharov, Kodirbek; Saidov, Doniyor | Center for Resilient and Evolving Intelligence, Kyungpook National University, Daegu, South Korea; Department of Algorithms and programming technologies, National University of Uzbekistan named after Mirzo Ulugbek, Tashkent, Uzbekistan; Department of Algorithms and programming technologies, National University of Uzbekistan named after Mirzo Ulugbek, Tashkent, Uzbekistan, Department of Applied Informatics, Kimyo International University in Tashkent, Tashkent, Uzbekistan; Department of Algorithms and programming technologies, National University of Uzbekistan named after Mirzo Ulugbek, Tashkent, Uzbekistan | 57226384015; 57226382733; 57226378546; 57221666213 | maxarov.qodirbek@gmail.com; | IAES International Journal of Artificial Intelligence | 2089-4872 | 13 | 1 | 0.66 | 2025-05-07 | 3 | Data cleaning; Dirty data; Invalid objects; Machine learning; Outliers; Preprocessing; Valid intervals | English | Final | 2024 | 10.11591/ijai.v13.i1.pp329-336 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Conference paper | Classification of Surface Defects on Steel Sheet Images Using DenseNet121 Architecture | Classifying surface defects is vital for steel sheet manufacturers. The conventional approaches have obtained moderate accuracies in terms of classifiers, while these methods have developed by depending on experts or different projects. DenseNet121 model, a machine-vision-based classification approach was proposed to overcome the drawbacks of traditional approaches. The goal of this paper is to apply pre-trained DenseNet121 network for classifying the steel defects categorized as rolled-in scales, patches, crazing, pitted surface, inclusion, and scratches. Fine-tuning transfer learning and k-fold cross-validation were implemented to train and evaluate the performance of the model. Additionally, this study uses Adaptive Moment Estimation (Adam) and Stochastic Gradient Descent (SGD) algorithms to optimize the model parameters. The testing result showed that all 5 folds were over 98.5% accuracy for both Adam and SGD optimizers. It also found that a gradient-weighted class activation mapping (Grad-CAM) was a good technique to visualize the surface failure locations of steel sheets. The findings indicated the ability of the proposed method to automatically classify the steel surface defect statuses. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. | Do, Tung-Lam; Nguyen, Truong-Giang; Nguyen, Khac-Quan; Nguyen, Tan-No; Nguyen, Nhut-Nhut | Faculty of Civil Engineering, Ho Chi Minh City Open University, Ho Chi Minh City, Viet Nam; Faculty of Civil Engineering, Ho Chi Minh City Open University, Ho Chi Minh City, Viet Nam; Faculty of Civil Engineering, Ho Chi Minh City Open University, Ho Chi Minh City, Viet Nam; Department of Civil Engineering, Kyungpook National University, Daegu, South Korea; Department of Civil Engineering, Kyungpook National University, Daegu, South Korea, Faculty of Civil Engineering, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Viet Nam, Vietnam National University Ho Chi Minh City, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Viet Nam | 58771606700; 58835058000; 58771715700; 57862912800; 57211211964 | nguyennhutnhut@hcmut.edu.vn; | Lecture Notes in Civil Engineering | 2366-2557 | 442 | 5.19 | 2025-04-16 | 2 | Convolutional neural network; Image classification; Surface defect; Transfer learning | Convolutional neural networks; Deep learning; Gradient methods; Optimization; Steel sheet; Stochastic models; Stochastic systems; Surface defects; Transfer learning; Classification approach; Conventional approach; Convolutional neural network; Images classification; Machine-vision; Moment estimation; Steel sheet manufacturer; Traditional approaches; Transfer learning; Vision based; Image classification | English | Final | 2024 | 10.1007/978-981-99-7434-4_74 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Review | Clearing techniques for deeper imaging of plants and plant–microbe interactions | Plant cells are uniquely characterized by exhibiting cell walls, pigments, and phenolic compounds, which can impede microscopic observations by absorbing and scattering light. The concept of clearing was first proposed in the late nineteenth century to address this issue, aiming to render plant specimens transparent using chloral hydrate. Clearing techniques involve chemical procedures that render biological specimens transparent, enabling deep imaging without physical sectioning. Drawing inspiration from clearing techniques for animal specimens, various protocols have been adapted for plant research. These procedures include (i) hydrophobic methods (e.g., Visikol™), (ii) hydrophilic methods (ScaleP and ClearSee), and (iii) hydrogel-based methods (PEA-CLARITY). Initially, clearing techniques for plants were mainly utilized for deep imaging of seeds and leaves of herbaceous plants such as Arabidopsis thaliana and rice. Utilizing cell wall-specific fluorescent dyes for plants and fungi, researchers have documented the post-penetration behavior of plant pathogenic fungi within hosts. State-of-the-art plant clearing techniques, coupled with microbe-specific labeling and high-throughput imaging methods, offer the potential to advance the in planta characterization of plant microbiomes. © The Author(s) 2024. | Kim, Ki Woo | Department of Forest Ecology and Protection, Tree Diagnostic Center, Kyungpook National University, Sangju, 37224, South Korea | 57201369889 | kiwoo@knu.ac.kr; | Applied Microscopy | 2287-5123 | 54 | 1 | 0.22 | 2025-05-07 | 1 | Cell wall; Fiber; Light scattering; Pigment | Bacteria; Cells; Cytology; Fungi; Rendering (computer graphics); Seed; Cell walls; Cell-be; Cell/B.E; Cell/BE; Deep imaging; Microscopic observations; Phenolic compounds; Plant-microbe interactions; Plants cells; Scattering light; Light scattering | English | Final | 2024 | 10.1186/s42649-024-00098-9 | 바로가기 | 바로가기 | |||||||||||||||
| ○ | Article | Clinical Impact of Coronavirus Disease 2019 Outbreaks in Korea on Seizures in Children | Purpose: Coronavirus disease 2019 (COVID-19) can be associated with neurological complications. This study investigated the impact of COVID-19 outbreaks on seizure incidence and duration in children in Korea. Methods: We retrospectively analyzed medical records from Kyungpook National University Children’s Hospital, including 768 children with seizures during the peak COVID-19 outbreaks in March and August 2022, and compared patterns with the same periods in 2021. We examined demographic and clinical characteristics, causes of seizures, underlying conditions, seizure durations, and COVID-19 test results. Results: Out of 16,373,836 COVID-19 cases during the first peak, 25.6% were children (4,184,383), and during the second peak, 20.5% of 6,400,244 cases were children (1,314,331). No significant age differences were observed between either peak and the previous year. However, when compared to the previous year, febrile seizures (FS) were more common during both peaks (25.9% vs. 65.1% in the first peak; 34.3% vs. 59.2% in the second peak). The prevalence of FS was significantly higher in the COVID-19-positive group (84.1%) than in the COVID-19-negative group (51.9%). The incidence of new-onset seizures or breakthrough seizures showed no significant difference. Seizure duration and the incidence of status epilepticus (SE) showed no significant changes, but SE was more common in the COVID-19-negative group (17.1% vs. 6.2%). The clinical features of FS were similar in both groups. Conclusion: COVID-19 appeared to increase the risk of FS in children, but there was no significant impact on the risk of breakthrough seizures or SE in children with epilepsy. Nevertheless, larger-scale studies are necessary. © 2024 Korean Child Neurology Society This is an Open Access article distributed under. | Lee, Seungjae; Hwang, Su-Kyeong; Lee, Yun-Jeong; Bae, Hyunwoo; Kwon, Soonhak | Department of Pediatrics, Daegu Fatima Hospital, Daegu, South Korea; Department of Pediatrics, Kyungpook National University Children’s Hospital, School of Medicine, Kyungpook National University, Daegu, South Korea; Department of Pediatrics, Kyungpook National University Children’s Hospital, School of Medicine, Kyungpook National University, Daegu, South Korea; Department of Pediatrics, Kyungpook National University Children’s Hospital, School of Medicine, Kyungpook National University, Daegu, South Korea; Department of Pediatrics, Kyungpook National University Children’s Hospital, School of Medicine, Kyungpook National University, Daegu, South Korea | 59213021400; 37761570400; 55978748900; 57877451300; 55468232200 | shkwon@knu.ac.kr; | Annals of Child Neurology | 2635-909X | 32 | 3 | 0 | 2025-05-07 | 0 | Child; COVID-19; Epilepsy; SARS-CoV-2; Seizures | age distribution; Article; child; childhood; clinical feature; coronavirus disease 2019; disease duration; epilepsy; epileptic state; febrile convulsion; female; human; incidence; major clinical study; male; pandemic; prevalence; retrospective study; risk factor; seizure; South Korea | English | Final | 2024 | 10.26815/acn.2024.00465 | 바로가기 | 바로가기 | |||||||||||||||
| ○ | ○ | Proceedings Paper | Cloud Memory Enabled Code Generation via Online Computing for Seamless Edge AI Operation | This paper introduces an innovative architecture designed to enhance the execution of Artificial Intelligence (AI) software on edge devices, which are often constrained by limited hardware resources. The core of proposal is to dynamically adapt AI models through server-mediated parameter updates and learning, thus allowing edge devices to efficiently process AI tasks in real-time and adapt to various operational conditions. By leveraging the computational power of cloud resources for the heavy lifting of AI model training, the computational burden on edge devices is alleviated, enabling them to focus on inference tasks with updated models. This approach significantly improves the operational efficiency and adaptability of edge computing in AI applications. Our architecture employs server-based emulation to monitor and dynamically update edge devices, ensuring their execution is optimized for current conditions. Experimental results demonstrate a substantial reduction in operational time up to 75% compared to traditional edge devices without accelerators and 49% when compared to devices equipped with accelerators. Moreover, proposed model shows an ability to improve accuracy by 20% in scenarios with biased inputs through continuous learning and parameter updating, highlighting its adaptability to changing environments. This research contributes to the field of edge computing by demonstrating a viable solution for deploying sophisticated AI models in resource-constrained environments. By offloading computationally intensive tasks to the cloud, proposed architecture ensures that edge devices can operate more efficiently and handle a broader range of AI applications. This study not only underscores the potential of integrating cloud and edge computing to overcome the limitations of edge devices but also opens new avenues for future research in intelligent edge computing systems. | Kang, Myeongjin; Park, Daejin | Kyungpook Natl Univ, Sch Elect Engn, Daegu, South Korea | 57216440453; 55463943600 | boltanut@knu.ac.kr; | 2024 IEEE 48TH ANNUAL COMPUTERS, SOFTWARE, AND APPLICATIONS CONFERENCE, COMPSAC 2024 | 2836-3787 | 0 | 2025-05-07 | 0 | 0 | Edge computing; Embedded system; Remote software execution | Edge computing; Embedded system; Remote software execution | Cloud platforms; Computation offloading; Embedded software; Mobile edge computing; Codegeneration; Edge computing; Embedded-system; Hardware resources; Intelligence models; Intelligence operations; Intelligence software; Online computing; Remote software execution; Software execution; Cloud computing architecture | English | 2024 | 2024 | 10.1109/compsac61105.2024.00379 | 바로가기 | 바로가기 | 바로가기 | |||||||||||||
| ○ | Article | CNN-based Fall Detection Model for Humanoid Robots | Humanoid robots, designed to interact in human environments, require stable mobility to ensure safety. When a humanoid robot falls, it causes damage, breakdown, and potential harm to the robot. Therefore, fall detection is critical to preventing the robot from falling. Prevention of falling of a humanoid robot requires an operator controlling a crane. For efficient and safe walking control experiments, a system that can replace a crane operator is needed. To replace such a crane operator, it is essential to detect the falling conditions of humanoid robots. In this study, we propose falling detection methods using Convolution Neural Network (CNN) model. The image data of a humanoid robot are collected from various angles and environments. A large amount of data is collected by dividing video data into frames per second, and data augmentation techniques are used. The effectiveness of the proposed CNN model is verified by the experiments with the humanoid robot MAX-E1. © 2024, Korean Sensors Society. All rights reserved. | Park, Shin-Woo; Joe, Hyun-Min | Department of Robot and Smart System Engineering, Kyungpook National University, Techno building 406, 80 Daehak-ro, Buk-gu, Daegu, South Korea; Department of Robot and Smart System Engineering, Department of Artificial Intelligence, Kyungpook National University, Techno building 406, 80 Daehak-ro, Buk-gu, Daegu, South Korea | 58839299500; 57188687051 | hmjoe@knu.ac.kr; | Journal of Sensor Science and Technology | 1225-5475 | 33 | 1 | 0 | 2025-05-07 | 0 | CNN; Fall detection; Humanoid robot; Image augmentation | Korean | Final | 2024 | 10.46670/jsst.2024.33.1.18 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Article | Collection and analysis of quantitative change in freshness data during rice storage: real case studies; [쌀 보관과정에서의 신선도 변화 데이터 구축 및 분석: 실제 사례 연구-Abstract] | This study was conducted to collect and analyze freshness data from rice stored in various environments for various periods. Three case studies were conducted to investigate changes in quality associated with actual rice storage environments. The results of these three case studies reveal that freshness is significantly higher when rice is stored for one month in summer and two months in winter. When storage began in summer, a significant difference in freshness was observed between rice stored at room temperature and rice stored at low temperature. When storage started in winter, no difference in freshness between room and low-temperature stored rice was observed. Regardless of the storage period, freshness was the highest with low temperature storage, such as in refrigerators or kimchi refrigerators. These data and their implications could help formulate guidelines for safe storage and quality control. © The Korean Society of Food Science and Technology. | Hong, Jeehwa; Park, Eunsoo; Kim, Yongku | Experiment Research Institute, National Agricultural Products Quality Management Service, South Korea; Experiment Research Institute, National Agricultural Products Quality Management Service, South Korea; Department of Statistics, Kyungpook National University, South Korea | 56625395700; 59232888500; 47962102500 | kim.1252@knu.ac.kr; | Korean Journal of Food Science and Technology | 0367-6293 | 56 | 3 | 0 | 2025-05-07 | 0 | data analysis; freshness; rice; storage location; storage period | Korean | Final | 2024 | 10.9721/kjfst.2024.56.3.303 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | ○ | Proceedings Paper | Collision prediction and driving safety warning system for mobile robots using 3D LiDAR and 2D cameras | The introduction of advanced driver assistance systems (ADAS) is playing a pivotal role in modern vehicle technology, as advances in driver assistance technologies are key to improving road safety and driving comfort. This research detects and predicts far- field hazards that are beyond the range of traditional near-field radar-based systems. Here, we demonstrate a novel system that integrates 3D LiDAR and 2D camera technology to provide a comprehensive solution to these limitations. The system not only predicts potential collision points with high accuracy, but also provides advanced warning signals to the driver to improve reaction time and situational awareness. The results of the study show that this integrated approach successfully predicts far-field collision risk in a variety of scenarios, outperforming traditional radar-based ADAS. This research has important implications for the development of autonomous driving technology by showing how it can significantly reduce the incidence of traffic accidents and improve overall traffic safety. The implications of this research go beyond the immediate field and could influence future innovations in vehicle safety systems and help them evolve towards fully autonomous solutions. | Oh, Jun Seok; Kim, Min Young | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea | 59307816400; 56739349100 | gsu04295@nate.com;minyoung.kim2@gmail.com; | 2024 FIFTEENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS, ICUFN 2024 | 2165-8528 | 2165-8536 | 0 | 2025-05-07 | 0 | 0 | ROS; YOLOv8; Kalman Filter; Waring System | Kalman Filter; ROS; Waring System; YOLOv8 | Autonomous vehicles; Highway accidents; Kalman filters; Magnetic levitation vehicles; Mobile robots; Motor transportation; Vehicle safety; Advanced driver assistances; Collision prediction; Driver assistance; Driver-assistance systems; Driving safety; Far-field; ROS; Vehicle technology; Waring system; YOLOv8; Advanced driver assistance systems | English | 2024 | 2024 | 10.1109/icufn61752.2024.10625530 | 바로가기 | 바로가기 | 바로가기 | ||||||||||||
| ○ | ○ | Proceedings Paper | ComBoost: An Instruction Complexity Aware DTM Technique for Edge Devices | Recent edge devices show high power density in CPUs, resulting in excessive heat generation. Since mechanical cooling solutions are impractical in edge devices due to their small form factor, software-controlled dynamic thermal management (DTM) plays a crucial role in resolving thermal problems. In state-of-the-art edge devices, proactive DTM techniques such as ARM intelligent power allocation (IPA) mainly exploit the current CPU status (e.g., on-chip temperature, core utilization, and frequency) to estimate the current power consumption which eventually affects the future on-chip temperature. However, they overlook the impact of instruction complexity on thermal behaviors, which results in too conservative or aggressive voltage and frequency control. Even with the same frequency and core utilization, the on-chip temperature increases with different gradients depending on the instruction complexity of workloads. In this paper, we propose an instruction complexity aware DTM technique for edge devices, called ComBoost. Based on the real-time monitoring of on-chip temperature, utilization, and frequency, ComBoost examines the instruction complexity as well as the current CPU status to determine the target frequency. ComBoost then proactively adjusts the voltage and frequency of cores to minimize the performance degradation from thermal throttling. In the off-the-shelf edge device, ComBoost improves performance by 16.8%, 18.6%, and 15.5%, on average, compared to the legacy, IPA, and prior RL-based technique, respectively. | Choi, Seung Hun; Kong, Joonho; Chung, Sung Woo | Korea Univ, Dept Comp Sci & Engn, Seoul, South Korea; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea | 57211108323; 25927220400; 57224448963 | csh30096@korea.ac.kr;joonho.kong@knu.ac.kr;swchung@korea.ac.kr; | PROCEEDINGS OF THE 29TH ACM/IEEE INTERNATIONAL SYMPOSIUM ON LOW POWER ELECTRONICS AND DESIGN, ISLPED 2024 | 0 | 2025-05-07 | 0 | 0 | Instruction Complexity; Dynamic Thermal Management; Edge Devices | dynamic thermal management; edge devices; instruction complexity | Computer debugging; Cooling systems; Decision making; Programmable logic controllers; Thermal management (electronics); 'current; Core utilization; Dynamic thermal management; Edge device; Instruction complexity; Intelligent power; Management techniques; On-chip temperature; Power allocations; Thermal | English | 2024 | 2024 | 10.1145/3665314.3670820 | 바로가기 | 바로가기 | 바로가기 | ||||||||||||||
| ○ | Article | Comparative Analysis of Energy Consumption according to the Change of Curb Weight of Electric Vehicles in On-Road Driving; [실도로 주행시험 기반 전기자동차 공차중량 변화에 따른 에너지 소비패턴비교 분석] | It is widely known that as curb weight increases, energy efficiency decreases. However, unlike traditional vehicles, electric vehicles use regenerative braking, which can reduce the impact of weight on energy efficiency. Therefore, this study conducted on-road driving tests using an electric vehicle and measured energy consumption. Four weight conditions(curb weight at +0 kg, 100 kg, 200 kg, 300 kg) were tested on the same driving route, while other factors, such as ambient temperature and driving speed, which could affect energy efficiency, were kept constant. Energy consumption was calculated using the data obtained from the vehicle, which included altitude, vehicle speed, motor speed, and motor torque. The results showed that, under the driving conditions used in this study, energy efficiency decreased by about 8.63 % from +0 kg to +300 kg. This implies that electric vehicles' weight significantly impacts energy efficiency. © 2024 Korean Society of Automotive Engineers. All rights reserved. | Jang, Jaewoo; Song, Jingeun | School of Automotive Engineering, Kyungpook National University, Gyeongbuk, 37224, South Korea; School of Automotive Engineering, Kyungpook National University, Gyeongbuk, 37224, South Korea | 59393487600; 56714139600 | sjg@knu.ac.kr; | Transactions of the Korean Society of Automotive Engineers | 1225-6382 | 32 | 10 | 0 | 2025-05-07 | 0 | Drag resistance; Gradient resistance; Motor efficiency; Motor energy consumption; Rolling resistance | Korean | Final | 2024 | 10.7467/ksae.2024.32.10.789 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Article | Comparative analysis of evaporation estimation formulas for long-term agricultural water resource management | Accurate evapotranspiration estimation is critical for optimizing water resource management, agricultural planning, hydrological modeling, and climate adaptation. This study evaluates the performance of two evapotranspiration estimation formulas: the Hargreaves (HG) formula and the Penman-Monteith FAO (PM FAO) formula, utilizing meteorological data from 2017 to 2020 collected at eight sites within the Nakdong River basin. The analysis demonstrates that the PM FAO formula exhibits a superior correlation with observed monthly and daily average evapotranspiration rates compared to the HG formula. The MAE of the HG potential evapotranspiration was 1.81 mm/day, with a tendency for overestimation, particularly in the summer. In contrast, the Mean absolute error (MAE) of the PM FAO potential evapotranspiration was 1.26 mm/day, showing less error than the HG formula. Performance indices, such as NSE and R², further supported the "Good" rating for PM FAO across most study areas. Although the PM FAO formula requires extensive data, it offers more accurate potential evapotranspiration estimates. Thus, integrating the PM FAO formula into models used for agricultural and water resource management, where data availability permits, can significantly improve flow estimation accuracy, supporting better-informed decision-making for sustainable water resource management. © 2024 Korea Water Resources Association. All rights reserved. | Kim, Beomgu; Seong, Yeon Jeong; Choo, Innkyo; Yu, Yeong Uk; Lim, Kyoung Jae; Jung, Younghun | School of Advanced Science and Technology Convergence, Kyungpook National University, Sangju, South Korea; Sangju Carbon Neutrality Support Center, Sangju, South Korea; School of Advanced Science and Technology Convergence, Kyungpook National University, Sangju, South Korea; School of Advanced Science and Technology Convergence, Kyungpook National University, Sangju, South Korea; Department of Regional Infrastructure Engineering, Kangwon National University, Chuncheon, South Korea; School of Advanced Science and Technology Convergence, Kyungpook National University, Sangju, South Korea | 59322132600; 57202956507; 58861565400; 59532622400; 35176071700; 55195880200 | y.jung@knu.ac.kr; | Journal of Korea Water Resources Association | 2799-8746 | 57 | 11 | 0 | 2025-05-07 | 0 | Agricultural water; Climate change; Evaporation; Hargreaves; Penman-Monteith FAO | Korean | Final | 2024 | 10.3741/jkwra.2024.57.11.945 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Conference paper | Comparative Analysis of Partial Discharge Pattern Recognition Using Deep Learning and Machine Learning | Partial Discharge (PD) defect type analysis is important for evaluating insulation performance. A machine learning feature extraction algorithm is presented for AC PD pattern data collected in the laboratory, along with deep learning algorithms for PD pattern images and PD time series data. In addition, data is collected under conditions different from those used for artificial intelligence (AI) training, and algorithm performance is evaluated and compared. © 2024 The Korean Institute of Electrical Engineers (KIEE). | Hong, Tae-Yun.; Ahn, Hyun-Mo.; Jang, Hyun-Jae.; Park, Jun-Kyu.; Sun, Jong-Ho.; Kim, Jin-Gyu. | Korea Electrotechnology, Research Institute(KERI), Changwon, South Korea; Korea Electrotechnology, Research Institute(KERI), Changwon, South Korea; Korea Electrotechnology, Research Institute(KERI), Changwon, South Korea; Korea Electrotechnology, Research Institute(KERI), Changwon, South Korea; Korea Electrotechnology, Research Institute(KERI), Changwon, South Korea; Kyungpook National University, Daegu, South Korea | 57218937685; 35253278300; 57188757033; 55521224400; 56115744900; 54680957000 | 2024 10th International Conference on Condition Monitoring and Diagnosis, CMD 2024 | 0 | 2025-05-07 | 0 | deep learning; high voltage; machine learning; partial discharge; phase resolved partial discharge | Contrastive Learning; Deep learning; Comparative analyzes; Deep learning; Defect type; High-voltages; Machine-learning; Partial discharge defects; Partial discharge pattern; Partial discharge pattern recognition; Phase resolved partial discharges; Type analysis; Adversarial machine learning | English | Final | 2024 | 10.23919/cmd62064.2024.10766190 | 바로가기 | 바로가기 | |||||||||||||||||||
| ○ | ○ | Proceedings Paper | Comparative Analysis of Pathloss at 28 GHz and 140 GHz Frequencies in Identical Environment | To meet the high data rate demands of 5th generation mobile communication (5G), the millimeter-wave (mmWave) frequency band is crucial for securing extensive bandwidth. As cellular systems evolve toward 6th generation mobile communication (6G), the sub-terahertz (sub-THz) frequency band has received growing research attention, and comparative studies of the two aforementioned bands are underway. However, a significant frequency band gap between the two bands and absence of a third generation partnership project reference model present challenges in their direct comparison. These issues can be addressed by comparing their one-to-one mapped data when conditions are identical in both bands. To this end, we conducted a comparative analysis of the propagation characteristics of mmWave 28 GHz and sub-THz 140 GHz bands under identical conditions. This analysis encompassed multipath phenomena, indoor and outdoor pathlosses, outdoor-to-indoor pathloss, as well as penetration losses, including those related to human body and glass. Experimental results show that line of sight and non-line of sight at the sub-THz band have sparse multipath characteristics and experience much higher loss than the mmWave band. This study provides valuable insights into predicting performance when sub-THz equipment is installed near existing mmWave equipment. | Lee, Jinyoung; Kim, Jihoon; Shin, Yunhwa; Choi, Jeongsik; Lee, Jaehyun; Na, Minsoo | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea; SK Telecom Co Ltd, Dev Team 6G, Pangyo, South Korea | 59269755000; 59527687200; 59526818900; 58534394200; 56768488800; 56808918400 | wlsdud5706@knu.ac.kr;kjh2782@knu.ac.kr;jeenyyh615@knu.ac.kr;jeongsik.choi@knu.ac.kr;jaehyun_lee@sk.com;minsoo.na@sk.com; | 2024 IEEE 35TH INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS, PIMRC | 2166-9570 | 0 | 2025-05-07 | 0 | 0 | 5G; 6G; mmWave band; sub-THz band; pathloss measurement | MILLIMETER-WAVE | 5G; 6G; mmWave band; pathloss measurement; sub-THz band | Millimeter wave devices; 5g; 6g; Comparative analyzes; Millimeter-wave band; Mobile communications; Path loss; Pathloss measurement; Sub-terahertz; Sub-terahertz band; Terahertz band; 5G mobile communication systems | English | 2024 | 2024 | 10.1109/pimrc59610.2024.10817215 | 바로가기 | 바로가기 | 바로가기 | ||||||||||||
| ○ | Conference paper | Comparative Analysis of Quantum Adder Circuits in Computation Accuracy on Noisy Quantum Computers | Since the advent of quantum computing, the accuracy performance of quantum adders in Noisy Intermediate-Scale Quantum (NISQ) computing has received significant attention. This paper analyzes the accuracy of exact quantum adders in the NISQ environment. Our results show the impacts of noise vary significantly on the quantum circuits, reaching up to 86%, 0.23, and 0.66 in error rate (ER), normalized mean error distance (NMED), and mean relative error distance (MRED), respectively. Furthermore, the bitflip noise model impacts the greatest on quantum adders, showing, on average, 12.20, 11.30, and 11.62 times higher values in ER, NMED, and MRED, respectively. These findings highlight that the accuracy of exact quantum adders is affected by NISQ computing. © 2024 IEEE. | Hwang, Sungyoun; Seo, Hyoju; Kim, Yongtae | Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea; Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea; Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea | 59321195200; 57215662369; 55699627900 | yongtae@knu.ac.kr; | Proceedings - International SoC Design Conference 2024, ISOCC 2024 | 3 | 2025-05-07 | 2 | noisy intermediate-scale quantum (NISQ); quantum adder; quantum computing | Adders; Quantum electronics; Quantum noise; Quantum optics; Adder circuit; Comparative analyzes; Computation accuracy; Error distance; Error rate; Mean error distances; Mean relative error; Noisy intermediate-scale quantum; Quantum adders; Quantum Computing; Quantum computers | English | Final | 2024 | 10.1109/isocc62682.2024.10762297 | 바로가기 | 바로가기 |
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