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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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| ○ | ○ | Article | Role of UV Radiation Management Strategies: Towards Mitigating Postharvest Losses, Quality, Phenolic and Antioxidant Activity and Ripening Rate of Mango (Mangifera indica L) Cultivars | Mango fruit is nutritious yet perishable; scientists are trying their best to extend its shelf life while keeping the quality of the fruit up to standard. During this study, the aim was to compare the quality, shelf life, and wastage of mango fruit exposed to ultraviolet (UV)-C radiation, both untreated and as it ripened at the tree. The fruits were harvested at the mature, hard green stage (untreated) and stored at 30 degrees C. Some of the harvested fruit was subjected to UV-C radiation and stored at 30 degrees C until ripened. The results obtained were compared to the ones that ripened on the tree. The results showed that 'S. B. Chaunsa' mango fruits have higher amounts of total sugar, total carotenoids, pH, and total soluble solids. However, 'Langra' mango fruits have higher concentrations of ascorbic acid, titratable acidity, moisture content, and total soluble solids. The results concluded that the tree-ripened and UV-C-irradiated fruits were better in quality than the untreated ones, whereas the wastage was highest in tree-ripened and lowest in UV-C-treated fruit, irrespective of variety. The chemical constituents of fruit measured after 5 days of storage and at the ripened stage indicated that all chemical contents were highest in the case of fruit ripened on the tree (T3) and then were highest for T2, irrespective of the variety. The 'S. B. Chaunsa' mango fruit variety contains higher amounts of carotenoids (58.12 mu g/g), ascorbic acid (171.7 mg/100 g), pH (3.48), and total solids (22.64%) than the 'Langra' variety. The total phenolic content was significantly increased in UV-C-treated (T2) and fruits repined on trees (T3) of the two varieties of mango fruits after 5 days of harvesting and at the ripening stage as compared to untreated fruits (T1). The most pronounced increases were detected in fruits treated with UV and also in the 'S. B. Chaunsa' variety. The antioxidant activity of UV-C-treated samples was significantly enhanced when compared to the corresponding controls. It was also noted that the ripening period was longer in 'S. B. Chaunsa' as compared to the 'Langra' variety. The rate of ripening of the fruit was estimated and found to be highest for untreated stored fruit as compared to other treatments for both varieties. The results showed that the waste percent was lowest in UV-C-treated fruit (T2) and highest in tree-ripened fruit (T3), irrespective of the variety. In conclusion, the fruit exposed to UV-C radiation was the best option. UV-C showed potential for increasing the quality, shelf life, and marketability of mangos, which are generally recognized as safe for consumers. | Fatima, Farzana; Basit, Abdul; Osaidullah; Mohamed, Heba I. | Univ Agr, Fac Crop Prod Sci, Dept Hort, Peshawar 25120, Pakistan; Kyungpook Natl Univ, Dept Hort Sci, Daegu 41566, South Korea; Ain Shams Univ, Fac Educ, Biol & Geol Sci Dept, Cairo 11341, Egypt | mohamed, heba/U-8673-2019; Basit, Abdul/AAX-2414-2021 | 58046503000; 58696991300; 59232929400; 37102371200 | hebaibrahim79@gmail.com; | APPLIED FRUIT SCIENCE | APPL FRUIT SCI | 2948-2623 | 2948-2631 | 66 | 4 | SCIE | HORTICULTURE | 2024 | N/A | 0 | 2025-05-07 | 1 | 1 | Ascorbic acid; Carotenoids; Moisture content; Soluble sugars; Total solids | C IRRADIATION; SHELF-LIFE; BIOACTIVE COMPOUNDS; FRUIT | Ascorbic acid; Carotenoids; Moisture content; Soluble sugars; Total solids | English | 2024 | 2024-08 | 10.1007/s10341-024-01116-6 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | Book chapter | Roles of Gibberellins in Plant Defense against Biotic and Abiotic Stress | A group of plant hormones known as gibberellins is crucial for controlling multiple stages of plant development (Hedden and Sponsel 2015). Gibberellins are categorized by their enantiomeric (ent) structure rather than biological action. Avar et al. (2015) categorize them as ent-gibberellin-ringed cyclic diterpenes. C20 GAs are those that have all 20 carbon atoms, while C19 GAs are those that lack one carbon atom (Sponsel 2016). The GAs that affect higher plants biologically are C19 compounds. A group of closely similar tetracyclic diterpenoid acids known as gibberellins serves an essential function as plant growth hormones. An individual subscription number, GAn, is assigned to each recognized gibberellin, where n generally corresponds to the discovery order. Gibberellic acid (GA) is the first gibberellin with a recognized structural identity. The abundance of known gases is due to the variety of the ent-gibberellin ring system (Toner et al. 2021). Due to this diversity, cells can undergo various structural changes. Gibberellins are produced by higher plants, fungi, and bacteria, and their chemical structure is based on diterpenoid acids that contain isoprene residues (Jan et al. 2021). © 2024 CRC Press. | Muhammad, Murad; Basit, Abdul; Arooj, Aqsa; Dixit, Gopal; Majeed, Muhammad; Sinha, Dwaipayan; Mohamed, Heba I.; Li, Wen-Jun | State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China, University of Chinese Academy of Sciences, Beijing, 100049, China; Department of Horticulture Science, Kyungpook National University, Daegu, 41566, South Korea; Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, No. 1799 Jimei Road, Xiamen City, Fujian, 361021, China; Department of Botany, Upadhi PG College (MJP Rohilkhand University), Pilibhit, India; Department of Botany, University of Gujrat, Hafiz Hayat Campus Gujrat-50700, Punjab, Pakistan; Department of Botany, Government General Degree College, Paschim Medinipur, West Bengal, Mohanpur, India; Department of Biological and Geological Sciences, Faculty of Education, Ain Shams, University, Cairo, 11341, Egypt; State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China, State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Resources and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, China | 57223331609; 58696991300; 58868708600; 59392570000; 58589294500; 57210702599; 37102371200; 59968447300 | Muradbotany1@uop.edu.pk; | Plant Growth Regulators to Manage Biotic and Abiotic Stress in Agroecosystems | 0 | 2025-05-07 | 3 | English | Final | 2024 | 10.1201/9781003389507-9 | 바로가기 | 바로가기 | ||||||||||||||||||||
| ○ | Article | RSSI Fingerprinting-Based Indoor Localization Algorithm Using an Interval of Estimated Distance | The problem of localization in indoor wireless networks has been actively studied using RSSI(Received Signal Strength Indicator) fingerprinting techniques. In this paper, we propose two localization algorithms, ML(Maximum Likelihood) algorithm and VAML(Valid Area Maximum Likelihood) algorithm, which are based on RSSI fingerprinting, and present key parameters for them. To inspect the effect of the main parameters of the VAML algorithm on the accuracy of the estimated location, the performance of the algorithm was compared by performing simulations and varying the value of key parameters such as the number of iterations the sensor node measures RSSI, the number of reference nodes, and the range of estimated distances calculated by an RSSI value. Lastly, the accuracy of the estimated locations and time complexities of the presented algorithms and wKNN(weighted KNN) algorithm were compared to verify that the VAML algorithm shows better performance compared to the wKNN algorithm and the ML algorithm. © 2024, Korean Institute of Communications and Information Sciences. All rights reserved. | Bae, Jonghyeon; Baek, Hoki | Kyungpook National University, School of Computer Science and Engineering, South Korea; Kyungpook National University, School of Computer Science and Engineering, South Korea | 59136764600; 35112685500 | neloyou@knu.ac.kr; | Journal of Korean Institute of Communications and Information Sciences | 1226-4717 | 49 | 4 | 0 | 2025-05-07 | 0 | Fingerprinting; Indoor localization; Path loss model; RSSI; Time complexity | Korean | Final | 2024 | 10.7840/kics.2024.49.4.590 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Article | Safe Return Home Solution Using a Smart Drone Scout | The women's safe return home service is short on operating hours and manpower. To address this social issue, this paper proposes an unmanned solution using a smart drone. When a user calls this system, it generates an initial safe path based on data from electronic tag wearers (i.e., obstacles) and map information. As the obstacles move, the safe path is re-planned to avoid them. The smart drone tracks and monitors the users returning home along the planned safe path at a certain distance and angle in real time. Since the raw GPS data from the user's app are unreliable, these are corrected to map-matching points for the drone to determine the points to track. Moreover, the smart drone identifies corners to avoid losing the monitored field of view at corners and adjusts its tracking accordingly. Flight test results validate the overall functionality and performance of the proposed solution, i.e., the proposed system improves user safety by effectively minimizing contact with electronic tag wearers while maintaining a certain distance and angle from the user by controlling the direction and speed of the drone. © ICROS 2024. | Heo, Hyeonjeong; Lee, Hojun; Lee, Kyuman | Department of Robot and Smart System Engineering, Kyungpook National University, South Korea; School of Computer Science and Engineering, Kyungpook National University, South Korea; School of Space Engineering Sciences, Kyungpook National University, South Korea | 58888646100; 58110625800; 57193932345 | klee400@knu.ac.kr; | Journal of Institute of Control, Robotics and Systems | 1976-5622 | 30 | 9 | 0.42 | 2025-05-07 | 1 | map matching; path planning; safe return home; smart drone; tracking | Aircraft detection; Target drones; Electronic tags; Home services; Map matching; Operating hours; Path-based; Real- time; Safe return home; Smart drone; Social issues; Tracking; Drones | Korean | Final | 2024 | 10.5302/j.icros.2024.24.0131 | 바로가기 | 바로가기 | |||||||||||||||
| ○ | Article | Salt and Heat Stress Trigger Morpho-Physiological Changes, Antioxidant Enzyme and Secondary Metabolites Gene Expression in Rice (Oryza sativa L.) | Climate change significantly increases salt and heat stress in rice plants. This condition causes plants to activate antioxidant enzymes and produce secondary metabolites. This study aimed to determine the morpho-physiological changes and gene expression profiles of antioxidant enzymes and secondary metabolites. This study used a completely randomized design factorial. The first factor was local rice varieties (IR64, Silaun, and Cigeulis), and the second factor was stress treatments (control, NaCl 150 mM, 40°C, and NaCl 150 mM + 40°C). The results showed that multiple stress significantly affected the plant height, stem length, stem diameter, leaf area, root length, total main root, plant biomass, necrotic length, chlorophyll content, relative water content, and plant ROS production. Multiple stress could up-regulate the gene expression of antioxidant enzymes (Mn-SOD, Cu/Zn SOD, Cytosolic APX, OsAPX1, CAT, OsCATA, and GPOD) in rice after stress combination treatments and increase the secondary metabolites gene expression (P5CS and GABA-T) in all rice varieties. Still, the OsNOMT gene was only active in the Cigeulis variety. © 2024, Bogor Agricultural University. All rights reserved. | Ubaidillah, Mohammad; Rozzita, Noor; Mufadilah, Mitha Aprilia; Thamrin, Nurhaliza; Puspito, Agung Nugroho; Kim, Kyung Min | Study Program of Agrotechnology, Faculty of Agriculture, University of Jember, Jember, 68121, Indonesia, Division of Plant Biosciences, School of Applied BioSciences, College of Agriculture and Life Science, Kyungpook National University, Korea Science and Technology, Daegu, South Korea; Study Program of Agrotechnology, Faculty of Agriculture, University of Jember, Jember, 68121, Indonesia; Study Program of Agrotechnology, Faculty of Agriculture, University of Jember, Jember, 68121, Indonesia; Study Program of Agrotechnology, Faculty of Agriculture, University of Jember, Jember, 68121, Indonesia; Graduate School of Biotechnology, University of Jember, Jember, 68121, Indonesia; Division of Plant Biosciences, School of Applied BioSciences, College of Agriculture and Life Science, Kyungpook National University, Korea Science and Technology, Daegu, South Korea | 56011434400; 58593107400; 58157593700; 58157762300; 55914230100; 34868260300 | moh.ubaidillah.pasca@unej.ac.id; | HAYATI Journal of Biosciences | 1978-3019 | 31 | 2 | 0 | 2025-05-07 | 0 | Antioxidant Enzymes; Gene Expression; Heat Stress; Plant Response; Rice; Salt Stress | English | Final | 2024 | 10.4308/hjb.31.2.256-270 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Article | Scalability and performance of decision tree for cardiovascular disease prediction | As one of the most common types of disease, cardiovascular disease is a serious health concern worldwide. Early detection is crucial for successful treatment and improved survival rates. The decision tree is a robust classifier for predicting the risk of cardiovascular disease and getting insights that would assist in making clinical decisions. However, selecting a better model for cardiovascular disease could be challenging due to scalability issues. Hence, this study examines the scalability and performance of decision trees for cardiovascular disease prediction. The study evaluated the performance of a decision tree for predicting cardiovascular disease. The performance evaluation was carried out by employing a confusion matrix, cross-validation score, model complexity, and training score for varying sizes of training samples. The experiment depicted that, the decision tree model was 88.8% accurate in predicting the presence or absence of cardiovascular disease. Therefore, the implementation of the decision tree is beneficial for the prediction and early detection of heart disease events in patients. © 2024, Institute of Advanced Engineering and Science. All rights reserved. | Assegie, Tsehay Admassu; Napa, Komal Kumar; Thulasi, Thiyagu; Kumar, Angati Kalyan; Priya, Maran Jeyanthiran Thiruvarasu Vasantha; Dhamodaran, Vigneswari | School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea; Department of Computer Science and Engineering (Data Science), Madanapalle Institute of Technology & Science, Madanapalle, India; Department of Computer Science and Engineering (Cyber Security), Madanapalle Institute of Technology & Science, Madanapalle, India; Department of Computer Science and Engineering (Data Science), Madanapalle Institute of Technology & Science, Madanapalle, India; Department of Artificial Intelligence and Data Science, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai, India; Department of Information Technology, KCG College of Technology, Karapakkam, Chennai, India | 57209398365; 57212324259; 57488734600; 58832808000; 59815929100; 57203924588 | tsehayadmassu2006@gmail.com; | IAES International Journal of Artificial Intelligence | 2089-4872 | 13 | 3 | 0 | 2025-05-07 | 1 | Automated diagnostics; Computational model; Machine learning; Scalability in machine learning | English | Final | 2024 | 10.11591/ijai.v13.i3.pp2540-2545 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | ○ | Proceedings Paper | Scalable Emotion Recognition Model with Context Information for Driver Monitoring System | Understanding emotions from an individual's perspective is critical for daily social interactions. If machines could similarly comprehend emotions, they could interact more effectively with people. Recognizing emotions accurately often necessitates considering the situational context, which helps in identifying a broader spectrum of emotions. Current emotion detection systems predominantly rely on facial images, often overlooking contextual influences. This paper proposes an emotion recognition model that combines facial feature analysis with an understanding of the surrounding context. The validation on the EMOTIC benchmark confirms the model's usefulness, registering an overall accuracy percentage of 84.9%. The paper emphasizes the necessity of combining contextual information for more accurate emotion recognition, which will pave the way for advances in sectors such as medical imaging, augmented reality, and human-computer interaction. | Colaco, Savina Jassica; Han, Dong Seog | Kyungpook Natl Univ, Ctr ICT & Automot Convergence, Daegu, South Korea; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea | 57211180064; 7403219442 | savinacolaco@knu.ac.kr;dshan@knu.ac.kr; | 2024 FIFTEENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS, ICUFN 2024 | 2165-8528 | 2165-8536 | 0 | 2025-05-07 | 0 | 0 | Classification; convolutional neural network (CNN); emotion recognition | Classification; convolutional neural network (CNN); emotion recognition | Emotion Recognition; Human computer interaction; Broad spectrum; Context information; Convolutional neural network; Driver monitoring system; Emotion recognition; Recognition models; Recognizing emotions; Situational context; Social interactions; Convolutional neural networks | English | 2024 | 2024 | 10.1109/icufn61752.2024.10625353 | 바로가기 | 바로가기 | 바로가기 | ||||||||||||
| ○ | Conference paper | Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency | Scene graph generation (SGG) is an important task in image understanding because it represents the relationships between objects in an image as a graph structure, making it possible to understand the semantic relationships between objects intuitively. Previous SGG studies used a message-passing neural networks (MPNN) to update features, which can effectively reflect information about surrounding objects. However, these studies have failed to reflect the co-occurrence of objects during SGG generation. In addition, they only addressed the long-tail problem of the training dataset from the perspectives of sampling and learning methods. To address these two problems, we propose CooK, which reflects the Co-occurrence Knowledge between objects, and the learnable term frequency-inverse document frequency (TF-l-IDF) to solve the long-tail problem. We applied the proposed model to the SGG benchmark dataset, and the results showed a performance improvement of up to 3.8% compared with existing state-of-the-art models in SGGen subtask. The proposed method exhibits generalization ability from the results obtained, showing uniform performance improvement for all MPNN models. Copyright 2024 by the author(s) | Kim, Hyeongjin; Kim, Sangwon; Ahn, Dasom; Lee, Jong Taek; Ko, Byoung Chul | Department of Computer Engineering, Keimyung University, Daegu, South Korea; Electronics and Telecommunications Research Institute (ETRI), Daegu, 42994, South Korea; Department of Computer Engineering, Keimyung University, Daegu, South Korea; Department of Computer Engineering, Kyungpook National University, Daegu, South Korea; Department of Computer Engineering, Keimyung University, Daegu, South Korea | 57942813700; 57211283842; 57942176500; 24341317500; 7102833929 | niceko@kmu.ac.kr; | Proceedings of Machine Learning Research | 2640-3498 | 235 | 1.92 | 2025-05-07 | 1 | Adversarial machine learning; Contrastive Learning; Graph theory; Inverse problems; Neural networks; Co-occurrence; Graph generation; Graph structures; Long tail; Message-passing; Neural-networks; Performance; Scene-graphs; Semantic relationships; Term Frequency; Knowledge graph | English | Final | 2024 | 바로가기 | |||||||||||||||||||
| ○ | Article | Search Operations With Geolocation Estimation of Missing Persons Based on Real-time Drone Images | The use of drones in search-and-rescue missions allows us to easily search areas that are inaccessible to humans and enables rapid and efficient mission execution with minimal manpower. In this paper, we propose a search operation method that involves automatically recognizing missing persons based on real-time images captured by a camera mounted on a drone and estimating their geolocation information. Given a particular search area, we plan a flight path while taking into consideration a cost function with constraints. Using a deep-learning model trained using cropped, generated, and augmented data, we recognize missing persons through real-time images taken by the drone following the planned path. Additionally, we estimate the geolocation of the missing persons by coordinate-transforming the reference pixels of recognized objects in the image. Based on the estimated geolocation, we identify identical objects and count the total number of objects recognized during missions. We validate the proposed search method by completing a search-and-rescue challenge using a drone. © ICROS 2024. | Lee, Joohyuk; Lee, Ho Jun; Arachchige, Sasanka Kuruppu; Kim, Namyoung; Heo, Hyeonjeong; Lee, Kyuman | Department of Robot and Smart System Engineering, Kyungpook National University, South Korea; School of Computer Science and Engineering, Kyungpook National University, South Korea; Department of Robot and Smart System Engineering, Kyungpook National University, South Korea; Department of Robot and Smart System Engineering, Kyungpook National University, South Korea; Department of Robot and Smart System Engineering, Kyungpook National University, South Korea; School of Space Engineering Sciences, Kyungpook National University, South Korea | 59202680300; 58110625800; 59139565600; 57997999800; 58888646100; 57193932345 | klee400@knu.ac.kr; | Journal of Institute of Control, Robotics and Systems | 1976-5622 | 30 | 8 | 0.84 | 2025-05-07 | 3 | geolocation estimation; object counting; object recognition; search and rescue; unmanned aerial vehicle | Aerial photography; Deep learning; Drones; Helicopter rescue services; Motion capture; Aerial vehicle; Geolocation estimation; Geolocations; Object counting; Objects recognition; Real time images; Search and rescue; Search area; Search operations; Unmanned aerial vehicle; Cost functions | Korean | Final | 2024 | 10.5302/j.icros.2024.24.0087 | 바로가기 | 바로가기 | |||||||||||||||
| ○ | Article | Secondary Beams at High-Intensity Electron Accelerator Facilities | The interaction of a high-current O(100 µA), medium energy O(10 GeV) electron beam with a thick target O(1m) produces an overwhelming shower of standard model particles in addition to hypothetical light dark matter particles. While most of the radiation (gamma, electron/positron) is contained in the thick target, deep penetrating particles (muons, neutrinos, and light dark matter particles) propagate over a long distance, producing high-intensity secondary beams. Using sophisticated Monte Carlo simulations based on FLUKA and GEANT4, we explored the characteristics of secondary muons and neutrinos and (hypothetical) dark scalar particles produced by the interaction of the Jefferson Lab 11 GeV intense electron beam with the experimental Hall-A beam dump. Considering the possible beam energy upgrade, this study was repeated for a 22 GeV CEBAF beam. © 2024 by the authors. | Battaglieri, Marco; Bianconi, Andrea; Bondí, Mariangela; De Vita, Raffaella; Fulci, Antonino; Gosta, Giulia; Grazzi, Stefano; Jo, Hyon-Suk; Lee, Changhui; Mandaglio, Giuseppe; Mascagna, Valerio; Nagorna, Tetiana; Pilloni, Alessandro; Spreafico, Marco; Tagliapietra, Luca J.; Venturelli, Luca; Vittorini, Tommaso | Istituto Nazionale di Fisica Nucleare, Sezione di Genova, Genova, 16146, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Pavia, Pavia, 27100, Italy, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia, Brescia, 25123, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Catania, Catania, 95125, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Genova, Genova, 16146, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Catania, Catania, 95125, Italy, Dipartimento di Scienze MIFT, Università degli Studi di Messina, Messina, 98166, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Pavia, Pavia, 27100, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Genova, Genova, 16146, Italy, Dipartimento di Scienze MIFT, Università degli Studi di Messina, Messina, 98166, Italy; Department of Physics, Kyungpook National University, Daegu, 41566, South Korea; Department of Physics, Kyungpook National University, Daegu, 41566, South Korea; Istituto Nazionale di Fisica Nucleare, Sezione di Catania, Catania, 95125, Italy, Dipartimento di Scienze MIFT, Università degli Studi di Messina, Messina, 98166, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Pavia, Pavia, 27100, Italy, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia, Brescia, 25123, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Genova, Genova, 16146, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Catania, Catania, 95125, Italy, Dipartimento di Scienze MIFT, Università degli Studi di Messina, Messina, 98166, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Genova, Genova, 16146, Italy, Dipartimento di Fisica, Universitá degli Studi di Genova, Genova, 16126, Italy; NEVNUCLAB, 123 W Nye Lane, Carson City, 89706, NV, United States; Istituto Nazionale di Fisica Nucleare, Sezione di Pavia, Pavia, 27100, Italy, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia, Brescia, 25123, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Genova, Genova, 16146, Italy, Dipartimento di Fisica, Universitá degli Studi di Genova, Genova, 16126, Italy | 7004520678; 7102358422; 54398256600; 59345445900; 57218222805; 56711891800; 56875468300; 35227429400; 58195426800; 12545060400; 22135531000; 57192813403; 55364479600; 57221112096; 57219796664; 22136651400; 58538014300 | antonino.fulci@unime.it; | Instruments | 2410-390X | 8 | 1 | 0.5 | 2025-05-07 | 1 | BSM physics; dark matter; intensity frontier; muon beam; neutrino interaction | English | Final | 2024 | 10.3390/instruments8010001 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Article | Security-based low-density parity check encoder for 5G communication | The fifth generation (5G) of mobile telecommunication standards is intended to offer better performance and efficiency. One of the most significant difficulties in delivering safe data transfer through the transmission channel in the emerging 5G technology is channel-coding security. This research primarily focused on offering information transmission that is secure in the place of novel assaults such as side-channel attacks. In this research, we present a low-density parity check (LDPC) encoder that is constructed using the multiplicative masking method to overcome side-channel attacks, one of the most significant security concerns for the upcoming 5G system. As a result, it offers greater security, reduced complexity, and higher performance. Power, area, and delay can all be calculated using LDPC codes. Comparing multiplicative masking implemented LDPC encoders to ordinary channel coding techniques in terms of security seen that multiplicative masking implemented LDPC encoders offer more security. The program Xilinx ISE 14.7 can synthesize the analysis. The advantage of multiplicative masking is that it offers a promising level of security through the principle of randomization, which is the foundation of the procedure. According to the analysis, the secured transmission of the data by the proposed multiplicative masking implemented LDPC encoder is increased. © 2024, Institute of Advanced Engineering and Science. All rights reserved. | Rajangam, Balamurugan; Alagarsamy, Manjunathan; Radhakrishnan, Chirakkal Rathish; Assegie, Tsehay Admassu; Salau, Ayodeji Olalekan; Quansah, Andrew; Chowdhury, Nur Mohammad; Chowdhury, Ismatul Jannat | Department of Electronics and Communication Engineering, K. Ramakrishnan College of Engineering, Tamil Nadu, India; Department of Electronics and Communication Engineering, K. Ramakrishnan College of Technology, Tamil Nadu, India; Department of Computer Engineering, New Horizon College of Engineering, Bengaluru, India; School of Electronics Engineering, Kyungpook National University, Daegu, South Korea; Department of Electrical/Electronics and Computer Engineering, Afe Babalola University, Ado-Ekiti, Nigeria, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Tamil Nadu, India; Department of Electrical and Computer Engineering, University of North Carolina at Charlotte, Charlotte, United States; Department of Computer Science, Louisiana Tech University in Ruston, Los Angeles, United States; Department of Electrical and Computer Engineering, University of North Carolina at Charlotte, Charlotte, United States | 57315649600; 56872841600; 56644821200; 57209398365; 57204911824; 58085343600; 59608733100; 59180411400 | tsehayadmassu2006@gmail.com; | Bulletin of Electrical Engineering and Informatics | 2089-3191 | 13 | 4 | 0.43 | 2025-05-07 | 1 | 5G; Encoder; Low-density parity check codes; Security; Side-channel attack | English | Final | 2024 | 10.11591/eei.v13i4.7019 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Conference paper | Segmentation of Concrete Surface Cracks Using DeeplabV3+ Architecture | Concrete is a common construction material used in structural engineering, but it is prone to cracks which can negatively impact the quality and longevity of structures. Therefore, timely and accurate detection of cracks in concrete surfaces is an important task in structural health monitoring. Currently, deep learning has emerged as a powerful technique in different fields due to its ability to learn from large data sets, recognize patterns, and make accurate predictions. The aim of this study is to suggest an effective backbone solution for the concrete surface crack detection task using DeepLabv3+ architecture. Specifically, seven different back-bones investigated in this study were MobileNet-v2, EfficientNet-b0, Res-NeXt50-32x4d, timm-regNetx-002, timm-regNety-002, timm-gerNet-s, timm-efficientNet-b0. For the training process, we used the Adam algorithm for updating the weights of the model and the Dice loss function as the objective function. The study results show that all backbones effectively detected concrete cracks with over 92% Intersection over Union (IoU). The ResNeXt50-32x4d presents the best performance of 93.8% IoU. The findings highlighted the feasibility and effectiveness of models in concrete crack segmentation tasks. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. | Nguyen, Tan-No; Tran, Thanh Danh; Cuong, Phan Viet | Department of Civil Engineering, Kyungpook National University, Daegu, South Korea; 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 | 57862912800; 57226534956; 14053421600 | pvcuong0406@gmail.com; | Lecture Notes in Civil Engineering | 2366-2557 | 442 | 5.19 | 2025-04-16 | 2 | Concrete crack; Deep learning; DeepLabV3+; Semantic segmentation; Transfer learning | Concretes; Crack detection; Deep learning; Semantic Segmentation; Structural health monitoring; Surface defects; Accurate prediction; Concrete cracks; Concrete surface; Deep learning; Deeplabv3+; Large datasets; Learn+; Semantic segmentation; Surface cracks; Transfer learning; Semantics | English | Final | 2024 | 10.1007/978-981-99-7434-4_164 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Editorial | Selected Area of Wireless Communications and Networking | [No abstract available] | Kim, Dongkyun; Wang, Wei | School of Computer Science and Engineering, Kyungpook National University, South Korea; Department of Computer Science, San Diego State University, United States | 35753648800; 57075307000 | Proceedings of the ACM Symposium on Applied Computing | 0 | 2025-05-07 | 0 | English | Final | 2024 | 바로가기 | |||||||||||||||||||||||
| ○ | Article | Selection of chemical marker for Cnidii Rhizoma by Gyeongbuk production area and harvest time using UPLC-QTOF/MS and multivariate statistical analysis techniques | Cnidii Rhizoma is a perennial herb belonging to the Umbelliferae family. Its origin is China, and it is distributed in Korea and Japan. It has been reported that phthalide and phenolic compounds are the main ingredients. To confirm changes in metabolites from Gyeongbuk production area and harvested time, metabolite profiling and multivariate statistical analysis techniques were performed. As a result, a total of thirty-two compounds including sixteen of phthalide, phenolic acid, three of coumarin, one of aromatic glycoside, flavonoid, and steroid, two of phenylpropanoid, and unknown compounds were identified. In addition, the s-plot model of Orthogonal Partial Least Squares-Discriminant Analysis was applied to identify chemical markers that contribute to discrimination between groups by production area and harvest time. The clustering tendency of the 2019 and 2020 groups in Gyeongbuk-Bonghwa and Gyeongbuk-Yeongyang areas was confirmed. The chemical markers which were peaks No. 4, 25, and 28 identified were phenolic acid, phenylpropanoid, and phthalide glycoside. © The Korean Society for Applied Biological Chemistry 2024. | Song, Ha Eun; Oh, Seon Min; Kim, In Seon; Kim, Doo-Young; Kim, Hyoung-Geun; Yoon, Dahye; Ryu, Hyung Won; Lee, Dae Young | Natural Product Research Center and Natural Product Central Bank, KRIBB, 30-Yeongudanji-ro, Ochang-eup, Cheongwon-gu, Chungcheongbuk-do, Cheongju-si, 28116, South Korea; Natural Product Research Center and Natural Product Central Bank, KRIBB, 30-Yeongudanji-ro, Ochang-eup, Cheongwon-gu, Chungcheongbuk-do, Cheongju-si, 28116, South Korea; Natural Product Research Center and Natural Product Central Bank, KRIBB, 30-Yeongudanji-ro, Ochang-eup, Cheongwon-gu, Chungcheongbuk-do, Cheongju-si, 28116, South Korea; Natural Product Research Center and Natural Product Central Bank, KRIBB, 30-Yeongudanji-ro, Ochang-eup, Cheongwon-gu, Chungcheongbuk-do, Cheongju-si, 28116, South Korea; Natural Product Research Center and Natural Product Central Bank, KRIBB, 30-Yeongudanji-ro, Ochang-eup, Cheongwon-gu, Chungcheongbuk-do, Cheongju-si, 28116, South Korea; Department of Herbal Crop Research, National Institute of Horticultural and Herbal Science, RDA, Eumseong, 27709, South Korea; Natural Product Research Center and Natural Product Central Bank, KRIBB, 30-Yeongudanji-ro, Ochang-eup, Cheongwon-gu, Chungcheongbuk-do, Cheongju-si, 28116, South Korea; BK21 FOUR KNU Creative BioResearch Group, School of Life Sciences, Kyungpook National University, Daegu, 41566, South Korea | 58309516700; 58404032700; 58309706300; 55791606600; 57192300072; 55855383700; 9042289900; 57750904900 | ryuhw@kribb.re.k;dylee80@knu.ac.kr; | Journal of Applied Biological Chemistry | 1976-0442 | 67 | 1 | 0.46 | 2025-04-16 | 1 | Cnidii Rhizoma; Metabolites profiling; Multivariate statistical analysis; Phenolic compounds; Phthalide compounds; Ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry | Korean | Final | 2024 | 10.3839/jabc.2024.016 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Article | Self Attention Distillation-based Rotational 3D Object Recognition for Nadir FOV Safety Surveillance System | Accidents originating from mobile cranes account for approximately 13% of all accidents in the construction industry, which is significantly higher than all other accident cases. Thus, there has been a strong demand for technology solutions to prevent collisions between salvage and surrounding objects. We herein propose a safety surveillance system using rotational 3D object recognition in the nadir field of view (vertically downward FOV) based on self-attention distillation (SAD). We developed training, validation, and test datasets for the environment of an actual construction site to develop a rotational object detection model for the proposed system. Moreover, we introduced an SAD method for the backbone network to improve the representation of the backbone network and guarantee the accurate detection of objects and salvages. Overall, the proposed rotational object detection model, which is based on Real-Time Models for object Detection (RTMDet) and SAD, could achieve a performance of over 78% mean average precision (mAP). © ICROS 2024. | Woo, Min Woo; Lee, Choonghwan; Kim, Byeong Hak | Korea Institute of Industrial Technology, South Korea, School of Computer Science and Engineering, Kyungpook National University, South Korea; FLEX System, South Korea; Korea Institute of Industrial Technology, South Korea | 57297761400; 59535653800; 56406686400 | bhkim81@kitech.re.kr; | Journal of Institute of Control, Robotics and Systems | 1976-5622 | 30 | 12 | 0 | 2025-05-07 | 0 | crawler crane; knowledge distillation; object detection; rotation object detection; self attention distillation | Accidents; Cranes; Distillation equipment; Petroleum products; 3d object recognition; Back-bone network; Crawler cranes; Detection models; Knowledge distillation; Objects detection; Rotation object detection; Self attention distillation; Surveillance systems; Construction industry | Korean | Final | 2024 | 10.5302/j.icros.2024.24.0225 | 바로가기 | 바로가기 |
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