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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 | Accelerating DSP Applications on a 16-Bit Processor: Block RAM Integration and Distributed Arithmetic Approach | Modern processors have improved performance but still face challenges such as power consumption, storage limitations, and the need for faster processing. The 16-bit Digital Signal Processors (DSPs) accelerate DSP applications by significantly enhancing speed and performance for tasks including audio processing, telecommunications, image and video processing, wireless communication, and consumer electronics. This paper presents a novel technique for accelerating DSP applications on a 16-bit processor by combining two methods: Block Random Access Memory (BRAM) and Distributed Arithmetic (DA). Integrating BRAM as a replacement for conventional RAM minimizes timing and critical route delays, improving processor efficiency and performance. Furthermore, the Distributed Arithmetic approach enhances performance and efficiency by utilizing precomputed lookup tables to expedite multiplication operations within the Arithmetic and Logic Unit (ALU). We use the Xilinx Vivado tool, a robust development environment for FPGA-based systems, for the design process and execute the hardware implementation using the Genesys2 Kintex board. The proposed work produces improved efficiency with a cycle per instruction of 2, where the delay is 2.009 ns, the critical path delay is 8.182 ns, and the power consumption is 4 mW. | Bharathi, M.; Mohanarangam, Krithikaa; Shirur, Yasha Jyothi M.; Choi, Jun Rim | Mohan Babu Univ, Erstwhile Sree Vidyanikethan Engn Coll, Sch Engn Technol, Dept ECE, Tirupati 517102, India; VTU, BNM Inst Technol, Bangalore 560070, India; Symbiosis Int Univ, Symbiosis Inst Technol, Pune Campus, Pune 412115, India; BNM Inst Technol, Dept ECE, Bangalore 560070, India; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daehak Ro, Daegu 41566, South Korea; Kyungpook Natl Univ, Coll IT Engn, Sch Elect Engn, Daehak Ro, Daegu 41566, South Korea | Shirur, Dr. Yasha Jyothi/ABH-1112-2021; M Shirur, Yasha jyothi/ABH-1112-2021; Mohanarangam, Krithikaa/IAO-1286-2023 | 57210599591; 56955462000; 55813708100; 7501392846 | bharathi.m@vidyanikethan.edu;krithikaamohan@gmail.com;yashajyothimshirur@bnmit.in;jrchoi@ee.knu.ac.kr; | ELECTRONICS | 2079-9292 | 12 | 20 | 0.47 | 2025-06-25 | 1 | 4 | 16-bit processor; distributed arithmetic (DA); Block RAM (BRAM); Xilinx Vivado; Genesys2 Kintex | 16-bit processor; Block RAM (BRAM); distributed arithmetic (DA); Genesys2 Kintex; Xilinx Vivado | English | 2023 | 2023-10 | 10.3390/electronics12204236 | 바로가기 | 바로가기 | 바로가기 | |||||||||||
| ○ | Conference paper | Accelerating YOLO-based Real-time Object Detection via Foveated Rendering | Foveated rendering emulates human vision by prioritizing sharpness at the center while introducing peripheral blur outside this central area. We explore its potential for enhancing object detection performance by integrating it into various object detection methods. Our investigation demonstrates that foveated rendering effectively reduces detection time and false alarm detections, thus showcasing its utility in improving object detection performance. Experimental results indicate a reduction in detection time of up to 20% compared with object detection using conventional rendering techniques. © 2023 IEEE. | Kea, Kimleang; Lee, Sanghyeon; Kwak, Myeongjin; Han, Youngsun | Pukyong National University, Department of Ai Convergence, Busan, South Korea; Pukyong National University, Department of Ai Convergence, Busan, South Korea; Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea; Pukyong National University, Department of Ai Convergence, Busan, South Korea | 57983752100; 59951851100; 57222516282; 7404096461 | kimleangkea@pukyong.ac.kr; | 2023 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2023 | 0 | 2025-06-25 | 0 | Foveated Rendering; Object Detection | Computer vision; Object recognition; % reductions; Alarm detection; Detection performance; Detection time; Falsealarms; Foveated rendering; Human vision; Object detection method; Objects detection; Real- time; Object detection | English | Final | 2023 | 10.1109/icce-asia59966.2023.10326345 | 바로가기 | 바로가기 | ||||||||||||||||||
| ○ | Book | Accelerators for convolutional neural networks | Accelerators for Convolutional Neural Networks provides basic deep learning knowledge and instructive content to build up convolutional neural network (CNN) accelerators for the Internet of things (IoT) and edge computing practitioners, elucidating compressive coding for CNNs, presenting a two-step lossless input feature maps compression method, discussing arithmetic coding -based lossless weights compression method and the design of an associated decoding method, describing contemporary sparse CNNs that consider sparsity in both weights and activation maps, and discussing hardware/software co-design and co-scheduling techniques that can lead to better optimization and utilization of the available hardware resources for CNN acceleration. © 2024 by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved. | Munir, Arslan; Kong, Joonho; Qureshi, Mahmood Azhar | Kansas State University, United States; Kyungpook National University, South Korea; Kansas State University, United States | 24587067400; 25927220400; 57215561321 | Accelerators for Convolutional Neural Networks | 0.56 | 2025-06-25 | 2 | English | Final | 2023 | 바로가기 | |||||||||||||||||||||||
| ○ | Conference paper | Accuracy improvement for 6-axis serial robot using double ball-bar | To increase productivity in manufacturing using a robot, it is required to monitor its performance periodically. Circular test using a double ball-bar (DBB) is one of the simple, and reasonable method to check the robot's performance. For this reason, if the error compensation can be done by the circular test, the productivity can be increased by reducing the costs for maintaining accuracy performance. This work is targeting to improve accuracy of a 6-axis serial robot using a single DBB. This process consists of 3 steps, (1) measuring tool centre point (TCP), (2) estimating kinematic parameters, and (3) verification of the obtained values. At first, the position of the TCP with respect to the end-effector is measured using geometry-based method using DBB. Secondly, a mathematical relation of the kinematic parameters and the distance error is derived. Then the parameters which are redundant or merely affect distance errors are eliminated, and the identifiable parameters are analysed through the mathematical model. The measurement is carried out on a nominal circular path, then the kinematic parameters are calculated from the above method. The validity of the obtained values is determined by checking error reduction after re-measuring with the calibrated values applied. The contribution of this work is suggesting a rapid, simple method to improve the accuracy of a 6-axis serial robot. As this work does not require additional devices for measuring TCP, the whole process can be done only using a single DBB. © 2023 Euspen Headquarters. | Yang, Seung-Han; Jeon, Heung-Ki; Kweon, Seong-Hwan; Lee, Kwang-Il | School of Mechanical Engineering, Kyungpook National University, Daegu, 41566, South Korea; School of Mechanical Engineering, Kyungpook National University, Daegu, 41566, South Korea; Digital Design & Digital Manufacturing R&D Center, Kyungpook National University, Daegu, 41566, South Korea; School of Mechanical Automotive Engineering, Kyungil University, Daegu, 38428, South Korea | 8407949900; 57848660300; 58669067800; 57196250383 | European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 23rd International Conference and Exhibition, EUSPEN 2023 | 0 | 2025-06-25 | 0 | Calibration; Error; Measurement; Robot | Error compensation; Kinematics; Nanotechnology; Parameter estimation; Precision engineering; Transmission control protocol; Accuracy Improvement; Circular tests; Double ball bar; Kinematics parameters; Measuring tools; Performance; Robot performance; Serial robots; Simple++; Tool center points; Robots | English | Final | 2023 | 바로가기 | |||||||||||||||||||||
| ○ | Article | Acute epiglottitis with early-stage coronavirus disease 2019 infection | [No abstract available] | Heo, Sung Jae; Nho, Woo Young | Department of Otorhinolaryngology-Head and Neck Surgery, School of Medicine, Kyungpook National University, Daegu, South Korea; Department of Emergency Medicine, School of Medicine, Kyungpook National University, Daegu, South Korea | 55822906000; 57215831839 | wooyoung.nho@gmail.com; | Visual Journal of Emergency Medicine | 2405-4690 | 32 | 0 | 2025-06-25 | 0 | Acute epiglottitis; Case report; COVID-19; Odynophagia; Thumb sign | English | Final | 2023 | 10.1016/j.visj.2023.101758 | 바로가기 | 바로가기 | |||||||||||||||||
| ○ | ○ | Proceedings Paper | AD-TIN: Edge Anomaly Detection for Temporal Interaction Networks using Multi-representation Attention | Anomaly detection in temporal interaction networks (TINs) has become critical in network security, digital finance, and social networks. While recent studies based on Graph Neural Networks (GNNs) have yielded promising results, the existing methods are still limited by insufficient labels and noisy data, often ignoring the information filtering for unrelated user interactions. Therefore, this paper proposes a dynamic edge anomaly detection framework, AD-TIN, to address these challenges based on a multi-representation attention mechanism. It encodes graph structural information using a network information propagation module with neighbor sampling and graph diffusion. Furthermore, the network update module combines past node states with current structural features to capture the temporal information in potential user relationships, effectively mitigating the impact of noisy data. Extensive experiments on three real-world datasets demonstrate the robustness and efficacy of AD-TIN in addressing noise and unrelated interactions for edge anomaly detection. | Wu, Aming; Kwon, Young-Woo | Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu, South Korea | ; Kwon, Young-Woo/HGE-6607-2022 | 58262125900; 57208480210 | wuaming@knu.ac.kr;ywkwon@knu.ac.kr; | PROCEEDINGS OF THE 2023 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING, ASONAM 2023 | 2473-9928 | 2473-991X | 0 | 2025-06-25 | 0 | 0 | Anomaly detection; Temporal interaction network; Attention mechanism; Graph diffusion | anomaly detection; attention mechanism; graph diffusion; temporal interaction network | Graph neural networks; Information dissemination; Information filtering; Network security; Anomaly detection; Attention mechanisms; Graph diffusion; In networks; Interaction networks; Multi-representations; Network edges; Networks security; Noisy data; Temporal interaction network; Anomaly detection | English | 2023 | 2023 | 10.1145/3625007.3627502 | 바로가기 | 바로가기 | 바로가기 | |||||||||||
| ○ | ○ | Article | Adaptation of Deep Learning Image Reconstruction for Pediatric Head CT: A Focus on the Image Quality | Purpose To assess the effect of deep learning image reconstruction (DLIR) for head CT in pediatric patients. Materials and Methods We collected 126 pediatric head CT images, which were reconstructed using filtered back projection, iterative reconstruction using adaptive statistical iterative reconstruction (ASiR)-V, and all three levels of DLIR (TrueFidelity; GE Healthcare). Each image set group was divided into four subgroups according to the patients' ages. Clinical and dose-related data were reviewed. Quantitative parameters, including the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), and qualitative parameters, including noise, gray matter-white matter (GM-WM) differentiation, sharpness, artifact, acceptability, and unfamiliar texture change were evaluated and compared. Results The SNR and CNR of each level in each age group increased among strength levels of DLIR. High-level DLIR showed a significantly improved SNR and CNR (p < 0.05). Sequential reduction of noise, improvement of GM-WM differentiation, and improvement of sharpness was noted among strength levels of DLIR. Those of high-level DLIR showed a similar value as that with ASiR-V. Artifact and acceptability did not show a significant difference among the adapted levels of DLIR. Conclusion Adaptation of high-level DLIR for the pediatric head CT can significantly reduce image noise. Modification is needed while processing artifacts. | Lee, Nim; Cho, Hyun-Hae; Lee, So Mi; You, Sun Kyoung | Ewha Womans Univ, Med Res Inst, Dept Radiol, Coll Med,Mokdong Hosp, 1071 Anyangcheon Ro, Seoul 07985, South Korea; Yonsei Univ, Res Inst Radiol Sci, Severance Hosp, Coll Med,Dept Radiol, Seoul, South Korea; Kyungpook Natl Univ, Chilgok Hosp, Sch Med, Dept Radiol, Daegu, South Korea; Chungnam Natl Univ, Chungnam Natl Univ Hosp, Dept Radiol, Coll Med, Daejeon, South Korea | 57639553500; 56544900900; 56824903400; 56710939300 | pedradchh@ewha.ac.kr; | JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY | 2951-0805 | 84 | 1 | 1.29 | 2025-06-25 | 6 | 6 | Brain; Children; Computed Tomography, X-Ray; Image Quality Enhancement; Deep Learning; Image Processing, Computer-Assisted | ITERATIVE RECONSTRUCTION; DOSE REDUCTION; ABDOMINAL CT | Brain; Children; Computed Tomography; Computer-Assisted; Deep Learning; Image Processing; Image Quality Enhancement; X-Ray | English | 2023 | 2023-01 | 10.3348/jksr.2021.0073 | 바로가기 | 바로가기 | 바로가기 | |||||||||||
| ○ | Conference paper | Adaptive Control of Congestion Window in QUIC | The QUIC protocol offers a variety of distinctive features over TCP, which includes rapid handshaking process, zero-RTT capabilities, and connection migration. Among these, the connection migration plays a pivotal role in facilitating mobility for a myriad of mobile devices. However, the current implementation of connection migration necessitates the window size initialization when the IP address changes, such as during handovers. This leads to a decline in throughput performance. In this paper, we introduce an adaptive control of congestion window size when the client undergoes the connection migration due to IP changes. From the experimentation results, we can see that the proposed adaptive congestion control scheme provides significant performance improvement. © 2023 IEEE. | Kim, So-Yong; Koh, Seok-Joo | Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea; Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea | 57218590446; 8958394800 | thdyd324@gmail.com; | International Conference on ICT Convergence | 2162-1233 | 0 | 2025-06-25 | 0 | Congestion Window; Connection Migration; QUIC | Adaptive control systems; 'current; Adaptive congestion control; Adaptive Control; Congestion window; Congestion window size; Connection migration; Hand over; QUIC; Throughput performance; Window Size; Internet protocols | English | Final | 2023 | 10.1109/ictc58733.2023.10393389 | 바로가기 | 바로가기 | |||||||||||||||||
| ○ | ○ | Proceedings Paper | Adaptive Margin-based Contrastive Network for Generalized Zero-Shot Learning | Generalized zero-shot learning is a challenging problem that aims to recognize images from seen and unseen classes. Recent methods are costly and time-consuming or have a bias problem. To tackle this problem, we proposed an adaptive margin-based contrastive network that aims to distinguish similar classes in generalized zero-shot learning. The proposed method employs the architecture of transferable contrastive network to classify unseen classes and adaptive margin to transfer discriminative knowledge. Experiments on the AwA2 dataset demonstrate competitive results against state-of-the-art benchmarks. | Lee, Jeong-Cheol; Shibu, Athul; Lee, Dong-Gyu | Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu, South Korea | 58121964800; 58090284100; 57169003900 | jclee2716@knu.ac.kr;athulshibu@knu.ac.kr;dglee@knu.ac.kr; | 2023 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS, ICCE | 1.78 | 2025-06-25 | 2 | 2 | Adaptive margin; contrastive network; deep learning; generalized zero-shot learning; zero-shot learning | Adaptive margin; contrastive network; deep learning; generalized zero-shot learning; zero-shot learning | Computer vision; Deep learning; Adaptive margin; Bias problems; Contrastive network; Deep learning; Generalized zero-shot learning; State of the art; Zero-shot learning | English | 2023 | 2023 | 10.1109/icce56470.2023.10043553 | 바로가기 | 바로가기 | 바로가기 | ||||||||||||||
| ○ | Book chapter | African legume, pulse, and oilseed-based fermented products | There is an increasing global consumer demand for functional foods due to the prevalence of non-communicable and chronic diseases. Such functional foods including fermented food products are of interest due to the presence of beneficial health constituents. In Africa, fermentation is one of the traditional food bioprocessing techniques employed to practically achieve adequate nutrition and food security. This chapter describes notable African fermented products derived from legumes, pulses, and oilseeds. Although numerous products exist, only few have been investigated. As such is the need for more studies into the nutritional, health-promoting, and microbiota of these plethora of fermented food products, as they are vital to the diet of the African populace and of economic importance. The nutritional composition, health-promoting properties, and microbiota of these fermented foods are discussed. © 2023 Elsevier Inc. All rights reserved. | Chinma, Chiemela Enyinnaya; Ezeocha, Vanessa Chinelo; Adedeji, Olajide Emmanuel; Inyang, Comfort Ufot; Enujiugha, Victor Ndigwe; Adebo, Oluwafemi Ayodeji | Department of Food Science and Technology, Federal University of Technology, Minna, Nigeria, Department of Biotechnology and Food Technology, Faculty of Science, University of Johannesburg, Gauteng, South Africa; Department of Food Science and Technology, Michael Okpara University of Agriculture, Abia State, Umudike, Nigeria; Department of Food Science and Technology, Federal University Wukari, Wukari, Nigeria, School of Food Science and Biotechnology, Kyungpook National University, Daegu, South Korea; Department of Microbiology, University of Uyo, Uyo, Nigeria; Department of Food Science and Technology, Federal University of Technology Akure, Akure, Nigeria; Food Innovation Research Group, Department of Biotechnology and Food Technology, Faculty of Science, University of Johannesburg, Gauteng, South Africa | 16038622800; 57916404800; 57202229091; 56271857300; 6507612391; 56725372400 | chinmachiemela@futminna.edu.ng; | Indigenous Fermented Foods for the Tropics | 6.86 | 2025-06-25 | 4 | health properties; Indigenous fermented foods; legumes; microbiota; nutritional composition | English | Final | 2023 | 10.1016/b978-0-323-98341-9.00012-8 | 바로가기 | 바로가기 | |||||||||||||||||||
| ○ | Conference paper | Age-of-Information Aware Intelligent MAC for Congestion Control in NR-V2X | The third-generation partnership project (3GPP) introduces the 5G NR-V2X to supplement the C-V2X to support advanced applications. 3GPP defines the semi-persistent scheduling for distributed resource scheduling likewise in C-V2X, however new medium access control (MAC) features are introduced in NR-V2X mode 2. Re-evaluation mechanism is added in semi-persistent scheduling to reduce resource contention. Despite with new MAC feature, NR-V2X mode 2 cannot handle the scheduling of aperiodic packets efficiently. With the increase in vehicular density, channel congestion occurs leading to packet collision. 3GPP defines the channel congestion control mechanism based on two metrics; channel busy ratio (CBR) and channel occupancy ratio (CR). These metrics, however, have considered the system-level requirements but ignore the application-level requirements such as age-of-information (AoI) associated with the message packet. In this paper, we proposed a deep reinforcement learning-based congestion control mechanism to support both system and application requirements. The performance of the proposed scheme is evaluated and compared with the conventional decentralized congestion control mechanism in a simulator designed inline with the 3GPP specifications. © 2023 IEEE. | Saad, Malik Muhammad; Tariq, Muhammad Ashar; Seo, Junho; Ajmal, Mahnoor; Kim, Dongkyun | Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea; Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea; Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea; Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea; Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea | 57220715290; 57219865336; 57208740581; 57238144300; 35753648800 | maliksaad@knu.ac.kr; | International Conference on Ubiquitous and Future Networks, ICUFN | 2165-8528 | 2023-July | 2.98 | 2025-06-25 | 6 | Age-of-Information; Congestion Control; MAC; NR-V2X; Semi-peristent Scheduling | 5G mobile communication systems; Deep learning; Reinforcement learning; Vehicle to Everything; Age-of-information; Congestion control; Congestion control mechanism; Control features; Information-aware; Intelligent medium access controls; New media; NR-V2X; Semi-peristent scheduling; Third generation partnership project (3GPP); Medium access control | English | Final | 2023 | 10.1109/icufn57995.2023.10200859 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Conference paper | Airy YOLOv5 for Disabled Sign Detection | Designated parking spaces for individuals with disabilities are only meant to be used by vehicles with proper handicapped signage. Real-time monitoring is necessary to ensure that only authorized vehicles are parked in these spaces and to prevent unauthorized vehicles from using them. First, this research proposes to replace the backbone of a baseline YOLOv5 model which has 9 blocks with 6 EfficientNet blocks with less parameters but still have a higher accuracy in detecting disabled signs among other signages on the windshield of cars. Second, to compensate for the loss of blocks we have included an attention mechanism before detection part in our architecture which allows us to focus on the important regions needed for the task. Additionally, we propose to use a better optimizer AdamW to prevent overfitting. Based on these improvements, we have created a new object detector named Airy YOLOv5. To evaluate the effectiveness of our proposed method, a dataset containing images of cars with disabled signage on their windshields will be gathered and labeled. Experiments using this dataset show that our model achieves a better F1 score of 0.67 with 5 percent less parameters compared to the baseline model. © 2023 IEEE. | Rakhmonov, Akhrorjon Akhmadjon Ugli; Subramanian, Barathi; Kim, Taehun; Kim, Jeonghong | Kyungpook National University, Computer Science and Engineering Department, Daegu, South Korea; Kyungpook National University, Computer Science and Engineering Department, Daegu, South Korea; Dipvision, Daegu, South Korea; Kyungpook National University, Computer Science and Engineering Department, Daegu, South Korea | 58482208000; 57221053219; 55696523100; 55138548100 | r.akhror@knu.ac.kr; | International Conference on Ubiquitous and Future Networks, ICUFN | 2165-8528 | 2023-July | 0.5 | 2025-06-25 | 1 | depthwise separable convolution; disabled signage; small object detection; supervised learning | Machine learning; Object recognition; Traffic signs; Windshields; Attention mechanisms; Depthwise separable convolution; Disabled signage; High-accuracy; Optimizers; Overfitting; Parking spaces; Real time monitoring; Sign detection; Small object detection; Object detection | English | Final | 2023 | 10.1109/icufn57995.2023.10200853 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | ○ | Article | Alleviation of Hg-, Cr-, Cu-, and Zn-Induced Heavy Metals Stress by Exogenous Sodium Nitroprusside in Rice Plants | The cultivation of rice is widespread worldwide, but its growth and productivity are hampered by heavy metals stress. However, sodium nitroprusside (SNP), a nitric oxide donor, has been found to be effective for imparting heavy metals stress tolerance to plants. Therefore, the current study evaluated the role of exogenously applied SNP in improving plant growth and development under Hg, Cr, Cu, and Zn stress. For this purpose, heavy metals stress was induced via the application of 1 mM mercury (Hg), chromium (Cr), copper (Cu), and zinc (Zn). To reverse the toxic effects of heavy metals stress, 0.1 mM SNP was administrated via the root zone. The results revealed that the said heavy metals significantly reduced the chlorophyll contents (SPAD), chlorophyll a and b, and protein contents. However, SNP treatment significantly reduced the toxic effects of the said heavy metals on chlorophyll (SPAD), chlorophyll a and b, and protein contents. In addition, the results also revealed that heavy metals significantly increased the production of superoxide anion (SOA), hydrogen peroxide (H2O2), malondialdehyde (MDA), and electrolyte leakage (EL). However, SNP administration significantly reduced the production of SOA, H2O2, MDA, and EL in response to the said heavy metals. Furthermore, to cope with the said heavy metals stress, SNP administration significantly enhanced the activities of superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), and polyphenol peroxidase (PPO). Furthermore, in response to the said heavy metals, SNP application also upregulated the transcript accumulation of OsPCS1, OsPCS2, OsMTP1, OsMTP5, OsMT-I-1a, and OsMT-I-1b. Therefore, SNP can be used as a regulator to improve the heavy metals tolerance of rice in heavy-metals-affected areas. | Niyoifasha, Chrizostom Julius; Borena, Birhanu Miressa; Ukob, Irasapa Tanimu; Minh, Phan Ngoc; Al Azzawi, Tiba Nazar Ibrahim; Imran, Muhammad; Ali, Sajid; Inthavong, Anousone; Mun, Bong-Gyu; Lee, In-Jung; Khan, Murtaza; Yun, Byung-Wook | Kyungpook Natl Univ, Dept Appl Biosci, Daegu 41566, South Korea; Rural Dev Adm, Natl Inst Agr Sci, Biosafety Div, Jeonju 55365, South Korea; Yeungnam Univ, Dept Hort & Life Sci, Gyongsan 38541, South Korea | ; Imran, Muhammad/AFL-6590-2022; Ali, Sajid/GLS-7322-2022; Mun, BongGyu/GYD-6010-2022; Lee, In-Jung/GLS-0432-2022 | 57203863723; 58185950600; 58185950700; 58186611600; 57224980187; 58282433800; 57214290889; 58185619300; 57147241300; 16425830900; 57207990116; 8245123600 | murtazakhan@yu.ac.kr;bwyun@knu.ac.kr; | PLANTS-BASEL | 2223-7747 | 12 | 6 | 4.51 | 2025-06-25 | 24 | 25 | sodium nitroprusside; radical oxygen species; gene expression; rice; heavy metals stress | MOLECULAR-MECHANISMS; NITRIC-OXIDE; TOXICITY; ACID | gene expression; heavy metals stress; radical oxygen species; rice; sodium nitroprusside | English | 2023 | 2023-03 | 10.3390/plants12061299 | 바로가기 | 바로가기 | 바로가기 | ||||||||||
| ○ | Conference paper | Ambient Sound Analysis for Non-Invasive Indoor Activity Detection in Edge Computing Environments | Research on detecting the behavior of residents using sounds generated in living spaces has been conducted by sending the sound data to a server or cloud and utilizing a relatively large artificial intelligence model. However, this method generates excessive data traffic and carries a privacy risk by transmitting sounds unnecessary for behavior detection. In this paper, we explored data processing methods suitable for a non-invasive indoor noisy sound analysis system operating in an edge environment. To achieve this goal, we implemented Mel-spectrogram and Mel-Frequency Cepstral Coefficients (MFCC) based models for classifying environmental sounds, comparing their performance based on different preprocessing parameters and optimizations. Furthermore, we evaluated the computational resource usage and performance of the models in both the Raspberry Pi and microcontroller environments. © 2023 IEEE. | Lee, Cheolhwan; Kang, Ho-Min; Jeon, Yeongjun; Kang, Soon Ju | School of Electronic and Eletrical Engineering, Kyungpook National University, Daegu, South Korea; School of Electronic and Eletrical Engineering, Kyungpook National University, Daegu, South Korea; School of Electronic and Eletrical Engineering, Kyungpook National University, Daegu, South Korea; School of Electronic and Eletrical Engineering, Kyungpook National University, Daegu, South Korea | 57216824872; 57952244800; 57208863636; 55666313900 | Proceedings - IEEE Symposium on Computers and Communications | 1530-1346 | 2023-July | 1.37 | 2025-06-25 | 3 | Ambient sound analysis; Edge computing; Indoor activity detection; Non-invasive sound analysis | Data handling; Activity detection; Ambient sound analyse; Ambient sounds; Computing environments; Edge computing; Indoor activities; Indoor activity detection; Non-invasive sound analyse; Sound analysis; Edge computing | English | Final | 2023 | 10.1109/iscc58397.2023.10217851 | 바로가기 | 바로가기 | |||||||||||||||||
| ○ | ○ | Article | An Analysis of Intrusive Morbid Imagery in Rorschach Responses The Cases of Traumatized First Responders in Korea | First responders are generally a high-risk group, repeatedly exposed to traumatic and distressing scenes and events on their daily duties. Identification of detailed features and recurring patterns of intrusive visual imagery for first responders with posttraumatic stress disorder (PTSD) can uncover the psychological difficulties, defenses, and further adjustment issues of occupational groups exposed to repetitive trauma. To this end, 20 Rorschach protocols for Korean first responders with PTSD symptoms were collected and analyzed. The analysis of the Rorschach records was twofold. First, the structural features of the Rorschach responses, including R and the Trauma Content Index, were examined quantitatively. Second, the detailed features of the morbid content, such as thematic classification, trauma memory responses, and emotional reactions, were qualitatively reviewed. Both analyses identified a biphasic pattern between constricted and flooded responses, showing the participants' unsuccessful endeavors to defend against intrusive trauma-related imagery, which resulted in significant disorganization in thought and affect. | Hwang, Chang Ui; Kim, Eun Young; Lee, Hae Joon; Park, Min Ju; Lee, Mi Sun; Kim, Tae Hwan; Kim, Ju Kyeong | Kyungpook Natl Univ, Dept Educ, Daegu, South Korea | ; Lee, Mi-Sun/O-3944-2016; Kim, Tae-Hwan/M-3962-2017 | 58144936400; 57689003300; 58144734200; 58144936500; 58144734300; 58145540800; 58144734400 | hyunhuk@knu.ac.kr; | RORSCHACHIANA | 1192-5604 | 2151-206X | 44 | 1 | 1.29 | 2025-06-25 | 8 | 6 | trauma-related imagery; Rorschach Test; TCI; morbid content; biphasic patterns; first responders | POSTTRAUMATIC-STRESS; CONTENT INDEX; SEXUAL-ABUSE; FIREFIGHTERS; PTSD; TURNOVER; CHILDREN | biphasic patterns; first responders; morbid content; Rorschach Test; TCI; trauma-related imagery | English | 2023 | 2023-03-15 | 10.1027/1192-5604/a000164 | 바로가기 | 바로가기 | 바로가기 |
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