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Photonic Instrumentation engineering XI 2024

作者： Mazzo, Paulo H.R. Torelli, Gabriel A. Dreyer, Uilian J. Pelegrin, Jessé Stel, Henrique Da Silva, Luiz C.T. Romero, Gabriel A. Morales, Rigoberto E.M. da Silva, Jean C.C. Graduate Program in Electrical and Computer Engineering Federal University of Technology UTFPR Paraná PR Curitiba Brazil Graduate Program in Energy Systems Federal University of Technology UTFPR Paraná PR Curitiba Brazil Multiphase Flow Research Center - NUEM Federal University of Technology UTFPR Paraná PR Curitiba Brazil CENPES/PDIEP EE Petrobras Brazil Federal Institute Catarinense IFC Santa Catarina Brazil

ISBN: (纸本)9781510670464

This paper presents a study and development on the thermal mapping of a Three-phase Induction Motor for harsh environments application. These machines’ exceptional performance and precise speed control make them essential equipment in multiple industrial processes, such as Artificial Lift, which integrates with a multistage centrifugal pump to elevate fluids from the reservoirs to the surface. Increased motor speeds for higher production requirements can result in temperature rise, damaging the stator winding. Employing the Raman Distributed Temperature Sensing System (RDTS), we generate a comprehensive heat distribution map of the motor. ANSYS Motor-CAD was applied for computational simulations to perform steady-state thermal analysis, giving an overview of heat transfer among internal components and thermal limits for the instrumented motor. This preliminary study presents a series of experimental tests to evaluate the advantages of fiber optic temperature sensing in harsh environments, emphasizing its significance in improving electrical machines’ performance and reliability. © 2024 SPIE.

关键词： Centrifugal pumps

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Hotel Information System Management Audit Using COBIT 2019 - APO12 2

Hotel Information System Management Audit Using COBIT 2019 -...

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2nd International Conference for Innovation in Technology, INOCON 2023

作者： Utamajaya, Joy Nashar Supangat, Suhono Harso Gaol, Ford Lumban Ranti, Benny BINUS University BINUS Graduate Program School of Information System Jakarta Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatic Bandung Indonesia Bina Nusantara University Computer Science Department BINUS Graduate Program Computer Science Jakarta Indonesia University of Indonesia Computer Science Department Faculty of Computer Science Depok Indonesia

ISBN: (纸本)9798350320923

In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company's business goals. Given the large contribution of information technology in the application of hotel applications as a supporting information system, it is a vital system that must avoid risks that can hinder and cause harm to the hotel management business processes. Therefore, it is necessary to carry out risk management using the COBIT 5 framework to manage possible risks that may occur based on the APO12 (Manage Risk) domain. From the evaluation results of the data obtained through observation and interviews as well as the calculation of the results of the questionnaire based on 6 APO12 subdomains, the results of the risk management level capability assessment in hotel applications are still at level 3 or have reached the level of established process with the target to be achieved at level 4 resulting in a gap of 1 level. Based on the results obtained, it is necessary to propose recommendations that can be used by hotels in improving the application of information technology risk management so that in the future it can achieve the expected target level so that the APO12 level of capability can increase and become more optimal. © 2023 IEEE.

关键词： Risk management

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An event-driven approach for resources planning in distributed power generation systems

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International Journal of electrical Power and Energy Systems 2022年 137卷 107768-107768页

作者： Maschio, Dierli M.R. Duarte, Bruno Lazzaretti, André E. Lafay, Jean-Marc S. Adzkiya, Dieky da Costa, Jean Patric Teixeira, Marcelo Graduate Program in Electrical Engineering Federal University of Technology Paraná Brazil Graduate Program in Electrical Engineering and Industrial Informatics Federal University of Technology Paraná Brazil Department of Mathematics Institut Teknologi Sepuluh Nopember Indonesia

Renewable Energy Sources (RESs) stand as a straightforward alternative to complement the energy grid and have been recurrently integrated into the generation and distribution matrices. Physically, generation components have distributed nature and they are expected to work coordinately, complementing each other to supply centralised microgrids, which interface them with the main power grid and consumers. As RESs have intermittent nature, engineers are limited to plan resources consumption, fulfil unit commitments, stratify time, cost, environmental impact, and quality of energy. This paper exploits the event-driven behaviour of microgrids to provide ways for them to recognise their context and cooperate towards common goals. Our main result is a Petri net simulation model that estimates customisation policies to be applied back over the microgridvia event-based control. Results show that in some cases it is possible to save effort (and resources) of power generation by replacing reactiveness for a more balanced, context-aware, energy chain. A real photovoltaic plant is modelled by our approach with 86% accuracy. © 2021 Elsevier Ltd

关键词： Renewable energy resources

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Influence of Phototype, Sweating and Moisturizing Lotions on Human Skin Emissivity: A Possible Cause of Screening Errors of Feverish People in Sanitary Barriers 9th

Influence of Phototype, Sweating and Moisturizing Lotions on...

引用

9th Latin American Congress on Biomedical engineering, CLAIB 2022 and 28th Brazilian Congress on Biomedical engineering, CBEB 2022

作者： Ninke, Andriele Lemos, João Thomaz Muniz, Pablo Rodrigues Nunes, Reginaldo Barbosa Campos, Hércules Lázaro Morais Simão, Josemar /Campus Vitória Undergraduate Electrical Engineering Course Vitória Brazil /Campus Vitória Graduate Program in Sustainable Technologies Vitória Brazil /Institute of Health and Biotechnology Federal Coari Brazil /Campus Vitória Electrotechnical Course Vitória Brazil

ISBN: (纸本)9783031494093

Due to the Coronavirus Disease 2019 (Covid-19) pandemic scenario, the implementation of sanitary barriers to screening feverish individuals in places of large circulation of people was adopted, aiming to contain the disease spread. Since contamination by the virus occurs through contact and one of the most common symptoms is fever, measuring the temperature of passers-by through non-contact infrared thermography has been a technique used in sanitary barriers. One of the main factors that significantly change the temperature value indicated by thermal imagers is the emissivity of the inspected surface. Skin emissivity, a dimensionless quantity, is found in the literature with a recurrent value of 0.98. The objective of this study is to investigate whether this value is also valid for skin with sweating or using moisturizing lotions, as well as, for different phototypes. Thus, tests and evaluation of emissivity with volunteers in laboratory can answer these questions. The partial results include 37 volunteers of five skin tones of the Fitzpatrick scale, which has six phototypes. Volunteer’s thermographic images were obtained in different situations: dry skin, using moisturizing lotion, and sweaty skin. From the analysis of these images by software and using the tape method, it was possible to estimate the skin emissivity value for each situation. With the emissivity data in hand, a statistical analysis was carried out to assess whether the influence of the conditions studied is significant for the emissivity value and consequently for the temperature measured by the instruments based on the principle of infrared thermography. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Thermography (imaging)

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Generalize or Specialize? The Effect of Coil Combining in Deep Learning Based MR Image Reconstruction

Generalize or Specialize? The Effect of Coil Combining in De...

引用

IEEE International Symposium on Biomedical Imaging

作者： Natalia Dubljevic Richard Frayne Roberto Souza Biomedical Engineering Graduate Program Hotchkiss Brain Institute University of Calgary Calgary AB Canada Seaman Family MR Research Centre Foothills Medical Centre Calgary AB Canada Biomedical Engineering Graduate Program Radiology Clinical Neurosciences Hotchkiss Brain Institute University of Calgary Calgary AB Canada Biomedical Engineering Graduate Program Electrical and Software Engineering Hotchkiss Brain Institute University of Calgary Calgary AB Canada

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

With the advent of deep-learning based MR image reconstruction, new questions are raised regarding best design choices. In particular, when using recent reconstruction models that have been developed for processing multi-channel MR data. A fundamental question is whether to first combine channels to improve model generalizability (i.e., a “coil-combined” approach) or to keep channel processing separate to fully utilize multi-channel information (i.e., an “all-coil” approach). In this work, we compare three popular architectures using coil-combined and all-coil styles on brain MR images. All-coil styles improved in-distribution performance, such as when reconstructing only presumed healthy individu-als. Coil-combined designs better generalized to unseen data from patients with pathology.

关键词： Deep learning Coils Pathology Codes Magnetic resonance Brain modeling Data models Image reconstruction Biomedical imaging

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An Autonomous Mobile Robot Path Planner using Spline Curves and Differential Evolution

An Autonomous Mobile Robot Path Planner using Spline Curves ...

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2023 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2023

作者： de Rezende Freitas, Elias José Cohen, Miri Weiss Guimarães, Frederico Gadelha Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Federal Institute of Minas Gerais IFMG Av. Antônio Carlos 6627 MG Belo Horizonte31270-901 Brazil Department of Software Engineering Braude College of Engineering Karmiel Israel Department of Electrical Engineering Universidade Federal de Minas Gerais UFMG MG Belo Horizonte Brazil

ISBN: (纸本)9798350348071

Robots that operate autonomously require a path planner that ensures the robot reaches the desired position in a safe manner. The robot will be able to achieve greater speeds along the path if the path is smooth, minimizing the effort of the controller. This work presents two new path planners, called DE-Spline and DE-NURBS. These planners provide a smooth path directly by the cost function optimization using the algorithm L-SHADE (Success-History based Adaptive of Differential Evolution using linear population size reduction algorithm) and two path’s parametrization: Ferguson cubic spline and NURBS. Additionally, it ensures that the robot reaches the target in the desired orientation. The planners are compared with a Vector Field-based planner, widely used in robot soccer. Based on the results, it has been found that both planners provide a smoother path along the shortest path, by accounting for the robot’s starting angle and its goal angle. Furthermore, DE-NURBS provides a greater degree of planning freedom than DE-Spline. © 2023 IEEE.

关键词： Motion planning

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SCENE TEXT RECOGNITION MODELS EXPLAINABILITY USING LOCAL FEATURES

arXiv

引用

arXiv 2023年

作者： Ty, Mark Vincent Atienza, Rowel Electrical and Electronics Engineering Institute University of the Philippines Philippines AI Graduate Program University of the Philippines Philippines

Explainable AI (XAI) is the study on how humans can be able to understand the cause of a model's prediction. In this work, the problem of interest is Scene Text Recognition (STR) Ex-plainability, using XAI to understand the cause of an STR model's prediction. Recent XAI literatures on STR only provide a simple analysis and do not fully explore other XAI methods. In this study, we specifically work on data explainability frameworks, called attribution-based methods, that explain the important parts of an input data in deep learning models. However, integrating them into STR produces inconsistent and ineffective explanations, because they only explain the model in the global context. To solve this problem, we propose a new method, STRExp, to take into consideration the local explanations, i.e. the individual character prediction explanations. This is then benchmarked across different attribution-based methods on different STR datasets and evaluated across different STR models. © 2023, CC BY-SA.

关键词： Forecasting

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An efficient beaconing of bluetooth low energy by decision making algorithm

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Discover Artificial Intelligence 2024年第1期4卷 26页

作者： Fujisawa, Minoru Yasuda, Hiroyuki Isogai, Ryosuke Arai, Maki Yoshida, Yoshifumi Li, Aohan Kim, Song-Ju Hasegawa, Mikio Department of Electrical Engineering Tokyo University of Science 6–3–1 Niijuku Tokyo Katsushika-ku125–8585 Japan Graduate Schools for Law and Politics The University of Tokyo 7–3–1 Hongo Tokyo Bunkyo-ku113–8654 Japan Seiko Future Creation Inc. 563 Takatsukashinden Chiba Matsudo-shi270–2222 Japan Graduate School of Informatics and Engineering The University of Electro-Communications 1–5–1 Chofugaoka Tokyo Chofu182–8585 Japan SOBIN Institute LLC. 3–38–7 Keyakizaka Hyogo Kawanishi666–0145 Japan

Ongoing research endeavors are exploring the potential of artificial intelligence to enhance the efficiency of wireless communication systems. Nevertheless, complex computational mechanisms, such as those inherent in neural networks, are not optimally suited for applications where the reduction of computational intricacy is of paramount importance. The rise in Bluetooth-enabled devices has led to the widespread adoption of Bluetooth Low Energy (BLE) in various IoT applications, primarily due to its low power consumption. For specific applications, such as lost and found tags which operate on small batteries, it’s especially important to further reduce power usage. With the objective of achieving low power consumption by optimally selecting channels and advertisement intervals, this paper introduces a parameter selection method derived from the Multi-Armed Bandit (MAB) algorithm, a technique known for addressing human decision-making challenges. In this study, we evaluate our proposed method using simulations in diverse environments. The outcomes indicate that, without compromising much on reliability, our approach can reduce power consumption by up to 40% based on the wireless surroundings. Additionally, when this method was implemented on an actual BLE device, it demonstrated effectiveness in reducing power consumption by about 35% in real environments. © The Author(s) 2024.

关键词： Decision making

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Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains

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Computational and Structural Biotechnology Journal 2024年 23卷 1864-1876页

作者： Do, Duyen Thi Yang, Ming-Ren Vo, Tran Nam Son Le, Nguyen Quoc Khanh Wu, Yu-Wei Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Business Administration College of Management Lunghwa University of Science and Technology Taoyuan City Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan TMU Research Center for Digestive Medicine Taipei Medical University Taipei Taiwan

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR. © 2024 The Authors

关键词： Genes

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Low-cost Embedded System Applied to Data Processing and Indicator Generation of Motor Vehicles 15

Low-cost Embedded System Applied to Data Processing and Indi...

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15th IEEE International Conference on Industry Applications, INDUSCON 2023

作者： Lisboa, Kevin L. Castro, Gabriel G.R. Bastos, Adriana F.V. Pinto, Milena F. Federal Center for Technological Education Celso Suckow da Fonseca - CEFET/RJ Electrical Engineering Graduate Program RJ Rio de Janeiro Brazil Federal Institute of Pernambuco PE Campus Cabo de Santo Agostinho Brazil

ISBN: (纸本)9798350314182

The performance of different automotive vehicles can be compared based on measurements of their real conditions parameters recorded over time, such as position, acceleration, battery consumption, engine speed, fuel type, transmission, odometry, and engine cooling temperature, among others. These parameters are essential for a true picture of the cars' situation, helping to reduce maintenance, e.g., fuel waste, toxic gas emissions, and predictive maintenance. It is important to note that in the literature, several pieces of equipment are inserted in the vehicle's network and exported information to the user online. However, products that access vehicle data and store it for an extended period are not easily available on the market. In most cases, the user only has access to products that show the vehicle's data while the device is connected. When the car is turned off, the data is lost. This work presents a product that fills these gaps, giving the owner a long-term history of the vehicle's information, showing it as easy to understand on a developed interface, and using accessible products to build the device. The tests indicated the product's effectiveness in getting long-term vehicle data for more than a month only using 1% of its storage capacity. For last, research contemplating 1000 possible customers was also implemented to validate product price and interest on the market. © 2023 IEEE.

关键词： Automotive Systems Electronic device Performance parameters Sensors

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