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Recent Advancements in AI-Enabled Smart Electronics Packaging for Structural Health Monitoring

Vinamra Bhushan Sharma, Saurabh Tewari, Susham Biswas, Bharat Lohani, Umakant Dhar Dwivedi, Deepak Dwivedi, Ashutosh Sharma, Jae Pil Jung
2021 Metals  
Three smart data capturing methods of SHM, namely, camera-based, smartphone-based, and unmanned aerial vehicle (UAV)-based methods, are also discussed, having made the utilization of intelligent paradigms  ...  Furthermore, current challenges and future perspectives of AI-based SHM systems are also described separately.  ...  The fusion of 1D CNN-SVM was implemented for the leakage detection and graph-based method for the localization of leakage fault [92, 99] .  ... 
doi:10.3390/met11101537 fatcat:wayx7vsxxrekrgpjrzrmxpqswm

A multistep deep learning framework for the automated detection and segmentation of astrocytes in fluorescent images of brain tissue

Cihan Bilge Kayasandik, Wenjuan Ru, Demetrio Labate
2020 Scientific Reports  
module for cell detection based on multiscale directional filters and a segmentation routine that leverages deep learning and sparse representations to reduce the need of training data and improve performance  ...  To provide an unbiased and accurate framework for the quantitative analysis of fluorescent images of astrocytes, we introduce a new automated image processing pipeline whose main novelties include an innovative  ...  Author contributions D.L. conceived the algorithm pipeline and coordinated the project; C.K. designed and implemented the network architecture, conceived the post-processing stage and conducted the numerical  ... 
doi:10.1038/s41598-020-61953-9 pmid:32198485 fatcat:yyjjpp6ql5ds5orulwpmeiklru

Solving Management Problems in Water Distribution Networks: A Survey of Approaches and Mathematical Models

Oladipupo Bello, Adnan Abu-Mahfouz, Yskandar Hamam, Philip Page, Kazeem Adedeji, Olivier Piller
2019 Water  
Also, new directions for future research studies are suggested to enable water utility managers and researchers to improve the performance of water distribution networks.  ...  This paper presents a detailed review of the management problems and essential mathematical models that are used to address these problems at various phases of WDNs.  ...  Acknowledgments: This research work was supported by Tshwane University of Technology, Pretoria and the Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa.  ... 
doi:10.3390/w11030562 fatcat:xdrzv5j65vcdhdvq3iqtiqz4si

Vulnerabilities in Federated Learning

Nader Bouacida, Prasant Mohapatra
2021 IEEE Access  
A new decentralized training paradigm, known as Federated Learning (FL), enables multiple clients located at different geographical locations to learn a machine learning model collaboratively without sharing  ...  FL is often preferred in learning environments where security and privacy are the key concerns.  ...  The most prominent example of this type of defense is MOCHA [116] , a novel systems-aware optimization framework for federated multi-task learning.  ... 
doi:10.1109/access.2021.3075203 doaj:5e62c955db514036939a1c65011f46b8 fatcat:viv7tij6cffnlev4l52wggkxfe

A Novel Deep Learning Pipeline for Retinal Vessel Detection in Fluorescein Angiography [article]

Li Ding and Mohammad H. Bawany and Ajay E. Kuriyan and Rajeev S. Ramchandran and Charles C. Wykoff and Gaurav Sharma
2019 arXiv   pre-print
We propose a novel pipeline to detect retinal vessels in FA images using deep neural networks that reduces the effort required for generating labeled ground truth data by combining two key components:  ...  Experimental results demonstrate that the proposed pipeline significantly reduces the annotation effort and the resulting deep learning methods outperform prior existing FA vessel detection methods by  ...  The learning rate is fixed as 0.001. The coefficients used for computing running averages of gradient and its square are 0.9 and 0.999, respectively.  ... 
arXiv:1907.02946v1 fatcat:mwl3jofvrremzluqbekebowtwu

2021 Index IEEE Transactions on Instrumentation and Measurement Vol. 70

2021 IEEE Transactions on Instrumentation and Measurement  
Article numbers are based on specified topic areas and corresponding codes associated with the publication.  ...  Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TIM 2021 3510910 A Microwave Measuring System for Detecting and Localizing Anomalies in Metallic Pipelines.  ... 
doi:10.1109/tim.2022.3156705 fatcat:dmqderzenrcopoyipv3v4vh4ry

Perspectives on individual animal identification from biology and computer vision [article]

Maxime Vidal and Nathan Wolf and Beth Rosenberg and Bradley P. Harris and Alexander Mathis
2021 arXiv   pre-print
We conclude by offering recommendations for starting an animal identification project, illustrate current limitations and propose how they might be addressed in the future.  ...  Identifying individual animals is crucial for many biological investigations.  ...  Support for MV, BR, NW, and BPH was provided by Alaska Education Tax  ... 
arXiv:2103.00560v1 fatcat:6xdsiojn7vamxonhwmklse3tja

Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context [article]

Ehsan Toreini, Mhairi Aitken, Kovila P. L. Coopamootoo, Karen Elliott, Vladimiro Gonzalez Zelaya, Paolo Missier, Magdalene Ng, Aad van Moorsel
2022 arXiv   pre-print
We conclude with an identification of open research problems, with a particular focus on the connection between trustworthy machine learning technologies and their implications for individuals and society  ...  As a consequence, we survey in this paper the main technologies with respect to all four of the FEAS properties, for data-centric as well as model-centric stages of the machine learning system life cycle  ...  ACKNOWLEDGMENTS Research supported by UK EPSRC, under grant EP/R033595, "Trust Engineering for the Financial Industry",  ... 
arXiv:2007.08911v3 fatcat:gmswdvel6bdbvg5rvyzb2uygbu

Hardware-assisted Machine Learning in Resource-constrained IoT Environments for Security: Review and Future Prospective

Georgios Kornaros
2022 IEEE Access  
To protect an IoT infrastructure, various solutions look into hardware-based methods for ML-based IoT authentication, access control, secure offloading, and malware detection schemes.  ...  in integrating accelerators and customizing embedded device architectures for effective use of ML-based methods.  ...  Such methods for analyzing and evaluating a device's side-channel security via leakage detection, as well as standards (such as ISO/IEC 17825:2016) that provide a systematic set of leakage detection tests  ... 
doi:10.1109/access.2022.3179047 fatcat:damwrncpzzbxzamtghwlmrg6v4

Perspectives on individual animal identification from biology and computer vision

Maxime Vidal, Nathan Wolf, Beth Rosenberg, Bradley P Harris, Alexander Mathis
2021 Integrative and Comparative Biology  
We conclude by offering recommendations for starting an animal identification project, illustrate current limitations and propose how they might be addressed in the future.  ...  Identifying individual animals is crucial for many biological investigations.  ...  Computational pipelines for animal identification consist of a sensor and modules for feature extraction, decision-making, and a system database (Fig. 1c ; Jain et al. 2007) .  ... 
doi:10.1093/icb/icab107 pmid:34050741 pmcid:PMC8490693 fatcat:zp32mrr56fcvda4ubc3r2xotja

Decentralized Deep Learning for Multi-Access Edge Computing: A Survey on Communication Efficiency and Trustworthiness [article]

Yuwei Sun, Hideya Ochiai, Hiroshi Esaki
2021 arXiv   pre-print
Decentralized deep learning (DDL) such as federated learning and swarm learning as a promising solution to privacy-preserving data processing for millions of smart edge devices, leverages distributed computing  ...  of multi-layer neural networks within the networking of local clients, whereas, without disclosing the original local training data.  ...  For example, Cao et al. [54] presented produce crispier samples to train a local DL model using the a Euclidean distance-based malicious local model detection.  ... 
arXiv:2108.03980v4 fatcat:3chrjozkxrdzljthkjzlagg6uy

Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges

Muhammad Usama, Junaid Qadir, Aunn Raza, Hunain Arif, Kok-lim Alvin Yau, Yehia Elkhatib, Amir Hussain, Ala Al-Fuqaha
2019 IEEE Access  
In addition, unsupervised learning can unconstrain us from the need for labeled data and manual handcrafted feature engineering, thereby facilitating flexible, general, and automated methods of machine  ...  While a few survey papers focusing on applications of machine learning in networking have previously been published, a survey of similar scope and breadth is missing in the literature.  ...  [252] proposed a manifold learning based visualization tool for network traffic visualization and anomaly detection.  ... 
doi:10.1109/access.2019.2916648 fatcat:xutxh3neynh4bgcsmugxsclkna

Recommendations and future directions for supervised machine learning in psychiatry

Micah Cearns, Tim Hahn, Bernhard T. Baune
2019 Translational Psychiatry  
systems, and finally, future directions for our field.  ...  methods, recommendations, and future directions for applied machine learning in psychiatry.  ...  construction, optimization, and evaluation), and Auto Keras 51 (an opensource package based on TensorFlow for neural network architecture search).  ... 
doi:10.1038/s41398-019-0607-2 pmid:31641106 pmcid:PMC6805872 fatcat:lcq5ztlwbbetpilpim24jmocyi

Deep Learning in Mobile and Wireless Networking: A Survey

Chaoyun Zhang, Paul Patras, Hamed Haddadi
2019 IEEE Communications Surveys and Tutorials  
In this paper we bridge the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas.  ...  Subsequently, we provide an encyclopedic review of mobile and wireless networking research based on deep learning, which we categorize by different domains.  ...  Kang et al. shed light water leakage and localization in water distribution systems [354] . They represent the water pipeline network as a graph and assume leakage events occur at vertices.  ... 
doi:10.1109/comst.2019.2904897 fatcat:xmmrndjbsfdetpa5ef5e3v4xda

Secure and Provenance Enhanced Internet of Health Things Framework: A Blockchain Managed Federated Learning Approach

Md. Abdur Rahman, M. Shamim Hossain, M. Saiful Islam, Nabil A. Alrajeh, Ghulam Muhammad
2020 IEEE Access  
ACKNOWLEDGMENT The authors extend their appreciation to the Deputyship for Research & Innovation, "Ministry of Education "in Saudi  ...  The authors in [15] developed a private data leakage method in an FL environment.  ...  The edge nodes have a GPU and own local, private data for local training and inferencing.  ... 
doi:10.1109/access.2020.3037474 fatcat:6il44yktnjd4pak2y2rzlnvjdm
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