IEEE Sensors Letters最新文献_第9页

FOG: Fast Octree Generator for LiDAR Point Clouds FOG：激光雷达点云的快速八叉树生成器

IF 2.2

IEEE Sensors Letters Pub Date : 2024-12-26 DOI: 10.1109/LSENS.2024.3520800

Ricardo Roriz;Diogo Costa;Mongkol Ekpanyapong;Tiago Gomes

引用次数: 0

LG-Sleep: Local and Global Temporal Dependencies for Mice Sleep Scoring LG-Sleep：小鼠睡眠评分的局部和全局时间依赖性

IF 2.2

IEEE Sensors Letters Pub Date : 2024-12-26 DOI: 10.1109/LSENS.2024.3523427

Shadi Sartipi;Mie Andersen;Natalie Hauglund;Celia Kjaerby;Verena Untiet;Maiken Nedergaard;Mujdat Cetin

{"title":"LG-Sleep: Local and Global Temporal Dependencies for Mice Sleep Scoring","authors":"Shadi Sartipi;Mie Andersen;Natalie Hauglund;Celia Kjaerby;Verena Untiet;Maiken Nedergaard;Mujdat Cetin","doi":"10.1109/LSENS.2024.3523427","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3523427","url":null,"abstract":"Efficiently identifying sleep stages is crucial for unraveling the intricacies of sleep in both preclinical and clinical research. The labor-intensive nature of manual sleep scoring, demanding substantial expertise, has prompted a surge of interest in automated alternatives. Sleep studies in mice play a significant role in understanding sleep patterns and disorders and underscore the need for robust scoring methodologies. In response, this letter introduces LG-Sleep, a novel subject-independent deep neural network architecture designed for mice sleep scoring through electroencephalogram (EEG) signals. LG-Sleep extracts local and global temporal transitions within EEG signals to categorize sleep data into three stages: wake, rapid eye movement (REM) sleep, and non-REM sleep. The model leverages local and global temporal information by employing time-distributed convolutional neural networks to discern local temporal transitions in EEG data. Subsequently, features derived from the convolutional filters traverse long short-term memory blocks, capturing global transitions over extended periods. Crucially, the model is optimized in an autoencoder–decoder fashion, facilitating generalization across distinct subjects and adapting to limited training samples. Experimental findings demonstrate superior performance of LG-Sleep compared to conventional deep neural networks. Moreover, the model exhibits good performance across different sleep stages even when tasked with scoring based on limited training samples.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 2","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biquaternion Evolution in Attitude Estimation Using a Generalized Vector Measurement 基于广义矢量测量的姿态估计中的双四元数演化

IF 2.2

IEEE Sensors Letters Pub Date : 2024-12-25 DOI: 10.1109/LSENS.2024.3521956

Yang Liu;Jin Wu;Fulong Ma;Chengxi Zhang

引用次数: 0

Rapid and Sensitive Electrochemical Detection of Escherichia coli in Water Using Cr–Au IDE-Porous Silicon Sensor Cr-Au - ide -多孔硅传感器对水中大肠杆菌的快速灵敏电化学检测

IF 2.2

IEEE Sensors Letters Pub Date : 2024-12-25 DOI: 10.1109/LSENS.2024.3522457

Vandana Kumari Chalka;Kamaljit Rangra;Saakshi Dhanekar

{"title":"Rapid and Sensitive Electrochemical Detection of Escherichia coli in Water Using Cr–Au IDE-Porous Silicon Sensor","authors":"Vandana Kumari Chalka;Kamaljit Rangra;Saakshi Dhanekar","doi":"10.1109/LSENS.2024.3522457","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3522457","url":null,"abstract":"An efficient electrochemical sensor based on Cr–Au interdigitated electrode porous silicon has been developed to rapidly assess <italic>Escherichia coli (E. coli) bacteria in water. Coliform bacteria, particularly <italic>E. coli, contribute significantly to waterborne contamination, driven by overuse and insufficient cleanliness around water bodies. This letter incorporates the fabrication of porous silicon (PSi), characterization, synthesis of bacterial dilutions, and testing of the sensor in the presence of varying <italic>E. coli dilutions. The dilutions are prepared from the stock solution of bacterial concentrations and hydrogen peroxide (H2O2). The interaction of porous silicon with bacteria incubated in H2O2 leads to a change in potential across the electrodes in real time. The limits of detection and sensitivity for the sensor are 0.187 CFU/mL and 113 mV⋅mL/CFU, respectively. The response time and the recovery time of the sensor are 80 and 90 ms, respectively. In addition, analyses such as repeatability and testing in tap water, <italic>Pseudomonas, and <italic>Citrobacter are conducted. For a user-friendly output, the sensor has been interfaced with a signal conditioning circuit and a display. This prototype offers a quick and precise way to identify the quality of drinking water, making it a potential solution to the growing problems caused by water pollution.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 2","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142975822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributional Substitution for Intersensor Distances in Random Fields 随机场中传感器间距离的分布替换

IF 2.2

IEEE Sensors Letters Pub Date : 2024-12-24 DOI: 10.1109/LSENS.2024.3521994

Jia Ye;Shuping Dang;Shuaishuai Guo;Raed Shubair;Marwa Chafii

引用次数: 0

IEEE Sensors Letters Subject Categories for Article Numbering Information 用于物品编号信息的IEEE传感器字母主题分类

IF 2.2

IEEE Sensors Letters Pub Date : 2024-12-24 DOI: 10.1109/LSENS.2024.3521204

引用次数: 0

IEEE Sensors Letters Publication Information IEEE传感器通讯出版信息

IF 2.2

IEEE Sensors Letters Pub Date : 2024-12-24 DOI: 10.1109/LSENS.2024.3521200

引用次数: 0

Design of a Spore Germination Sensor for Orchids 兰花孢子萌发传感器的设计

IF 2.2

IEEE Sensors Letters Pub Date : 2024-12-20 DOI: 10.1109/LSENS.2024.3520018

Yi-Bing Lin;Yi-Ting Chen;Wan-Jung Hsieh;Wen-Liang Chen;Yun-Wei Lin;Edward Sun

{"title":"Design of a Spore Germination Sensor for Orchids","authors":"Yi-Bing Lin;Yi-Ting Chen;Wan-Jung Hsieh;Wen-Liang Chen;Yun-Wei Lin;Edward Sun","doi":"10.1109/LSENS.2024.3520018","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3520018","url":null,"abstract":"The Phalaenopsis orchid is highly valued in the ornamental flower market and is primarily cultivated in greenhouses. In a traditional commercial greenhouse, farmers must manually check daily for any signs of disease among the plants. Sick plants must be removed immediately to prevent the spread of diseases to healthy ones. In precision agriculture, farmers are expected to be alerted when a certain percentage (e.g., less than 2%) of the plants are infected so that they can be removed at the right time. Many experiments have been conducted in laboratories with constant temperature and humidity to investigate the spore germination rate, where spores typically germinate within a few days. However, these findings cannot be directly applied to large-scale greenhouses with long growth periods (over 200 days) and varying temperatures and humidity. The contribution of this letter is that we are the first to propose a sensor specifically designed for use in large-scale greenhouse environments to determine the spore germination rate for orchids. We have designed a simple yet novel algorithm to dynamically calibrate the spore germination sensor. Our experiments indicate that with the calibrated spore germination sensor, the outbreak probability can be completely eliminated, and human checking overhead can be reduced by up to 97.8%.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 2","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142976134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Low Complexity Gain-Phase Error Correction for Adaptive Underdetermined DOA Estimation in Sensor Arrays 传感器阵列自适应欠定DOA估计的低复杂度增益相位误差校正

IF 2.2

IEEE Sensors Letters Pub Date : 2024-12-19 DOI: 10.1109/LSENS.2024.3520524

Shouharda Ghosh;Nithin George

引用次数: 0

Predictive Sampling in Image Sensing for Sparse Image Processing 稀疏图像处理中的预测采样图像感知

IF 2.2

IEEE Sensors Letters Pub Date : 2024-12-19 DOI: 10.1109/LSENS.2024.3520408

Amin Biglari;Qisong Hu;Wei Tang

引用次数: 0