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Deep learning for brain age estimation: A systematic review

Information Fusion 2023年 96卷 130-143页

作者： Tanveer, M. Ganaie, M.A. Beheshti, Iman Goel, Tripti Ahmad, Nehal Lai, Kuan-Ting Huang, Kaizhu Zhang, Yu-Dong Del Ser, Javier Lin, Chin-Teng Department of Mathematics Indian Institute of Technology Indore Simrol Indore453552 India Department of Robotics University of Michigan Ann ArborMI48109 United States Department of Human Anatomy and Cell Science Rady Faculty of Health Sciences Max Rady College of Medicine University of Manitoba WinnipegMB Canada Biomedical Imaging Lab National Institute of Technology Silchar Assam 788010 India Department of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan Data Science Research Center Duke Kunshan University China School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom Derio48160 Spain Bilbao48013 Spain School of Computer Science Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia

Over the years, Machine Learning models have been successfully employed on neuroimaging data for accurately predicting brain age. Deviations from the healthy brain aging pattern are associated with the accelerated brain aging and brain abnormalities. Hence, efficient and accurate diagnosis techniques are required to elicit accurate brain age estimations. Several contributions have been reported in the past for this purpose, resorting to different data-driven modeling methods. Recently, deep neural networks (also referred to as deep learning) have become prevalent in manifold neuroimaging studies, including brain age estimation. In this review, we offer a comprehensive analysis of the literature related to the adoption of deep learning for brain age estimation with neuroimaging data. We detail and analyze different deep learning architectures used for this application, pausing at research works published to date quantitatively exploring their application. We also examine different brain age estimation frameworks, comparatively exposing their advantages and weaknesses. Finally, the review concludes with an outlook towards future directions that should be followed by prospective studies. The ultimate goal of this paper is to establish a common and informed reference for newcomers and experienced researchers willing to approach brain age estimation by using deep learning models. © 2023 Elsevier B.V.

关键词： Deep neural networks

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Fabrication of CMUTs Using Sacrificial Release Process with Ashing Assisted Polysilicon Release

Fabrication of CMUTs Using Sacrificial Release Process with ...

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2022 International Conference on Biomedical and Intelligent Systems, IC-BIS 2022

作者： Che, U. Kin Liu, Xin Yu, Yuanyu Wang, Jiujiang Pun, Sio Hang Chen, Fei Mak, Peng Un Vai, Mang I. Institude of Mircroelectronic University of Macau Avenida da Universidade Taipa China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Avenida da Universidade Taipa China Department of Electrical and Electronic Engineering Collage of Engineering Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9781510660212

Capacitive Micromachined Ultrasonic Transducer (CMUT) is a type of ultrasonic transducer that can be applied in many fields like chemical and mechanical sensing, physical imaging, and bio-imaging. Sacrificial layer release is one of the fabrication methods and cavity releasing is the key part of this method. The stress of the sacrificial material is one of the causes making membranes break in this procedure. The previous studies had a phospho-silicide-glass (PSG) layer deposited between polysilicon sacrificial layer and silicon nitride membrane with LPCVD partially solved the problem. However, its processing temperature is relatively high, which makes it not compatible with CMOS integrated circuits (ICs). This work fabricated CMUTs in the sacrificial layer release process, with polysilicon as the main sacrificial layer. Utilizing chemical reaction of polysilicon in ashing process, a thin oxide was formed between the sacrificial layer and membrane while removing the remaining photoresist with ashing. The result showed that it could also help produce large membranes with a lower processing temperature, which can be more compatible with CMOS ICs. After fabrication, the impedance of an element with 100 µm diameter cells was measured to be several hundred ohms in air with 30 V bias voltage and the resonance frequency was 4.7 MHz. © 2022 SPIE. All rights reserved.

关键词： Polysilicon

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IoT-Based Mobile Drug Dispenser for Developing Countries 8

IoT-Based Mobile Drug Dispenser for Developing Countries

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8th IET Smart Cities Symposium, SCS 2024

作者： Machingamidze, Keith Rushambwa, Munyaradzi Charles Yogesh, C.K. Palaniappan, Rajkumar Vijean, Vikneswaran Nabi, Fizza Ghulam Harare Institute of Technology Harare Zimbabwe School of Computer Science and Engineering Vellore Institute of Technology India Department of Mechatronics Engineering College of Engineering University of Technology Bahrain Bahrain Faculty of Electronic Engineering and Technology Universiti Malaysia Perlis Malaysia Department of Industrial Engineering and Management University of the Punjab Pakistan

ISBN: (纸本)9781837242672

This research focuses on the development of an Internet of Things (IOT) -based mobile drug dispenser that utilizes a line following robot, Node MCU, mobile applications, and a desktop application to ensure efficient drug administration. The line following robot is designed to navigate through a predefined path to deliver drugs to patients, while the Node MCU enables wireless communication and control. The mobile and desktop applications allow healthcare professionals to control and monitor the line following robot. This system aims to improve medication adherence and to enhance patient care. The IOT-based mobile drug dispenser has the potential to revolutionize drug administration in various healthcare settings, including hospitals, clinics, and home care. © The Institution of engineering & technology 2024.

关键词： Home health care

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A Deep and Systematic Review of the Intrusion Detection Systems Based on Machine Learning and Deep Learning Techniques

A Deep and Systematic Review of the Intrusion Detection Syst...

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International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： Guhan N K Sindhu Ravindran Ramachandran M Vikneswaran Vijean Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Faculty of Electronic Engineering & Technology Universiti Malaysia Perlis Kampus Alam UniMAP Perlis Malaysia

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384376

Intrusion detection systems are the primitive elements in safeguarding vital infrastructures, which are able to identify malicious activity on hosts or networks. The efficient IDS must be able to handle a variety of threats is a difficult security cum threat related problems. Numerous strategies have been put out in the literature as of right now to increase intrusion detection efficiency while taking into account some of these restrictions, like mobility and resource limitations. This review paper discusses about the early research works on performed on IDS using Deep Learning and Machine Learning techniques. This paper provides a qualitative assessment of these methods and deeper insights about the analysis as well as a summary of the field's current themes and the methods used to train and implement IDSs. We address the overall limitations of these solutions, namely the types of attacks that these approaches are unable to identify and the setup limitations that are specific to each of these works, even though they offer insightful information and solutions for certain aspects of these constraints.

关键词： Deep learning Cloud computing Accuracy Recurrent neural networks Computational modeling Wireless networks Intrusion detection Communication system security Long short term memory Cyberattack

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Straight-line: A new global path planning algorithm for Mobile Robot 2

Straight-line: A new global path planning algorithm for Mobi...

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2nd IEEE International Conference on electronic engineering, ICEEM 2021

作者： Nasr, Aida A. El-Bahnasawy, Nirmeen A. El-Sayed, Ayman Tanta University Faculty of Computers and Information Information Technology Dept. Egypt Menoufia University Faculty of Electronic Engineering Computer Science and Engineering Dept Egypt

ISBN: (纸本)9781665418423

Today most organizations use mobile robots for many purposes and to perform difficult and repetitive tasks. Robots are used to transport goods from one place to another within factories and warehouses. It is also used to provide different services in government and private institutions, as it can interact with people and help them to obtain different services with high quality and very quickly without any trouble. For the robot performs its functions better, it needs a path planning algorithm to avoid obstacles and works faster. Therefore, we develop a new algorithm called straight line algorithm. The new algorithm can get the optimal path with shortest length in low running time. The new algorithm searches for the optimal solution in the critical region firstly. This way capable of finding the shortest path faster. We evaluate straight-line algorithm with Genetic algorithm GA. We find that the new algorithm outperforms better than the GA in terms, distance, speed, and running time. © 2021 IEEE.

关键词： Motion planning

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Novel Bendable Mnxca(0.90−X)Ni0.10fe2o4 Substrate Based Symmetrical Metamaterial Absorber for Rf Energy Harvesting Application to Achieve Sustainable Development Goals

SSRN

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SSRN 2024年

作者： Hasan, Mohammad Shakibul Islam, Mohammad Tariqul Ouda, Mohammad Alenezi, Abdulmajeed M. Soliman, Mohamed S. Samsuzzaman, Md. Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Electrical Engineering Technology College of Engineering & Technology University of Doha for Science and Technology Doha24449 Qatar Department of Electrical Engineering Faculty of Engineering Islamic University of Madinah Madinah41411 Saudi Arabia Department of Electrical Engineering College of Engineering Taif University Taif21944 Saudi Arabia Department of Computer and Communication Engineering Faculty of Computer Science and Engineering Patuakhali Science and Technology University Bangladesh

This article presents a bendable substrate MnxCa(0.90−x)Ni0.10Fe2O4 based metamaterial absorber for RF energy harvesting from Wifi frequency of 5 GHz to the achievement of the Sustainable Development Goals. The bendable metamaterial absorber (BMMA) energy harvester unit cell constructed with the physical dimension of 21 × 21 *** proposed unit cell consist of cross sign shaped resonator surrounded by circular ring resonator is located middle portion and boundary split outer ring resonator. Based on the simulation findings, the proposed BMMA energy harvester provides maximum energy harvesting efficiency of 99.42% at 5 GHz. Due to the symmetrical design, the energy harvester unit cell shows excellent angle insensitive up to 90 degrees for incident angle and polarization angle. The proposed BMMA exhibits single negative properties, and it shows excellent harvesting efficiency for various bending conditions. The lightweight, flexibility of the structure indicate that MnxCa(0.90−x)Ni0.10Fe2O4 based bendable metamaterial absorber energy harvester have significant potential for RF energy harvesting application from wifi frequency of 5 GHz and it achieve Sustainable Development Goals (SDGs), specially alignment with SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), SDG 11 (Sustainable Cities and Communities),and SDG 13 (Climate Action). © 2024, The Authors. All rights reserved.

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Analytical Survey on the Security Framework of Cyber-Physical Systems for Smart Power System Networks

Analytical Survey on the Security Framework of Cyber-Physica...

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2022 International Conference on Cyber Resilience, ICCR 2022

作者： Ali Al-Jumaili, Ahmed Hadi Muniyandi, Ravie Chandren Hasan, Mohammad Kamrul Singh, Mandeep Jit Siaw Paw, Johnny Koh Universiti Kebangsaan Malaysia Faculty of Information Science and Technology Bangi43600 Malaysia University of Fallujah Computer Centre Department Anbar00964 Iraq Universiti Kebangsaan Malaysia Faculty of Engineering and Built Environment Department of Electrical Electronic and System Engineering Selango Bangi43600 Malaysia Universiti Tenaga Nasional Department of Electronic and Communication Engineering Selango Kajang Malaysia

ISBN: (纸本)9781665461221

Cyber-Physical Power System (CPPS) is one of the most critical infrastructure systems due to deep integration between power grids and communication networks. In the power system, cascading failure is spreading more readily in CPPS, even leading to blackouts as well as there are new difficulties with the power system security simulation and faults brought by physical harm or network intrusions. The current study summarized the cross- integration of several fields such as computer and cyberspace security in terms of the robustness of Cyber-Physical Systems, viewed as Interconnected and secure network systems. Therefore, the security events that significantly influenced the power system were evaluated in this study, besides the challenges and future directions of power system security simulation technologies were investigated for posing both challenges and opportunities for simulation techniques of power system security like building a new power system to accelerate the transformation of the existing energy system to a clean, low-carbon, safe, and efficient energy system which is used to assure power system stability through fusion systems that combine the cyber-physical to integrate the battery power station, power generation and renewable energy resources through the internet with the cyber system that contains Smart energy system control and attacks. © 2022 IEEE.

关键词： Cyber Physical System

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Enhanced Non-Contact Vital Sign Monitoring via Depth Camera-Assisted Millimeter-Wave Radar

Enhanced Non-Contact Vital Sign Monitoring via Depth Camera-...

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2024 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2024

作者： Zhang, Hanwen Dou, Chenglong Liu, Yucheng Wu, Yuan Qian, Liping Shi, Zhiguo Lu, Rongxing University of Macau State Key Laboratory of Internet of Things for Smart City China Zhuhai UM Science and Technology Research Institute Zhuhai China College of Information Engineering Zhejiang University of Technology Hangzhou310023 China College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China University of New Brunswick Faculty of Computer Science FrederictonNBE3B 5A3 Canada

ISBN: (纸本)9798331507886

Non-contact vital sign monitoring with mmWave radar has been regarded as an effective method for identifying lung and heart diseases due to its strong penetration and non-invasive capabilities. Nevertheless, relying solely on millimeter-wave radar for vital sign monitoring is susceptible to interference from multipath reflections, which degrades the measurement accuracy. To address this issue and enhance measurement accuracy, we propose a system design that leverages the depth camera for precise target location and subsequently employs dynamic beamforming techniques to effectively monitor the specified region. The experimental results demonstrate that our proposed system achieves an average error of 2.44 beats per minute (BPM) for heart rate monitoring and 0.22 breaths per minute (BPM) for respiratory rate monitoring. Compared to systems without beamforming, our system reduces the mean error for heart rate monitoring by 4.21 BPM and for respiratory rate monitoring by 0.51 BPM. © 2024 IEEE.

关键词： Heart

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3-D Near-Field Localization by Jointly Exploiting Spatial and Temporal Information Based on a Nonuniform Cross Array

3-D Near-Field Localization by Jointly Exploiting Spatial an...

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

作者： Zelong Yi Hua Chen Zhiwei Jiang Wei Liu Qing Wang Gang Wang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo China School of Electronic Engineering and Computer Science Queen Mary University of London London UK School of Electronic Informatin Engineering Tianjin University Tianjin China

In this paper, an underdetermined three-dimensional (3-D) near-field source localization method is proposed, based on a two-dimensional (2-D) symmetric nonuniform cross array. Firstly, the fourth-order cumulant of the near-field observations with multiple delay lags is exploited to construct virtual far-field pseudo-observations, leading to increased degrees of freedom (DOF); then, 2-D angles of the nearfield sources are jointly estimated by employing the recently proposed sparse and parametric approach (SPA) and Vandermonde decomposition technique, eliminating the need for parameter discretization. To estimate the range term, the one-dimensional (1-D) MUSIC algorithm is applied by resorting to the conjugate symmetry property of the signal's autocorrelation function. Numerical results are provided to demonstrate the superiority of our method.

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Area Recognition Based on Grid Structure for Rice Paddy Monitoring Using Wireless Sensor Network

Area Recognition Based on Grid Structure for Rice Paddy Moni...

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International Conference on Information technology, Information Systems and Electrical engineering (ICITISEE)

作者： Bambang Haryanto Marpaung Benny Benyamin Nasution Tulus Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Electronic Engineering at State Polytechnic of Medan Politeknik Negeri Medan Medan Indonesia

ISBN: (数字)9798350368970

ISBN: (纸本)9798350368987

In the era of precision agriculture, effective and efficient monitoring of rice paddy fields is vital for optimizing crop yield and ensuring environmental sustainability. This study presents a novel approach utilizing a grid-structured Wireless Sensor Network (WSN) to monitor key environmental parameters such as soil moisture, temperature, and methane gas concentration. The novelty of this research lies in the detailed implementation of a grid-based sensor system that provides comprehensive coverage, enhanced data precision, and integration with artificial intelligence (AI) for predictive analysis. This system not only enables realtime monitoring but also generates actionable insights through a color-coded alert system that signals abnormal conditions such as excessive heat or harmful gas levels. The study demonstrates significant improvements in resource efficiency, including water management and reduced chemical usage, resulting in higher crop yields. The results highlight the potential for grid-based WSN systems to drive sustainable agriculture, offering precise interventions based on real-time environmental data.

关键词： Temperature sensors Methane Wireless communication Wireless sensor networks Green products Production Artificial intelligence Monitoring Crop yield Water resources

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