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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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| ○ | ○ | Proceedings Paper | Deep Learning based Human Detection using Thermal-RGB Data Fusion for Safe Automotive Guided-Driving | Every year, the number of drivers increases, resulting in a corresponding increase in traffic fatalities. In Korea, pedestrian accidents constituted 35.5% of all traffic accidents for the last 2 years, with the number of child accidents rising annually. Autonomous vehicles currently rely on a lidar, which is insufficient in preventing accidents as it only recognizes obstacles that are far away. To mitigate these accidents, we propose selective thermal imaging data to identify people beyond the limited field of view. First, RGB camera image data for object recognition is performed. When vehicles or obstacles are present, the optional use of thermal data is applied. Thermal data can only identify a person, and it is used to prevent unforeseen incidents. The RGB images are divided into thirds and each section is assessed for obstacles, prioritizing the area with the most obstacles for integration with thermal data. Using the described algorithm, the level of accuracy increased by 2.07 times, from 40.43% to 83.91%. Additionally, experiments performed on a personal computer demonstrate that the algorithm is capable of functioning in real-time at a rate of 2.7 frames per second, utilizing 175.95 megabytes of memory at 0.36 seconds per image. When executed on a lightweight board such as the Jetson Nano, the algorithm runs at a rate of 0.75 frames per second, utilizing 140.08 megabytes of memory, at 1.33 seconds per image. | Heuijee, Yun; Park, Daejin | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea | 58966829000; 55463943600 | boltanut@knu.ac.kr; | 2024 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS WORKSHOPS AND OTHER AFFILIATED EVENTS, PERCOM WORKSHOPS | 2836-5348 | 3.06 | 2025-04-16 | 1 | 1 | Deep Learning; Thermal data; RGB image data; ADAS(Advanced Driver Assistance System) | ADAS(Advanced Driver Assistance System); Deep Learning; RGB image data; Thermal data | Accidents; Automobile drivers; Deep learning; Infrared imaging; Learning systems; Object detection; Object recognition; Personal computers; Automotives; Deep learning; Frames per seconds; Human detection; Image data; RGB image data; RGB images; Thermal; Thermal data; Traffic fatalities; Advanced driver assistance systems | English | 2024 | 2024 | 10.1109/percomworkshops59983.2024.10503400 | 바로가기 | 바로가기 | 바로가기 | |||||||||||||
| ○ | Proceedings Paper | Deep Learning-Based Calibration Method for An Augmented Reality Surgical Navigation System without Head-mounted Optical Markers | 2D medical visualization techniques often fall short in adequately representing complex 3D anatomical structures. 2D surgical navigation lacks depth information, which is a significant drawback. Additionally, displaying medical data on a 2D screen during surgery is suboptimal because it necessitates the surgeon to constantly shift their focus. Augmented Reality (AR) compensates for the significant drawback of 2D surgical navigation, which lacks depth information. AR is a technology that overlays computer-generated information onto the real world, providing users with an enhanced visual experience. By integrating digital information with the physical environment in real-time, AR offers more intuitive and useful information. Currently, research on surgical navigation using AR is actively progressing. This innovative technology is being explored and developed to enhance the precision, efficiency, and safety of surgical procedures. In this paper, we utilize a snapshot from the built-in forward camera of the OST-HMDs, capturing both virtual points and real marker balls, to automatically calculate the transformation matrix between the virtual and real world. This method requires precise positions of both the virtual points and the real markers to successfully overlay anatomical information onto the real world. we use the YOLOv8 model and Virtual Aruco Marker to precisely determine the positions of both real and virtual points, and to automatically identify their points, ensuring an enhanced AR Navigation System. | Kim, Seong Kyeong; Kim, Min Young | Kyungpook Natl Univ, Dept Elect & Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Res Ctr Neurosurg Robot Syst, Daegu 41566, South Korea | tjdrud9915@knu.ac.kr;minykim@knu.ac.kr; | 2024 24TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS, ICCAS 2024 | 2093-7121 | 0 | Yolov8; Aruco Marker; Augmented Reality | English | 2024 | 2024 | 바로가기 | |||||||||||||||||||||||
| ○ | Conference paper | Deep Learning-Based Calibration Method for An Augmented Reality Surgical Navigation System without Head-mounted Optical Markers | 2D medical visualization techniques often fall short in adequately representing complex 3D anatomical structures. 2D surgical navigation lacks depth information, which is a significant drawback. Additionally, displaying medical data on a 2D screen during surgery is suboptimal because it necessitates the surgeon to constantly shift their focus. Augmented Reality (AR) compensates for the significant drawback of 2D surgical navigation, which lacks depth information. AR is a technology that overlays computer-generated information onto the real world, providing users with an enhanced visual experience. By integrating digital information with the physical environment in real-time, AR offers more intuitive and useful information. Currently, research on surgical navigation using AR is actively progressing. This innovative technology is being explored and developed to enhance the precision, efficiency, and safety of surgical procedures. In this paper, we utilize a snapshot from the built-in forward camera of the OST-HMDs, capturing both virtual points and real marker balls, to automatically calculate the transformation matrix between the virtual and real world. This method requires precise positions of both the virtual points and the real markers to successfully overlay anatomical information onto the real world. we use the YOLOv8 model and Virtual Aruco Marker to precisely determine the positions of both real and virtual points, and to automatically identify their points, ensuring an enhanced AR Navigation System. © 2024 ICROS. | Kim, Seong Kyeong; Kim, Min Young | Kyungpook National University, Department of Electronic and Electrical Engineering, Daegu, 41566, South Korea; Kyungpook National University, Department of Electronic and Electrical Engineering, Daegu, 41566, South Korea, Kyungpook National University, Research Center for Neurosurgical Robotic System, Daegu, 41566, South Korea | 59504421000; 56739349100 | minykim@knu.ac.kr; | International Conference on Control, Automation and Systems | 1598-7833 | 0 | 2025-05-07 | 0 | Aruco Marker; Augmented Reality; Yolov8 | Electrotherapeutics; Helmet mounted displays; Metadata; Transplantation (surgical); Virtual environments; Aruco marker; Calibration method; Depth information; Medical visualization; Optical markers; Real-world; Surgical navigation; Surgical navigation systems; Virtual points; Yolov8; Augmented reality | English | Final | 2024 | 10.23919/iccas63016.2024.10773365 | 바로가기 | 바로가기 | |||||||||||||||||
| ○ | Conference paper | Deep Learning-Based Metasurface Design Platform with Self-Data Generation | Design parameters of metasurfaces representing the desired color were extracted through a deep learning based design platform. In addition, design accuracy was increased with self-generated data during the validation process. © 2024 The Author(s) | Jeong, Ki Won; Do, Yun Seon | School of Electronic and Electrical Engineering, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu, South Korea | 58672002300; 24338060500 | yuns.do@knu.ac.kr; | Conference on Lasers and Electro-Optics/Pacific Rim, CLEO-PR 2024 in Proceedings 2024 Conference on Lasers and Electro-Optics Pacific Rim (CLEO-PR) | 0 | 2025-05-07 | 0 | Data generation; Design parameters; Design platform; Metasurface; Validation process | English | Final | 2024 | 바로가기 | |||||||||||||||||||||
| ○ | Conference paper | Deep Learning-Based Metasurface Design Platform with Self-Data Generation | Design parameters of metasurfaces representing the desired color were extracted through a deep learning based design platform. In addition, design accuracy was increased with self-generated data during the validation process. © 2024 IEEE. | Jeong, Ki Won; Do, Yun Seon | School of Electronic and Electrical Engineering, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu, South Korea; School of Electronic and Electrical Engineering, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu, South Korea | 58672002300; 24338060500 | yuns.do@knu.ac.kr; | 16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024 | 0 | 2025-05-07 | 0 | Data generation; Design parameters; Design platform; Metasurface; Validation process | English | Final | 2024 | 10.1109/cleo-pr60912.2024.10676933 | 바로가기 | 바로가기 | |||||||||||||||||||
| ○ | Conference paper | Deep Learning-Based QoS Prediction for Optimization of Robotic Communication | The robustness of quality of service (QoS) in robotic communications is essential for operational efficiency and reliability. This paper presents an innovative deep learningbased methodology specifically designed for QoS prediction in robotic networks. A predictive model was developed by extensively analyzing communication data, including aspects such as latency and bandwidth, along with environmental factors. This model accurately predicts important QoS parameters. The results show a significant improvement in QoS prediction accuracy and overall network performance over traditional machine learning methods. The implications of this study are important for the development of autonomous robot operations and provide scalable and efficient solutions for realtime communication coordination that are pivotal to managing the complexity of adaptive robot systems. © 2024 IEEE. | Kim, Tae Hyun; Lee, Jong Hyuk; Lee, Jin Hyuk; Kim, Min Young | Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea; Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea; Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea; Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea | 58978891300; 57208132362; 58072935700; 56739349100 | 6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024 | 0 | 2025-04-16 | 1 | adaptive systems; Attention; autonomous robots; CNN; GNN; LSTM; predictive modeling; QoS; robotic communication | Forecasting; Learning systems; Long short-term memory; Robots; Attention; Efficiency and reliability; GNN; LSTM; Operational efficiencies; Operational reliability; Optimisations; Predictive models; Quality-of-service; Robotic communication; Quality of service | English | Final | 2024 | 10.1109/icaiic60209.2024.10463315 | 바로가기 | 바로가기 | |||||||||||||||||||
| ○ | Conference paper | Deep Neural Network NMPC for Computationally Tractable Optimal Power Management of Hybrid Electric Vehicles | This study presents a method for deep neural network nonlinear model predictive control (DNN-MPC) to reduce computational complexity, and we show its practical utility through its application in optimizing the energy management of hybrid electric vehicles (HEVs). For optimal power management of HEVs, we first design the online NMPC to collect the data set, and the deep neural network is trained to approximate the NMPC solutions. We assess the effectiveness of our approach by conducting comparative simulations with rule and online NMPC-based power management strategies for HEV, evaluating both fuel consumption and computational complexity. Lastly, we verify the real-time feasibility of our approach through process-in-the-loop (PIL) testing. The test results demonstrate that the proposed method closely approximates the NMPC performance while substantially reducing the computational burden. © 2024 AACC. | Park, Suyong; Nguyen, Duc Giap; Park, Jinrak; Kim, Dohee; Eo, Jeong Soo; Han, Kyoungseok | University of Kyungpook National, Mechanical Engineering, Daegu, Buk-gu, 41566, South Korea; University of Kyungpook National, Mechanical Engineering, Daegu, Buk-gu, 41566, South Korea; Hyundai Motor Company, Namyang-eup, Hwaseong-si, 18278, South Korea; Hyundai Motor Company, Namyang-eup, Hwaseong-si, 18278, South Korea; Hyundai Motor Company, Namyang-eup, Hwaseong-si, 18278, South Korea; University of Kyungpook National, Mechanical Engineering, Daegu, Buk-gu, 41566, South Korea | 57560254700; 57221496576; 57202138375; 57198638320; 36650692500; 56465294700 | Proceedings of the American Control Conference | 0743-1619 | 0 | 2025-05-07 | 0 | Deep neural network; Energy management; Hybrid electric vehicle; Model predictive control; Process-in-the-loop | Hybrid vehicles; Predictive control systems; Comparative simulation; Data set; Energy; First designs; ITS applications; Model-predictive control; Neural-networks; Nonlinear model predictive control; Optimal power; Process-in-the-loop; Hybrid power | English | Final | 2024 | 10.23919/acc60939.2024.10644283 | 바로가기 | 바로가기 | ||||||||||||||||||
| ○ | ○ | Proceedings Paper | Deep Reinforcement Learning-based Edge Discovery within the 3GPP Framework for C-ITS | With the evolution of edge computing, addressing challenges within the framework of the Third Generation Partnership Project (3GPP) standard has garnered attention. In particular, challenges such as edge discovery and relocation, session management function (SMF) selection, and edge lifecycle management pose significant hurdles in providing seamless services, especially in advanced Cooperative Intelligent Transportation Systems (C-ITS). This paper proposes an intelligent solution for edge discovery tailored to continuously provision C-ITS services to users within the 3GPP framework. Leveraging deep reinforcement learning (DRL), our proposed algorithm facilitates optimal edge discovery based on specific user requirements. We demonstrate the compatibility of our approach with 3GPP standard operations and address the critical challenge of edge discovery by employing an intelligent DRL-based methodology. | Saad, Malik Muhammad; Tariq, Muhammad Ashar; Ajmal, Mahnoor; Jeon, Donghyun; Kim, Jinhong; Lim, Kil-Taek; Baek, Jang Woon; Kim, Dongkyun | Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu, South Korea; Elect & Telecommun Res Inst, Daejeon, South Korea | Saad, Malik/ABF-9433-2021; Baek, JangWoon/ABE-2176-2020; 마, 누르아즈말/NRY-5736-2025 | 57220715290; 57219865336; 57238144300; 59308006000; 57195433331; 7403175725; 57219860188; 35753648800 | maliksaad@knu.ac.kr;tariqashar@knu.ac.kr;mahnoor.ajmal@knu.ac.kr;jdh0830@knu.ac.kr;jinhong@etri.re.kr;ktl@etri.re.kr;jwbaek98@etri.re.kr;dongkyun@knu.ac.kr; | 2024 FIFTEENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS, ICUFN 2024 | 2165-8528 | 2165-8536 | 0 | 2025-05-07 | 0 | 0 | Edge Computing; Edge Discovery; Cooperative Intelligent Transportation Systems (C-ITS) | Cooperative Intelligent Transportation Systems (C-ITS); Edge Computing; Edge Discovery | Reinforcement learning; 3GPP standard; Cooperative intelligent transportation system; Edge computing; Edge discovery; Intelligent transportation systems; Management functions; Reinforcement learnings; Seamless services; Session management; Third generation; Deep reinforcement learning | English | 2024 | 2024 | 10.1109/icufn61752.2024.10624860 | 바로가기 | 바로가기 | 바로가기 | |||||||||||
| ○ | Article | Deformed Zero-Sequence Flux Model of Open End Winding IPMSM; [권선 매입형 영구자석 동기전동기의 변형된 영상분 자속 모델] | This paper proposes a deformed zero-sequence flux model of open-end winding (OEW) Interior Permanent Magnet Synchronous Motor (IPMSM), which takes into account non-linearity and structural features of IPMSM. The flux and phase voltage of the IPMSM are investigated using finite element analysis (FEA). This analysis confirmed the existence of the zero sequence voltage (ZSV) that causes the zero sequence current (ZSC) when utilizing an OEW inverter. Additionally, the presence of coupled components between the zero-sequence and DQ axes due to the winding structure and core saturation is identified. The proposed model effectively expresses the properties of zero-sequence components in IPMSM. © The Korean Institute of Electrical Engineers. | Kim, Ji-Heon; Gu, Bon-Gwan; Lim, Jong-Kyong; Kim, Rae-Young | School of Energy Engineering, Kyungpook National University, Daegu, South Korea; School of Energy Engineering, Kyungpook National University, Daegu, South Korea; Dept. of Electrical Engineering, Hanyang University, South Korea; Dept. of Electrical Engineering, Hanyang University, South Korea | 59221545500; 50061273700; 57716104400; 7202933100 | bggu@knu.ac.kr; | Transactions of the Korean Institute of Electrical Engineers | 1975-8359 | 73 | 7 | 0 | 2025-05-07 | 0 | finite element analysis; flux model; IPMSM; Open-end winding (OEW); zero-sequence voltage | Permanent magnets; Synchronous motors; Winding; Finite element analyse; Flux modeling; Interior permanent magnet synchronous motor; Open-end winding; Open-end windings; Phase voltage; Structural feature; Zero sequence current; Zero sequence voltage; Zero sequences; Finite element method | Korean | Final | 2024 | 10.5370/kiee.2024.73.7.1162 | 바로가기 | 바로가기 | |||||||||||||||
| ○ | Proceedings Paper | Derivation and Analysis of New Small-Signal Model for Active Clamp Forward Converter | Active clamp forward converter (ACFC) is widely used for low-voltage and high-current applications. Despite its extensive usage, the open-loop power stage characteristics of the converter have not been fully investigated and require further analyses. This paper reveals that the power stage dynamics of ACFC are different from those of either other buck-derived isolated converters or forward converters with different reset schemes. This paper presents a new small-signal model of the ACFC and provides the factorized expressions of the power stage transfer functions, which carry the useful information on the control design and performance evaluation. The accuracy of the small-signal model and the validity of the factorized transfer functions are verified both SIMPLIS simulations and experimental measurements. | Lee, Dongheon; Kang, Yonghan; Choi, Byungcho; Cha, Honnyong | Kyungpook Natl Univ, Sch Energy Engn, Daegu, South Korea; Cisco Syst Inc, San Jose, CA USA; Kyungpook Natl Univ, Sch Elect Engn, Daegu, South Korea | 2024 IEEE APPLIED POWER ELECTRONICS CONFERENCE AND EXPOSITION, APEC | 1048-2334 | 0 | active clamp reset; forward converter; powerstage; transfer functions; small-signal modeling. | English | 2024 | 2024 | 10.1109/apec48139.2024.10509100 | 바로가기 | 바로가기 | ||||||||||||||||||||||
| ○ | Conference paper | Design and Implementation of a 5G Security Testbed Based on Zero Trust Architecture | This paper presents the design and implementation of a 5G security testbed based on Zero Trust Architecture (ZTA). As 5G networks offer ultra-high speeds, low latency, and massive connectivity, ensuring their security has become a critical challenge, especially with the distributed nature and numerous connected devices. Traditional perimeter-based security models are no longer sufficient. Therefore, Zero Trust Architecture, which continuously verifies and monitors all resources and users regardless of their location, has been proposed as a solution. In this study, we propose a comprehensive security management system by integrating ZTA into a 5G testbed, focusing on real-time monitoring and dynamic policy enforcement using data collected from the Access and Mobility Management Function (AMF) and User Plane Function (UPF). The testbed's effectiveness is demonstrated through the deployment of Nokia's network equipment, allowing the collection and analysis of high-resolution traffic data, which aids in early threat detection and response. The proposed system enhances 5G network security and offers significant potential for application across various industries. © 2024 IEEE. | Yoon, Mahnsuk; Seo, Jihun; Lee, Jonghoon; Cho, Keuchul | Future Mobile Communication Research Center, GERI(Gumi Electronics & Information Technology Research Institute), Gumi, South Korea; Center for Connected & Automated Driving Research, Korea Transport Institute, Department of The Fourth Industrial Revolution & Transport, Sejong, South Korea; ETRI(Electronics and Telecommunications Research Institute), Cyber Security Research Division, Daejeon, South Korea; School of Computer Secience and Engineering, Software Education Center, Kyungpook National University, Daegu, South Korea | 57203640624; 58000906600; 57195728430; 26031217700 | International Conference on ICT Convergence | 2162-1233 | 0 | 2025-05-07 | 0 | 5G Security; Dynamic Policy Enforcement; Real-time Monitoring; Zero Trust Architecture | Information management; Network security; Queueing networks; Security systems; Testbeds; 5g security; Critical challenges; Design and implementations; Dynamic policy enforcement; Low latency; Real time monitoring; Security management systems; Security modeling; Ultra high speed; Zero trust architecture; 5G mobile communication systems | English | Final | 2024 | 10.1109/ictc62082.2024.10826685 | 바로가기 | 바로가기 | ||||||||||||||||||
| ○ | Conference paper | Design and Implementation of a 5G Security Testbed for AI Solution Validation | The growing adoption of 5G private networks has significantly enhanced industries such as smart factories, autonomous vehicles, and smart homes, thanks to their high-speed data transmission, low latency, and support for large-scale device connectivity. These networks have driven advancements in real-time monitoring and process automation, boosting productivity and efficiency while reducing costs. However, the deployment of 5G private networks has also introduced various security challenges, particularly with the emergence of AI-driven technologies. This paper discusses these challenges, focusing on the design and implementation of a 5G security testbed to validate AI solutions within such environments. Key security threats associated with 5G private networks include the exploitation of AI and generative AI for sophisticated phishing and spoofing attacks, the hacking of autonomous vehicles and smart homes that can compromise both safety and privacy, and security breaches in AI-based smart factory systems, which could lead to operational disruptions and economic losses. These risks emphasize the need for proactive countermeasures to ensure the integrity and security of 5G private networks. This paper verifies the security of AI-based applications implemented through a testbed using Nokia's 5G network system and provides the necessary configurations for the stable deployment of AI-based service solutions. © 2024 IEEE. | Yoon, Mahnsuk; Kwon, Jaeuk; Seo, Jihun; Cho, Kyucheol | GERI(Gumi Electronics & Information Technology Research Institute), Future Mobile Communication Research Center, Gumi, South Korea; GERI(Gumi Electronics & Information Technology Research Institute), Future Mobile Communication Research Center, Gumi, South Korea; Korea Transport Institute, Center for Connected & Automated Driving Research, Department of The Fourth Industrial Revolution & Transport, Sejong, South Korea; School of Computer Secience and Engineering, Kyungpook National University, Software Education Center, Daegu, South Korea | 57203640624; 57991576500; 58000906600; 26031217700 | International Conference on ICT Convergence | 2162-1233 | 0 | 2025-05-07 | 0 | 5G Security; 5G Security testbed architecture; AI solution testbed | Cost reduction; Network security; Phishing; Smart manufacturing; Testbeds; 5g security; 5g security testbed architecture; AI solution testbed; Autonomous Vehicles; Design and implementations; High-speed data transmission; Large-scales; Low latency; Private networks; Smart homes; 5G mobile communication systems | English | Final | 2024 | 10.1109/ictc62082.2024.10827562 | 바로가기 | 바로가기 | ||||||||||||||||||
| ○ | Conference paper | Design of a Low-Cost Stochastic Computing-based Median Filter for Digital Image Processing | Stochastic computing (SC) is an approximate computation method that enables the design of low-cost and error-tolerant systems. The median filter (MF) is one of the widely used filters in image processing and is particularly effective in removing salt-and-pepper noise. In this paper, we propose an energy-efficient SC-based MF. The proposed SC-based MF increases hardware efficiency while maintaining performance quality by reducing the number of comparators. The proposed SC-based MF was implemented using Verilog HDL and synthesized using 65-nm CMOS technology. The proposed SC-based MF achieves up to 63.4% and 75.2% savings in area and power, respectively, compared to the binary implementation of MF. Furthermore, compared to the conventional SC-based MF, the proposed design improves by 13.2% and 10.2%, respectively. Despite a slight decrease in peak signal-to-noise ratio (PSNR), the proposed design exhibits excellent overall hardware performance. © 2024 IEEE. | Lee, Donghui; Kim, Yongtae | Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea; Kyungpook National University, School of Computer Science and Engineering, Daegu, South Korea | 57266466900; 55699627900 | yongtae@knu.ac.kr; | Proceedings - International SoC Design Conference 2024, ISOCC 2024 | 0 | 2025-05-07 | 1 | comparator; median filter; stochastic computing | Comparator circuits; Computer circuits; Wiener filtering; Approximate computation; Computation methods; Digital image; Energy efficient; Error-tolerant; Images processing; Low-costs; Median-Filter; Salt-and-pepper noise; Stochastic computing; Median filters | English | Final | 2024 | 10.1109/isocc62682.2024.10762709 | 바로가기 | 바로가기 | ||||||||||||||||||
| ○ | Conference paper | Design of an Efficient Parallel Random Number Generator Using a Single LFSR for Stochastic Computing | This paper proposes a parallel random number generator (RNG) using a single linear feedback shift register (LFSR) to generate two distinct random numbers, achieving twice the operational speed of a traditional serial RNG. The proposed RNG generates two distinct random numbers utilizing an LFSR. When implemented in a 65-nm CMOS technology, the proposed design leads to a 15.6% improvement in area and a 14.8 % improvement in power efficiency, addressing the trade-off between accuracy and energy efficiency in stochastic computing (SC). Furthermore, the proposed design not only matches but surpasses the performance of serial SC in an edge-detection digital image processing application. Therefore, for enhanced hardware efficiency and improved accuracy, the proposed parallel RNG architecture can be effectively employed. © 2024 IEEE. | Lee, Donghui; Seo, Hyoju; Kim, Yongtae | School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea; School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea; School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea | 57266466900; 57215662369; 55699627900 | yongtae@knu.ac.kr; | 6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024 | 0 | 2025-04-16 | 1 | linear feedback shift register (LFSR); parallel random num-ber generator (RNG); stochastic computing (SC) | Economic and social effects; Energy efficiency; Feedback; Number theory; Random number generation; Shift registers; Stochastic systems; 65 nm CMOS technologies; Design leds; Linear feedback shift register; Linear feedback shift registers; Parallel random num-ber generator; Parallel random number generator; Power-efficiency; Random Numbers; Stochastic computing; Image processing | English | Final | 2024 | 10.1109/icaiic60209.2024.10463230 | 바로가기 | 바로가기 | ||||||||||||||||||
| ○ | ○ | Proceedings Paper | Design of an Ultra-High-Speed Digital Interface Based on a Coplanar Stripline | A design for an ultra-high-speed digital interface, providing autonomous signal integrity improvement, is proposed. The proposed interface is on a coplanar stripline and verified to perform from DC to 30 GHz for 5G/6G communications. | Kim, Mun-Ju; Min, Byung-Cheol; Choi, Hyun-Chul; Kim, Kang-Wook | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea | 57478219300; 39161762500; 57193342681; 57204432422 | dranswn@knu.ac.kr;minbc4658@knu.ac.kr;hcchoi@ee.knu.ac.kr;kang_kim@ee.knu.ae.kr; | 2024 IEEE 33RD CONFERENCE ON ELECTRICAL PERFORMANCE OF ELECTRONIC PACKAGING AND SYSTEMS, EPEPS 2024 | 2165-4107 | 0 | 2025-05-07 | 0 | 0 | ultra-high-speed interface; vertical transition; ultra-high; speed digital transmission | ultra-high-speed digital transmission; ultra-high-speed interface; vertical transition | Coplanar striplines; Digital interfaces; High-speed digital transmission; High-speed interfaces; Signal Integrity; Ultra high speed; Ultra-high-speed digital transmission; Ultra-high-speed interface; Vertical transitions; 5G mobile communication systems | English | 2024 | 2024 | 10.1109/epeps61853.2024.10754372 | 바로가기 | 바로가기 | 바로가기 |
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