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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Evaluation of Shelf Life Prediction for Broccoli Based on Multispectral Imaging and Multi-Feature Data Fusion by Xiaoshuo Cui, Xiaoxue Sun, Shuxin Xuan, Jinyu Liu, Dongfang Zhang, Jun Zhang, Xiaofei Fan, Xuesong Suo

“…Savitzky–Golay (SG) convolution smoothing and standard normal variate (SNV) and normalization (Norm) preprocessing methods were employed to preprocess the original spectral data and textural features, while a successive projection algorithm (SPA) was used to extract relevant feature bands. …”
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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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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

“…However, challenges such as managing large volumes of data, addressing data gaps, and optimizing available data are key focuses in remote sensing research using automated machine learning models. …”
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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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High-Quality Short-Range Radar Imaging with Coprime Sampling by Yaping Wang, Tianjiao Zeng, Xu Zhan, Xiangdong Ma, Mou Wang, Jun Shi, Shunjun Wei, Xiaoling Zhang

“…Our approach is built upon three core perspectives: (1) physical sampling: we adopt a coprime pattern to form an extended sampling aperture with a structured layout, enabling effective utilization of limited channels and minimizing aperture loss; (2) signal measurement: we utilize the second-order statistics of the measured data to generate additional equivalent measurements, thus enhancing the system’s capability to capture diverse spatial information; and (3) scene reconstruction: we establish a novel forward measurement model, linking these equivalent measurements to the scene, and then formulate a sparsity-regularized optimization problem. We design a background-texture-preserving, target-enhanced resolving method based on the first-order proximal gradient algorithm to achieve robust and high-quality imaging results. …”
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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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Complex Cloud-Sea Background Simulation for Space-Based Infrared Payload Digital Twin by Wen Sun, Yejin Li, Fenghong Li, Guangsen Liu, Peng Rao

“…Static cloud-sea scenes are generated using Qilu-2 and New Technology satellite images, while dynamic scenarios are simulated with our iterative fractal dimension optimization algorithm. …”
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Establishing strength prediction models for low-carbon rubberized cementitious mortar using advanced AI tools by Fu Limei, Xu Feng

“…However, their reduced compressive strength (CS) due to the inclusion of rubber remains a significant barrier to widespread adoption. While several experimental studies exist, there is a clear gap in utilizing data-driven strategies to efficiently predict and optimize the strength performance of such materials. …”
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Know your competitor! Analyzing and predicting the location of competing stores: The case study of Valora at Swiss railway stations by Thomas Wieland

“…Binary logit models are built for the formats examined in order to identify the determinants of location choice. Machine learning algorithms are used to check and optimize the predictive ability of the models. …”
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What factors enhance students' achievement? A machine learning and interpretable methods approach. by Hui Mao, Ribesh Khanal, ChengZhang Qu, HuaFeng Kong, TingYao Jiang

“…This study addresses these limitations by employing an ensemble of five machine learning algorithms (SVM, DT, ANN, RF, and XGBoost) to model multivariate relationships between four behavioral and six instructional predictors, using final exam performance as our outcome variable. …”
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Training a Minesweeper Agent Using a Convolutional Neural Network by Wenbo Wang, Chengyou Lei

“…The results showed that in a 6 × 6 grid with four mines, the DQN model achieved an average win rate of 93.3% (standard deviation: 0.77%), while the supervised learning method achieved 91.2% (standard deviation: 0.9%), both outperforming human players and baseline algorithms and demonstrating high intelligence. …”
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Evaluation of Liver Fibrosis through Noninvasive Tests in Steatotic Liver Disease by Yuri Cho

“…The integration of multiple non-invasive methods can optimize diagnostic accuracy, reducing the need for invasive biopsies while identifying patients at risk of liver-related complications. …”
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Robust Model-Free Identification of the Causal Networks Underlying Complex Nonlinear Systems by Guanxue Yang, Shimin Lei, Guanxiao Yang

“…Due to the complexity of system modeling, the way in which universal and feasible inference algorithms are studied is a key challenge for network reconstruction. …”
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Adoption of the Creative Process According to the Immersive Method by Sonja Vuk, Tonka Tacol, Janez Vogrinc

“…This occurs with the mediation of an algorithmic scheme that enables students to adopt ways to solve problems, to express thoughts and emotions, to develop ideas and to transfer these ideas to form, medium and material. …”
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