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Total 2011 results found since Jan 2013.

Sensors, Vol. 23, Pages 4430: Enhancing Intrusion Detection Systems for IoT and Cloud Environments Using a Growth Optimizer Algorithm and Conventional Neural Networks
eh Alresheedi Intrusion detection systems (IDS) play a crucial role in securing networks and identifying malicious activity. This is a critical problem in cyber security. In recent years, metaheuristic optimization algorithms and deep learning techniques have been applied to IDS to improve their accuracy and efficiency. Generally, optimization algorithms can be used to boost the performance of IDS models. Deep learning methods, such as convolutional neural networks, have also been used to improve the ability of IDS to detect and classify intrusions. In this paper, we propose a new IDS model based on the combination of ...
Source: Sensors - April 30, 2023 Category: Biotechnology Authors: Abdulaziz Fatani Abdelghani Dahou Mohamed Abd Elaziz Mohammed A. A. Al-qaness Songfeng Lu Saad Ali Alfadhli Shayem Saleh Alresheedi Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4402: extendGAN: Transferable Data Augmentation Framework Using WGAN-GP for Data-Driven Indoor Localisation Model+
Lye Oh For indoor localisation, a challenge in data-driven localisation is to ensure sufficient data to train the prediction model to produce a good accuracy. However, for WiFi-based data collection, human effort is still required to capture a large amount of data as the representation Received Signal Strength (RSS) could easily be affected by obstacles and other factors. In this paper, we propose an extendGAN+ pipeline that leverages up-sampling with the Dirichlet distribution to improve location prediction accuracy with small sample sizes, applies transferred WGAN-GP for synthetic data generation, and ensures data q...
Source: Sensors - April 30, 2023 Category: Biotechnology Authors: Seanglidet Yean Wayne Goh Bu-Sung Lee Hong Lye Oh Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4402: extendGAN+: Transferable Data Augmentation Framework Using WGAN-GP for Data-Driven Indoor Localisation Model
Lye Oh For indoor localisation, a challenge in data-driven localisation is to ensure sufficient data to train the prediction model to produce a good accuracy. However, for WiFi-based data collection, human effort is still required to capture a large amount of data as the representation Received Signal Strength (RSS) could easily be affected by obstacles and other factors. In this paper, we propose an extendGAN+ pipeline that leverages up-sampling with the Dirichlet distribution to improve location prediction accuracy with small sample sizes, applies transferred WGAN-GP for synthetic data generation, and ensures data qu...
Source: Sensors - April 30, 2023 Category: Biotechnology Authors: Seanglidet Yean   Wayne Goh Bu-Sung Lee Hong Lye Oh Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4396: Electrochemical Detection of ompA Gene of C. sakazakii Based on Glucose-Oxidase-Mimicking Nanotags of Gold-Nanoparticles-Doped Copper Metal & ndash;Organic Frameworks
Sensors, Vol. 23, Pages 4396: Electrochemical Detection of ompA Gene of C. sakazakii Based on Glucose-Oxidase-Mimicking Nanotags of Gold-Nanoparticles-Doped Copper Metal–Organic Frameworks Sensors doi: 10.3390/s23094396 Authors: Hongyan Zhang Guiqing Xu Yuming Chen Xu Li Shaopeng Wang Feihao Jiang Pengyang Zhan Chuanfu Lu Xiaodong Cao Yongkang Ye Yunlai Tao The present work developed an electrochemical genosensor for the detection of virulence outer membrane protein A (ompA, tDNA) gene of Cronobacter sakazakii (C. sakazakii) by exploiting the excellent glucose-oxidase-mimicking activit...
Source: Sensors - April 29, 2023 Category: Biotechnology Authors: Hongyan Zhang Guiqing Xu Yuming Chen Xu Li Shaopeng Wang Feihao Jiang Pengyang Zhan Chuanfu Lu Xiaodong Cao Yongkang Ye Yunlai Tao Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4383: Cluster-Locating Algorithm Based on Deep Learning for Silicon Pixel Sensors
In this study, we constructed and compared the performance of one-stage detection algorithms with the representative YOLO (You Only Look Once) framework and two-stage detection algorithms with an RCNN (region-based convolutional neural network). In addition, we also compared transformer-based backbones and CNN-based backbones. The dataset was obtained from a heavy-ion test on a Topmetal-M silicon pixel sensor at HIRFL. Heavy-ion tests were performed on the Topmetal-M silicon pixel sensor to establish the dataset for training and validation. In general, we achieved state-of-the-art results: 68.0% AP (average precision) at a...
Source: Sensors - April 28, 2023 Category: Biotechnology Authors: Fatai Mai Haibo Yang Dong Wang Gang Chen Ruxin Gao Xurong Chen Chengxin Zhao Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4313: Vehicle Logo Recognition Using Spatial Structure Correlation and YOLO-T
aoyu Zhao The vehicle logo contains the vehicle’s identity information, so vehicle logo detection (VLD) technology has extremely important significance. Although the VLD field has been studied for many years, the detection task is still difficult due to the small size of the vehicle logo and the background interference problem. To solve these problems, this paper proposes a method of VLD based on the YOLO-T model and the correlation of the vehicle space structure. Aiming at the small size of the vehicle logo, we propose a vehicle logo detection network called YOLO-T. It integrates multiple receptive field...
Source: Sensors - April 27, 2023 Category: Biotechnology Authors: Li Song Weidong Min Linghua Zhou Qi Wang Haoyu Zhao Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4303: ML Approach to Improve the Costs and Reliability of a Wireless Sensor Network
sal Temperature-controlled closed-loop systems are vital to the transportation of produce. By maintaining specific transportation temperatures and adjusting to environmental factors, these systems delay decomposition. Wireless sensor networks (WSN) can be used to monitor the temperature levels at different locations within these transportation containers and provide feedback to these systems. However, there are a range of unique challenges in WSN implementations, such as the cost of the hardware, implementation difficulties, and the general ruggedness of the environment. This paper presents the novel results of a real-...
Source: Sensors - April 26, 2023 Category: Biotechnology Authors: Mehmet Bugrahan Ayanoglu Ismail Uysal Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4259: Wearable Motion Capture Devices for the Prevention of Work-Related Musculoskeletal Disorders in Ergonomics & mdash;An Overview of Current Applications, Challenges, and Future Opportunities
Sensors, Vol. 23, Pages 4259: Wearable Motion Capture Devices for the Prevention of Work-Related Musculoskeletal Disorders in Ergonomics—An Overview of Current Applications, Challenges, and Future Opportunities Sensors doi: 10.3390/s23094259 Authors: Carl Mikael Lind Farhad Abtahi Mikael Forsman Work-related musculoskeletal disorders (WMSDs) are a major contributor to disability worldwide and substantial societal costs. The use of wearable motion capture instruments has a role in preventing WMSDs by contributing to improvements in exposure and risk assessment and potentially improved effectiveness in ...
Source: Sensors - April 25, 2023 Category: Biotechnology Authors: Carl Mikael Lind Farhad Abtahi Mikael Forsman Tags: Review Source Type: research

Sensors, Vol. 23, Pages 4206: Progressively Hybrid Transformer for Multi-Modal Vehicle Re-Identification
nqing Zhu Multi-modal (i.e., visible, near-infrared, and thermal-infrared) vehicle re-identification has good potential to search vehicles of interest in low illumination. However, due to the fact that different modalities have varying imaging characteristics, a proper multi-modal complementary information fusion is crucial to multi-modal vehicle re-identification. For that, this paper proposes a progressively hybrid transformer (PHT). The PHT method consists of two aspects: random hybrid augmentation (RHA) and a feature hybrid mechanism (FHM). Regarding RHA, an image random cropper and a local region hybrider are desi...
Source: Sensors - April 23, 2023 Category: Biotechnology Authors: Wenjie Pan Linhan Huang Jianbao Liang Lan Hong Jianqing Zhu Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4186: A Practice-Distributed Thunder-Localization System with Crowd-Sourced Smart IoT Devices
ei Wang Lightning localization is of great significance to weather forecasting, forest fire prevention, aviation, military, and other aspects. Traditional lightning localization requires the deployment of base stations and expensive measurement equipment. With the development of IoT technology and the continuous expansion of application scenarios, IoT devices can be interconnected through sensors and other technical means to ultimately achieve the goal of automatic intelligent computing. Therefore, this paper proposes a low-cost distributed thunder-localization system based on IoT smart devices, namely ThunderLoc. The ...
Source: Sensors - April 22, 2023 Category: Biotechnology Authors: Bingxian Lu Ruochen Wang Zhenquan Qin Lei Wang Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4165: Reflective Fiber Temperature Probe Based on Localized Surface Plasmon Resonance towards Low-Cost and Wireless Interrogation
odnicki Reflection fiber temperature sensors functionalized with plasmonic nanocomposite material using intensity-based modulation are demonstrated for the first time. Characteristic temperature optical response of the reflective fiber sensor is experimentally tested using Au-incorporated nanocomposite thin films deposited on the fiber tip, and theoretically validated using a thin-film-optic-based optical waveguide model. By optimizing the Au concentration in a dielectric matrix, Au nanoparticles (NP) exhibit a localized surface plasmon resonance (LSPR) absorption band in a visible wavelength that shows a temperature s...
Source: Sensors - April 21, 2023 Category: Biotechnology Authors: Yang-Duan Su Carter Neal Leatherman Yuankang Wang Paul Richard Ohodnicki Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4124: A Multi-Strategy Improved Sparrow Search Algorithm for Coverage Optimization in a WSN
ihang Zhu To address the problems of low monitoring area coverage rate and the long moving distance of nodes in the process of coverage optimization in wireless sensor networks (WSNs), a multi-strategy improved sparrow search algorithm for coverage optimization in a WSN (IM-DTSSA) is proposed. Firstly, Delaunay triangulation is used to locate the uncovered areas in the network and optimize the initial population of the IM-DTSSA algorithm, which can improve the convergence speed and search accuracy of the algorithm. Secondly, the quality and quantity of the explorer population in the sparrow search algorithm are optimiz...
Source: Sensors - April 20, 2023 Category: Biotechnology Authors: Hui Chen Xu Wang Bin Ge Tian Zhang Zihang Zhu Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4106: Electrochemical and Photoelectrochemical Immunosensors for the Detection of Ovarian Cancer Biomarkers
This article is a review of studies on electrochemical (EC) and PEC sensors for ovarian cancer biomarkers in the last seven years (2016–2022). EC sensors were included because PEC is an improved EC; and a comparison of both systems has, expectedly, been carried out in many studies. Specific attention was given to the different markers of ovarian cancer and the EC/PEC sensing platforms developed for their detection/quantification. Relevant articles were sourced from the following databases: Scopus, PubMed Central, Web of Science, Science Direct, Academic Search Complete, EBSCO, CORE, Directory of open Access J...
Source: Sensors - April 19, 2023 Category: Biotechnology Authors: Ezinne U. Ekwujuru Abimbola M. Olatunde Michael J. Klink Cornelius C. Ssemakalu Muntuwenkosi M. Chili Moses G. Peleyeju Tags: Review Source Type: research

Sensors, Vol. 23, Pages 4007: Automated Machine Learning Strategies for Multi-Parameter Optimisation of a Caesium-Based Portable Zero-Field Magnetometer
aul F. Griffin Machine learning (ML) is an effective tool to interrogate complex systems to find optimal parameters more efficiently than through manual methods. This efficiency is particularly important for systems with complex dynamics between multiple parameters and a subsequent high number of parameter configurations, where an exhaustive optimisation search would be impractical. Here we present a number of automated machine learning strategies utilised for optimisation of a single-beam caesium (Cs) spin exchange relaxation free (SERF) optically pumped magnetometer (OPM). The sensitivity of the OPM (T/Hz), is optimi...
Source: Sensors - April 15, 2023 Category: Biotechnology Authors: Rach Dawson Carolyn O ’Dwyer Edward Irwin Marcin S. Mrozowski Dominic Hunter Stuart Ingleby Erling Riis Paul F. Griffin Tags: Article Source Type: research

Sensors, Vol. 23, Pages 3985: Signal Novelty Detection as an Intrinsic Reward for Robotics
In this study, an Autoencoder deep learning neural network was utilized as novelty detection for intrinsic rewards to guide the search process through a state space. The neural network processed signals from various types of sensors simultaneously. It was tested on simulated robotic agents in a benchmark set of classic control OpenAI Gym test environments (including Mountain Car, Acrobot, CartPole, and LunarLander), achieving more efficient and accurate robot control in three of the four tasks (with only slight degradation in the Lunar Lander task) when purely intrinsic rewards were used compared to standard extrinsic rewa...
Source: Sensors - April 14, 2023 Category: Biotechnology Authors: Martin Kubov čík Iveta Dirgov á Luptáková Ji ří Pospíchal Tags: Article Source Type: research