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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
Conference paper Enhancing Graph-Based Vulnerability Detection through Standardized Deep Learning Pipelines Identifying vulnerable code is crucial to software system security. With the rise of deep learning, graph neural networks (GNNs) have received much attention for detecting vulnerabilities. While many studies aim to enhance GNN performance by refining graph structures, improving datasets, or optimizing model architectures, three key questions remain unanswered: 1) How do simple graph structures impact model performance? 2) How similar are artificially generated datasets to vulnerable code in the real world? 3) Does a more complex model provide better benefits in vulnerability detection? To find answers to these questions, we did experiments to show how basic graph structures affect GNN models and give guidelines on how to choose datasets. In addition, we introduce VulGCANet, a model with a relatively simple architecture that utilizes code property graphs and combines Graph Convolutional Networks (GCN) and Graph Attention Network (GAT) layers for vulnerability detection. The experimental results demonstrate that VulGCANet exhibits 30% improvements in recall while performing similarly to other graph neural network-based models, highlighting the importance of reducing the complexity of GNN model architectures in graph-based vulnerability detection. These findings provide valuable insights for advancing GNN-based vulnerability detection efforts. © 2024 IEEE. Hao, Jiashun; Kwon, Young-Woo Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea; Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea 59919742400; 57208480210 ej2975589@knu.ac.kr; Proceedings of the IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2324-898X 2024 0 2025-06-11 0 deep learning; graph neural networks; program representations; Vulnerability detection Deep neural networks; Graph algorithms; Network theory (graphs); Deep learning; Graph neural networks; Graph structures; Graph-based; Modeling architecture; Neural network model; Program representations; Simple++; Software-systems; Vulnerability detection; Graph neural networks English Final 2024 10.1109/trustcom63139.2024.00174 바로가기 바로가기
Conference paper Enhancing Load Forecasting by Clustering in Distributed Microgrids Based Energy Internet Framework The intermittent nature of distributed renewable en-ergy sources and varying patterns of end-user loads in microgrids necessitate the manufacturers to accommodate unforeseen and expected fluctuations in energy consumption and production. Lack of accurate load forecasting may result in ineffective harnessing and storage of renewable energy and complicates energy trading and dynamic pricing. Existing literature on load forecasting of microgrids is limited to single microgrids, and the possibility of inter-microgrid communication is not addressed sufficiently. This study explores the enhancement of load fore-casting in an Energy Internet (EI) framework among multiple interconnected microgrids. A novel approach is proposed which integrates k-means clustering with Support Vector Regression (SVR) to forecast the load in the EI. We also investigate the influence of the communication network of the EI in improving short-term load forecasting (STLF). © 2024 IEEE. Vijayan, Anjana; Yang, Jung-Min School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea; School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea 59463425800; 57208450551 9th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2024 0 2025-05-07 0 communication networks; Energy Internet (EI); load forecasting; microgrids; support vector regression Clusterings; Communications networks; Distributed renewables; End-users; Energy consumption and production; Energy internet; Load forecasting; Microgrid; Support vector regressions English Final 2024 10.1109/bcd61269.2024.10743098 바로가기 바로가기
Conference paper Enhancing Medical Information Retrieval with a Language Model In this ever-evolving healthcare landscape, with the integration of cutting-edge technology, this study has exemplified a medical chatbot by harnessing the advanced Llama2 model. This chatbot places significant emphasis on instance training by changing and adding the meta, which enables it to continuously adapt and stay updated with the latest medical developments. Its adaptability also encompasses capabilities such as question-answering and mining knowledge from an extensive meta dataset. By leveraging its extensive ability to learn medical terminology, the chatbot provides precise and real-time responses to medical inquiries by establishing itself as a reliable information source. Access to a specially collected meta dataset further enhances its ability to deliver comprehensive medical insights while self-supervised learning techniques enhance the model efficacy. Consequently, this chatbot reshapes the way individuals access precise medical information by enabling a new era of advanced digital healthcare assistants in the digital age. © 2024 IEEE. Natarajan, Yuvaraj; Sri Preethaa, K.R.; Pandian, Sasikumar; Geetha, Shruti Umapathi; Senthilkumar, Sujadharshini Kpr Institute of Engineering and Technology, Department of Computer Science and Engineering, Coimbatore, India; Kyungpook National University, Department of Robot and Smart System Engineering, Daegu, 41566, South Korea; Kpr Institute of Engineering and Technology, Department of Computer Science and Engineering, Coimbatore, India; Kpr Institute of Engineering and Technology, Department of Computer Science and Engineering, Coimbatore, India; Kpr Institute of Engineering and Technology, Department of Computer Science and Engineering, Coimbatore, India 57204528689; 57214320928; 59155497900; 59478858500; 59155779600 yuvaraj.n@kpriet.ac.in; 2024 International Conference on Cognitive Robotics and Intelligent Systems, ICC - ROBINS 2024 3.23 2025-04-16 1 Chatbot and ChatGPT; Llama2; LLM; Medical Chatbot Bioinformatics; Health care; Learning systems; Medical informatics; Terminology; Chatbot and ChatGPT; Chatbots; Cutting edge technology; Language model; Llama2; LLM; Medical chatbot; Medical information; Question Answering; Supervised learning English Final 2024 10.1109/icc-robins60238.2024.10533903 바로가기 바로가기
Proceedings Paper Enhancing Microcontroller Security Through Volatile Memory-Resident Encrypted Code This paper presents a novel approach to enhancing microcontroller security by storing code in an encrypted format within flash memory and executing it from volatile memory. This method addresses critical vulnerabilities associated with executing code directly from non-volatile flash memory, such as susceptibility to reverse engineering and bit-level manipulation attacks. By decrypting sensitive code only during execution and performing cyclic redundancy checks to verify integrity before execution, the proposed approach significantly reduces the risk of unauthorized access and tampering. Additionally, the implementation of address space layout randomization during execution further enhances security by dynamically allocating memory for decrypted code. This study demonstrates the effectiveness of the proposed method in mitigating common security threats in embedded systems, with potential applications in automotive electronics, IoT devices, and other critical infrastructures. Future work may explore the integration of various encryption techniques and advanced security measures to further strengthen microcontroller security. Kim, Minjung; Park, Daejin Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea 58897306800; 55463943600 boltanut@knu.ac.kr; 2024 IEEE CONFERENCE ON DEPENDABLE AND SECURE COMPUTING, DSC 0 2025-05-07 0 0 security; embedded system; encryption; linker; firmware embedded system; encryption; firmware; linker; security Flash memory; Microcontrollers; Reverse engineering; Static random access storage; Address space layout randomizations; Bit level; Cyclic redundancy check; Embedded-system; Linker; Memory-resident; Nonvolatile; Security; Unauthorized access; Volatile memory; Firmware English 2024 2024 10.1109/dsc63325.2024.00028 바로가기 바로가기 바로가기
Conference paper Enhancing reality: Metalens array and color filter integration for immersive AR/VR AR and VR technologies are advancing rapidly, offering immersive experiences in the digital world. Researchers are exploring new ways to improve visual quality and user immersion. One promising solution is combining Metalens Arrays and Color Filters, which can enhance AR/VR experiences by manipulating light at a tiny scale. These technologies, integrated into AR/VR glasses, promise to revolutionize various fields by improving image resolution, color accuracy, and brightness. Users can expect more lifelike virtual environments, allowing deeper exploration and engagement in simulations and applications. Overall, the integration of Metalens Arrays and Color Filters represents a significant advancement in immersive experiences, opening up new possibilities in entertainment, education, and professional fields. In our research, we create a reflective Color Filter (CF) using a metasurface for RGB color filtering intended for AR/VR displays. This CF reflects light of specific wavelengths for desired colors while absorbing the rest. We assess color purity and accuracy using linear plots in Ansys Lumerical FDTD and chromaticity diagrams. Additionally, to focus this filtered light at various spots on the same plane, we design a metalens array in Ansys Lumerical FDTD and analyze its focusing profile. © 2024 SPIE. Fizan, Muhammad; Noureen, Sadia; Khaliq, Hafiz Saad; Mahmood, Nasir Department of Electrical Engineering, Information Technology University of the Punjab (ITU), Lahore, 54000, Pakistan; Department of Electrical Engineering, Information Technology University of the Punjab (ITU), Lahore, 54000, Pakistan; School of Electronic and Electrical Engineering, Kyungpook National University (KNU), Daegu, 41566, South Korea; Innovative Technologies Laboratories (ITL), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955, Saudi Arabia 58806526400; 57808658700; 56725698200; 57532706000 Proceedings of SPIE - The International Society for Optical Engineering 0277-786X 13012 0 2025-05-07 0 Augmented Reality (AR); Color Filter; Immersive Experience; Metalens Array; Nanoscale Manipulation; Virtual Reality (VR); Visual Quality Color; Image enhancement; Image resolution; Virtual reality; Augmented reality; Color accuracy; Color filters; Immersive; Immersive experience; MetaLens; Metalens array; Nanoscale manipulations; Virtual reality; Visual qualities; Augmented reality English Final 2024 10.1117/12.3022098 바로가기 바로가기
Article Enhancing the Quality and Fruit Yield of Sweet Cherry (Prunus Avium) Cultivars by Foliar Application of Boron A deficiency of boron can be observed mostly in sandy soil with a high pH level and with minimum soil organic matter. Being a significant micronutrient, its deficiency may decrease the photosynthetically active emission and absorption by leaves. It helps in the transport of photosynthetic foodstuffs from foliar parts to meristematic tissues in green parts and roots ensuring leaf, shoot, fruit, and seed formation. An experiment on sweet cherry cultivars ('Sasha', 'Stella,' and 'Sunburst') assigned to the main plot and boron levels (0%, 0.25%, 0.50%, 0.75%, and 1%) subjected to subplot was carried out at the Kalam Summer Station, Agriculture Research Institute, Swat, Pakistan. Among the cultivars, maximum leaf area (cm(2)), fruit diameter, percent pulp, total soluble solids (degrees Brix), titratable acidity (%), and total sugars (%) with the minimum number of fruit kg(-1) was recorded in sweet cherry cultivar 'Sunburst.' The maximum fruit set (%), and yield (kg.plant(-1)) with minimum fruit drop (%) were recorded in the sweet cherry cultivar 'Stella.' Regarding boron concentration, maximum leaf area (cm(2)), fruit set (%), fruit diameter (cm), yield (kg.plant(-1)), percent pulp (%), total soluble solids (degrees Brix), total sugars (%) with minimum fruit drop (%), and the number of fruit kg(-1) was recorded in sweet cherry cultivars sprayed with 1% of boron. However, the maximum titratable acidity (%) was recorded in control treatments. Sweet cherry cultivars 'Sunburst' and 'Stella' sprayed with 1% boron showed the best results regarding yield and quality fruits production under the agro-climatic condition of Swat Valley. Sajid, Muhammad; Basit, Abdul; Shah, Syed Tanveer; Khan, Ayesha; Ullah, Izhar; Bilal, Muhammad; Khan, Muhammad Suleman; Khan, Waleed Univ Agr Peshawar, Fac Crop Prod Sci, Dept Hort, Peshawar 25120, Pakistan; Kyungpook Natl Univ, Dept Hort Sci, Daegu 41566, South Korea; Univ Hazara, Dept Agr, Mansehra, Pakistan; Ondokuz Mayis Univ, Fac Agr, Dept Hort, Samsun, Turkiye; Kyungpook Natl Univ, Dept Appl Biosci, Lab Crop Prod, Daegu 41566, South Korea Shah, Syed Tasadaque/AAB-4890-2021; Basit, Abdul/AAX-2414-2021; Bilal, Muhammad/AET-1048-2022; Ullah, izhar/MYR-3437-2025; Khan, Ayesha/NKP-0640-2025 57213926335; 58696991300; 56089730700; 57199716425; 57211559793; 57224853341; 59206463000; 57822855200 abdulbasit97_lily@knu.ac.kr;msulemankhan25@aup.edu.pk; APPLIED FRUIT SCIENCE APPL FRUIT SCI 2948-2623 2948-2631 66 2 SCIE HORTICULTURE 2024 N/A 0.61 2025-05-07 2 2 Deficiency; Micronutrient; Fruit quality; Sweet cherry; Fruit drop APPLE; FERTILIZATION; CALCIUM; GROWTH; SPRAYS; TREES Deficiency; Fruit drop; Fruit quality; Micronutrient; Sweet cherry English 2024 2024-04 10.1007/s10341-023-01023-2 바로가기 바로가기 바로가기 바로가기
Conference paper Enhancing Tractor Safety over rough Terrains: A Numerical Study of Steering Instability Tractor overturn accidents pose a significant safety concern in agriculture, particularly in Korea where small tractors navigate challenging terrains like slippery fields and steep slopes. The risk stems from steering instability induced by bouncing and sliding, impacting both tractor safety and trajectory tracking precision in autonomous driving. The agricultural industry is shifting towards alternative energy sources such as electric and hydrogen tractors, necessitating a reevaluation of safety concerns due to changes in the tractor's center of gravity. This study focuses on a numerical investigation of tractor steering instability, combining bouncing and sliding models based on Coulomb's friction theory. Numerical experiments are conducted, varying parameters like travel velocity, static friction coefficient, bump length, and turning radius. A turning test evaluates the fundamental steering performance. Simulation results demonstrate that bouncing and sliding reduce cornering force, deviating from the desired trajectory. Operating the tractor on steep slopes exacerbates steering instability, potentially leading to overturn accidents under unfavorable conditions. These findings provide crucial insights for improving tractor safety in challenging agricultural settings. © 2024 ASABE Annual International Meeting. All rights reserved. Kim, Yeongsu; Son, Jinho; Kim, Yonggik; Ha, Yushin Department of Bio-industrial Machinery Engineering, College of Agriculture and Life Sciences, Kyungpook National University, Daegu, 41566, South Korea, Upland-field Machinery Research Center, Kyungpook National University, Daegu, 41566, South Korea; Department of Bio-industrial Machinery Engineering, College of Agriculture and Life Sciences, Kyungpook National University, Daegu, 41566, South Korea; Department of Bio-industrial Machinery Engineering, College of Agriculture and Life Sciences, Kyungpook National University, Daegu, 41566, South Korea; Department of Bio-industrial Machinery Engineering, College of Agriculture and Life Sciences, Kyungpook National University, Daegu, 41566, South Korea, Upland-field Machinery Research Center, Kyungpook National University, Daegu, 41566, South Korea 57210594021; 57879932100; 58419351400; 57192072314 yushin72@knu.ac.kr; 2024 ASABE Annual International Meeting 0 2025-05-07 0 Agricultural Terrain; Autonomous Driving Tractors; Numerical Investigation; Steering Instability; Tractor Safety Precision agriculture; Steering; Tractors (agricultural); Agricultural terrain; Autonomous driving; Autonomous driving tractor; Numerical investigations; Rough terrains; Safety concerns; Steep slope; Steering instability; Tractor overturn; Tractor safety; Friction English Final 2024 10.13031/aim.202400578 바로가기 바로가기
Article Equivalent Condition for the Existence of the Regular, Impulse-free and Unique Solution and Stochastic Stability Criterion for Rectangular Descriptor Markovian Jump Systems This paper suggests the equivalent condition for the regular, impulse-freeand stochastic stable unique solution of rectangular descriptor Markovian jump systems (RDMJSs). wo equivalent sets singular derivative matrix are proposed. Based on the proposed lemma, the authors the equivalent condition for regular, impulse-free, stochastic stableand unique solution for RDMJS into linear matrix inequalities (LMIs). The LMI variables in the proposed method can have more freedom than the existing work., can play an important role in controller synthesis. The validity of the proposed method is demonstrated through a numerical example. © ICROS 2024. Kwon, Nam Kyu; Park, Chan-Eun Department of Electronics Engineering, Yeungnam University, South Korea; School of Electronics Engineering, Kyungpook National University, South Korea 55902868000; 57001658700 chaneun@knu.ac.kr; Journal of Institute of Control, Robotics and Systems 1976-5622 30 5 0 2025-04-16 0 column impulse-freeness; column regularity; linear matrix inequality (LMI); Markovian jump system; Rectangular descriptor system Markov processes; Numerical methods; Robustness (control systems); Stability criteria; Stochastic systems; Column impulse-freeness; Column regularity; Descriptor systems; Descriptors; Equivalent condition; Linear matrix in equalities; Linear matrix inequality; Markovian jump systems; Rectangular descriptor system; Stochastics; Linear matrix inequalities Korean Final 2024 10.5302/j.icros.2024.24.0017 바로가기 바로가기
Article Erasing Racial Boundaries in "Hiram Powers' Greek Slave" Om, Donghee Kyungpook Natl Univ, Dept English Educ, Daegu, South Korea Om, Donghee/JGD-9332-2023 57218380238 dom@knu.ac.kr;donghee.om@gmail.com; ANQ-A QUARTERLY JOURNAL OF SHORT ARTICLES NOTES AND REVIEWS ANQ-Q J SHORT ART N 0895-769X 1940-3364 37 2 AHCI LITERATURE 2024 0.1 0 2025-05-07 0 0 English 2024 2024-04-02 10.1080/0895769x.2022.2114415 바로가기 바로가기 바로가기 바로가기
Book chapter Ethical considerations in drone cybersecurity The rapid proliferation of drones, coupled with their increasing integration into various aspects of our lives, has brought to the forefront a myriad of ethical considerations in the realm of cybersecurity. This chapter delves deep into the intricate web of ethical challenges surrounding drone cybersecurity, aiming to provide a comprehensive understanding of this critical issue. The introduction sets the stage by highlighting the essential role of ethics in drone cybersecurity, emphasizing the need for responsible decision-making in an age where drones are omnipresent. It lays out the scope, objectives, and key concepts of the research, underscoring the contributions it makes to the field. The core of the chapter explores the ethical principles underpinning cybersecurity and elucidates how these principles can be applied to the domain of drone technology. The authors delve into the delicate balance between security and privacy, discussing the ethical implications of data collection, retention, and surveillance in the context of drones. © 2024, IGI Global. All rights reserved. Sindiramutty, Siva Raja; Tan, Chong Eng; Shah, Bhavin; Khan, Navid Ali; Gharib, Abdalla Hassan; Manchuri, Amaranadha Reddy; Muniandy, Lalitha; Ray, Sayan Kumar; Jazri, Husin Taylor's University Sdn Bhd, Malaysia; Universiti Malaysia Sarawak, Malaysia; Lok Jagruti University, India; Taylor's University Sdn Bhd, Malaysia; Zanzibar University, Tanzania; Kyungpook National University, South Korea; Tunku Abdul Rahman University of Management and Technology, Malaysia; Taylor's University Sdn Bhd, Malaysia; Taylor's University Sdn Bhd, Malaysia 57216348438; 25825561000; 58976933600; 57216537861; 58775231300; 58343647900; 58994750200; 15060797500; 55701237200 Cybersecurity Issues and Challenges in the Drone Industry 8.23 2025-05-07 10 English Final 2024 10.4018/979-8-3693-0774-8.ch003 바로가기 바로가기
Article Ethnobotanical inventory and traditional medicinal applications of the flora in Kutwal Haramosh Valley, District Gilgit, Pakistan Background: In the Kutwal Valley Haramosh region, traditional ethnomedical knowledge and local flora are at risk due to the rise of modern medicine and rapid land conversion. Thus, the current study aims to document and explore the cultural significance of medicinal plants, emphasizing the urgent need for conservation efforts. Methods: We used semi-structured questionnaires to gather information from residents and interviewed farmers, shepherds, and elderly individuals who have traditional knowledge. Results: The study identified 91 plant species across 40 families in the local area, with Asteraceae being the predominant family, represented by 13 species. Herbs constituted 76% of the species, primarily utilizing aerial parts (29 species) and roots (20 species) in medicinal preparations, often consumed directly (35 species) or through decoction (22 species). The highest use values (1), relative frequency citation (0.9), and fidelity levels (100%) were observed for Saussurea simpsoniana, Tanacetum falconeri, Berberis lyceum, Pleurospermum brunonis, Euphorbia cornigera, and Punica granatum, indicating their paramount significance in traditional medicine. The highest Informant Consensus Factor values (1) were recorded for the community-based syndrome, immunity, stress, gastrointestinal issues, skin conditions, temperature regulation, headaches, blood disorders, infertility, and mental health. A strong positive correlation (r = 0.7699, p < 0.0001) between use values and relative frequency citation highlights the link between perceived medicinal value and local use. Conclusion: The study emphasizes the need for conservation efforts amidst threats such as overgrazing, deforestation, overexploitation, and habitat loss, and suggests further phytochemical research to validate medicinal properties. © 2024, Ilia State University, Institute of Botany, Department of Ethnobotany. All rights reserved. Ud Din, Shahab; Abbas, Qamar; Khadim, Salim; Abbas, Pervaz; Abbas, Hasnain; Zuhra, Tehseen; Irfani, Muhammad Aqeel Department of Animal Science and Biotechnology, Kyungpook National University, Gyeongsangbukdo, Sangju-si, 37224, South Korea, Department of Plant Sciences, Karakoram International University, Gilgit-Baltistan 15100, Pakistan; Department of Plant Sciences, Karakoram International University, Gilgit-Baltistan 15100, Pakistan; Department of Plant Sciences, Karakoram International University, Gilgit-Baltistan 15100, Pakistan; Department of Forestry, Wildlife and Range Management, Karakoram International University, Gilgit-Baltistan 15100, Pakistan; Department of Plant Sciences, Karakoram International University, Gilgit-Baltistan 15100, Pakistan; Department of Animal Sciences, Karakoram International University, Gilgit-Baltistan, 15100, Pakistan; National Institute for Bioinformatics, Quaid-e-Azam University, Islamabad Capital Territory, 15320, Pakistan 59206105600; 57254738400; 58569398600; 59206300000; 58253264100; 59178850300; 57751400800 salim.edu.pk@gmail.com; Ethnobotany Research and Applications 1547-3465 27 1.15 2025-05-07 1 Conservation; Ethnobotany; Gilgit; Kutwal Haramosh; Medicinal plants English Final 2024 10.32859/era.27.50.1-26 바로가기 바로가기
Conference paper Evaluating the Performance of Light Gradient Boosting Machine in Merging Multiple Satellite Precipitation Products Over South Korea Precipitation information with high accuracy plays a crucial role in hydrology and water resources management. With the advance in technology, satellite precipitation products (SPPs) provide an unprecedented opportunity for monitoring the spatial and temporal variation of precipitation from space. However, SPPs still present a low performance with high uncertainty. To overcome this problem, the current study aims to produce a new reanalysis of precipitation data by integrating information from observation data with multiple SPPs over South Korea under the aid of a fast and high-performance machine learning-based, namely a light gradient boosting machine. In addition, other statistical merging methods were also carried out to highlight the robustness of the machine learning-based algorithm. To examine the accuracy of merging precipitation products, observed data from 64 automated synoptic observation system rain gauge stations were collected and compared with merging precipitation products. A high agreement between merging precipitation data generated from the machine learning-based approach with observation was witnessed through several continuous criteria and categorical indicators. The results from this study point out that light gradient boosting machine not only has the capability in merging multi-sources precipitation but also it could provide extraordinary rainfall information for the region of interest, especially in areas with low observed station density. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Nguyen, Giang V.; Le, Xuan-Hien; Van, Linh Nguyen; Jung, Sungho; Choi, Chanul; Lee, Giha Kyungpook National University, Sangju, South Korea; Kyungpook National University, Sangju, South Korea, Thuyloi University, Hanoi, Viet Nam; Kyungpook National University, Sangju, South Korea; Kyungpook National University, Sangju, South Korea; Kyungpook National University, Sangju, South Korea; Kyungpook National University, Sangju, South Korea 57297771000; 57209735659; 57297359100; 57209733155; 58613779200; 35069799400 leegiha@knu.ac.kr; Lecture Notes in Civil Engineering 2366-2557 344 LNCE 5.19 2025-04-16 1 Light gradient boosting machine; Machine learning; Merging; Satellite precipitation Adaptive boosting; Image segmentation; Information management; Machine learning; Rain; Rain gages; Satellites; Water resources; Gradient boosting; Light gradient boosting machine; Light gradients; Machine-learning; Multiple satellites; Performance; Precipitation data; Satellite precipitation; Satellite precipitation products; South Korea; Merging English Final 2024 10.1007/978-981-99-2345-8_52 바로가기 바로가기
Article Evaluation of Anti-Helicobacter pylori Activity of Novel Lactic Acid Bacteria; [신규 젖산균을 활용한 Anti-Helicobacter pylori 활성] In this study, we aimed to isolate and identify strains of lactic acid bacteria from kkakdugi, to validate their potential use as alternative therapeutic agents against Helicobacter pylori. Eleven strains were identified, including Lactobacillus plantarum, Pediococcus pentosaceus, Lactobacillus brevis, Pediococcus acidilacti, and Leuconostoc mesenteroides. The paper disk method and urease inhibition activity were used to verify anti-H. pylori activity. Without pH adjustment, most strains exhibited an average inhibitory zone of 13.68 mm. However, when the pH was adjusted to 7.0, some strains showed inhibitory zones ranging from 11.65 to 13.15 mm. Nevertheless, upon comparison, it was observed that the antimicrobial activity was higher when the pH was not adjusted. On the other hand, antimicrobial activity against H. pylori G88026 strain was exhibited regardless of the pH. The results of urease inhibition confirmed a significant reduction of approximately 60∼90% in urease activity when the lactic acid bacterial culture supernatant was added. Except for the Lactobacillus sakei strain, the remaining strains exhibited potent urease inhibition activity. This suggests that the lactic acid bacteria isolated in this study could be promising candidates as alternative therapeutic agents against H. pylori. © 2024 The Korean Society of Food Science and Nutrition. Kim, Ji-Hye; Jung, Sung-Keun; Cho, Young-Je; Kim, Byung-Oh School of Food Science, Kyungpook National University, South Korea; School of Food Science, Kyungpook National University, South Korea, Research Institute of Tailored Food Technology, South Korea; School of Food Science, Kyungpook National University, South Korea, Research Institute of Tailored Food Technology, South Korea; School of Food Science, Kyungpook National University, South Korea, Research Institute of Tailored Food Technology, South Korea 59089372000; 35310491400; 55265396300; 7501567571 kimb@knu.ac.kr; Journal of the Korean Society of Food Science and Nutrition 1226-3311 53 5 0 2025-05-07 0 antimicrobial; Helicobacter pylori; kkakdugi; lactic acid bacteria; urease Korean Final 2024 10.3746/jkfn.2024.53.5.485 바로가기 바로가기
Conference paper Evaluation of Displacement of an L-shaped Concrete Specimen using Recurrent Neural Networks In engineering, most structural elements are damaged locally during fabrication or maintenance. Under different loading conditions, such localized damage will further expand into larger cracks and cause structural collapse. As a result, identifying the displacement under various loads in the structural elements is critical in the risk assessment of engineering structures. The objective of the present paper is to propose a deep-learning model to examine the displacement of L-shaped concrete specimens under loading conditions. The three state-of-theart models such as Simple RNN, LSTM, and GRU are built and trained based on load-displacement data. The experimental results show that the R2 values obtained from the Simple RNN, LSTM, and GRU models are 0.9967, 0.6169, and 0.5291, respectively. This proves that Simple RNN is superior to LSTM and GRU in the task of predicting the load-displacement relationship. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Nguyen, Quoc H.; Doan, Vi T. T.; Tran, Thanh Danh; Nguyen, Tan-No 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 59540329900; 59539166200; 57226534956; 57862912800 tannonguyen.ce@gmail.com; Lecture Notes in Civil Engineering 2366-2557 482 LNCE 0 2025-05-07 0 Concrete; Displacement; L-Shaped; Machine Learning; Recurrent Neural Network Pressure vessels; Concrete specimens; Displacement; L-shaped; Loading condition; Localized damage; Machine-learning; Neural-networks; Simple++; Structural collapse; Structural elements; Recurrent neural networks English Final 2024 10.1007/978-981-97-1972-3_38 바로가기 바로가기
Article Evaluation of DNA and cell damage induced by intense pulsed light in Pseudomonas aeruginosa; [Intense pulsed light에 의해 유도된 Pseudomonas aeruginosa의 DNA 및 세포 손상에 대한 평가] The present study aimed to evaluate the bactericidal effect of intense pulsed light (IPL) on Pseudomonas aeruginosa and DNA and cell damage induced by IPL treatment. Microbial inactivation by IPL improved with higher voltages and prolonged exposure, showing a reduction of approximately 6.0 log for 90 s at 600 V and 60 s at 800 V. The temperature changes during IPL treatment on P. aeruginosa cells were 1.05oC for 90 s at 600 V and 1.57oC for 60 s at 800 V. IPL treatment resulted in the accumulation of double-strand breaks (DSBs), single-strand breaks (SSBs), and cyclobutane pyrimidine dimers (CPDs) in the DNA of P. aeruginosa cells. Transmission electron microscopy (TEM) confirmed that the structure of untreated cells was maintained, whereas disrupted membranes and ruptured internal tissues were observed in treated cells. These findings suggest that IPL treatment effectively inactivates P. aeruginosa and has potential applications in food sterilization. ©The Korean Society of Food Science and Technology. Ryu, Hyeon min; Jeon, Je-Hyeok; Cheigh, Chan-Ick Department of Food and Food Service Industry, Kyungpook National University, South Korea; Department of Food and Food Service Industry, Kyungpook National University, South Korea; Department of Food and Food Service Industry, Kyungpook National University, South Korea 58719448300; 58631090700; 6506587023 cic@knu.ac.kr; Korean Journal of Food Science and Technology 0367-6293 56 6 0 2025-05-07 0 cyclobutane pyrimidine dimer; double-strand break; intense pulsed light; Pseudomonas aeruginosa Korean Final 2024 10.9721/kjfst.2024.56.6.814 바로가기 바로가기
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WoS Web of Science. Clarivate Analytics에서 제공하는 학술 데이터베이스입니다. 해당 논문이 WoS에 수록되어 있는지 여부를 표시합니다 (○: 수록됨).
SCOPUS Elsevier에서 제공하는 세계 최대 규모의 초록 및 인용 데이터베이스입니다. 해당 논문이 SCOPUS에 수록되어 있는지 여부를 표시합니다 (○: 수록됨).
Document Type 문헌의 유형을 나타냅니다. Article(원저), Review(리뷰), Proceeding Paper(학회논문), Editorial Material(편집자료), Letter(레터) 등으로 분류됩니다.
Title 논문의 제목입니다.
Abstract 논문의 초록(요약)입니다. 연구의 목적, 방법, 결과, 결론을 간략히 요약한 내용입니다.
Authors 논문의 저자 목록입니다. 공동 저자가 여러 명인 경우 세미콜론(;)으로 구분됩니다.
Affiliation 저자들의 소속 기관 정보입니다. 대학, 연구소, 기업 등 저자가 소속된 기관명이 표시됩니다.
ResearcherID (WoS) Web of Science의 고유 연구자 식별번호입니다. 동명이인을 구분하고 연구자의 업적을 정확하게 추적할 수 있습니다.
AuthorsID (SCOPUS) SCOPUS의 고유 저자 식별번호입니다. 연구자의 모든 출판물을 추적하고 관리하는 데 사용됩니다.
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.
eISSN Electronic ISSN. 전자 버전 저널에 부여되는 고유 식별번호입니다.
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.