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Defect engineering approaches for metal oxide semiconductor-based chemiresistive gas sensing

Coordination Chemistry Reviews 2025年 541卷

作者： Amit Kumar Julaiba Tahsina Mazumder Kenza Joyen Frédéric Favier Ali Mirzaei Jin-Young Kim Monika Kwoka Mikhael Bechelany Ravindra Kumar Jha Mahesh Kumar Hyoun Woo Kim Sang Sub Kim Department of Electrical Engineering Indian Institute of Technology Jodhpur Jodhpur 342030 India Department of Electronics Assam Skill University Mangaldai Assam 784125 India European Institut of Membranes (IEM) – UMR 5635 University of Montpellier ENSCM CNRS 34090 Montpellier France Institut Charles Gerhardt Montpellier (ICGM) – UMR 5253 University of Montpellier ENSCM CNRS 34090 Montpellier France Department of Materials Science and Engineering Shiraz University of Technology Shiraz 715557-13876 Islamic Republic of Iran Customized manufacturing R&D department Korea Institute of Industrial Technology Gyeonggi-do 15014 South Korea Department of Cybernetics Nanotechnology and Data Processing Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 44-100 Gliwice Poland Functional Materials Group Gulf University for Science and Technology (GUST) Mubarak Al-Abdullah 32093 Kuwait Department of Electronics and Electrical Engineering & Centre for Intelligent Cyber-Physical Systems Indian Institute of Technology Guwahati Guwahati 781039 India Division of Materials Science and Engineering Hanyang University Seoul 04763 South Korea Department of Materials Science and Engineering Inha University Incheon 22212 South Korea

Defect engineering in metal oxides presents a promising approach for tailoring material properties. This strategy enhances gas sorption, catalysis, and control over key physical characteristics such as bandgap, magnetic behavior, and electrical conductivity. Despite its potential, the role of defect engineering in advancing metal oxide semiconductor (MOS) gas-sensing performance remains underexplored. This review introduces defect engineering strategies, emphasizing their applications in gas sensing. Gas sensors play a vital role in environmental monitoring, industrial safety, healthcare, and in improving energy efficiency. The demand for advanced gas sensors has never been more critical, given the need for real-time, accurate, and cost-effective detection of pollutant gases. MOS-based gas sensors are widely used in air quality monitoring, industrial safety, and health diagnostics. Vacancies and defect architectures in MOS have been widely studied for their role in sensing performance, as they fundamentally influence sensor efficiency. The effectiveness of MOS sensors largely depends on the type and concentration of defects. This review introduces vacancies and defects in MOS, followed by an in-depth discussion of defect types, factors influencing defect formation, and their role in charge transport. Additionally, it examines the correlation between elemental chemical properties and defect chemistry. Special attention is given to the defect chemistry of metal oxides, including TiO 2 , ZnO, Co 3 O 4 , ZrO 2 , WO 3 , and CeO 2 . It concludes with an examination of surface engineering methods for defect control to improve gas-sensing capabilities.

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Activation maps of convolutional neural networks as a tool for brain degeneration tracking in early diagnosis of dementia in Parkinson's disease based on magnetic resonance imaging

Research Square

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Research Square 2021年

作者： Suwalska, Aleksandra Siuda, Joanna Kocot, Szymon Zmuda, Weronika Rudzinska-Bar, Monika Polanska, Joanna Department of Data Science and Engineering Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Department of Neurology School of Medicine Medical University of Silesia Katowice Poland Department of Neurology Faculty of Medicine and Health Sciences Andrzej Frycz Modrzewski Krakow University Krakow Poland

Identification of Parkinson’s Disease (PD) patients at risk for development of dementia is crucial for early intervention. However, diagnosing dementia in PD patients requires advanced, time-consuming and expensive imaging techniques (such as DaT-SCAN-SPECT). The study aims to prove the usefulness of convolutional neural networks (CNN) for the identification of brain areas related to the progress of cognitive impairment by using standard Magnetic Resonance Imaging (MRI) sequences. T1&T2 sequences of 18 patients were used in the pilot study. Activation maps were generated, and the brain regions most involved in the classification process were identified, showing areas potentially significant in the diagnosis of cognitive impairment severity. The cerebellum was proven significant for distinguishing the above-mentioned classes in relative cerebellum volume (ANOVA p-value=0.0038 with large effect size η2=0.5254) and folding (p-value=0.0031, η2=0.5357), which is consistent with reports by other authors. Our analysis demonstrates that convolutional neural networks combined with a proper image preprocessing pipeline could be used for feature extraction in MRI sequences and can successfully support the identification of disease-specific abnormalities of the brain image. © 2021, CC BY.

关键词： Magnetic resonance imaging

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The Use of Mathematical Fractional-Calculus to Modeling of Changes in Concentrations of Polycyclic Aromatic Hydrocarbons (Pahs) in Sewage Sludge

SSRN

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SSRN 2024年

作者： Wlodarczyk-Makula, Maria Wlodarczyk, Maciej Czestochowa University of Technology Faculty of Infrastructure and Environment 69 Dąbrowskiego Str. Czestochowa42-201 Poland Kielce University of Technology Faculty of Electrical Engineering Automatic Control and Computer Science 7 Av. Tysiąclecia Państwa Polskiego Kielce25-314 Poland

Sewage sludge constitutes waste generated during wastewater treatment in any treatment plant. Sludge that meets the quality conditions specified in the legal regulations, due to fertilising properties, can be used for natural purposes (use in the recovery process on the surface of the earth or for the reclamation cover of landfills). However, sewage sludge contains various organic microcontaminants, such as, for example, PAHs that are toxic to aquatic and soil organisms, and the legal regulations do not specify the acceptable concentrations of these compounds. However, restrictions concerning PAHs in European legislation are proposed. The aim of the study was to use fractional order derivatives to develop a mathematical model describing changes in the concentration of polycyclic aromatic hydrocarbons (PAHs) in sewage sludge stored in natural conditions. The concentrations of selected PAHs were monitored for 3 months at fixed time intervals under conditions reflecting the use of sludge for natural purposes. A qualitative and quantitative analysis of PAHs was carried out using the GC-MS system. For the mathematical description of changes in the concentration values of individual compounds, fractional order derivatives were used and approximation was carried out using the classical equation of the first order. The developed mathematical model allows for predicting changes in PAH concentrations regarding sludge as well as determining the time necessary to obtain the required concentration of these compounds. © 2024, The Authors. All rights reserved.

关键词： Polycyclic aromatic hydrocarbons

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A computer Vision-Based Solution for Assessing Prosthetic Leg Length Discrepancy

A Computer Vision-Based Solution for Assessing Prosthetic Le...

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E-Health and Bioengineering Conference (EHB)

作者： Otilia Zvorişteanu Dimitrie-Cristian Fodor Vasile-Ion Manta Neculai-Eugen Seghedin Ştefan-Daniel Achirei Dragoş-Florin Chitariu Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Iaşi Romania “Dr. Iacob Czihac” Military Emergency Clinical Hospital Iaşi Dept. of Digital Production Systems Faculty of Machine Manufacturing and Industrial Management “Gheorghe Asachi” Technical University of Iaşi Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

This paper presents a novel computer vision-based approach for assessing leg length discrepancy (LLD) in individuals with prosthetic limbs. The proposed solution uses image processing techniques to detect markers placed on the patient's knee, prosthesis, and a reference wall, allowing for precise measurement of limb alignment. Through a comparative analysis of the initial reference position, set by a specialist, and the current limb positioning, the algorithm identifies discrepancies in leg length. The system employs a non-invasive methodology, utilizing an IP camera to capture images and communicate them via Wi-Fi to a computing unit for further analysis. Experimental validation, conducted on simulated LLDs ranging from 1mm to 10mm, demonstrates the system's high sensitivity and accuracy in detecting subtle changes in limb alignment. This approach offers a scalable, automated alternative to traditional manual methods, improving both the reliability and ease of prosthetic adjustments.

关键词： Legged locomotion Wireless communication Limbs Prosthetic limbs Current measurement Manuals Cameras Reliability IP networks Wireless fidelity

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Plenary Lectures

Plenary Lectures

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Mediterranean Conference on control and Automation (MED)

作者： Bart De Moor Yasamin Mostofi Maryam Kamgarpour Zdenko Kovačić Maja Cepanec Airlie Chapmar Mehran Mesbahi Department of Electrical Engineering (ESAT-STADIUS) KU Leuven Leuven Belgium Department of Electrical & Computer Engineering University of of California Santa Barbara CA USA Automatic Control Laboratory Swiss Federal Institute of Technology Zurich Zurich Switzerland University of Zagreb Faculty of Electrical Engineering and Computing University of Zagreb Faculty of Education and Rehabilitation Sciences University of Melbourne Australia University of Washington USA

The following topics are dealt with: control system synthesis; stability; nonlinear control systems; closed loop systems; robust control; feedback; Lyapunov methods; mobile robots; uncertain systems; and position cont... 详细信息

ISBN: (纸本)9781538674994;9781538678909

关键词： Robot sensing systems Electrical engineering Education Autism Robot kinematics Decision making

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New class of impulsive noise reduction filters based on kernel density estimation

New class of impulsive noise reduction filters based on kern...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： B. Smolka K.N. Plataniotis R. Lukac A.N. Venetsanopoulos Department of Automatic Control Silesian University of Technology Poland The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto Toronto ONT Canada Slovak Image Processing Center Dobsina Slovakia Faculty of Applied Science and Engineering University of Toronto Toronto ONT Canada

The paper presents a new filtering scheme for the removal of impulsive noise in color images. It is based on estimating the probability density function for color pixels in a filter window by means of the kernel density estimation method. A quantitative comparison of the proposed filter with the vector median filter shows its excellent ability to reduce noise while simultaneously preserving fine image details.

关键词： Noise reduction Filters Kernel Colored noise Color Histograms Filtering Probability density function Shape Multidimensional systems

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引用

IEEE International Conference on Multimedia and Expo (ICME)

In this paper a novel approach to the problem of impulsive noise removal in color images based on the nonparametric density estimation is presented. The basic idea behind the new image filtering technique is the maximization of the similarities between pixels in a predefined filtering window. The new method is faster than the standard vector median filter and preserves better edges and fine image details. Simulation results show that the proposed method outperforms other standard algorithms of the reduction of impulsive noise in color images.

关键词： Colored noise Color Filtering Pixel Strontium Educational institutions Image processing Noise reduction Nonlinear filters Gray-scale

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Improving fNIRS Signal Quality Using Smoothing Filtering

Improving fNIRS Signal Quality Using Smoothing Filtering

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Progress in Applied Electrical engineering (PAEE)

作者： Aleksandra Kawala-Sterniuk Dariusz Mikołajewski Luis A. Leiva Tuukka Ruotsalo Adam Lysiak Barbara Grochowicz Edward Jacek Gorzeńariczyk Adrian Luckiewicz Anna Wieczorek Mariusz Pelc Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland Department of Computer Science University of Luxembourg Luxembourg Luxembourg University of Helsinki Denmark University of Copenhagen Finland Institute of Philosophy Kazimiez Wielki University Bydgoszcz Poland

Biomedical signals are extremely difficult to analyze, mainly due to the non-stationary nature of these signals. Filtering does not always bring the desired results, because often the desired information is filtered out. In the case of EEG signals, smoothing filters gave very good results. In this paper, various types of smoothing filters for the analysis of infrared spectroscopy signals were compared.

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Self-Tuning PID controllers Based on Dynamics Inversion Method

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IFAC Proceedings Volumes 2000年第4期33卷 167-172页

作者： Vladimír Bobál Petr Dostál Jiří Macháček Miluše Vitečková Department of Automatic Control Faculty of Technology Zlin Brno University of Technology nám. TGM 275 762 72 Zlin Czech Republic Phone Fax: +420 67 721 1521 Department of Process Control and Computer Techniques University of Pardubice nám. Čs. Legií 565 532 10 Pardubice Czech Republic Department of Control Systems and Instrumentation Faculty of Mechanical Engineering Technical University of Ostrava 17. Listopadu 15 708 33 Ostrava-Poruba Czech Republic

A self – tuning PID controller algorithm has been derived in this paper. The process is identified by the regression (ARX) continuous – time model using the recursive least squares method (RLSM) with applied directional forgetting. The recursive parameter estimates of the continuous – time model (differential equation) are used to synthesis the PID controller. controller synthesis is designed on the basis of a dynamics inversion method. This method allows the tuning of standard analog and digital controllers for chosen types of controlled processes without or with time delay. The algorithm is suitable for the automatic setting of analog and digital PID controllers for deterministic processes or the adaptive control of stochastic and nonlinear processes. The analog modification PID controller has been verified by computer simulation.

关键词： continuous – time ARX model recursive least squares inverse dynamics control PID control self-tuning control

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Pilot Study on Using Hybrid–Cascade Filtering on Brain Signals for the control Purposes

Pilot Study on Using Hybrid–Cascade Filtering on Brain Sign...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Mariusz Pelc Dariusz Mikołajewski Edward Jacek Gorzelańczyk Anna Wieczorek Henryk Racheniuk Adam Sudoł Kayhan Latifzadeh Luis A. Leiva Aleksandra Kawala-Sterniuk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland Faculty of Physical Education and Physiotherapy Opole University of Technology Opole Poland Faculty of Natural and Technical Sciences University of Opole Opole Poland Department of Computer Science University of Luxembourg Luxembourg Luxembourg

We present an initial study conducted on fNIRS signals using Hybrid-Cascade filters for the purpose of their quality improvement. Whilst many studies focus on filtering brain signals, so that their frequency domain properties would allow e.g. widely understood diagnostics, here we focus on the study of time-domain signal characteristics, which is relevant for potential control purposes. Taking into account various kinds of artifacts, we propose a novel cascade 1D Kalman filter to handle fNIRS signals.

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