Review
Computer Science, Information Systems
Ali Ghubaish, Tara Salman, Maede Zolanvari, Devrim Unal, Abdulla Al-Ali, Raj Jain
Summary: The advancements in Internet of Things (IoT) technologies have transformed the healthcare industry through remote patient monitoring, enhancing patient care efficiency. Yet, the security of these systems remains a major challenge, requiring robust measures to safeguard data.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Materials Science, Multidisciplinary
Aleksandra Gridyakina, Natalia Kasian, Mi losz S. Chych Lowski, Marta Kajkowska, Piotr Lesiak
Summary: Multicomponent liquid crystal systems are of great interest in scientific research and practical applications. By combining liquid crystals, polymers, and nanoparticles into a three-component system, it is possible to optimize the performance in display applications and expand the applications of multicomponent systems.
MATERIALS TODAY PHYSICS
(2023)
Article
Automation & Control Systems
Jiancun Wu, Chen Peng, Hongchenyu Yang, Yu-Long Wang
Summary: This paper provides a survey of recent advances in event-triggered security control for networked control systems under malicious attacks. It elaborates on cyber-attacks from the communication layer, reviews secure control results, and analyzes improved event-triggered strategies resilient to cyber-attacks. The paper also explores the application of part event-triggered secure resilient control to power systems and presents challenging issues for future research in the field.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2022)
Article
Engineering, Electrical & Electronic
Yuanqing Xia, Yuan Zhang, Li Dai, Yufeng Zhan, Zehua Guo
Summary: Networked control systems (NCSs) play a crucial role in the Internet of Things (IoTs) for creating interactive and responsive intelligent environments. However, traditional NCSs face challenges in handling big data collection, storage, and analysis in large-scale IoT applications. To address these challenges, cloud control systems (CCSs), a new paradigm of NCSs, have been proposed. This article surveys recent advances in CCSs and presents a taxonomy of existing results, including cloud control perspectives, security and privacy, and CCSs for industry automation. Future directions for designing more efficient and practical CCSs are also discussed.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2022)
Review
Engineering, Electrical & Electronic
Hyun Woo Song, Wonbin Choi, Taesu Jeon, Joon Hak Oh
Summary: The development of the Internet of Things and artificial intelligence has sparked significant interest in using various sensing techniques to gather information. This review presents the research trends and prospects for sensing technologies based on organic materials, which collect information from the environment through the Internet of Things. Cutting-edge chemical, optical, and physical organic sensors show great potential in creating smart environmental systems with IoT network platforms.
ACS APPLIED ELECTRONIC MATERIALS
(2023)
Review
Chemistry, Physical
Sandhya Venkateshalu, Mohammed Shariq, Byeongyoon Kim, Monika Patel, Kajal Shakil Mahabari, Sang-Il Choi, Nitin K. Chaudhari, Andrews Nirmala Grace, Kwangyeol Lee
Summary: Since the discovery of Ti3C2Tx, the research on 2D transition metal carbides and nitrides (MXenes) has rapidly increased. While most reports focus on Ti-based MXenes, recent studies have revealed intriguing properties in MXenes beyond Ti-only systems. This forward-looking review summarizes the trends, synthesis, properties, and applications of non-Ti MXenes, aiming to encourage researchers to explore their characteristics and unleash their full potential. The review also highlights theoretically predicted non-Ti MXenes to stimulate further experimental research. Finally, it presents challenges to be addressed and future research directions.
JOURNAL OF MATERIALS CHEMISTRY A
(2023)
Review
Chemistry, Analytical
Ailar Nakhlband, Houman Kholafazad-Kordasht, Mahdi Rahimi, Ahad Mokhtarzadeh, Jafar Soleymani
Summary: Various types of magnetic materials demonstrate high potential for exploitation in scientific applications such as bioimaging, catalysis, and energy storage. Advancement in point-of-care detection methods like microfluidics has led to the development of portable sensing devices with short response times and automated capabilities.
MICROCHEMICAL JOURNAL
(2022)
Review
Optics
Andre D. Gomes, Hartmut Bartelt, Orlando Frazao
Summary: The optical Vernier effect enhances sensitivity and resolution of fiber sensors by generating magnified sensing capabilities in the output spectrum. This effect relies on the overlap between signals of two slightly detuned interferometers, leading to a new generation of highly sensitive sensing devices.
LASER & PHOTONICS REVIEWS
(2021)
Article
Computer Science, Artificial Intelligence
Zhimin Zhang, Huansheng Ning, Feifei Shi, Fadi Farha, Yang Xu, Jiabo Xu, Fan Zhang, Kim-Kwang Raymond Choo
Summary: This paper reviews the applications of artificial intelligence in cybersecurity, such as user access authentication, network situation awareness, dangerous behavior monitoring, and abnormal traffic identification. It also proposes a conceptual human-in-the-loop intelligence cybersecurity model based on identified limitations and challenges.
ARTIFICIAL INTELLIGENCE REVIEW
(2022)
Article
Engineering, Electrical & Electronic
Yiling Liu, Yanqiong Wang, Xi Yang, Chao-Yang Gong, Yuan Gong
Summary: This review article summarizes the recent advances in optofluidic lasers (OFLs) and their applications in biochemical analysis. OFLs achieve high performance in bio-chemical sensing due to the strong light-matter interaction in the laser cavity. The physical mechanisms, structure, and materials used in OFLs to achieve high sensitivity, disposability, fast response, and high throughput are discussed, as well as the inter-relationship between these performance indicators. The effects of new materials and a comparison with other optical biochemical sensors are also presented, along with the prospects of OFLs.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2023)
Article
Chemistry, Analytical
Pantea Nadimi Goki, Thomas Teferi Mulugeta, Roberto Caldelli, Luca Poti
Summary: This paper introduces a technique of generating and reading digital signatures for fiber-optic pigtails in order to enhance physical layer security. The signatures are attributed to networks and devices for easy identification and authentication, reducing vulnerability to attacks. The use of an optical physical unclonable function (OPUF) ensures robustness against tampering and cyber attacks. The Rayleigh backscattering signal (RBS) is investigated as a strong OPUF for generating reliable signatures.
Article
Chemistry, Multidisciplinary
Junjun Liu, Lin Yang, Ping Qin, Shiqing Zhang, Ken Kin Lam Yung, Zhifeng Huang
Summary: Inorganic nanoparticles are a versatile platform for biomedical applications, particularly in the study and application of chiral effects. Recent research focuses on characterizing 3D stereochirality, bionic fabrication of hierarchical chirality, studying optical activities, and experimental demonstration in biomedical applications. These studies pave the way for fully understanding and utilizing chiral effects in the design and fabrication of inorganic chiral nanoparticles for practical problem-solving in environment and public health.
ADVANCED MATERIALS
(2021)
Review
Engineering, Electrical & Electronic
Amjad Omar, Sara AlMaeeni, Hussain Attia, Maen Takruri, Ahmed Altunaiji, Mihai Sanduleanu, Raed Shubair, Moh'd Sami Ashhab, Maryam Al Ali, Ghaya Al Hebsi
Summary: This paper discusses the current research status of smart street lighting systems, comparing multiple published studies and highlighting the limitations of each system. Current and future trends are also mentioned.
JOURNAL OF SENSORS
(2022)
Article
Optics
Kavan Ahmadi, Artur Carnicer
Summary: The paper aims to implement an optically-based visual encryption system that can work with a large set of optical codes. The system consists of a holographic system and an imaging module, with a trained neural network for encryption and decryption.
OPTICS AND LASERS IN ENGINEERING
(2023)
Review
Chemistry, Multidisciplinary
Salah M. Tawfik, Shavkatjon Azizov, Mohamed R. Elmasry, Mirkomil Sharipov, Yong-Ill Lee
Summary: Nanomicelles as drug carriers show potential in selective and efficient drug delivery, forming organized structures through self-assembly and releasing drugs in response to various stimuli. The properties of core and corona forming blocks determine the size and shape of nanomicelles.
Article
Engineering, Electrical & Electronic
Tiantian Yin, Chao-Fu Wang, Kuiwen Xu, Yulong Zhou, Yu Zhong, Xudong Chen
Summary: Inspired by volume integral equation and method of moments, this paper proposes an electric flux density learning method (EFDLM) using cascaded neural networks to solve 3-D electromagnetic scattering problems involving lossless dielectric objects. The EFDLM outperforms black-box learning methods and is able to solve scattering problems with higher contrasts by increasing the number of subnetworks.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2022)
Article
Optics
Yin Xiao, Lina Zhou, Zilan Pan, Yonggui Cao, Wen Chen
Summary: In this paper, a method of physically-secured high-fidelity free-space optical data transmission through scattering media using physically- and dynamically-generated scaling factors is proposed. The method ensures high security and fidelity in data transmission.
Article
Optics
Yin Xiao, Lina Zhou, Zilan Pan, Yonggui Cao, Wen Chen
Summary: In this research, a physically enhanced ghost encoding scheme is proposed by utilizing the optical channel characteristics and dynamically generated scaling factors as security keys. The dynamic scaling factors are controlled in the optical path to achieve physical enhancement of ghost encoding. The proposed method introduces a variable beam attenuator and an amplitude-only spatial light modulator (SLM) to generate dynamic scaling factors. Optical experiments are conducted to verify the feasibility and effectiveness of the proposed scheme, which could bring new research perspectives to optical ghost encoding.
Editorial Material
Optics
Wen Chen
Summary: The high degrees of freedom of light and the various optical structures and materials can be utilized to develop optical encryption for information security. A novel optical image encryption approach based on spatial nonlinear optics has been proposed.
LIGHT-SCIENCE & APPLICATIONS
(2022)
Article
Optics
Yin Xiao, Lina Zhou, Zilan Pan, Yonggui Cao, Mo Yang, Wen Chen
Summary: This study introduces an approach for high-fidelity optical transmission in free space through scattering media using 2D randomly-distributed binary patterns. By utilizing ghost diffraction, high-fidelity signals can be transmitted without complex post-processing algorithms. This method shows high robustness and flexibility for various applications in free-space optical data transmission and communication.
OPTICS AND LASERS IN ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Yulong Zhou, Ning Leng, Zhun Wei, Xiuzhu Ye, Ming Bai, Xudong Chen
Summary: This article proposes a systematic material characterization method via the coaxial resonator-based near-field scanning microwave microscopy. By studying the effective interaction region and applying Huygens' principle, the method can accurately extract the permittivity of homogeneous samples.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2022)
Article
Engineering, Electrical & Electronic
Kai Tan, Tiantian Yin, Hongning Ruan, Siegfred Balon, Xudong Chen
Summary: This article proposes a high-accuracy and efficient classification method using machine learning techniques on FMCW radar. By establishing a novel mapping relationship and extracting four physical features, a multilayer perceptron is employed for classification, resulting in real-time operation. The proposed physics-assisted classifier outperforms the state of the art in automotive radar applications, achieving an overall accuracy of about 99% even with complex multiple-target cases.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2022)
Article
Engineering, Electrical & Electronic
Amartansh Dubey, Xudong Chen, Ross Murch
Summary: We propose a correction to the conventional Rytov approximation and investigate its performance in predicting wave scattering. The correction incorporates high-frequency theory of inhomogeneous wave propagation for lossy media into the Rytov approximation. Numerical investigation shows that the corrected model has a larger validity range in predicting wave scattering.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2022)
Article
Engineering, Electrical & Electronic
Tiantian Yin, Li Pan, Xudong Chen
Summary: In this article, a novel non-iterative method, called the subspace-Rytov approximation (SRA) method, is proposed to solve inverse scattering problems. This method improves the inversion results by retaining the neglected integral term in the Rytov approximation. The SRA method calculates the major part of the integrand using the subspace method and approximates the integration on the whole space by truncation. Experimental results show that the SRA method outperforms other commonly used methods.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2022)
Article
Engineering, Electrical & Electronic
Yulong Zhou, Ning Leng, Zhun Wei, Tiantian Yin, Ming Bai, Xudong Chen
Summary: This article presents a physics-assisted learning scheme (PALS) for quantitative imaging using near-field scanning microwave microscopy (NFSMM) in a nondestructive way, which is important for analyzing and evaluating the dielectric properties of investigated samples accurately. By utilizing the Rayleigh approximation method, an efficient input generation is achieved to avoid black-box usage of machine learning. Numerical and experimental examples demonstrate that the proposed PALS recovers the dielectric parameters of subsurface perturbation more accurately and exhibits better generalization ability. This learning scheme provides a reasonable approach to integrate machine learning with underlying physics in NFSMM, instead of blindly utilizing machine learning. The same principle is potentially applicable to other types of scanning microscopies, such as optical and thermal ones.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2023)
Article
Engineering, Electrical & Electronic
Yulong Zhou, Ning Leng, Zhun Wei, Xiuzhu Ye, Tiantian Yin, Ming Bai, Xudong Chen
Summary: This research proposes a learning-based method for quantitative subsurface imaging using near-field scanning microwave microscopy. The method improves image resolution and recovers dielectric properties of subsurface perturbations. It outperforms traditional methods in terms of resolution and time cost, and has the potential for nondestructive and real-time local dielectric evaluation of subsurface objects.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2022)
Article
Geochemistry & Geophysics
Anqi Gao, Bing Sun, Yukun Guo, Jingwen Li, Chunsheng Li, Xudong Chen
Summary: This article proposes a parameter-adjusting auto-registration overlapped subaperture algorithm (PAAR-OSA) to enlarge the imaging swath of auto-registration. By collaboratively designing the subapertures within each frame and among different frames in the stabilized-scene coordinate and cooperatively compensating the phase error of all frames, auto-registration with larger imaging swath can be achieved.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Yuyue Zhang, Tiantian Yin, Zhiqin Zhao, Zaiping Nie, Xudong Chen
Summary: This article proposes an iterative domain decomposition technique based on the framework of the subspace-based optimization method to solve highly nonlinear inverse scattering problems. The method reduces the nonlinearity of the problem and reconstructs stronger scatterers by reducing the unknowns and considering the different effects of different parts of the scatterers on the scattered fields. The technique can be used repeatedly to improve the reconstruction quality.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Yu Liu, Hao Zhao, Rencheng Song, Xudong Chen, Chang Li, Xun Chen
Summary: This article proposes an unrolling algorithm of the iterative subspace-based optimization method for solving full-wave inverse scattering problems. The unrolling network updates the induced current and the permittivity by imitating iterations, demonstrating good generalization ability and superior performance.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Amartansh Dubey, Samruddhi Deshmukh, Li Pan, Xudong Chen, Ross Murch
Summary: In this study, a high-frequency approximation method is proposed to accurately reconstruct objects with high relative permittivity and large electrical size. The effectiveness and accuracy of the method are demonstrated in RF indoor imaging using phaseless measurements from WiFi nodes.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
