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2023 International Conference on electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Kaučić, Luka Kovačević, Ivana Aleksi, Ivan Keser, Tomislav Zidar, Josip Rimac-Drlje, Snježana Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Computer Engineering and Automation Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Communications Osijek Croatia

ISBN: (纸本)9798350322972

Monitoring sugar concentration during fermentation is crucial for producing high-quality alcoholic beverages. Traditional methods for measuring sugar concentration can be costly and time-consuming, especially for small-scale producers. In this study, we developed a low-cost buoyant force measurement device for monitoring sugar concentration in water solutions. The device consists of a buoyant object fully submerged in the solution and connected to a load-cell sensor. As the sugar concentration in the liquid increases, the buoyant force on the object increases, and the load-cell measures this force. Proposed device is calibrated using solutions of known sugar concentrations and its high accuracy and precision is presented. The device is tested in controlled environment to ensure accurate tracking changes in sugar concentration over time. Proposed device can be a valuable tool for small-scale producers looking to optimize their fermentation processes while minimizing costs. © 2023 IEEE.

关键词： Fermentation

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Secure Encryption and Decryption Circuit on 8T1C Structure-Based Charge Accumulation and Dissipation 9

Secure Encryption and Decryption Circuit on 8T1C Structure-B...

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9th International Conference on Integrated Circuits and Microsystems, ICICM 2024

作者： Zhang, Shutong Wang, Pengjun Zhou, Ziyu Zhang, Yuejun Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China College of Electrical and Electronic Engineering Wenzhou University Wenzhou China

ISBN: (纸本)9798331509453

To solve the large resource overhead and risk problems of traditional encryption and decryption technologies. This paper presents a secure computing scheme of 8T1C structure based on charge accumulation and dissipation which is used to implement low-cost encryption and decryption circuits. Firstly, the scheme uses the characteristics of capacitor charge accumulation and dissipation to complete the XOR encryption. Decryption of data is performed by dynamically charging and discharging the load capacitor. Secondly the 8T1C SRAM unit structure is designed in combination with the Static Random-Access Memory Physical Unclonable Function (SRAM PUF) structure. The encryption and decryption operations are built into the storage unit to reduce the hardware resource overhead, by integrating additional MOS tubes and capacitors. Finally, the encrypted data is reshaped by the sense amplifier and stored in the same unit. The function of safe data storage is realized through hardware reuse of circuit resources. The security encryption and decryption circuit is simulated and verified In the TSMC 65nm process. The experimental results show that the designed encryption and decryption circuit structure can confuse the traces of the original data and recover the original information content in the decryption process. PUF key uniqueness is 50.31%, randomness is 99.9%, and it has passed the NIST randomness test. Under the working environment of -50°C 125°C and 0.8V to 1.5V, the worst bit error rate is 7.6%, which can be applied to the security encryption field of the Internet of Things. © 2024 IEEE.

关键词： Static random access storage

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Access Management in IoT: Implementing a Secure Access Control System 15

Access Management in IoT: Implementing a Secure Access Contr...

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15th International Conference on Communications, COMM 2024

作者： Neculai, Razvan-Sebastian Bogdan, Ioana-Corina Alexandru, Marian Robu, Dan-Nicolae Transilvania University of Brasov & Eviden Faculty of Electrical Engineering and Computer Science Department of Cybersecurity Braşov Romania Transilvania University of Brasov Faculty of Electrical Engineering and Computer Science Department of Electronics and Computers Braşov Romania

ISBN: (纸本)9798350355956

This paper aims to implement and use the Spring Security framework to secure and authenticate the connection between a web application and the ESP32 device. In the context of a web application, by analyzing the integration of the Spring Security framework, it investigates the ways in which it manages the complex process of authentication and authorization, thus providing a secure and protected connection to an IoT device. Additionally, this study investigates the integration and use of the RTOS operating system to manage physical access in an IoT environment, in particular by implementing the opening of a door using tags. The mechanism described above leads to an additional level of security and control over physical access in an IoT ecosystem. © 2024 IEEE.

关键词： Radio frequency identification (RFID)

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A Novel Adaptive Non-uniform Conformal Meshing Method for Efficient FDTD Simulation

A Novel Adaptive Non-uniform Conformal Meshing Method for Ef...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Chen, Wei-Xin Wang, Jian Shi, Wen Liu, Qi-Feng Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China Chongqing University School of Electrical Engineering Chongqing400044 China

ISBN: (纸本)9798350355581

In the process of generating conventional FDTD meshes, the model voxelization often takes up too many computational resources. To address this issue, this paper is devoted to presenting an effective mesh voxelization technique with adaptive partitioning and non-uniform grid generation. In this scheme, the entire computational domain is divided into subintervals based on the model's demarcation points, and the mesh generation parameters can be adaptively adjusted according to the information of each sub-interval in order to generate a reasonable non-uniform mesh. Besides, the scheme corrects mesh generation conditions for voxels across the model interface and records their conformal information, resolving the staircase approximation issue caused by traditional voxelization. The proposed mesh generation technique can minimize the number of grids while ensuring the geometrical accuracy of the model. The mesh quality is further validated by applied to meshing some typical objects in computational electromagnetics problems. © 2024 IEEE.

关键词： Mesh generation

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Learning of Multimodal Point Descriptors in Radar and LIDAR Point Clouds

Learning of Multimodal Point Descriptors in Radar and LIDAR ...

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2024 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2024

作者： Rottter, Jan M. Cohrs, Simon Blume, Holger Wagner, Bernardo Leibniz University of Hannover Realtime Systems Group The Faculty of Electrical Engineering and Computer Science Hannover30167 Germany Institute of Microelectronic Systems The Faculty of Electrical Engineering and Computer Science Leibniz University of Hannover Hannover30167 Germany

ISBN: (纸本)9798350368031

Registration of point clouds is a fundamental task in robotic SLAM pipelines. Typically this task is performed only on point clouds of the same sensor or at least the same sensing modality. However, robots designed for challenging environments are often equipped with redundant sensors for the same task where some sensors are more accurate and others are more robust against disturbing environmental conditions. Being able to register the data across the modalities is an important step to more fault-tolerant localization and mapping. We therefore propose a learning framework, which describes the points in the point cloud invariant of their modality. This description is then used in a transformer-like model to find point matches for the registration process. We demonstrate our results using a scanning lidar and radar sensor on our own and publicly available datasets. © 2024 IEEE.

关键词： SLAM robotics

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Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality 40

Reasons for the Superiority of Stochastic Estimators over De...

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40th International Conference on Machine Learning, ICML 2023

作者： Ohayon, Guy Adrai, Theo Elad, Michael Michaeli, Tomer Faculty of Computer Science Technion Haifa Israel Faculty of Electrical and Computer Engineering Technion Haifa Israel

Stochastic restoration algorithms allow to explore the space of solutions that correspond to the degraded input. In this paper we reveal additional fundamental advantages of stochastic methods over deterministic ones, which further motivate their use. First, we prove that any restoration algorithm that attains perfect perceptual quality and whose outputs are consistent with the input must be a posterior sampler, and is thus required to be stochastic. Second, we illustrate that while deterministic restoration algorithms may attain high perceptual quality, this can be achieved only by filling up the space of all possible source images using an extremely sensitive mapping, which makes them highly vulnerable to adversarial attacks. Indeed, we show that enforcing deterministic models to be robust to such attacks profoundly hinders their perceptual quality, while robustifying stochastic models hardly influences their perceptual quality, and improves their output variability. These findings provide a motivation to foster progress in stochastic restoration methods, paving the way to better recovery algorithms. © 2023 Proceedings of Machine Learning Research. All rights reserved.

关键词： Stochastic models

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Wideband Slot Antenna Array with Stable Low Sidelobe Performance

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IEEE Antennas and Wireless Propagation Letters 2025年第5期24卷 1248-1252页

作者： Zhang, Fengyuan Zhang, Hanlin You, Qingchun Huang, Jifu Ningbo University Faculty of Electrical Engineering and Computer Science Zhejiang Ningbo315211 China University of Birmingham School of Engineering B15 2TT United Kingdom

This letter presents a dispersion compensation method that integrates a comb-shaped slow-wave structure with a defected ground structure (DGS) to achieve wideband low-sidelobe performance. This method effectively ensures phase balance within the feed network, achieving a stable low sidelobe level over a wide frequency range. A prototype planar array antenna operating in the 21.6-30.8 GHz range was designed, fabricated, and measured. The experimental results demonstrate that the antenna achieves a fractional bandwidth (FBW) of 35.1%, with the first sidelobe level maintained below -21 dB across the entire band and a fluctuation confined within ±1.3 dB. © 2002-2011 IEEE.

关键词： Defected ground structures

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Evaluating the Performance of Clinical data using Machine learning Approach- An Ensemble Model 2

Evaluating the Performance of Clinical data using Machine le...

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2nd IEEE International Conference on Networks, Multimedia and Information Technology, NMITCON 2024

作者： Abdullah, A. Sheik Vinod, A Aashish Pranav, A G Vishal Govindarajan, Yeshwanth Selvakumar, Subramanian Vellore Institute of Technology School of Computer Science and Engineering Chennai India Bahir Dar University Faculty of Electrical and Computer Engineering Ethiopia

ISBN: (纸本)9798350372892

In the rapidly evolving field of healthcare, accurate clinical predictions are paramount for effective disease management and treatment planning. This paper introduces a novel ensemble machine learning model that utilizes the combined strengths of decision trees, neural networks, random forests, and support vector machines, integrated through a sophisticated linear regression meta-learner. This advanced integration strategy enhances predictive accuracy by optimally weighting the contributions of each base model based on their predictive reliability and effectiveness. The ensemble model amalgamates diverse algorithms with a meta-learning approach to harness a broader spectrum of data insights, thereby overcoming the limitations of traditional single-model approaches. Comparative analysis reveals that the ensemble model significantly outperforms existing methods, achieving superior accuracy in clinical predictions. These results underscore the potential of ensemble approaches in revolutionizing predictive analytics in healthcare, offering a promising tool for improving diagnostic precision and patient outcomes. © 2024 IEEE.

关键词： Contrastive Learning

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Integrating Cloud and Edge/Fog Computing in Advanced Metering Infrastructure

Integrating Cloud and Edge/Fog Computing in Advanced Meterin...

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2024 International Symposium on Sensing and Instrumentation in 5G and IoT Era, ISSI 2024

作者： Ungurean, Ioan Gaitan, Nicoleta Cristina Stefan cel Mare University of Suceava Faculty of Electrical Engineering and Computer Science Suceava Romania

ISBN: (纸本)9798350378689

Advanced Metering Infrastructure (AMI) is a system consisting of smart meters, communications networks, and data management systems that enable two-way communication between utilities and customers. This paper aims to introduce a solution for an Advanced Metering Infrastructure (AMI) that utilizes cloud technologies as well as edge and fog computing technologies. We propose an innovative solution for AMI that combines the high performance and scalability of cloud computing with low latency and local processing strength in edge/fog systems. This integrated solution improves the accuracy and promptness of energy consumption data capture, either at a stand-alone level or combined network concept, which provides real-time data processing. Our solution utilizes LoRaWAN technology to collect data from geographically dispersed meters. The data collected are stored in an Internet of Things (IoT) framework for real-time dashboards and data analysis. The proposed solution established a robust and efficient framework for modern energy management by integrating these technologies. © 2024 IEEE.

关键词： Advanced metering infrastructures

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Predictive Analysis of Sarajevo's AQI using Machine Learning Models for Varied Data Granularity and Prediction Windows 47

Predictive Analysis of Sarajevo's AQI using Machine Learning...

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47th ICT and Electronics Convention, MIPRO 2024

作者： Zolota, Emina Hasić, Vahidin Mević, Amina Delić, Amra Krivić, Senka University Of Sarajevo Faculty Of Electrical Engineering Department For Computer Science And Informatics Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9798350382495

This study scrutinizes five years of Sarajevo's Air Quality Index (AQI) data using diverse machine learning models - Fourier autoregressive integrated moving average (Fourier ARIMA), Prophet, and Long short-term memory (LSTM) - to forecast AQI levels. Focusing on various prediction frames, we evaluate model performances and identify optimal strategies for different temporal granularities. Our research unveils subtle insights into each model's efficacy, shedding light on their strengths and limitations in predicting AQI across varied timeframes. This research presents a robust framework for automatic optimization of AQI predictions, emphasizing the influence of temporal granularity on prediction accuracy, automatically selecting the most efficient models and parameters. These insights hold significant implications for data-driven decision-making in urban air quality control, paving the way for proactive and targeted interventions to improve air quality in Sarajevo and similar urban environments. © 2024 IEEE.

关键词： Air quality

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