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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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A low-cost buoyant force measurement device for monitoring sugar concentration in water solution

A low-cost buoyant force measurement device for monitoring s...

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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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Combining Extreme Learning Machine and Linear Discriminant Analysis for Optimized Apple Leaf Disease Classification 4

Combining Extreme Learning Machine and Linear Discriminant A...

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4th International Conference on Electronic and electrical engineering and Intelligent System, ICE3IS 2024

作者： Parjito Ahmad, Imam Borman, Rohmat Indra Alexander, Allan D. Jusman, Yessi Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Universitas Bhayangkara Jakarta Raya Faculty of Computer Science South Jakarta Indonesia Universitas Muhammadiyah Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350378368

Apple trees are an agricultural commodity with high economic value that often face serious challenges due to various leaf diseases. Early detection and proper treatment are crucial to reducing economic losses and ensuring healthy plant growth. Manual methods for detecting apple leaf diseases tend to be time-consuming and require specialized expertise, making them difficult to apply on a large scale. This study aims to develop an automatic classification system based on image processing to detect apple leaf diseases by combining Extreme Learning Machine (ELM) and Linear Discriminant Analysis (LDA) algorithms. ELM offers high training speed with randomly assigned weights, while LDA performs dimensionality reduction to retain the most relevant features, thereby improving model performance. The study results indicate that the combination of ELM and LDA produces a model capable of classifying apple leaf diseases with an accuracy of 92.50%, an improvement of 6.25% compared to using ELM alone. This demonstrates that the model is highly effective in classifying apple leaf diseases. © 2024 IEEE.

关键词： Fruits

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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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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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Design of PID Droop Control for Fast Power Sharing in Inverter-Based Microgrid

Design of PID Droop Control for Fast Power Sharing in Invert...

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2024 Energy Conversion Congress and Expo Europe, ECCE Europe 2024

作者： Nazeri, Ahmad Ali Friebe, Jens Zacharias, Peter Faculty of Electrical Engineering Computer Science University of Kassel Department of Power Electronics Kassel Germany

ISBN: (纸本)9798350364446

Microgrids (MGs) serve as central interfaces for distributed generation, predominantly employing voltage source inverters (VSIs). These MGs operate in either autonomous or grid-connected modes, facilitating local power generation and storage. However, autonomous MGs, lacking grid support, are susceptible to instability, particularly with multiple generators sharing power. This paper addresses instability challenges in VSI-based MGs through comprehensive system modeling, analysis, and design. A novel approach is proposed, employing a modified virtual inertia PID droop control with virtual impedance, facilitates swift response to frequency and voltage fluctuations, ensuring precise power allocation among paralleled VSIs. Moreover, this paper presents the small signal analysis of the PID droop control and outlines the secondary control design, encompassing DDSRF-PLL, frequency, and voltage restoration loops. System validation is conducted through MATLAB/Simulink modeling and experimental verification on a hardware-in-the-loop (HiL) testbench, confirming the efficacy of the proposed methodologies in low inertia MGs. © 2024 IEEE.

关键词： MATLAB

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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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Light Pollution Caused by Railway Station Lighting Systems - Case Study

Light Pollution Caused by Railway Station Lighting Systems -...

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2024 IEEE Sustainable Smart Lighting World Conference and Expo, LS24 2024

作者： Houzva, Martin Novak, Tomas Valicek, Pavel VSB - Technical University of Ostrava Faculty of Electrical Engineering and Computer Science Ostrava Czech Republic

ISBN: (纸本)9798331540197

This paper deals with the radiation of outdoor lighting systems on railways. Due to the number and size of railway stations and their areas, these can contribute significantly to the increase of "light pollution"through the radiation of their luminous flux into the upper hemisphere. Outdoor lighting systems on railways behave de-facto like road lighting systems, but they are usually not taken into account as a significant contributor to light pollution and are of little *** aim of the paper is to show, by the example of the behaviour of a small railway station, the changes in the behaviour of the luminous flux in a given small railway station. The findings address whether new LED-based lighting systems, which respect all normative recommendations not only in terms of the required light technical parameters in the visual task areas, but especially in terms of the requirements for minimizing direct radiation into the upper hemisphere, are really better than the physically and morally obsolete lighting systems implemented 20 to 40 years ago, dominated by luminaires equipped with high-pressure sodium lamps. The paper discusses not only the light technical parameters, but also the power input parameters and the number of luminaires that are necessary to achieve the normative requirements, which result not from environmental requirements, but from safety requirements. © 2024 IEEE.

关键词： Railroads

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Graphene oxide-coated microbottle resonators for relative humidity sensing

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Optoelectronics Letters 2024年第7期20卷 400-405页

作者： Huda Adnan Zain Malathy Batumalay Md Ashadi Md Johari Hazli Rafis Abdul Rahim Sulaiman Wadi Harun Department of Electrical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur 50603Malaysia Faculty of Data Science and Information Technology INTI International UniversityNilai 71800Malaysia1 Faculty of Electrical and Electronic Engineering Technology Universiti Teknikal Malaysia MelakaMelaka 76100Malaysia Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia MelakaMelaka 76100Malaysia

Graphene oxide(GO)is a 2D coating material used to improve fiber optics sensors’response to relative *** resonators(MBRs)have garnered more attention as sensing media *** MBR with a 190μm diameter was coated with ***,tapered fiber light coupling was used to investigate the relative humidity sensing performance in the range of 35—70%RH at 25℃.The MBR showed a higher Q factor before and after GO *** sensitivity of 0.115 dB/%RH was recorded with the 190μm GO-coated MBR sample compared to a sensitivity of 0.022 dB/%RH for the uncoated MBR *** results show that the MBR can be used in fiber optic sensing applications for environmental sensing.

关键词： humidity oxide bottle

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A Square Coaxial Transmission Line With Partially Filled Low-Cost 3-D Printing Insulator 12

A Square Coaxial Transmission Line With Partially Filled Low...

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12th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2024

作者： Yu, Xuzhou Zhu, Lei University of Macau Taipa Department of Electrical and Computer Engineering Faculty of Science and Technology 999078 China

ISBN: (纸本)9798350351019

This paper presents a square coaxial transmission line that is partially filled with 3-D printing low-cost insulator. The proposed coaxial line is composed of two metal conductors and 3D printing insulator. To reduce the dielectric loss, the space between two conductors is partially filled with 3-D printing insulator. Herein, the insulator is the resin whose cost is lower than conventional PTFE, and the relative permittivity and loss tangent are measured first. Then, the guide-wave characteristic of the proposed transmission line is studied. Finally, a transmission line with two transitions is designed and simulated to verify the analysis. © 2024 IEEE.

关键词： Coaxial cables

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