Article
Chemistry, Analytical
Dongyue Wang, Dongzhi Zhang, Qian Mi
Summary: This paper reports a benzene sensor based on Pd-doped CoTiO3/TiO2 nanocomposite, with improved gas sensing performance. The sensor demonstrated remarkable benzene sensing properties, attributed to the formation of CoTiO3/TiO2 p-n heterojunction and catalytic action of Pd. The unique advantage of Pd-CTT nanocomposite for benzene sensing was highlighted in this work.
SENSORS AND ACTUATORS B-CHEMICAL
(2022)
Article
Acoustics
Yufei Ma, Yinqiu Hu, Shunda Qiao, Ziting Lang, Xiaonan Liu, Ying He, Vincenzo Spagnolo
Summary: This paper reports on the performance of quartz tuning fork (QTF) based laser spectroscopy sensing using multiple QTFs. Two resonance frequency matching methods are proposed to avoid degradation of sensor performance. Experimental results validate the effectiveness of the proposed methods.
Article
Biochemical Research Methods
Sarah Battat, David A. Weitz, George M. Whitesides
Summary: This article discusses how the field of microfluidics can increase its impact by improving technologies and enabling new functionalities, focusing on applications in diagnostics, food safety, and materials production. The article identifies technical challenges, including simplifying sample preparation procedures, finding materials for microfluidic device production, and automating the operation of microfluidic devices.
Article
Chemistry, Analytical
Prakash Mohan, Neelakandan Subramani, Youseef Alotaibi, Saleh Alghamdi, Osamah Ibrahim Khalaf, Sakthi Ulaganathan
Summary: This study introduces an improved metaheuristics-based clustering with multihop routing protocol for underwater wireless sensor networks (UWSNs), aiming to improve the energy efficiency and lifetime of UWSNs. The IMCMR-UWSN technique utilizes the chaotic krill head algorithm for clustering and self-adaptive glow worm swarm optimization algorithm for multihop routing, showing superior performance in terms of energy efficiency.
Article
Chemistry, Analytical
Adarsh Vulli, Parvathaneni Naga Srinivasu, Madipally Sai Krishna Sashank, Jana Shafi, Jaeyoung Choi, Muhammad Fazal Ijaz
Summary: This study introduces a new method for automated diagnosis and detection of metastases in breast cancer using the Fast AI framework and the 1-cycle policy, and compares it with previous methods. The proposed model has achieved an accuracy of over 97.4% and surpasses other state-of-the-art methods. Additionally, a mobile application has been developed for prompt diagnosis of metastases in early-stage cancer.
Article
Engineering, Electrical & Electronic
Vijay Shanker Chaudhary, Dharmendra Kumar, Gyan Prakash Mishra, Sneha Sharma, Santosh Kumar
Summary: This paper proposes a photonic crystal fiber (PCF) based plasmonic biosensor for the detection of various blood compositions. The biosensor operates on the surface plasmon resonance (SPR) theory and utilizes gold and titanium dioxide coatings on the PCF to enhance sensitivity. The proposed biosensor has high wavelength sensitivity and can detect different blood compositions based on their refractive index.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Ailiang Lin, Bingzhi Chen, Jiayu Xu, Zheng Zhang, Guangming Lu, David Zhang
Summary: Automatic medical image segmentation has greatly benefited from powerful deep representation learning. This article proposes a novel framework called DS-TransUNet, which incorporates hierarchical swin transformer into the encoder and decoder, enhancing semantic segmentation quality through self-attention computation and dual-scale encoding. The extensive experiments demonstrate the effectiveness of DS-TransUNet and its superiority over state-of-the-art methods in medical image segmentation tasks.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Multidisciplinary
Dong H. Kang, Young-Jin Cha
Summary: In this paper, a novel semantic transformer representation network (STRNet) is developed for crack segmentation with fast processing speed and high performance. The network is trained and tested in complex scenes, achieving high precision, recall, F1 score, and mIoU. Comparing with other advanced networks, STRNet shows the best performance in evaluation metrics with the fastest processing speed.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2022)
Article
Engineering, Multidisciplinary
Hongfeng Tao, Long Cheng, Jier Qiu, Vladimir Stojanovic
Summary: With the rapid development of industrial informatization and deep learning technology, modern data-driven fault diagnosis methods based on deep learning have attracted attention from the industry. However, the scarcity of fault samples in actual industrial environments and cross-domain problems between different devices limit the development of these methods. This paper proposes a model unknown matching network model for fault diagnosis with few samples, which combines parameter optimization and feature metric to address these limitations and achieves promising results in experiments.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2022)
Article
Automation & Control Systems
Zhitai Liu, Weiyang Lin, Xinghu Yu, Juan J. Rodriguez-Andina, Huijun Gao
Summary: This article proposes an approximation-free robust synchronization control scheme for dual-linear-motors-driven systems. It achieves high-precision tracking and synchronization performance without requiring explicit system model, reducing computational burden and complexity. The concept of prescribed performance is adopted to guarantee control effect and state constraints.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Automation & Control Systems
Zhijian Wang, Xinxin He, Bin Yang, Naipeng Li
Summary: Due to data distribution discrepancy, fault diagnosis models trained in one scene may fail in classifying data from other scenes. To address this issue, we propose a new model called SATLN, which combines subdomain adaptation and domain adaptation techniques to reduce both marginal and conditional distribution biases, improving classification performance and generalization.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Engineering, Multidisciplinary
Tabjula L. Jagadeeshwar, Sheetal Kalyani, Prabhu Rajagopal, Balaji Srinivasan
Summary: In this study, a baseline-free statistical approach based on the resonant cavity phenomenon is proposed for the identification and localization of delamination in composite structures. The proposed method utilizes sparse sampling and density-based spatial clustering of applications with noise (DBSCAN) technique for rapid inspection with minimal human intervention. Simulation and experimental results demonstrate the effectiveness and robustness of the proposed technique in determining the precise location of delamination defects.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2022)
Article
Engineering, Multidisciplinary
Qihang Li, Danqing Song, Canming Yuan, Wen Nie
Summary: This study simulated the deformation process of a large and steep rock slope in China under variable rainfall, finding that the increased deformation region is positively correlated with increasing pore water pressure and water content values, while the infiltration of rainfall softens weak interlayers and leads to failure of the slope toe first, followed by the middle and upper parts sliding and failing sequentially. The proposed improved region growing segmentation method showed a significantly reduced average identification error in X and Y directions compared to the original method, indicating its potential for high-precision identification of rock slope deformation in complex scenes.
Article
Acoustics
Shunda Qiao, Angelo Sampaolo, Pietro Patimisco, Vincenzo Spagnolo, Yufei Ma
Summary: In this paper, an ultra-highly sensitive light-induced thermoelastic spectroscopy (LITES) based HCl sensor using a custom low-frequency QTF and a fiber-coupled MPC was demonstrated. The results showed that the low-frequency QTF provided improved signal enhancement compared to a standard QTF, and the fiber-coupled MPC enhanced system robustness. The sensor exhibited an excellent linear response to HCl gas concentration.
Review
Chemistry, Analytical
Shibo Zhang, Yaxuan Li, Shen Zhang, Farzad Shahabi, Stephen Xia, Yu Deng, Nabil Alshurafa
Summary: The development of mobile and wearable devices has enabled various applications that measure and improve our daily lives, such as activity tracking, wellness monitoring, and human-computer interaction. Many of these applications rely on low-power sensors in these devices to perform human activity recognition (HAR). In recent years, deep learning has made significant advancements in HAR on mobile and wearable devices. This paper categorizes and summarizes existing work on deep learning methods for wearables-based HAR, and provides an analysis of the current advancements, developing trends, and major challenges. The paper also presents cutting-edge frontiers and future directions for deep learning-based HAR.
Article
Automation & Control Systems
Ximing Liu, Xin Ma, Rui Feng, Yulin Chen, Yangyang Shi, Shiqiang Zheng
Summary: This article explores a new control scheme to deal with the challenging topic of strong gimbal persistent disturbance torque and plant perturbations in magnetically suspended control moment gyros. The scheme combines a robust controller and an adaptive feedforward controller to handle the multiparameter perturbations and strong persistent disturbances. The stability of the proposed control scheme is verified through analysis and simulations on an MSCMG prototype.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Review
Chemistry, Analytical
Jaya Baranwal, Brajesh Barse, Gianluca Gatto, Gabriela Broncova, Amit Kumar
Summary: Electrochemical sensors are widely used in various industries due to their variable reporting signals and low theoretical detection limits. This review article covers the latest advances and applications of electrochemical sensors in different industries, as well as the role of nanomaterials in their research and advancements.
Article
Engineering, Aerospace
Martin C. Weisskopf, Paolo Soffitta, Luca Baldini, Brian D. Ramsey, Stephen L. O'Dell, Roger W. Romani, Giorgio Matt, William D. Deininger, Wayne H. Baumgartner, Ronaldo Bellazzini, Enrico Costa, Jeffery J. Kolodziejczak, Luca Latronico, Herman L. Marshall, Fabio Muleri, Stephen D. Bongiorno, Allyn Tennant, Niccolo Bucciantini, Michal Dovciak, Frederic Marin, Alan Marscher, Juri Poutanen, Pat Slane, Roberto Turolla, William Kalinowski, Alessandro Di Marco, Sergio Fabiani, Massimo Minuti, Fabio La Monaca, Michele Pinchera, John Rankin, Carmelo Sgro', Alessio Trois, Fei Xie, Cheryl Alexander, D. Zachery Allen, Fabrizio Amici, Jason Andersen, Angelo Antonelli, Spencer Antoniak, Primo Attina, Mattia Barbanera, Matteo Bachetti, Randy M. Baggett, Jeff Bladt, Alessandro Brez, Raffaella Bonino, Christopher Boree, Fabio Borotto, Shawn Breeding, Daniele Brienza, H. Kyle Bygott, Ciro Caporale, Claudia Cardelli, Rita Carpentiero, Simone Castellano, Marco Castronuovo, Luca Cavalli, Elisabetta Cavazzuti, Marco Ceccanti, Mauro Centrone, Saverio Citraro, Fabio D'Amico, Elisa D'Alba, Laura Di Gesu, Ettore Del Monte, Kurtis L. Dietz, Niccolo' Di Lalla, Giuseppe Di Persio, David Dolan, Immacolata Donnarumma, Yuri Evangelista, Kevin Ferrant, Riccardo Ferrazzoli, MacKenzie Ferrie, Joseph Footdale, Brent Forsyth, Michelle Foster, Benjamin Garelick, Shuichi Gunji, Eli Gurnee, Michael Head, Grant Hibbard, Samantha Johnson, Erik Kelly, Kiranmayee Kilaru, Carlo Lefevre, Shelley Le Roy, Pasqualino Loffredo, Paolo Lorenzi, Leonardo Lucchesi, Tyler Maddox, Guido Magazzu, Simone Maldera, Alberto Manfreda, Elio Mangraviti, Marco Marengo, Alessandra Marrocchesi, Francesco Massaro, David Mauger, Jeffrey McCracken, Michael McEachen, Rondal Mize, Paolo Mereu, Scott Mitchell, Ikuyuki Mitsuishi, Alfredo Morbidini, Federico Mosti, Hikmat Nasimi, Barbara Negri, Michela Negro, Toan Nguyen, Isaac Nitschke, Alessio Nuti, Mitch Onizuka, Chiara Oppedisano, Leonardo Orsini, Darren Osborne, Richard Pacheco, Alessandro Paggi, Will Painter, Steven D. Pavelitz, Christina Pentz, Raffaele Piazzolla, Matteo Perri, Melissa Pesce-Rollins, Colin Peterson, Maura Pilia, Alessandro Profeti, Simonetta Puccetti, Jaganathan Ranganathan, Ajay Ratheesh, Lee Reedy, Noah Root, Alda Rubini, Stephanie Ruswick, Javier Sanchez, Paolo Sarra, Francesco Santoli, Emanuele Scalise, Andrea Sciortino, Christopher Schroeder, Tim Seek, Kalie Sosdian, Gloria Spandre, Chet O. Speegle, Toru Tamagawa, Marcello Tardiola, Antonino Tobia, Nicholas E. Thomas, Robert Valerie, Marco Vimercati, Amy L. Walden, Bruce Weddendorf, Jeffrey Wedmore, David Welch, Davide Zanetti, Francesco Zanetti
Summary: The Imaging X-ray Polarimetry Explorer (IXPE) is a collaborative mission between NASA and the Italian Space Agency (ASI) that aims to investigate imaging X-ray polarimetry. It features three identical telescopes with polarization-sensitive imaging X-ray detectors, and will conduct precise polarimetry for a 2-year baseline mission.
JOURNAL OF ASTRONOMICAL TELESCOPES INSTRUMENTS AND SYSTEMS
(2022)
Review
Instruments & Instrumentation
Snezana Dordevic, Maria Medel Gonzalez, Inmaculada Conejos-Sanchez, Barbara Carreira, Sabina Pozzi, Rita C. Acurcio, Ronit Satchi-Fainaro, Helena F. Florindo, Maria J. Vicent
Summary: The field of nanomedicine faces challenges in regulatory clarity and consistency. Developing nanomedicines requires considerations of critical quality attributes, appropriate analytical methods, important process parameters, and pre-clinical models. Close collaboration with regulatory agencies is advised to accelerate the development of future nanomedicines.
DRUG DELIVERY AND TRANSLATIONAL RESEARCH
(2022)
Article
Automation & Control Systems
Jian Hu, Hongwen He, Zhongbao Wei, Yang Li
Summary: This article proposes a novel ISC diagnostic method that utilizes polarization dynamics instead of conventional charge depletion. The method demonstrates high robustness to measurement disturbances and battery aging. The recursive total least squares method is used to mitigate the adverse effect of measurement disturbances and achieve unbiased estimation of the ISC resistance. The proposed method is validated theoretically and experimentally for high diagnostic accuracy and strong robustness to battery degradation and disturbance.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
