An Enhanced Deep Neural Network Approach for WiFi Fingerprinting-Based Multi-Floor Indoor Localization by Shehu Lukman Ayinla, Azrina Abd Aziz, Micheal Drieberg, Misfa Susanto, Afidalina Tumian, Mazlaini Yahya

“…The CV process is repeated multiple times to assess the RFE’s generalization ability for optimal feature selection, and the BN algorithm is integrated into each layer of the DNN to ensure consistent activation value distribution and stabilization of the training process. …”
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Intelligent recognition of tobacco leaves states during curing with deep neural network by Qiang Xu, Yanling Zhang, Aiguo Wang, Guangqing Chen, Xianjie Cai, Shuoye Zhou, Junying Li, Baofeng Jin, Ding Yan, Jiajie Huang, Zuxiao Chen, Heng Zhang, Jianwei Wang, Weimin Guo, Jianjun Liu

“…IntroductionThe state monitoring of tobacco leaves during the curing process is crucial for process control and automation of tobacco agricultural production. While most of the existing research on tobacco leaves state recognition focused on the temporal state of the leaves, the morphological state was often neglected. …”
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Deepfake Face Detection and Adversarial Attack Defense Method Based on Multi-Feature Decision Fusion by Shanzhong Lei, Junfang Song, Feiyang Feng, Zhuyang Yan, Aixin Wang

“…Ultimately, the model’s robustness was validated by generating adversarial samples using the I-FGSM algorithm and optimizing model performance through adversarial training. …”
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A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…This method centered on the initial meter gas production index and integrated multiple machine-learning algorithms. The results showed that: 1） The Beggs & Bill model and Gray model exhibited poor applicability for predicting the bottom-hole flowing pressure of deep CBM wells, while the single-phase gas model demonstrated reduced overall error as water production declined. …”
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Photovoltaic Farm Power Generation Forecast Using Photovoltaic Battery Model with Machine Learning Capabilities by Agboola Benjamin Alao, Olatunji Matthew Adeyanju, Manohar Chamana, Stephen Bayne, Argenis Bilbao

“…To address these limitations, the proposed model integrates an Adaptive Neuro-Fuzzy Inference System (ANFIS) with a multi-input multi-output (MIMO) prediction algorithm, utilizing historical temperature and irradiance data for accurate and efficient forecasting. …”
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Characterization of Irrigated Rice Cultivation Cycles and Classification in Brazil Using Time Series Similarity and Machine Learning Models with Sentinel Imagery by Andre Dalla Bernardina Garcia, Ieda Del’Arco Sanches, Victor Hugo Rohden Prudente, Kleber Trabaquini

“…The processing of input data and exploratory analysis were performed using a clustering algorithm based on Dynamic Time Warping (DTW), with K-means applied to the time series. …”
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Variable-Rate Nitrogen Application in Wheat Based on UAV-Derived Fertilizer Maps and Precision Agriculture Technologies by Alexandros Tsitouras, Christos Noulas, Vasilios Liakos, Stamatis Stamatiadis, Miltiadis Tziouvalekas, Ruijun Qin, Eleftherios Evangelou

“…Variable-rate nitrogen (VR-N) application allows farmers to optimize nitrogen (N) input site-specifically within field boundaries, enhancing both economic efficiency and environmental sustainability. …”
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Lightweight deep neural network for contour detection and extraction of wheat spikes in complex field environments by Xin Xu, Haiyang Zhang, Jiangchuan Lu, Ziyi Guo, Juanjuan Zhang, Jibo Yue, Hongbo Qiao, Xinming Ma

“…Ablation studies confirm LDSNet-ELA integration reduces false positives by 27.6%, while the enhanced loss function system improves small-object recall by 19.4%. …”
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Association Between Per- and Polyfluoroalkyl Substances and All-Cause Mortality in Diabetic Patients: Insights from a National Cohort Study and Toxicogenomic Analysis by Zhengxiao Wei, Jinyu Chen, Xue Mei, Yi Yu

“…Preliminary logistic regression identified three PFAS compounds (perfluorooctanoic acid [PFOA], perfluorooctane sulfonic acid [PFOS], and 2-(N-methyl-PFOSA) acetate acid [MPAH]) as significantly associated with mortality in the diabetic population. The optimal cut-off values for PFOS, PFOA, and MPAH were determined using the X-tile algorithm, and participants were categorized into high- and low-exposure groups. …”
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Machine Learning and Deep Learning for Crop Disease Diagnosis: Performance Analysis and Review by Habiba Njeri Ngugi, Andronicus A. Akinyelu, Absalom E. Ezugwu

“…The review method includes an in-depth analysis of algorithm performance using key metrics such as accuracy, precision, recall, and F1 score across various datasets. …”
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Using Deep Learning Techniques to Enhance Blood Cell Detection in Patients with Leukemia by Mahwish Ilyas, Muhammad Bilal, Nadia Malik, Hikmat Ullah Khan, Muhammad Ramzan, Anam Naz

“…While our model is built on a typical CNN architecture, we make significant advances by using preprocessing techniques and hyperparameter tuning. …”
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Outcomes among children and adults at risk of severe dengue in Sri Lanka: Opportunity for outpatient case management in countries with high disease burden. by Champica K Bodinayake, Ajith DeS Nagahawatte, Vasantha Devasiri, Niroshana J Dahanayake, Gaya B Wijayaratne, Nayani P Weerasinghe, Madureka Premamali, Tianchen Sheng, Bradly P Nicholson, Harshanie A Ubeysekera, Ruvini Mp Kurukulasooriya, Aruna D de Silva, Truls Østbye, Christopher W Woods, L Gayani Tillekeratne

“…<h4>Conclusions</h4>One-half of patients hospitalized with acute dengue progressed to develop DHF and a very small number developed DSS or severe dengue. Developing an algorithm for triaging patients to ambulatory versus inpatient management should be the future goal to optimize utilization of healthcare resources in dengue-endemic countries.…”
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Research on ecological management zoning in Jilin Province based on a human well-being framework by Baihao Zhang, Jiafu Liu, Zhenyu Zhang, Yu Zhu

“…To further delineate ecological management zones, the SC K-means clustering algorithm and the coupling coordination degree model are employed. …”
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A framework for flood risk zoning and prioritization combining maximum entropy and game theory by Ali Haghizadeh, Reza Fathiganji, Ehsan Sohrabi, Aghdas Lotfi, Leila Ghasemi

“…Variable selection was performed using the Random Forest algorithm, resulting in the identification of nine key factors influencing flood occurrence. …”
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Research of Physical and Mechanical Properties of Self-Compacting Concrete Based on Polyfractional Binder by Meiram M. Begentayev, Daniyar A. Akhmetov, Rauan E. Lukpanov, Erzhan I. Kuldeyev, Zhanar O. Zhumadilova, Tolebi Myrzaliyev, Duman S. Dyussembinov, Aigerim K. Tolegenova

“…A software and calculation complex featuring a three-dimensional modeling algorithm, Drop and Roll, was used to select the optimal composition. …”
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Synergistic Effects of Drivers on Spatiotemporal Changes in Carbon and Water Use Efficiency in Irrigated Cropland Ecosystems by Guangchao Li, Zhaoqin Yi, Tiantian Qian, Yuhan Chang, Hanjing Gao, Fei Yu, Liqin Han, Yayan Lu, Kangjia Zuo

“…Based on a multi-source remote sensing dataset, this study applies a trend analysis (Sen + Mann–Kendall), a dual-type randomized extraction algorithm, and an optimized XGBoost model to examine the spatiotemporal variations in cropland CWUE, including the water use efficiency of net primary production (WUE_NPP), water use efficiency of gross primary production (WUE_GPP), and carbon use efficiency (CUE) in Henan Province from 2001 to 2019. …”
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Surface Clay and Mineral Exploration Using Hyperspectral Imaging: Advanced Techniques for Geospatial Analysis by S. Raut, N. Andure, A. Kadam, A. Dongare, A. Fulari, G. M. Sayyad, S. B. Sayyad, S. K. Shaikh, S. Sawant

“…Traditional approaches such as geological mapping, geochemical assays, and field surveys, while fundamental, often prove inefficient in terms of time and resources, especially in the challenging topography of the Aravalli Range. …”
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Deployment of real-time particle detection monitoring system in operating theatres for airborne contamination assessments: a methodological evaluation by Frans Stålfelt, Johan Tenghamn, Henrik Malchau, Karin Svensson Malchau

“…Future research should focus on integrating predictive algorithms and machine-learning to enhance clinical utility and drive improvements in surgical safety. …”
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Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation by Simone Costantini, Anna Falivene, Mattia Chiappini, Giorgia Malerba, Carla Dei, Silvia Bellazzecca, Fabio A. Storm, Giuseppe Andreoni, Emilia Ambrosini, Emilia Biffi

“…Additionally, feature reduction did not yield any advantages, while data augmentation consistently enhanced classifiers performance. …”
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Feasibility of Implementing Motion-Compensated Magnetic Resonance Imaging Reconstruction on Graphics Processing Units Using Compute Unified Device Architecture by Mohamed Aziz Zeroual, Natalia Dudysheva, Vincent Gras, Franck Mauconduit, Karyna Isaieva, Pierre-André Vuissoz, Freddy Odille

“…Motion correction in magnetic resonance imaging (MRI) has become increasingly complex due to the high computational demands of iterative reconstruction algorithms and the heterogeneity of emerging computing platforms. …”
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