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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Henrique Seidel Morgana da Rosa Rodrigo Lopes Eduardo da Costa Rafael Soares Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

We present an energy-efficient implementation of the level-2 Pruned Discrete Haar Wavelet Transform (PDHWT-2) for R-peak detection in ECG signals. Approximate computing techniques were employed, including five well-established approximate adders (AxPPA, COPY, ETA-I, LOA, and Trunc) and bit truncation (T), to reduce energy consumption while maintaining accuracy above 99% for reliable R-peak detection. By focusing on the second-level detail coefficient $(D_{2})$ for peak detection and pruning the approximation coefficient, the PDHWT-2 design achieves significant reductions in computational complexity. The architecture, evaluated with ECG signals from the MIT-BIH database, maintained accuracy above 99% even with aggressive bit truncation and approximation, ensuring reliable medical-grade analysis. Integration of approximate adders (AxAs) and truncation enabled significant power and area savings. Specifically, the use of the AxPPA demonstrated power savings of up to 40% with area reductions of around 45%, making the PDHWT-2 a highly efficient solution for low-power ECG monitoring systems.

关键词： Accuracy Approximate computing Transforms Computer architecture Electrocardiography Energy efficiency Discrete wavelet transforms Reliability Adders Monitoring

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Neural fractional order PID controller embedded in an 8-bit microcontroller for neonatal incubator

Neural fractional order PID controller embedded in an 8-bit ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Igor R. Sousa Guilherme A. Barreto Graduate Program on Teleinformatics Engineering Federal University of Ceara Fortaleza Ceará

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

In this work, a fractional order PID controller for temperature of a neonatal incubator is implemented through a neural network in an embedded system with an 8-bit microcontroller. Using real data from a retrofitted commercial incubator, the plant transfer function is obtained, achieving RMSE = 0.0598. The fractional order PID controller parameters were obtained through particle swarm optimization metaheuristics using the Grunwald–Letnikov definition to calculate the control system fractional derivatives and integrals. The multilayer perceptron neural network is used in order to mitigate the loss of optimality that occurs in discretization methods of fractional order PID controllers, since they are infinite order filters. The neural fractional order PID controller in a simulated environment achieved RMSE = 0.0660 and was compared to the Merrikh-Bayat discretization technique, which obtained RMSE = 0.6578. The neural controller, with only 4 neurons in the hidden layer, was embedded in an 8-bit microcontroller to control the system, requiring only 6.511 ms to execute the MLP, occupying 1556 bytes of program memory and 241 bytes of RAM.

关键词： Pediatrics Filters Embedded systems Microcontrollers Neurons Memory management Random access memory

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Exploring Approximate Adders for Accuracy- and Energy-Quality VLSI Watermarking Systems Design

Exploring Approximate Adders for Accuracy- and Energy-Qualit...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Morgana da Rosa Eduardo da Costa Rafael Soares Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

Approximate computing (AxC) has emerged as a viable alternative to enhance computational efficiency by leveraging the intrinsic error resilience of many applications. One of the leading strategies of AxC involves exploring different approximation adder (AxA) configurations as a viable form of reducing power consumption in many applications. This work explores the use of AxAs in a hybrid watermarking technique that combines discrete Haar-Wavelet (DHWT) and discrete cosine transforms (DCT). The proposed hybrid method, HyDHWCT, integrates these transforms to improve robustness and imperceptibility in watermarking systems while optimizing for energy efficiency. We evaluate the performance of various AxAs, including Copy, ETA, LOA, Truncation (Trunc), VLSPPAs, and the AxPPA, regarding energy consumption, circuit area, and error resilience. Our results demonstrate that the AxPPA-based HyDHWCT offers superior accuracy and energy-quality trade-offs over other state-of-the-art AxAs. Specifically, the AxPPA on HyDHWCT with K = 1 achieves up to 72.85% energy savings and 88.32% area savings compared to the exact HyDHWCT while maintaining high accuracy, with a normalized cross-correlation (NC) of 0.9949 and a structural similarity (SSIM) of 0.9920 for the extracted watermark. These results make the AxPPA-based HyDHWCT a highly effective solution for robust and energy-efficient watermarking systems.

关键词： Energy consumption Accuracy Energy conservation Watermarking DH-HEMTs Energy efficiency Robustness Discrete cosine transforms Adders Resilience

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Classification of Human Tactile Perception Using Vibration Data 23

Classification of Human Tactile Perception Using Vibration D...

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23rd International Conference on Cyberworlds, CW 2024

作者： Lee, Hyung-Tak Bak, Keungyonh Chun, Sungwoo Hwang, Han-Jeong Korea University Dept. Electronics and Information Engineering Sejong Korea Republic of Korea University Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Sejong Korea Republic of

ISBN: (纸本)9798331527174

To enhance the sense of reality in the VR environment, it is essential to incorporate not only visual and hearing but also tactile feedback. Previous studies related to tactile sensation have only focused on object classification to identify the object in contact with the tactile sensor. When people encounter a new object, they can use tactile perception information, such as roughness, to understand the object's attributes and functions. Therefore, for tactile research to be applicable in real-life scenarios, tactile perception classification is essential not only for classifying an object but also for recognizing its attributes and functions. This study aims to investigate the possibility of predicting roughness, one of the important human tactile perceptions, using deep learning models. We created 63 tactile samples, measured the vibration data of each sample using an acceleration sensor, and investigated how humans perceive the roughness of the tactile samples with five different levels. Object classification was performed using five deep learning models, among which the Shallow ConvNet achieved the highest performance, confirming its suitability as the most appropriate model for analyzing vibration data. Using the Shallow ConvNet, we attained a high accuracy of 98.6 ±5.6% for the identification of five levels of roughness, demonstrating that different levels of tactile perception information can be discriminated with high performance. © 2024 IEEE.

关键词： Deep learning Human tactile perception Roughness Vibration data Virtual reality

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Balancing Dual DC Voltage Control in Quasi Single-Stage Converter for Low-Voltage Energy Storage System Grid-Connected 20

Balancing Dual DC Voltage Control in Quasi Single-Stage Conv...

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20th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2023

作者： Manokum, Warissara Kumsuwan, Yuttana Faculty of Engineering Chiang Mai University Graduate Program in Electrical Engineering Department of Electrical Engineering Chiang Mai Thailand Provincial Electricity Authority Bangkok Thailand Chiang Mai University Faculty of Engineering Department of Electrical Engineering Chiang Mai Thailand

ISBN: (纸本)9798350310467

The aim of a bidirectional quasi single-stage converter (QSSC) for low-voltage energy storage systems that are grid-connected is to reduce the power conversion stage of the dc-dc converter, which results in improved overall efficiency. The QSSC configuration relies on a modified modulation strategy due to the unequal dual dc port (upper and lower dc ports) voltage. The control for ensuring that the dual dc port voltages are equal is presented in this paper. When the lower dc port is varied in response to battery voltage, another is controlled to track in response to the lower dc port, so that the voltage ratio between the upper and lower dc port is always equal to one. Furthermore, power sharing in a dual dc port is equal, which means that a dc-dc converter automatically operates at 50% of the battery power. Thus, the existing modulation can be used and the power stage conversion of the dc-dc converter can be decreased. The proposed control for the QSSC is verified with simulation results. © 2023 IEEE.

关键词： Energy storage

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Exploring Approximate Adders for Energy-Efficient Discrete Walsh-Hadamard Transform

Exploring Approximate Adders for Energy-Efficient Discrete W...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Leonardo Antonietti Rodrigo Lopes Morgana da Rosa Eloisa Barros Eduardo da Costa Rafael Soares Graduate Program on Computing - Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing - Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

This work investigates the use of the Discrete Walsh-Hadamard Transform (DWHT) for cryptographic applications, particularly within resource-constrained environments like microcontrollers such as RISC-V. DWHT's use of adder and subtractor arithmetic operations makes it highly suitable for low-complexity algorithms. In order to enhance efficiency further, our work integrates various approximate adders (AxAs) such as AxPPA, COPY, ETA-I, LOA, and Trunc into both forward (DWHT) and inverse (IDWHT) transform architectures. Our approach outperforms existing methods from the literature regarding accuracy metrics, particularly for lower approximation levels $(K=1\ \text{to}\ K=3)$ , with substantial improvements in PSNR and SSIM. Additionally, our designs significantly reduce power and area compared to existing hardware implementations, show-casing their potential for deployment in real-world cryptographic and hardware security applications.

关键词： Measurement Accuracy Microcontrollers Circuits and systems Hardware security Transforms Energy efficiency Encryption Adders Arithmetic

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Novel virtual nasal endoscopy system based on computed tomography scans

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Virtual Reality & Intelligent Hardware 2022年第4期4卷 359-379页

作者： Fábio de O.SOUSA Daniel S.da SILVA Tarique da S.CAVALCANTE Edson C.NETO Victor JoséT.GONDIM Ingrid C.NOGUEIRA Auzuir Ripardo de ALEXANDRIA Victor Hugo C.de ALBUQUERQUE Federal Institute of Ceará-IFCE Telecommunication Engineering ProgramBrazil Graduate Program on Teleinformatics Engineering Federal University of CearáFortaleza/CEBrazil Centro Universitário Christus-UniChristus Brazil Centro Universitário Sete de Setembro-Uni7 Brazil

Background Currently,many simulator systems for medical procedures are under *** systems can provide new solutions for training,planning,and testing medical practices,improve performance,and optimize the time of the ***,to achieve the best results,certain premises must be followed and applied to the model under development,such as usability,control,graphics realism,and interactive and dynamic *** This study presents a system for simulating a medical examination procedure in the nasal cavity for training and research purposes,using a patient′s accurate computed tomography(CT)as a *** pathologies that are used as a guide for the development of the system are ***,an overview of current studies covering bench medical mannequins,3D printing,animals,hardware,software,and software that use hardware to boost user interaction,is ***,a comparison with similar state-of-the-art studies is *** The main result of this work is interactive gamification techniques to propose an experience of simulation of an immersive exam by identifying pathologies present in the nasal cavity such as hypertrophy of turbinates,septal deviation adenoid hypertrophy,nasal polyposis,and tumor.

关键词： Virtual nasal endoscopy Computed tomography Gamification Endoscopy teaching

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Spatial, Temporal, and Geometric Fusion for Remote Sensing Images

arXiv

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arXiv 2024年

作者： Albanwan, Hessah Graduate Program in Civil Engineering The Ohio State University United States

Remote sensing (RS) images play an important role in monitoring and surveying the earth’s surface at varying spatial scales. Continuous observations from various remote sensing sources over time complement single observations and provide better interpretability and analyzability for various applications. A critical need is to fuse these observations into single or multiple images that are more informative, accurate, complete, and coherent. Studies have intensively investigated spatial-temporal fusion for specific applications, such as pan-sharpening and spatial-temporal fusion of remote sensing images for time-series image analysis. Today, fusion methods have exceeded these typical applications, extending to encompass and accommodate different types of images, modalities, and tasks. Typically, fusion methods are expected to be robust and able to adapt to various types of images (e.g., spectral image, classification maps, and elevation maps) and scene complexities. In this work, we present a few solutions to improve the performance of existing fusion methods by adapting to gridded data with multimodality and considering their type-specific uncertainties. The main contributions of this work include the following: 1) A spatial-temporal filtering method that addresses the spectral heterogeneity of multitemporal images. 2) Three-dimensional (3D) iterative spatiotemporal filtering that enhances the spatiotemporal inconsistencies of classification maps. 3) Adaptive semantic-guided fusion that enhances the accuracy of DSMs, and an analysis of the adaptive fusion approaches comparing them with traditional nonadaptive approaches to show the significant importance of adaptive methods to boost the performance of fusion. 4) A comprehensive analysis of deep learning (DL) stereo matching methods against traditional Census semi-global matching (SGM) to obtain detailed knowledge on the accuracy of the DSMs at the stereo matching level. We analyze the overall performance, robustness,

关键词： Remote sensing

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Agent-Based Modeling for Forest Fire Simulation in Chiang Mai, Thailand 23

Agent-Based Modeling for Forest Fire Simulation in Chiang Ma...

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23rd International Symposium on Communications and Information Technologies, ISCIT 2024

作者： Tappanom, Teerapat Leelawat, Natt Saengtabtim, Kumpol Tang, Jing Risk and Disaster Management Program Graduate School Chulalongkorn University Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Industrial Engineering Bangkok Thailand Graduate School of System Design and Management Keio University Yokohama Japan Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9798350353952

Forest fires have a significant impact on ecosystems and human life, especially in northern Thailand, where Chiang Mai is severely affected. Traditional methods for detecting forest fires have limitations, so there is a need for advanced simulation models. This research uses Agent-Based Modeling (ABM) to develop a forest fire simulation for Chiang Mai. The methodology involves collecting historical data, performing Multiple Regression Analysis, designing the simulation, and testing it. Data from 1998 to 2021, including temperature, relative humidity, wind speed/direction, burn area, and slope, were collected from various sources. Multiple regression analysis identified wind speed as the most significant factor affecting burn area. The forest fire simulation, designed using ZF Wang's spread model and tested with AnyLogic, showed that wind direction and speed are crucial in fire spread. The simulation accurately predicted high-risk areas, helping in proactive planning and response. This study confirms that wind is a critical factor in forest fire spread, providing a valuable tool for fire districts to improve preparedness and management. Future research should focus on refining the model with localized data and integrating real-time detection to improve its accuracy and applicability. © 2024 IEEE.

关键词： Forest ecology

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Development of a Mixed-Reality Dual-User Training System for Robot Laparoscopic Surgery

Development of a Mixed-Reality Dual-User Training System for...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Chen, Ting-You Young, Kuu-Young Graduate Degree Program of Robotics National Yang Ming Chiao Tung University Hsinchu Taiwan National Yang Ming Chiao Tung University Department of Electrical Engineering Hsinchu Taiwan

ISBN: (纸本)9781665410205

As robot surgery becomes more popular these days, it consequently solicits a high demand on its training system. Currently, most of the systems are intended for personal training, while it may be more effective if an experienced expert can also be involved. It thus motivates us to propose a dual-user robotic surgical training system that can closely link the mentor and trainee together. The system is developed in a mixed-reality environment that integrates the information from both the virtual and real worlds. The haptic feedback and virtual fixtures are employed for assistance during skill transfer. The proposed system can assess the proficiency level of the trainee for the mentor to provide proper assistance during training. The experimental results demonstrate that the proposed system is capable of enhancing the trainee's ability for surgery. Especially, similar effectiveness is observed during comparative studies with direct hands-on guidance frequently adopted for skill transfer during sport training. © 2024 IEEE.

关键词： Robotic surgery

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