HCAFNet: Hierarchical Cross-Modal Attention Fusion Network for HSI and LiDAR Joint Classification by Jiajia Bai, Na Chen, Jiangtao Peng, Lanxin Wu, Weiwei Sun, Zhijing Ye

“…Hyperspectral image (HSI) and light detection and ranging (LiDAR) data can provide complementary features and have shown great potential for land cover classification. …”
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New generation Cherenkov telescope array: HADAR and its performance introduction by Qingyuan Hou, Qingqian Zhou, Tianlu Chen, Youliang Feng, Hengjiao Liu, Yiqing Guo, Cheng Liu, Zihao Zhang, Xinlong Li, Qi Gao, Maoyuan Liu, Xiangli Qian, Yuanqi Liu, Jiadan Xie, Shanjie Shu, Weiqi Han, Qijiao Fang, Yanan Wang, Shaohua Zhang

“…It is designed to indirectly detect gamma-rays by capturing Cherenkov radiation produced by extensive air showers initiated by primary gamma-rays. …”
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LSTM-ANN-GA A HYBRID DEEP LEARNING MODEL FOR PREDICTIVE MAINTENANCE OF INDUSTRIAL EQUIPEMENT by Farouk Noumich, Abouchabaka Jaafar, Amrani Ayoub

“…Unlike traditional predictive approaches based on existing data for fault detection, which rely on a single deep model and often struggle to maintain satisfactory generalization performance across various forecasting scenarios, these approaches encounter difficulties in effectively initializing and optimizing reset parameters, impeding performance and accuracy. …”
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Hybrid-CID: Securing IoT with Mongoose Optimization by S. Merlin Sheeba, R. S. Shaji

“…To combat these issues, a novel hybrid optimization-enabled neural network for classification of intrusion data against IoT system (Hybrid-CID) is proposed particularly to identify intrusions in resource-constrained IoT devices. Initially, the incoming data are standardized by removing the irrelevant information through preprocessing to ensure the performance of detection models. …”
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Broadband Low-Cost Normal Magnetic Field Probe for PCB Near-Field Measurement by Ruichen Luo, Zheng He, Lixiao Wang

“…The probe’s structural parameters and magnetic field response were initially determined through simulations, and the calibration factor was subsequently verified by calibration experiments. …”
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Effectiveness of a Community-Based Oral Cancer Screening Program Using Portable Fluorescence Spectroscopy in Rural Madhya Pradesh, India by Anuj Singh Parihar, Mahendrakumar A. Chaudhari, Hiren H. Patadiya, Jitender Kumar, Sanja Samir Sahu, Rashmi Laddha, Megha C Patel

“…Portable fluorescence spectroscopy demonstrated a sensitivity of 88.2% and specificity of 92.6% for detecting OPMDs. For oral cancer detection, the sensitivity was 90.0%, and the specificity was 94.1%. …”
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MCFTNet: Multimodal Cross-Layer Fusion Transformer Network for Hyperspectral and LiDAR Data Classification by Wei Huang, Tianren Wu, Xueyu Zhang, Liangliang Li, Ming Lv, Zhenhong Jia, Xiaobin Zhao, Hongbing Ma, Gemine Vivone

“…Moreover, traditional Transformer models use an external classification token (CLS token) that is randomly initialized and often struggles to generalize effectively. …”
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Kidney Disease Segmentation and Classification Using Firefly Sigma Seeker and MagWeight Rank Techniques by Dilovan Asaad Zebari

“…This automated diagnostic process facilitates the early detection of kidney disease by identifying any abnormalities or signs of disease. …”
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Multi-Sided Delayed Impulsive Feedback Method for Controlling Chaos and Reducing Loss Ratio in Switched Arrival System with Switching Time Greater than 0 by Ming Chen, Xueshuai Zhu

“…The possible intervals for the optimal control coefficient under the same initial conditions are detected. Period-1 orbits are detected at switching times greater than 0, and the stability of system operation is verified.…”
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Multi-Decision Vector Fusion Model for Enhanced Mapping of Aboveground Biomass in Subtropical Forests Integrating Sentinel-1, Sentinel-2, and Airborne LiDAR Data by Wenhao Jiang, Linjing Zhang, Xiaoxue Zhang, Si Gao, Huimin Gao, Lin Sun, Guangjian Yan

“…Initially, the optimal feature subsets for each model were identified using SFS, followed by hyperparameter optimization through a grid search strategy. …”
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Functional Diagnosis of Digital State Automation Networks by I. V. Bystrova, B. P. Podkopaev

“…The procedure minimizes the sought for functional diagnosis devices with respect to the order when preserving the initial detecting ability within any network component. …”
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Cybersecurity Challenges in PV-Hydrogen Transport Networks: Leveraging Recursive Neural Networks for Resilient Operation by Lei Yang, Saddam Aziz, Zhenyang Yu

“…Additionally, the study introduces an in-depth examination of the detection dynamics, illustrating that while detection rates generally decrease as incident frequency increases—due to system overload—the employment of advanced RNNs effectively mitigates this trend, sustaining high detection rates of up to 95% even under high-frequency scenarios. …”
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Amperometric sensing of prostate cancer biomarker (Sarcosine) using HiPIMS deposited nickel nitride films-decorated zinc oxide nanorod heterostructures by Nishchal Pardhi, Wei-Chun Cheng, Sheng-Chi Chen, Hui Sun, Mani Govindasamy

“…The electrode shows excellent selectivity towards Sar, repeatability with a reduction in current response to 2.51 % of the initial current response after 30 days of storage at room temperature, reproducibility, and a short response time of 4.1 s on average for the detection of Sar. …”
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Potential of Chest Radiography in Primary Diagnosis of Lung Cancer by A. V. Bereznikov, S. O. Shkitin, I. E. Tyurin

“…Chest radiography does not reliably detect LC signs at early stages in 84.3% of cases.Conclusion. …”
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Ensemble LVQ Model for Photovoltaic Line-to-Line Fault Diagnosis Using K-Means Clustering and AdaGrad by Peyman Ghaedi, Aref Eskandari, Amir Nedaei, Morteza Habibi, Parviz Parvin, Mohammadreza Aghaei

“…To this end, the present paper proposes a learning vector quantization (LVQ)-based ensemble learning model in which three LVQs are individually trained to detect and classify LL faults in PV arrays. The initial LVQ vectors are determined using the k-means clustering method, and the learning rate is optimized by the adaptive gradient (AdaGrad) optimizer. …”
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Application of a Texture Appearance Model for Segmentation of Lung Nodules on Computed Tomography of the Chest by F. Shariaty, V. A. Pavlov, S. V. Zavjalov, M. Orooji, T. M. Pervunina

“…Lung cancer is one of the most critical diseases globally, with more than 1.6 million new cases registered every year. Early detection of lung cancer is essential; therefore, particular attention should be paid to the development of effective diagnostic and therapeutic procedures. …”
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Analysis of arrhythmic episodes in patients with implanted cardioverter defibrillators and a high risk of sudden cardiac death by A. S. Postol, N. M. Neminushchi, A. V. Ivanchenko, V. V. Lyashenko, S. A. Mishanin, А. B. Vygovsky, Yu. A. Schneider

“…In order to minimize the amount of shock effects applied, the following defibrillator programming techniques were used: prolongation of the duration of tachycardia detection in the ventricular fibrillation (VF) zone from the nominal parameters and changing the plan of applying antitachycardia stimulation (ATS) in VF zone (the number of stimuli in the exposure pack was increased and the stimulation interval was shortened by 10-20% in comparison with the initial parameters). …”
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Testing convolutional neural network based deep learning systems: a statistical metamorphic approach by Faqeer ur Rehman, Clemente Izurieta

“…., convolutional neural networks (CNNs)) that have a stochastic nature (because of randomly initializing the network weights) in their training. …”
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A non-invasive wearable microwave sensor for Alzheimer's Stage differentiation using realistic 3D human head phantoms by Jinan N. Shehab, Malik Jasim Farhan, Saad Al-Azawi

“…The stage classification was based on medical research, with the disease initially occurring in the hippocampus before spreading to the rest of the brain. …”
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Maximum likelihood DOA estimation based on improved ant colony optimization algorithm by JIAO Yameng, LI Wenping, WU Yue, CUI Lin

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