Review
Automation & Control Systems
Tianci Zhang, Jinglong Chen, Fudong Li, Kaiyu Zhang, Haixin Lv, Shuilong He, Enyong Xu
Summary: Research on intelligent fault diagnosis using artificial intelligence technologies has achieved significant progress, particularly in the field of S&I-IFD. Existing strategies include data augmentation, feature learning, and classifier design. Future research directions involve meta-learning and zero-shot learning.
Article
Instruments & Instrumentation
Lea-Adriana Keller, Olivia Merkel, Andreas Popp
Summary: In the last decade, there has been a growing interest in intranasal drug delivery in pharmaceutical R&D. This review article highlights the advantages of nasal delivery for local and systemic drug delivery, as well as for CNS indications, compared to conventional systemic approaches. However, formulation limitations and toxicological considerations remain areas that need further optimization in this field.
DRUG DELIVERY AND TRANSLATIONAL RESEARCH
(2022)
Article
Chemistry, Analytical
Pavel Trojovsky, Mohammad Dehghani
Summary: This paper introduces a new stochastic nature-inspired optimization algorithm called Pelican Optimization Algorithm (POA) to solve optimization problems in various scientific disciplines. By simulating the natural behavior of pelicans during hunting, the POA demonstrates high performance in approaching optimal solutions for unimodal functions and exploring the main optimal area for multimodal functions. Comparison with eight well-known metaheuristic algorithms confirms the competitiveness of POA in providing optimal solutions for optimization problems.
Article
Chemistry, Analytical
Mamoona Majid, Shaista Habib, Abdul Rehman Javed, Muhammad Rizwan, Gautam Srivastava, Thippa Reddy Gadekallu, Jerry Chun-Wei Lin
Summary: This article introduces the fourth industrial revolution (Industry 4.0) and its applications in the fields of Internet of Things (IoT) and wireless sensor networks (WSN), discusses the various issues and future directions in this area, and provides a systematic literature review of relevant research in recent years.
Article
Engineering, Electrical & Electronic
Nianyin Zeng, Peishu Wu, Zidong Wang, Han Li, Weibo Liu, Xiaohui Liu
Summary: In this article, a novel enhanced multiscale feature fusion method called ABFPN is proposed to improve the detection performance of small objects. It is evaluated on benchmark datasets and applied to detect surface defects on printed circuit boards. Experimental results demonstrate its reliability and efficiency.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Chemistry, Analytical
Qianyi Shangguan, Zihao Chen, Hua Yang, Shubo Cheng, Wenxing Yang, Zao Yi, Xianwen Wu, Shifa Wang, Yougen Yi, Pinghui Wu
Summary: The paper proposes an ultra-narrow band graphene refractive index sensor with high absorption efficiency, adjustability, and sensitivity, which can be applied to photon detection in the terahertz band and biochemical sensing.
Article
Chemistry, Analytical
Upesh Nepal, Hossein Eslamiat
Summary: In-flight system failure is a safety concern for unmanned aerial vehicles (UAVs) in urban environments. This paper investigates the feasibility of using object detection methods to find safe landing spots for UAVs suffering from in-flight failures. Different versions of the YOLO objection detection method are compared, and the YOLOv5l algorithm is found to outperform YOLOv4 and YOLOv3 in terms of detection accuracy.
Article
Instruments & Instrumentation
Delly Ramadon, Maeliosa T. C. McCrudden, Aaron J. Courtenay, Ryan F. Donnelly
Summary: Transdermal drug delivery systems have become an intriguing research topic in pharmaceutical technology area and one of the most frequently developed pharmaceutical products in global market. This article reviews the current trends, and future applications of transdermal technologies, with specific focus on providing a comprehensive understanding of transdermal drug delivery systems and enhancement strategies. The use of microneedle technology has shown promising results in improving transdermal delivery systems, with opportunities for intradermal delivery of drugs/biotherapeutics and therapeutic drug monitoring.
DRUG DELIVERY AND TRANSLATIONAL RESEARCH
(2022)
Article
Chemistry, Analytical
A. Abbasi, W. Farooq, El Sayed Mohamed Tag-ElDin, Sami Ullah Khan, M. Ijaz Khan, Kamel Guedri, Samia Elattar, M. Waqas, Ahmed M. Galal
Summary: This study numerically investigates the blood flow in a complex wavy curved channel in the presence of hybrid nanoparticles. The results reveal that the concentration of nanoparticles reduces the velocity of the blood and assists in the non-uniform channel core. Moreover, the volume fraction of nanoparticles and the dimensionless curvature of the channel decrease the temperature profile.
Article
Instruments & Instrumentation
P. Ajay, B. Nagaraj, R. Arun Kumar, Ruihang Huang, P. Ananthi
Summary: This article presents a novel approach to studying hyperspectral microscopic images using deep learning and effective unsupervised learning, highlighting the significance of deep learning in modern AI.
Article
Automation & Control Systems
Zhiyi He, Haidong Shao, Ziyang Ding, Hongkai Jiang, Junsheng Cheng
Summary: This article proposes a modified deep autoencoder method driven by multi-source parameters for fault prognosis of aeroengines. The method utilizes a fused health index to characterize performance degradation and establishes accurate mapping hidden in the health index using adaptive Morlet wavelet. Parameter transfer learning is used to enable the model to have cross-domain fault prognosis capability.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Automation & Control Systems
Zhongbao Wei, Zhongyi Quan, Jingda Wu, Yang Li, Josep Pou, Hao Zhong
Summary: This article proposes a knowledge-based and multiphysics-constrained fast charging strategy for lithium-ion batteries, which takes into account thermal safety and degradation. The proposed strategy combines a model-based state observer with a deep reinforcement learning-based optimizer to provide a solution for fast charging. Experimental results demonstrate the superiority of the proposed strategy in terms of charging speed, thermal safety, and battery life extension.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Engineering, Electrical & Electronic
Ling Xu, Feng Ding, Quanmin Zhu
Summary: This article presents a high-precision signal modeling algorithm based on a parameter separation scheme for combinational signals and periodic signals, implemented through gradient search. Research shows that the SS iterative signal modeling algorithm can effectively estimate combinational signals with multiple frequencies and periodic signals.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Wu Deng, Zhongxian Li, Xinyan Li, Huayue Chen, Huimin Zhao
Summary: This article proposes a novel compound fault diagnosis method MDSRCFD based on optimized MCKD and sparse representation, which separates and extracts the compound fault characteristics of rolling bearings through parameter optimization using intelligent optimization algorithms. The simulation and practical application results demonstrate that this method achieves accurate compound fault diagnosis.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Multidisciplinary
Mahmoud Elsisi, Minh-Quang Tran, Karar Mahmoud, Diaa-Eldin A. Mansour, Matti Lehtonen, Mohamed M. F. Darwish
Summary: This paper introduces a method that integrates Internet of Things (IoT) architecture with deep learning for online monitoring of power transformer status and protection against cyberattacks. Experimental results confirm the effectiveness of the proposed method.
Review
Engineering, Multidisciplinary
Arman Malekloo, Ekin Ozer, Mohammad AlHamaydeh, Mark Girolami
Summary: Conventional damage detection techniques are being replaced by advanced smart monitoring and decision-making solutions in the age of smart cities, Internet of Things, and big data analytics. Machine learning algorithms are offering tools to enhance the capabilities of structural health monitoring systems and provide intelligent solutions for challenges of the past. The future of structural health monitoring systems lies in connecting critical information in infrastructures through the Internet of Things paradigm.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2022)
Review
Chemistry, Analytical
Tao Li, Dawei Shang, Shouwu Gao, Bo Wang, Hao Kong, Guozheng Yang, Weidong Shu, Peilong Xu, Gang Wei
Summary: This review discusses the recent advances in fabrication of 2DM-based electrochemical sensors and biosensors for applications in food safety and biomolecular detection related to human health. It includes the synthesis methods, structure, and surface chemistry of various 2DMs, as well as their applications in detecting nitrite, heavy metal ions, antibiotics, pesticides, and key small molecules for disease monitoring.
Article
Chemistry, Analytical
Ines Chabani, Fateh Mebarek-Oudina, Abdel Aziz I. Ismail
Summary: This study numerically investigates the heat transfer of Cu-TiO2/EG hybrid nano-fluid inside a porous annulus using the multi-physics COMSOL software and the Darcy-Brinkman-Forchheimer model. The results show that, except for the Hartmann number which decelerates the flow rate, all other parameters have a positive impact on the thermal transmission rate.
Article
Chemistry, Analytical
Muhammad Faizan Ahmed, A. Zaib, Farhan Ali, Omar T. Bafakeeh, El Sayed Mohamed Tag-ElDin, Kamel Guedri, Samia Elattar, Muhammad Ijaz Khan
Summary: This study conducted a numerical investigation of time-dependent magneto-hydro-dynamics (MHD) Eyring-Powell liquid, considering thermal radiation and the regulation of floating nanoparticles using bioconvection. The study found that bioconvection can stabilize nanoparticles and impact the velocity field and dynamic density distribution.
Article
Chemistry, Analytical
Neelakandan Subramani, Prakash Mohan, Youseef Alotaibi, Saleh Alghamdi, Osamah Ibrahim Khalaf
Summary: In recent years, the underwater wireless sensor network (UWSN) has gained significant attention for various applications. Energy efficiency is a major challenge for UWSN due to restricted sensor energy and the difficulty of recharging or replacing batteries. This study focuses on designing a metaheuristics-based clustering and routing protocol called MCR-UWSN, which addresses the issues of underwater current, low bandwidth, high water pressure, propagation delay, and error probability. By utilizing cultural emperor penguin optimizer-based clustering (CEPOC) and grasshopper optimization (MHR-GOA) for routing, the MCR-UWSN technique demonstrates improved performance compared to existing techniques.
