Rathlavath Priyanka;L. Chandrasekar;Rameez Raja Shaik;Kumar Prasannajit Pradhan
{"title":"Corrections to “Label Free DNA Detection Techniques Using Dielectric Modulated FET: Inversion or Tunneling?”","authors":"Rathlavath Priyanka;L. Chandrasekar;Rameez Raja Shaik;Kumar Prasannajit Pradhan","doi":"10.1109/JSEN.2025.3533876","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3533876","url":null,"abstract":"Presents corrections to the paper, Corrections to “Label Free DNA Detection Techniques Using Dielectric Modulated FET: Inversion or Tunneling?”.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 7","pages":"12538-12538"},"PeriodicalIF":4.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10947255","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Retraction Notice: A Proposed MIMO Antenna Prototype for Frequency Identification","authors":"Amin H. Al Ka’bi","doi":"10.1109/JSEN.2025.3546793","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3546793","url":null,"abstract":"Frequency Identification in Cognitive Radio (CR) networks is the key step to find the unused frequencies, so CR networks use less bandwidth and energy. The MIMO antenna system which is proposed for spectrum sensing in CR systems is a small super-wideband (SWB) design, which includes three band-notched diversity antennas. There are four identical semi-elliptical monopole antennas, directed perpendicularly with feed lines gently widened CWG type, which constitute a MIMO antenna. Every SWB characteristic has an antenna that has the cross-slot carved through its bottom just like a radiator. The antenna radiator is composed of two linked slits that replicate the image of the split ring resonator and also have a backward-S shaped slit to ensure that there is no negative impact on SWB. The antenna has a bandwidth ratio of 36:1mm and 0.2-43mm waves. In addition, 18dB of isolation and an envelope correlation coefficient of less than 0.01 have been implemented in a resonant frequency band for the MIMO antenna that has orthogonally placed antenna elements. On a frequency of 3.5GHz, 5.5GHz, and 8.5GHz, the gain level drops leading to a maximum gain of 4 dBi for the antenna. The proposed antenna has higher bandwidth ratio and hence incorporates easily into an existing RF equipment. In this manner, this SWB, MIMO antenna demonstrates superiority over those mentioned in the literature with a multi-notched band. In the same manner, we obtain three small super-wideband (SWB), which have not been filtered, so, the design and implementation of the antenna is feasible.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 6","pages":"10512-10512"},"PeriodicalIF":4.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10916580","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143628713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiong Cheng;Zhixiang Zhai;Pengfei Zhang;Yiqi Zhou;Rui Wang;Wenhua Gu;Xiaodong Huang;Daying Sun
{"title":"Corrections to “Generating Multiple Distinct Feasible Solutions for MEMS Accelerometers Using Deep Learning”","authors":"Xiong Cheng;Zhixiang Zhai;Pengfei Zhang;Yiqi Zhou;Rui Wang;Wenhua Gu;Xiaodong Huang;Daying Sun","doi":"10.1109/JSEN.2025.3528277","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3528277","url":null,"abstract":"Presents corrections to the paper, Corrections to “Generating Multiple Distinct Feasible Solutions for MEMS Accelerometers Using Deep Learning”.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 5","pages":"9209-9209"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10912817","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Corrections to “Improved XGBoost and GM UWB/MEME IMU Positioning Methods for Non-Line-of-Sight Environments”","authors":"Xin Sui;Bangwen Liao;Changqiang Wang;Zhengxu Shi","doi":"10.1109/JSEN.2024.3524872","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3524872","url":null,"abstract":"Presents corrections to the paper, (Corrections to “Improved XGBoost and GM UWB/MEME IMU Positioning Methods for Non-Line-of-Sight Environments”).","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 5","pages":"9208-9208"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10912815","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michele Magno;Daniela de Venuto;Giuseppe Ferri;Seonyeong Heo
{"title":"Guest Editorial Special Issue on Energy-Efficient Embedded Intelligent Sensor Systems (S1)","authors":"Michele Magno;Daniela de Venuto;Giuseppe Ferri;Seonyeong Heo","doi":"10.1109/JSEN.2025.3537212","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3537212","url":null,"abstract":"","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 5","pages":"7733-7733"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10912814","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"MFSonar: Multiscale Frequency-Domain Contextual Denoising for Forward-Looking Sonar Image Semantic Segmentation","authors":"Jiayuan Li;Zhen Wang;ShenAo Yuan;Zhu-Hong You","doi":"10.1109/JSEN.2025.3545146","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3545146","url":null,"abstract":"Semantic segmentation of forward-looking sonar (FLS) images is crucial for enhancing situational awareness in marine environments. However, FLS images are often degraded by environmental noise, similarity noise, and shading effects, which result in low resolution, poor signal-to-noise ratio, and suboptimal image quality. These issues significantly hinder the accuracy of semantic segmentation in FLS images. To address these challenges, we propose a novel method called MFSonar, which is based on the Transformer-Mamba architecture. MFSonar incorporates a context channel denoising module (CCDM) that exploits the similarity characteristics of local and global features to effectively suppress similarity noise and enhance target features. Additionally, the Multiscale Frequency-Domain Decoding Module integrates multiscale frequency-domain convolution with visual state-space (VSS) blocks, leveraging frequency-domain characteristics to mitigate environmental noise and occlusion shadows. Furthermore, our approach prioritizes local features before global features to achieve effective fusion and enhancement of global semantic features and multiscale local visual information. Extensive comparative experiments across multiple datasets demonstrate that MFSonar achieves state-of-the-art performance. Moreover, ablation studies and visual comparisons on a primary dataset validate the superiority, effectiveness, and uniqueness of our approach. Our implementation is available at <uri>https://github.com/NWPUFranklee/PVSonar.git</uri>.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 7","pages":"11792-11808"},"PeriodicalIF":4.3,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Improved Principal Component Analysis for Magnetic Gradient Signal Detection Using Dual Three-Axis Magnetometers","authors":"Hongyi Yang;Jianying Zheng;Qinglei Hu;Yong Cui","doi":"10.1109/JSEN.2025.3544707","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3544707","url":null,"abstract":"Magnetic anomaly detection (MAD) is an effective technique for detecting ferromagnetic materials in the presence of a geomagnetic field. In this article, by integrating and enhancing the orthogonal basis function (OBF) and principal component analysis (PCA), a high-sensitivity PCA (HSPCA) method is proposed, achieving both low computational complexity and high detection accuracy in MAD tasks. We first employ the PCA method to decompose the target signal used in the full magnetic gradient OBF (FMG-OBF) method for detection, referred to as the PCA baseline method, which achieves rapid and automated decomposition. It achieves the detection accuracy of FMG-OBF while reducing the real-time processing time by 61.1%. Furthermore, we propose the HSPCA method as an improvement by modifying the form of target signal to enhance detection sensitivity, establishing a mapping to eliminate the influence of redundant sampling parameters, and applying weights to the basis functions to balance their relative contributions. Ultimately, the computational time of this improved method is only 1.3% of that of the PCA baseline method, and its detection rate is increased by 53.1% compared to FMG-OBF at a noise level of −20 dB with a false alarm rate of 4%. Field experiments are conducted to validate the convenience and practicality of the proposed methods.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 7","pages":"10922-10933"},"PeriodicalIF":4.3,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}