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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 | Mitigating Overflow of Object Detection Tasks Based on Masking Semantic Difference Region of Vision Snapshot for High Efficiency | Object recognition functions are essential to properly perform safety and autonomous driving functions. However, sophisticated object recognition work requires extensive computation. It is difficult to handle a large amount of computation on the lightweight embedded boards currently used in vehicles. In this paper, we propose a method using machine learning and deep learning for lightweight object recognition algorithm in lightweight embedded boards. We created an algorithm suitable for lightweight embedded boards by appropriately using deep neural network architecture that requires small computational volumes but provides low accuracy, as well as deep-learning algorithms that require large computational volumes but provide high accuracy. After determining the area using a deep neural network architecture algorithm with a relatively small amount of computation, we improved the accuracy by using a more accurate deep learning algorithm. We used OpenCV to process input images in Python, and we processed image by using efficient neural network (ENet) and You Only Look Once (YOLO). By executing this algorithm, we can realize more accurate and lightweighted object recognition. © 2022 IEEE. | Yun, Heuijee; Park, Daejin | Kyungpook National University, School of Electronics Engineering, Daegu, South Korea; Kyungpook National University, School of Electronics Engineering, Daegu, South Korea | 57222516795; 55463943600 | boltanut@knu.ac.kr; | 4th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2022 - Proceedings | 0.55 | 2025-06-25 | 2 | Autonomous driving; deep learning; ENet; object detection; OpenCV; YOLO | Autonomous vehicles; Deep neural networks; Learning algorithms; Network architecture; Object detection; Semantics; Autonomous driving; Computational volume; Deep learning; Efficient neural network; Embedded boards; Neural network architecture; Neural-networks; Objects recognition; Opencv; You only look once; Object recognition | English | Final | 2022 | 10.1109/icaiic54071.2022.9722651 | 바로가기 | 바로가기 | ||||||||||||||||||
| ○ | Conference paper | Modal parameters of a laser spot welded structure using wave-based substructuring scheme | The laser spot weld is widely used to join automotive structural components due to the advantages of being inexpensive and more efficient. However, developing a reliable FE model of a laser spot weld for investigating a structure's modal parameters is very challenging. A repeated assessment of the welded joint model can significantly affect the efficiency of the finite element method, especially for a large complex structure that usually consists of huge numbers of degrees of freedom. This paper presents a wave-based substructuring method to speed up a modal parameters analysis of a laser spot welded structure. A reduced model is developed based on the wave-based substructuring scheme and compared with the full finite element model in computational time and accuracy. It was found that the proposed scheme was able to reduce the computational time of a modal parameters analysis significantly. The proposed scheme may provide advantages for research requiring high computational analysis. © 2022 Author(s). | Basri, A. B. Ahmad; Febrina, Rina; Afriani, Lusmeilia; Rani, M. N. Abdul; Yunus, M.A.; Mirza, W. I. I. Wan Iskandar; Shah, M. A. S. Aziz | School of Automotive Engineering, Kyungpook National University, 2559 Gyeongsang-daero, Gyeonsangbuk-do, Sangju, 37224, South Korea; Department of Civil Engineering, Malahayati University, Lampung, Indonesia; Civil Engineering Department, Universitas Lampung, 35142, Indonesia; Structural Dynamics Analysis & Validation (SDAV), College of Engineering, Universiti Teknologi Mara (UiTM), Shah Alam, Selangor, 40450, Malaysia; Structural Dynamics Analysis & Validation (SDAV), College of Engineering, Universiti Teknologi Mara (UiTM), Shah Alam, Selangor, 40450, Malaysia; Structural Dynamics Analysis & Validation (SDAV), College of Engineering, Universiti Teknologi Mara (UiTM), Shah Alam, Selangor, 40450, Malaysia; Structural Dynamics Analysis & Validation (SDAV), College of Engineering, Universiti Teknologi Mara (UiTM), Shah Alam, Selangor, 40450, Malaysia | 24469638000; 55701665100; 57208130016; 55061632800; 56890638600; 57192870864; 57205540587 | mnarani@uitm.edu.my; | AIP Conference Proceedings | 0094-243X | 2545 | 0 | 2025-06-25 | 0 | English | Final | 2022 | 10.1063/5.0103295 | 바로가기 | 바로가기 | ||||||||||||||||||
| ○ | Book chapter | MOF-Derived Noble Metal-Free Electrocatalysts for Water Splitting | Electrocatalysts: From Fundamentals to Recent Advances. In the quest for sustainable hydrogen production, the challenge remains to identify new electrocatalysts for water electrolysis. While noble metals are the most effective catalysts for water splitting- A promising pathway to sustainable hydrogen production-they are expensive and scarce. Hence, there is a need to find environmentally friendly, earth abundant, highly stable, and economically viable alternatives. This book provides current state-of-the-art knowledge of a wide range of noble metal-free electrocatalysts for energy applications. Volume 2 reviews noble metal-free electrocatalysts for energy applications: Thin films, metal-organic frameworks, metal hydroxides, and transition metal-doped nanocarbon-based electrocatalysts. Some emerging materials, such as perovskites and covalent organic framework-based electrocatalysts, are covered in detail, along with phosphide-based electrocatalysts and advances in electrocatalysts for flexible devices. © 2022 American Chemical Society. All rights reserved. | Dipto, Nafiz Imran; Bhowmik, Snahasish; Tahmid, Ishmam; Mim, Kamrun Nahar; Dey, Shaikat Chandra; Molla, Md. Ashraful Islam; Paul, Shujit Chandra; Jhung, Sung Hwa; Sarker, Mithun | Department of Applied Chemistry and Chemical Engineering, Faculty of Engineering and Technology, University of Dhaka, Dhaka, 1000, Bangladesh; Department of Applied Chemistry and Chemical Engineering, Noakhali Science and Technology University, Sonapur, Noakhali, 3814, Bangladesh; Department of Applied Chemistry and Chemical Engineering, Faculty of Engineering and Technology, University of Dhaka, Dhaka, 1000, Bangladesh; Department of Civil Engineering, Rajshahi University of Engineering and Technology, Rajshahi, 6204, Bangladesh; Department of Applied Chemistry and Chemical Engineering, Faculty of Engineering and Technology, University of Dhaka, Dhaka, 1000, Bangladesh, Department of Forest Biomaterials, North Carolina State University, Campus Box 8005, Raleigh, 27695, NC, United States; Department of Applied Chemistry and Chemical Engineering, Faculty of Engineering and Technology, University of Dhaka, Dhaka, 1000, Bangladesh; Department of Applied Chemistry and Chemical Engineering, Noakhali Science and Technology University, Sonapur, Noakhali, 3814, Bangladesh; Department of Chemistry and Green-Nano Materials Research Center, Kyungpook National University, Daegu, 41566, South Korea; Department of Applied Chemistry and Chemical Engineering, Faculty of Engineering and Technology, University of Dhaka, Dhaka, 1000, Bangladesh | 58037453700; 57226616122; 57232895700; 58037523200; 57212406719; 57196148108; 57198824042; 6701659467; 57192257396 | ACS Symposium Series | 0097-6156 | 1432 | 1.47 | 2025-06-25 | 3 | Electrolysis; Hydrogen production; Organic polymers; Organometallics; Perovskite; Precious metals; 'current; Economically viable; Energy applications; Highly stables; Metal-free electrocatalysts; State of the art; Thin film metal; Water electrolysis; Water splitting; ]+ catalyst; Electrocatalysts | English | Final | 2022 | 10.1021/bk-2022-1432.ch004 | 바로가기 | 바로가기 | ||||||||||||||||||
| ○ | ○ | Article | Molecular Detection and Genetic Diversity of Blastocystis in Korean Dogs | Blastocystis is a genus of unicellular heterokont parasites belonging to a group of organisms known as Stra-menopiles, which includes algae, diatoms, and water molds. Blastocystis includes several species that habitat in the gas-trointestinal tracts of organisms as diverse as humans, farm animals, birds, rodents, reptiles, amphibians, fish, and cock-roaches. It is important to public health and distributed globally, but its prevalence in dogs in Korea has not been reported to date. Here, we collected 787 canine fecal samples and assessed Blastocystis infection by age, sex, region, season, and diarrhea symptoms. We determined Blastocystis subtypes using phylogenetic analyses based on 18S rRNA gene sequences. We identified, 10 Blastocystis positive samples (1.3%). A higher proportion of infected dogs was asymptom-atic; however, infection rates did not significantly differ according to region, age, sex, and season. Phylogenetic analysis showed that the Blastocystis sp. identified belonged to 4 subtypes (STs), ST1, ST5, ST10, and ST14, thus revealed the genetic diversity of Blastocystis sp. in dogs Korean. This is first report on the presence of Blastocystis sp. in dogs Korean. This study revealed a lower infection rate than expected and differed from previous studies in STs. Further studies are warranted to observe the national infection status of Blastocystis in dogs and the genetic characteristics of this genus. | Suh, Sangsu; Lee, Haeseung; Seo, Min-Goo; Kim, Kyoo-Tae; Eo, Kyung-Yeon; Kwon, Young-Sam; Park, Sang-Joon; Kwon, Oh-Deog; Kim, Tae-Hwan; Kwak, Dongmi | Kyungpook Natl Univ, Coll Vet Med, Daegu 41566, South Korea; Semyung Univ, Coll Healthcare & Biotechnol, Dept Anim Hlth & Welf, Jecheon 27136, South Korea | Seo, Min-Goo/NQF-4335-2025 | 57866669400; 57202497862; 53982155300; 56680415000; 26631541100; 7403459426; 7501825941; 7402195886; 57202984578; 7007148758 | dmkwak@knu.ac.kr; | KOREAN JOURNAL OF PARASITOLOGY | 0023-4001 | 1738-0006 | 60 | 4 | 0.69 | 2025-06-25 | 5 | 5 | Blastocystis; phylogeny; dog; prevalence; subtyping; 18S rRNA | RHIZOPODA; PROTISTA | 18S rRNA; Blastocystis; dog; phylogeny; prevalence; subtyping | Animals; Blastocystis; Blastocystis Infections; Dogs; Feces; Genetic Variation; Humans; Phylogeny; Prevalence; animal; Blastocystis; blastocystosis; dog; feces; genetic variation; genetics; human; parasitology; phylogeny; prevalence; veterinary medicine | English | 2022 | 2022-08 | 10.3347/kjp.2022.60.4.289 | 바로가기 | 바로가기 | 바로가기 | ||||||||
| ○ | Article | Molecular mechanisms of hederagenin in bone formation; [Hederagenin의 뼈 형성 관련 작용 기전 연구] | Purpose: Osteoporosis is characterized by structural deterioration of the bone tissue because of the loss of osteoblastic activity or the increase in osteoclastic activity, resulting in bone fragility and an increased risk of fractures. Hederagenin (Hed) is a pentacyclic triterpenoid saponin isolated from Dipsaci Radix, the dried root of Dipsacus asper Wall. Dipsaci Radix has been used in Korean herbal medicine to treat bone fractures. In this study, we attempted to demonstrate the potential anti-osteoporotic effect of Hed by examining its effect on osteoblast differentiation in MC3T3-E1 cells. Methods: Osteoblastic MC3T3-E1 cells were cultured in 0, 1, and 10 μg/mL Hed for 3 and 7 days. The activity of alkaline phosphatase (ALP), bone nodule formation and level of expression of bone-related genes and proteins were measured in MC3T3-E1 cells exposed to Hed. The western blot test was used to detect the activation of the bone morphogenetic protein-2 (BMP2)/Suppressor of Mothers against Decapentaplegic (SMAD)1 pathway. Results: Hed significantly increased the proliferation of MC3T3-E1 cells. Intracellular ALP activity was significantly increased in the 1 μg/mL Hed-treated group. Hed significantly increased the concentration of calcified nodules. Furthermore, Hed significantly upregulated the expression of genes and proteins associated with osteoblast proliferation and differentiation, such as Runt-related transcription factor 2 (Runx2), ALP, osteopontin (OPN), and type I procollagen (ProCOL1). Induction of osteoblast differentiation by Hed was associated with increased BMP2. In addition, Hed induced osteoblast differentiation by increasing the activity of SMAD1/5/8. These results suggest that Hed has the potential to prevent osteoporosis by promoting osteoblastogenesis in osteoblastic MC3T3-E1 cells via the modulation of the BMP2/SMAD1 pathway. Conclusion: The results presented in this study indicate that Hed isolated from Dipsaci Radix has the potential to be developed as a healthcare food and functional material possessing anti-osteoporosis effects. © 2022 The Korean Nutrition Society This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. | Seo, Hyun-Ju; Kwun, In-Sook; Kwon, Jaehee; Sim, Yejin; Cho, Young-Eun | Department of Food Science and Nutrition, Andong National University, Andong, 36729, South Korea, Exosome Convergence Research Center, Kyungpook National University, Daegu, 41944, South Korea, Agriculture Science and Technology Research Institute, Andong National University, Andong, 36729, South Korea; Department of Food Science and Nutrition, Andong National University, Andong, 36729, South Korea; Department of Food Science and Nutrition, Andong National University, Andong, 36729, South Korea; Department of Food Science and Nutrition, Andong National University, Andong, 36729, South Korea; Department of Food Science and Nutrition, Andong National University, Andong, 36729, South Korea, Agriculture Science and Technology Research Institute, Andong National University, Andong, 36729, South Korea | 57219941260; 6602312720; 58022958600; 57220600274; 56390104900 | yecho@andong.ac.kr; | Journal of Nutrition and Health | 2288-3886 | 55 | 6 | 0 | 2025-06-25 | 0 | BMP2 protein; hederagenin; osteoblasts; osteoporosis; SMAD1 protein | Korean | Final | 2022 | 10.4163/jnh.2022.55.6.617 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Book chapter | Molecular structure characterization of crude oil and its products by mass spectrometry | Crude oil and its products, including light oils, heavy oils, fuels, tar, asphalt, lubricating oils, heavy oils, spilled oils, and hydrotreated oils, are complex mixtures containing thousands of chemical compounds with diverse structures. The chemical structural identification of crude oil and its products is extremely important for gaining insights into the chemistry of petroleum in the petrochemical industry. Mass spectrometry (MS), particularly ultrahigh-resolution MS (UHR-MS), is considered an important technique for the accurate analysis of the underlying mass and structure of crude oil components. Hydrogen/deuterium exchange (HDX) tandem MS and ion-mobility (IM) spectrometry coupled with HR-MS have attracted significant attention for their application in investigating the molecular structures of petroleum and its products. The most effective HDX technique used for crude oil analysis is atmospheric pressure in-source HDX, which is suitable for the detailed structural identification of complex mixtures, such as crude oil. By combining atmospheric pressure ionization techniques, such as electrospray ionization (ESI), atmospheric-pressure photoioniza-tion (APPI), and atmospheric-pressure chemical ionization (APCI), the sample preparation step for HDX MS can be considerably simplified, enabling the attainment of high-quality results and the specification of the heteroatom classes in crude oil. To isolate ions with specific m/z values and, thus, understand the core structures of oil compounds, the fragmentation patterns of the oil compounds are studied by tandem MS with collision-induced dissociation (CID) or infrared multiphoton dissociation coupled with HR-MS. In addition, IM separation with multiple cycles combined with quadru-pole selection is considered a powerful technique for isolating ions with specific mobility values during complex mixture analysis. Recently, IM coupled with HR-MS, experimental collision cross-section (CCS) and theoretical CCS values was employed to study the chemical structures of petroleum compounds. Due to the separation of isomeric or isobaric ions in IM cells, improved peak capacities and highly accurate structural assignments of crude oil compounds can be achieved. This chapter provides an overview of some of the key applications of HDX, tandem MS, and IM-MS techniques to the structural analysis of crude oil and its products. © 2022 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved. | Acter, Thamina; Uddin, Nizam; Kim, Sunghwan | Department of Mathematical and Physical Sciences, East West University, A/2, Jahurul Islam Avenue, Aftabnagar, Dhaka, 1212, Bangladesh; Department of Nutrition and Food Engineering, Faculty of Allied Health Science, Daffodil International University, 102, Shukrabad, Dhanmondi, Dhaka, 1207, Bangladesh; Department of Chemistry, Kyungpook National University, Daegu, 702-701, South Korea, Green-Nano Materials Research Center, Daegu, 41566, South Korea | 56768064900; 57188533756; 57203772967 | The Chemistry of Oil and Petroleum Products | 0 | 2025-06-25 | 0 | English | Final | 2022 | 10.1515/9783110694529-012 | 바로가기 | 바로가기 | |||||||||||||||||||||
| ○ | ○ | Article | Mortality and Causes of Death among Individuals Diagnosed with Human Immunodeficiency Virus in Korea, 2004-2018: An Analysis of a Nationwide Population-Based Claims Database | The mortality rate and causes of death among individuals diagnosed with human immunodeficiency virus (HIV) infection in Korea were described and compared to those of the general population of Korea using a nationwide population-based claims database. We included 13,919 individuals aged 20-79 years newly diagnosed with HIV between 2004 and 2018. The patients' vital status and cause of death were linked until 31 December 2019. Standardized mortality ratios (SMRs) for all-cause death and specific causes of death were calculated. By the end of 2019, 1669 (12.0%) of the 13,919 HIV-infected participants had died. The survival probabilities of HIV-infected individuals at 1, 5, 10, and 15 years after diagnosis in Korea were 96.2%, 91.6%, 85.9%, and 79.6%, respectively. The main causes of death during the study period were acquired immunodeficiency syndrome (AIDS; 59.0%), non-AIDS-defining cancer (8.2%), suicide (7.4%), cardiovascular disease (4.9%), and liver disease (2.7%). The mortality rate of men and women infected with HIV was 5.60-fold (95% CI = 5.32-5.89) and 6.18-fold (95% CI = 5.30-7.09) that of men and women in the general population, respectively. After excluding deaths due to HIV, the mortality remained significantly higher, with an SMR of 2.16 (95% CI = 1.99-3.24) in men and 3.77 (95% CI = 3.06-4.48) in women. HIV-infected individuals had a higher overall mortality than the general population, with AIDS the leading cause of mortality. Additionally, mortality due to non-AIDS-related causes was higher in HIV-infected individuals. | Park, Boyoung; Choi, Yunsu; Kim, Jung Ho; Seong, Hye; Kim, Youn Jeong; Lee, Myungsun; Seong, Jaehyun; Kim, Shin-Woo; Song, Joon Young; Choi, Hee-Jung; Park, Dae Won; Kim, Hyo Youl; Choi, Jun Yong; Kim, Sang Il; Choi, Bo-Youl | Hanyang Univ, Dept Prevent Med, Coll Med, 222 Wangsimni Ro, Seoul 04763, South Korea; Yonsei Univ, Dept Internal Med, Coll Med, 50-1 Yonsei Ro, Seoul 03722, South Korea; Yonsei Univ, AIDS Res Inst, Coll Med, 50-1 Yonsei Ro, Seoul 03722, South Korea; Korea Univ, Dept Internal Med, Div Infect Dis, Coll Med, Anam Dong 5 Ga, Seoul 08308, South Korea; Catholic Univ Korea, Coll Med, Incheon St Marys Hosp, Div Infect Dis,Dept Internal Med, 56 Dongsu Ro, Incheon 21431, South Korea; Korea Natl Inst Hlth, Natl Inst Infect Dis, Ctr Emerging Virus Res, Div Clin Res, Osong Hlth Technol Adm Complex 187, Osong Eup 28159, Cheongju Si, South Korea; Kyungpook Natl Univ, Sch Med, Dept Internal Med, 680 Gukchaebosang Ro, Deagu 41944, South Korea; Ewha Womans Univ, Dept Internal Med, Coll Med, 52 Ewhayeodae Gil, Seoul 03760, South Korea; Yonsei Univ, Dept Internal Med, Wonju Coll Med, 162 Ilsan Dong, Wonju 26426, South Korea; Catholic Univ Korea, Coll Med, Seoul St Marys Hosp, Div Infect Dis,Dept Internal Med, 222 Banpo Daero, Seoul 06591, South Korea | ; Choi, Yunsu/AAH-1260-2021; Kim, Jung/L-9791-2019; Choi, Jah/AAA-4835-2022 | 57217335056; 57195931031; 56657199800; 57193717138; 26659471500; 58603003300; 57207936392; 8710731500; 57214400146; 57217262202; 55724785200; 56819456800; 57791298700; 56941143600; 57236918400 | hayejine@hanyang.ac.kr; | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH | 1660-4601 | 19 | 18 | 0.99 | 2025-06-25 | 12 | 11 | human immunodeficiency virus; acquired immunodeficiency syndrome; mortality; standardized mortality ratio | HIV-INFECTED PATIENTS; GENERAL-POPULATION; COHORT; TRENDS; ERA; INITIATION; HIV/AIDS | acquired immunodeficiency syndrome; human immunodeficiency virus; mortality; standardized mortality ratio | Acquired Immunodeficiency Syndrome; Causality; Cause of Death; Female; HIV; HIV Infections; Humans; Male; Mortality; Korea; antiretrovirus agent; acquired immune deficiency syndrome; cause of death; disease severity; health geography; health status; human immunodeficiency virus; life expectancy; medical geography; mortality; survival; acquired immune deficiency syndrome; administrative claims (health care); adult; aged; all cause mortality; Article; calculation; cardiovascular disease; cause of death; controlled study; data base; female; highly active antiretroviral therapy; human; Human immunodeficiency virus infected patient; Human immunodeficiency virus infection; infection; Korea; liver disease; major clinical study; male; malignant neoplasm; middle aged; mortality rate; patient selection; population research; sex difference; standardized mortality ratio; suicide; survival rate; young adult; acquired immune deficiency syndrome; causality; cause of death; Human immunodeficiency virus; Human immunodeficiency virus infection; mortality | English | 2022 | 2022-09 | 10.3390/ijerph191811788 | 바로가기 | 바로가기 | 바로가기 | |||||||||
| ○ | Conference paper | Multi-domain Vision based Sign Language Recognition based on Auto Labeled Hand Tracking Data Learning | Remote operating and autonomous systems are widely applied in various fields, and the development of technology for human machine interface and communication is strongly demanded. In order to overcome the limitations of the conventional keyboard and tablet devices, various vision sensors and state-of-the-art artificial intelligence image processing techniques are used to recognize hand gestures. In this study, we propose a method for recognizing a reference sign language using auto labeled AI model training datasets. This study can be applied to the remote control interfaces for drivers to vehicles, person to home appliances, and gamers to entertainment contents and remote character input technology for the metaverse environment. © 2022 SPIE. | Lee, Junha; Won, Hong-In; Kim, Min Young; Kim, Byeong Hak | Kyungpook National University (KNU), 80 Daehakro, Daegu, South Korea, Korea Institute of Industrial Technology (KITECH), 15 Jisiksanneop-ro, Gyeongsan, South Korea; Korea Institute of Industrial Technology (KITECH), 15 Jisiksanneop-ro, Gyeongsan, South Korea; Kyungpook National University (KNU), 80 Daehakro, Daegu, South Korea; Korea Institute of Industrial Technology (KITECH), 15 Jisiksanneop-ro, Gyeongsan, South Korea | 57417335200; 57548175800; 56739349100; 56406686400 | minykim@knu.ac.kr;bhkim81@kitech.re.kr; | Proceedings of SPIE - The International Society for Optical Engineering | 0277-786X | 12267 | 0 | 2025-06-25 | 0 | deep learning; hand tracking; human machine interface; machine learning; multi-domain sensing; object detection; remote sensing; sign language recognition | Deep learning; Domestic appliances; Learning systems; Object detection; Palmprint recognition; Remote control; Deep learning; Hand-tracking; Human Machine Interface; Machine-learning; Multi-domain sensing; Multi-domains; Objects detection; Remote-sensing; Sign Language recognition; Vision based sign language recognition; Remote sensing | English | Final | 2022 | 10.1117/12.2638450 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Conference paper | Multi-RIS Deployment for High Data-Rate Communications | This paper proposes using multiple reconfigurable intelligent surfaces (RISs) in SISO communications, considering that RISs can flexibly extend the wireless communication range. In a given area with multiple RISs, we propose an algorithm to select the optimal locations from a set of candidate points to deploy the RISs, aiming to maximize the achievable data rate. We investigate the impact of single-hop and multi-hops communication on the achievable data rate for the proposed algorithm and the results show that the deployment height and number of communication hops significantly affect the achievable data rate. © 2022 IEEE. | Khan, Muhammad Fawad; Mei, Haoran; Rahim, Shahnila; Peng, Limei; Ho, Pin-Han | School of Computer Science and Engineering, Kyungpook National University, Deagu, South Korea; School of Computer Science and Engineering, Kyungpook National University, Deagu, South Korea; School of Computer Science and Engineering, Kyungpook National University, Deagu, South Korea; School of Computer Science and Engineering, Kyungpook National University, Deagu, South Korea; University of Waterloo, Department of Electrical and Computer Engineering, Waterloo, ON, Canada | 58295476600; 57208655106; 57416456600; 7201574271; 7402211578 | Proceedings - 2022 International Conference on Networking and Network Applications, NaNA 2022 | 0.72 | 2025-06-25 | 3 | Capacity maximization; multi-hop communication; multi-RIS deployment | Capacity maximization; Communication range; Data-rate; High data rate communications; Multi hop communication; Multi-reconfigurable intelligent surface deployment; Optimal locations; Reconfigurable; Single hop; Wireless communications | English | Final | 2022 | 10.1109/nana56854.2022.00076 | 바로가기 | 바로가기 | |||||||||||||||||||
| ○ | Conference paper | Multi-scale synergy approach for real-time semantic segmentation | In deep convolution neural network based models for semantic segmentation, diverse receptive fields improve the performance by capturing disparate context information. Multiscale inference is good for both thin and large objects. However, the final result is not optimal through averaging or Max pooling combination. In this paper, we propose an approach to take advantage of multi-scale predictions. Our uncertain-pixels part discovers the worse prediction of a low scale and chooses the complement from a high scale. The final output is effectively merged from two scales. We validate our proposed model with a series of experiments on different datasets. The results achieve the accuracy and speed for real-time semantic segmentation. On Cityscapes dataset, our network achieves 76.3 % mIoU at 50 FPS, and on Mapillary, 42.6 % mIoU. © 2022 IEEE. | Van Toan, Quyen; Kim, Min Young | Kyungpook National University, School of Electronic and Electrical Engineering, Daegu, South Korea; Kyungpook National University, School of Electronic and Electrical Engineering, Daegu, South Korea | 57563580600; 56739349100 | 4th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2022 - Proceedings | 1.09 | 2025-06-25 | 4 | Multi-scale; real time; semantic segmentation | Computer vision; Semantics; Context information; Convolution neural network; Max-pooling; Multi-scales; Network-based modeling; Performance; Real- time; Real-time semantics; Receptive fields; Semantic segmentation; Semantic Segmentation | English | Final | 2022 | 10.1109/icaiic54071.2022.9722687 | 바로가기 | 바로가기 | |||||||||||||||||||
| ○ | ○ | Article | Multicenter validation of a deep-learning-based pediatric early-warning system for prediction of deterioration events | Background: Early recognition of deterioration events is crucial to improve clinical outcomes. For this purpose, we developed a deep-learning-based pediatric early-warning system (pDEWS) and aimed to validate its clinical performance. Methods: This is a retrospective multicenter cohort study including five tertiary-care academic children's hospitals. All pediatric patients younger than 19 years admitted to the general ward from January 2019 to December 2019 were included. Using patient electronic medical records, we evaluated the clinical performance of the pDEWS for identifying deterioration events defined as in-hospital cardiac arrest (IHCA) and unexpected general ward-to-pediatric intensive care unit transfer (UIT) within 24 hours before event occurrence. We also compared pDEWS performance to those of the modified pediatric early-warning score (PEWS) and prediction models using logistic regression (LR) and random forest (RF). Results: The study population consisted of 28,758 patients with 34 cases of IHCA and 291 cases of UIT. pDEWS showed better performance for predicting deterioration events with a larger area under the receiver operating characteristic curve, fewer false alarms, a lower mean alarm count per day, and a smaller number of cases needed to examine than the modified PEWS, LR, or RF models regardless of site, event occurrence time, age group, or sex. Conclusions: The pDEWS outperformed modified PEWS, LR, and RF models for early and accurate prediction of deterioration events regardless of clinical situation. This study demonstrated the potential of pDEWS as an efficient screening tool for efferent operation of rapid response teams. | Shin, Yunseob; Cho, Kyung-Jae; Lee, Yeha; Choi, Yu Hyeon; Jung, Jae Hwa; Kim, Soo Yeon; Kim, Yeo Hyang; Kim, Young A.; Cho, Joongbum; Park, Seong Jong; Jhang, Won Kyoung | VUNO Inc, Seoul, South Korea; Seoul Natl Univ Childrens Hosp, Dept Pediat, Seoul, South Korea; Yonsei Univ, Severance Childrens Hosp, Dept Pediat, Coll Med, Seoul, South Korea; Kyungpook Natl Univ, Kyungpook Natl Univ Childrens Hosp, Sch Med, Dept Pediat, Daegu, South Korea; Pusan Natl Univ Childrens Hosp, Dept Pediat, Yangsan, South Korea; Sungkyunkwan Univ, Samsung Med Ctr, Sch Med, Dept Crit Care Med, Seoul, South Korea; Univ Ulsan, Asan Med Ctr Childrens Hosp, Dept Pediat, Coll Med, Seoul, South Korea | ; Cho, Hwa Jin/AFA-1420-2022; Kim, Sooyeon/AAA-8521-2022; Kim, Young A/HSG-2689-2023; cho, hwa jin/AFA-1420-2022; LEE, Keon-Joo/AAO-4206-2020 | 57848107100; 57215545848; 57202891529; 56583002600; 57211126210; 57196231273; 57032023800; 57196050642; 50360978300; 35211375100; 23481560600 | wkjhang@amc.seoul.kr; | ACUTE AND CRITICAL CARE | ACUTE CRIT CARE | 2586-6052 | 2586-6060 | 37 | 4 | ESCI | CRITICAL CARE MEDICINE | 2022 | 1.8 | 0.82 | 2025-06-25 | 4 | 6 | cardiac arrest; critical care; deep learning; early warning score; pediatrics | SCORE | cardiac arrest; critical care; deep learning; early warning score; pediatrics | English | 2022 | 2022-11 | 10.4266/acc.2022.00976 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | Book chapter | Multilevel inverter topologies and their applications | [No abstract available] | Faraji, Faramarz; Aghajani, Amir Abbas; Eldoromi, Mojtaba; Birjandi, Ali Akbar Moti; Ghias, Amer M.Y.M.; Cha, Honnyong | School of Energy Engineering, Kyungpook National University, South Korea; Electrical Faculty, Shahid Rajaee Teacher Training University, Iran; Electrical Faculty, Shahid Rajaee Teacher Training University, Iran; Electrical Faculty, Shahid Rajaee Teacher Training University, Iran; School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore; School of Energy Engineering, Kyungpook National University, South Korea | 57191226987; 57704413000; 57207816331; 56385905500; 46062041900; 24450248400 | Power Electronics for Next-Generation Drives and Energy Systems: Converters and control for drives | 0 | 2025-06-25 | 0 | English | Final | 2022 | 바로가기 | |||||||||||||||||||||||
| ○ | ○ | Proceedings Paper | Multimodal Object Detection and Ranging Based on Camera and Lidar Sensor Fusion for Autonomous Driving | A robust perception system is critical in autonomous driving. It is responsible for object detection, classification, and ranging under challenging circumstances. Camera and lidar sensors provide complementary information, and by combining these two modalities, we can increase the robustness and accuracy of the overall perception system. This paper presents the implementation of sensor fusion based perception using camera images and lidar point clouds for object detection and ranging in a real-time driving environment. The experiment results obtained with our test vehicle demonstrate that the perception of vehicle surroundings can be more effectively achieved by means of camera-lidar sensor fusion compared with using a single type of sensor. | Khan, Danish; Baek, Minjin; Kim, Min Young; Han, Dong Seog | Kyungpook Natl Univ, Ctr ICT & Automot Convergence, Daegu, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Daegu, South Korea | Baek, Minjin/L-4425-2016; Khan, Danish/AAW-6708-2021 | 57200212320; 57848675100; 56739349100; 7403219442 | danish@knu.ac.kr;mbaek@knu.ac.kr;minykim@knu.ac.kr;dshan@knu.ac.kr; | 2022 27TH ASIA PACIFIC CONFERENCE ON COMMUNICATIONS (APCC 2022): CREATING INNOVATIVE COMMUNICATION TECHNOLOGIES FOR POST-PANDEMIC ERA | 2163-0771 | 3.05 | 2025-06-25 | 3 | 8 | camera; lidar; sensor fusion; perception; object detection; ranging; autonomous driving | autonomous driving; camera; lidar; object detection; perception; ranging; sensor fusion | Automobile drivers; Autonomous vehicles; Object detection; Object recognition; Optical radar; Autonomous driving; Camera images; Camera sensor; Lidar point clouds; LIDAR sensors; Multi-modal; Objects detection; Perception systems; Real- time; Sensor fusion; Cameras | English | 2022 | 2022 | 10.1109/apcc55198.2022.9943618 | 바로가기 | 바로가기 | 바로가기 | ||||||||||||
| ○ | ○ | Proceedings Paper | Multiswitch Fault-detection for VSI fed Multiphase Motor Drive Based on Machine Learning | Detecting early faults in an electric drive system in order to maintain reliability and uninterrupted post-fault operation is an extremely difficult task. In recent years, early fault detection has become one of the most important areas of cuttingedge research in the fields of electric vehicles, offshore-ship propulsion, air taxis, electric vertical take-off and landing, etc. In this paper, a generalized fault detection method for the fivephase induction motor drive is presented based on an optimized support vector machine (SVM) learning algorithm. Using the second low-frequency processing method, low-frequency signals were extracted from fault currents and employed for SVM training. This expedites fault detection and reduces memory allocation. The proposed fault detection algorithm has been validated through simulation in steady-state and dynamic loading conditions of the drive for a variety of fault scenarios. | Chikondra, Bheemaiah; Gonuguntla, Venkateswarlu; Al Zaabi, Omar; Behera, Ranjan Kumar; Veluvolu, Kalyana C. | Khalifa Univ, Dept Elect Engn & Comp Sci, Abu Dhabi, U Arab Emirates; Vellore Inst Technol, Sch Elect Engn, Vellore, India; Symbiosis Int Univ, Symbiosis Ctr Med Image Anal, Pune, India; IIT Patna, Dept Elect Engn, Patna, India; Kyungpook Natl Univ, Sch Elect Engn, Daegu, South Korea | Veluvolu, Kalyana/C-6366-2011; Chikondra, Bheemaiah/AAP-9146-2020; BEHERA, RANJAN/I-2680-2017; Gonuguntla, Venkateswarlu/AAH-5239-2021 | 57212455117; 55696595000; 57221966256; 57210095386; 8703318200 | 2022 IEEE INTERNATIONAL CONFERENCE ON POWER ELECTRONICS, DRIVES AND ENERGY SYSTEMS, PEDES | 0.47 | 2025-06-25 | 1 | 1 | Artificial intelligence; fault-tolerance; multiphase machines; support vector machine; voltage source inverter | 5-PHASE; DIAGNOSIS | Artificial intelligence; fault-tolerance; multiphase machines; support vector machine; voltage source inverter | Dynamic loads; Electric drives; Electric inverters; Fault detection; Fault tolerance; Induction motors; Learning algorithms; Learning systems; Offshore oil well production; Ship propulsion; Early fault; Faults detection; Machine-learning; Motor drive; Multi-phase motors; Multiphase machines; On-machines; Support vectors machine; Voltage source inverter; Voltage-source inverter; Support vector machines | English | 2022 | 2022 | 10.1109/pedes56012.2022.10080697 | 바로가기 | 바로가기 | 바로가기 | |||||||||||||
| ○ | ○ | Proceedings Paper | Multivariate-aided Power-consumption Prediction Based on LSTM-Kalman Filter | Forecasting the power consumption of home appliances on a time-series basis is significant in monitoring and predicting daily human behaviors. On the other hand, time-series forecasting is challenged by the uncertain and complex external environment, such as weather conditions that affect prediction accuracy. A promising method to improve the prediction accuracy is to adopt multiple external environment variables. Regarding this, the paper proposes using the multivariate dataset and the Kalman filter (KF) to predict the electrical power consumed by the smart home appliance. We conduct extensive experiments based on the real datasets of power consumption, which are classified into multivariate and univariate and used in the LSTM-KF model to predict the power consumption of the smart home appliance. The LSTM here stores the data information for static prediction, and the Kalman filter dynamically adjusts the prediction results to obtain a final prediction value. The LSTM-KF models applying the proposed multivariate and the univariate are compared in terms of the RMSE and the determination coefficient R2. The LSTM-KF using multivariate shows the best accuracy. Nonetheless, the univariate method using the Kalman filter outperforms the multivariate method without using the Kalman filter, implying the significance of using multiple variables together with the Kalman filter in improving the prediction accuracy. | Lyu, Shuai; Mei, Haoran; Peng, Limei; Chang, Shih Yu; Mo, Jiang | Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu 41566, South Korea; San Jose State Univ, Sch Appl Data Sci, San Jose, CA 95192 USA; Pukyong Natl Univ, Sch Human, Busan 48513, South Korea | 57991691600; 57208655106; 7201574271; 57221159388; 58068977900 | chanceuxshuai@knu.ac.kr;meihaoran@knu.ac.kr;auroraplm@knu.ac.kr;shihyu.chang@sjsu.edu;mojiang8666@naver.com; | 2022 INTERNATIONAL CONFERENCE ON NETWORKING AND NETWORK APPLICATIONS, NANA | 0.48 | 2025-06-25 | 0 | 2 | SIoT energy consumption; multivariate; time-series prediction; LSTM; Kalman filter | Kalman filter; LSTM; multivariate; SIoT energy consumption; time-series prediction | Behavioral research; Domestic appliances; Electric power utilization; Forecasting; Long short-term memory; Time series; Energy-consumption; External environments; Kalman filter model; LSTM; Multivariate; Prediction accuracy; SIoT energy consumption; Smart homes; Time series prediction; Univariate; Kalman filters | English | 2022 | 2022 | 10.1109/nana56854.2022.00100 | 바로가기 | 바로가기 | 바로가기 |
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