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Design of High Sensitivity Split Ring Resonator Sensor for Invasive Blood Glucose Monitoring

IFAC-PapersOnLine 2024年第24期58卷 303-308页

作者： Ameer B. Alsultani Omer S. Alkhafaf Ákos Szlávecz J. Geoffrey Chase Balázs Benyó Budapest University of Technology and Economics Faculty of Electrical Engineering and Information Technology Department of Control Engineering and Information Technology Budapest Hungary Department of Mechanical Engineering University of Canterbury Christchurch New Zealand Department of Communications Engineering University of Technology Iraq

Blood glucose level is one of the most frequently measured physiological parameters in clinical and home-care settings. This study aimed to develop a novel biosensor using a Split Ring Resonator (SRR) for measuring the glucose concentration of solutions like blood. In the simulation, changes in the solution's dielectric properties yielded a significant shift of the original, 6.8 GHz, resonance frequency when the SRR, constructed on a Rogers RO4003 substrate, was exposed to solutions with varying glucose concentrations. The frequency shift can indicate the solution's glucose levels, enabling the sensor to detect concentrations ranging from 20 mg/dL up to 200 mg/dL. The proposed method shows promise for invasive blood glucose monitoring with a sensitivity of 4.4 MHz per mg/dL and a straightforward structure design.

关键词： Biomedical sensors Blood Glucose Monitoring Microwave technology Split Ring Resonator

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Exploring the Use of Particle and Kalman Filters for Obstacle Detection in Mobile Robots

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2023年第4期67卷 384-393页

作者： Gyenes, Zoltán Bölöni, Ladislau Szádeczky-Kardoss, Emese Gincsainé Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Muegyetem rkp. 3. BudapestH-1111 Hungary Department of Computer Science University of Central Florida 4328 Scorpius St OrlandoFL32816-2362 United States

The present study aims to explore the adaptation of estimation methodologies, specifically Particle filters and Kalman filters, for the purpose of determining the position and velocity vector of obstacles within the operational workspace of mobile robots. These algorithms are commonly employed in the motion planning tasks of mobile robots for the estimation of their own position. The proposed methodology utilizes LiDAR sensor data to estimate the position vectors and calculate the velocity vectors of obstacles. Additionally, an uncertainty parameter can be determined using the introduced perception method. The performance of the newly adapted algorithms is evaluated through comparison of the absolute error in position and velocity vector estimations. © 2023 Budapest University of technology and Economics. All rights reserved.

关键词： Mobile robots

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Judgment of blast furnace iron-tapping status based on data differential processing and dynamic window analysis algorithm

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Progress in Natural Science:Materials International 2023年第4期33卷 450-457页

作者： Youcheng Zong Zixian Wang Xiang Liu Yi Nian Jianian Pan Chaojie Zhang Yingxue Wang Jianhua Chu Liqiang Zhang The Intelligent Metallurgy Research Institute School of Metallurgical Engineering Anhui University of Technology Department of Technical Quality Manufacturing Management Division(Technical Center) Anhui Changjiang Steel Co. Ltd. National Engineering Research Center for Public Safety Risk Perception and Control by Big Data(RPP) China Academic of Electronics and Information Technology

Ironmaking plants hold a core position in steel production. Efficient level detection and iron-tapping status judgment can accurately measure the liquid level and predict the amount of molten iron in the ladle, thereby ensuring production safety and improving production efficiency. At present, the judgment of the start and end statuses of blast furnace iron-tapping mainly relies on manual visual inspection. However, due to the high-temperature environment on-site and interference from iron powder, gunning mud, and other dust, operators find it challenging to make accurate judgments. To address these issues, this study proposes a robust and accurate method for judging the iron-tapping status of blast furnaces. This study collected four million on-site liquid level data, underwent interpolation, noise reduction, normalization, and other preprocessing steps, and then used differential processing to calculate the iron-tapping rate. Combined with dynamic window feature analysis, it effectively captured the change characteristics of the liquid level in the ladle under different iron-tapping *** simulated on-site experiments, the method achieved a 96.6 % accuracy rate for iron-tapping status *** real-time iron-tapping status judgment method based on differential processing of liquid level data and dynamic window feature analysis proposed in this study demonstrates high precision and robustness in the complex environment of ironmaking plants. This technology not only improves the production efficiency of the iron and steel link but also frees on-site operators from the harsh working environment, eliminating human errors in judgments and omissions, further promoting the intelligent process of ironmaking plants.

关键词： Blast furnace iron-tapping Molten iron level Radar level gauge Iron-tapping status judgment Data differential processing Sliding window

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Personalized Federated Learning with Kolmogorov-Arnold Enhanced CNN for Rotating Equipment Fault Diagnosis 21

Personalized Federated Learning with Kolmogorov-Arnold Enhan...

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21st International Computer Conference on Wavelet Active Media technology and information Processing, ICCWAMTIP 2024

作者： Kulevome, Delanyo Kwame Bensah Man, Qiu Mawuli, Ernest Smith Opoku-Mensah, Edward Qilu Institute of Technology Department of Computer and Information Engineering Shandong Jinan250200 China Qilu Institute of Technology Department of Intelligent Manufacturing and Control Engineering Shandong Jinan250200 China Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development Department of Electrical/Electronic Technology Education Kumasi Ghana HEC Department of Information Technologies Montréal Canada

ISBN: (纸本)9798331519254

Fault diagnosis of rotating equipment plays a crucial role in ensuring operational reliability and minimizing downtime in industrial systems. This study proposes a novel approach that integrates personalized federated learning (PFL) with a Kolmogorov-Arnold network (KAN)-enhanced convolutional neural network (CNN) to improve diagnostic accuracy across heterogeneous operational environments. The framework is designed to address variations in equipment conditions and data distributions, providing personalized models tailored to specific clients. A comprehensive evaluation is conducted using benchmark datasets, demonstrating significant improvements in fault classification accuracy, model interpretability, and training efficiency under non-IID data settings using the KAN-enhanced CNN model. This study contributes to advancing predictive maintenance practices, paving the way for resilient and intelligent industrial systems. © 2024 IEEE.

关键词： Federated learning

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A Novel Cutting Fluids Performance Assurance System for CNC Machine Tools

A Novel Cutting Fluids Performance Assurance System for CNC ...

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2024 International Automatic control Conference, CACS 2024

作者： Chou, You-Syuan Chen, Yi-Shiang Chiang, Fu-Yu Yang, Chen-Yen Shi, Zhe-Xun Lin, Yu-Sheng Lin, Shang-Chih Su, Shun-Feng Huang, Yennun Feng Chia University Institute of Automatic Control Engineering Taichung407 Taiwan Feng Chia University Department of Automatic Control Engineering Taichung407 Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei115 Taiwan

ISBN: (纸本)9798350354904

In the CNC machine tool industry, cutting fluid is a crucial component of the machining process. Nevertheless, as the duration of cutting fluid use increases, its performance progressively deteriorates, presenting a significant challenge that necessitates resolution. This study introduces an innovative intelligent monitoring system designed to optimize the preparation of cutting fluid in CNC machine tools. The aim is to extend the fluid's service life, mitigate tool wear, and address issues arising from fluid degradation. The system integrates a heating plate, sensors, pumping motors, and embedded systems to monitor and manage the cutting fluid effectively. Testing was conducted using a customdesigned container, and data analysis identified the optimal supply strategy, thereby extending the usable lifespan of the cutting fluid. This system enhances production longevity and allows for the configuration of containers with appropriate capacities based on specific requirements, ensuring consistent and high-quality production. © 2024 IEEE.

关键词： Cutting fluids

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Developing modified k–εturbulence models for neutral atmospheric boundary layer flow simulation using OpenFOAM

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Building Simulation 2024年第12期17卷 2281-2295页

作者： Yuanbo Wang Jiqin Li Wei Liu Jiankai Dong Jing Liu School of Architecture Harbin Institute of TechnologyKey Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and TechnologyMinistry of Industry and Information TechnologyHarbin 150090China Tianjin Key Laboratory of Indoor Air Environmental Quality Control School of Environmental Science and EngineeringTianjin University92 Weijin RoadTianjin 300072China Division of Sustainable Buildings Department of Civil and Architectural EngineeringKTH Royal Institute of TechnologyBrinellvägen 2310044 StockholmSweden

Accurate turbulence modeling is essential for simulation studies of urban *** this study,the comprehensive atmospheric boundary layer(ABL)model involving a variable model coefficient and an additional turbulent dissipation source term was implemented using the open-source software *** with consistent inlet wind profiles and rough wall functions of different turbulence variables based on the aerodynamic roughness,the model maintained the horizontal homogeneity ***,a hybrid approach was introduced to consider buildings immersed in ABL flows,enabling automatic transformation of the turbulence model between the region around the buildings and the free flow region away from any ***,the effects of applying different model forms to the airflow field around buildings were evaluated in detail through three-dimensional building cases representing six urban prototypes based on three wind tunnel *** findings indicated that all modified k–εmodels perform well in reproducing the flow data of the CEDVAL and Architectural Institute of Japan(AIJ)experiments consisting of a single building,an array of buildings,and an isolated high-rise ***,the modified k–εmodel with an additional correction term performed poorly in the database of Niigata Institute of technology and the case of complex terrain and urban building configurations,because the correction term inhibited the generation of turbulent kinetic *** addition,from the comparison between the experimental data of all cases,the model with the original formulation of the coefficient performed the best in terms of prediction *** root mean square errors of the normalized velocity were 0.1250,0.0879,0.1145,0.1350,and 0.1492 in different cases,which proved the reliability of this turbulence model.

关键词： urban airflow computational fluid dynamics(CFD) atmospheric boundary layer OpenFOAM turbulence model

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Optimization of Electrocardiogram Classification Using Dipper Throated Algorithm and Differential Evolution

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Computers, Materials & Continua 2023年第2期74卷 2379-2395页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Faten Khalid Karim Sameer Alshetewi Abdelhameed Ibrahim Abdelaziz A.Abdelhamid D.L.Elsheweikh Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt General Information Technology Department Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Specific EducationMansoura UniversityEgypt

Electrocardiogram(ECG)signal is a measure of the heart’s electrical ***,ECG detection and classification have benefited from the use of computer-aided systems by *** goal of this paper is to improve the accuracy of ECG classification by combining the Dipper Throated Optimization(DTO)and Differential Evolution Algorithm(DEA)into a unified algorithm to optimize the hyperparameters of neural network(NN)for boosting the ECG classification *** addition,we proposed a new feature selection method for selecting the significant feature that can improve the overall *** prove the superiority of the proposed approach,several experimentswere conducted to compare the results achieved by the proposed approach and other competing ***,statistical analysis is performed to study the significance and stability of the proposed approach using Wilcoxon and ANOVA *** results confirmed the superiority and effectiveness of the proposed *** classification accuracy achieved by the proposed approach is(99.98%).

关键词： Electrocardiogram differential evolution algorithm dipper throated optimization neural networks

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Feature Enhancement Method for Multimodal Nighttime Pedestrian Detection 7

Feature Enhancement Method for Multimodal Nighttime Pedestri...

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7th International Conference on Electrical, Mechanical and Computer engineering, ICEMCE 2023

作者： Wang, Yonggui Zhu, Zhongpan Li, Jian Wang, Zhipeng Chang, Qi He, Bin School of Electronic Information and Artificial Intelligence Shanxi University of Science & Technology Xi'an China College of Electronics and Information Engineering Tongji University Department of Control Science and Engineering Shanghai China

ISBN: (纸本)9798350382877

Nighttime Pedestrian Detection in Low-Light Conditions poses a challenging task, as previous processing methods often introduced noise and limited model generalization due to the low image quality in low-light conditions. This study presents a feature enhancement algorithm tailored for multimodal nighttime pedestrian detection, harnessing the advantages of infrared and visible light data. Our approach utilizes an adaptive weight fusion algorithm and a spatial detail module for multimodal fusion and spatial detail feature extraction, respectively, to accomplish the nighttime pedestrian detection task. Experimental results demonstrate that our method, compared to the baseline algorithm, achieves performance improvements of 3.3%, 11.9%, and 4.5% on the LLVIP dataset. © 2023 IEEE.

关键词： Feature extraction

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RRT Autonomous Detection Algorithm Based on Multiple Pilot Point Bias Strategy and Karto SLAM Algorithm

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Computers, Materials & Continua 2024年第2期78卷 2111-2136页

作者： Lieping Zhang Xiaoxu Shi Liu Tang Yilin Wang Jiansheng Peng Jianchu Zou Key Laboratory of Advanced Manufacturing and Automation Technology(Guilin University of Technology) Education Department of Guangxi Zhuang Autonomous RegionGuilin541006China College of Mechanical and Control Engineering Guilin University of TechnologyGuilin541006China Guilin Mingfu Robot Technology Company Limited Guilin541199China Key Laboratory of AI and Information Processing(Hechi University) Education Department of Guangxi Zhuang Autonomous RegionYizhou546300China

A Rapid-exploration Random Tree(RRT)autonomous detection algorithm based on the multi-guide-node deflection strategy and Karto Simultaneous Localization and Mapping(SLAM)algorithm was proposed to solve the problems of low efficiency of detecting frontier boundary points and drift distortion in the process of map building in the traditional RRT algorithm in the autonomous detection strategy of mobile ***,an RRT global frontier boundary point detection algorithm based on the multi-guide-node deflection strategy was put forward,which introduces the reference value of guide nodes’deflection probability into the random sampling function so that the global search tree can detect frontier boundary points towards the guide nodes according to random *** that,a new autonomous detection algorithm for mobile robots was proposed by combining the graph optimization-based Karto SLAM algorithm with the previously improved RRT *** algorithm simulation platform based on the Gazebo platform was *** simulation results show that compared with the traditional RRT algorithm,the proposed RRT autonomous detection algorithm can effectively reduce the time of autonomous detection,plan the length of detection trajectory under the condition of high average detection coverage,and complete the task of autonomous detection mapping more ***,with the help of the ROS-based mobile robot experimental platform,the performance of the proposed algorithm was verified in the real environment of different *** experimental results show that in the actual environment of simple and complex obstacles,the proposed RRT autonomous detection algorithm was superior to the traditional RRT autonomous detection algorithm in the time of detection,length of detection trajectory,and average coverage,thus improving the efficiency and accuracy of autonomous detection.

关键词： Autonomous detection RRT algorithm mobile robot ROS Karto SLAM algorithm

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Accounting for Non-Uniform Ambient Lighting in Ray Traced Ambient Occlusion

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2022年第3期66卷 248-252页

作者： Fridvalszky, András Tóth, Balázs Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Muegyetem rkp. 3. BudapestH-1111 Hungary

Ambient occlusion is a popular method to enhance the visuals of real-time applications. The generally accepted equation assumes that incoming ambient lighting is uniform in the enclosing hemisphere around the surface point. This assumption does not always hold and can cause artifacts. With screen-space techniques the artifact may not be present, because of the lack of information, but it becomes visible with more accurate methods. This is especially true for ray tracing based implementations which are widely used to create the ground truth image to measure other techniques. With recent advancements of the graphics hardware, they also found their way into real-time applications where these shortcomings were neither discussed nor addressed. In this paper we analyze the problem and demonstrate its presence in popular game engines. We also propose a ray tracing based extension to eliminate these artifact in a physically plausible way. © 2022 Budapest University of technology and Economics. All rights reserved.

关键词： Ray tracing

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