DELTa: Dynamic Energy-and-Latency-Aware Task Scheduling for Fog-Cloud Paradigm by Abhijeet Mahapatra, Rosy Pradhan, Santosh K. Majhi, Kaushik Mishra

“…To address this, Fog computing has been incorporated in this research as a complementary paradigm to the Cloud-based computing model. It thereby reduces the huge distance between end-user IoT gadgets and the Cloud computing servers. …”
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Magnetic Resonance Imaging Texture Analysis Based on Intraosseous and Extraosseous Lesions to Predict Prognosis in Patients with Osteosarcoma by Yu Mori, Hainan Ren, Naoko Mori, Munenori Watanuki, Shin Hitachi, Mika Watanabe, Shunji Mugikura, Kei Takase

“…<b>Objectives:</b> To construct an optimal magnetic resonance imaging (MRI) texture model to evaluate histological patterns and predict prognosis in patients with osteosarcoma (OS). …”
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Comparing Gradient Boosting and Neural Networks in Predicting Age Based on Coronal Pulp Height from Panoramic Radiographs – A Retrospective Radiographic Study by Kishorwara Ramamoorthy, Devika S. Pillai, Pradeep Kumar Yadalam, Prasanthi Sitaraman

“…Hyperparameter tuning was performed to optimize the model’s performance, ensuring that it could accurately predict age from the TCI values. …”
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Improvement and Experimental Explore on Coordinated Control of Kinematic Mechanism of FDM 3D Printer by Guozhu Li

“…The defects of small size, slow printing speed, and low precision are deeply studied, and the machine structure is optimized according to the structural strength analysis. …”
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AER U-Net: attention-enhanced multi-scale residual U-Net structure for water body segmentation using Sentinel-2 satellite images by Naga Surekha Jonnala, Shaik Siraaj, Y. Prastuti, P. Chinnababu, B. Praveen babu, Shonak Bansal, Prashant Upadhyaya, Krishna Prakash, Mohammad Rashed Iqbal Faruque, K. S. Al-mugren

“…Additionally, the attention mechanism ensures precise refinement of skip connections, further improving segmentation performance. The model is trained using the Adam optimizer combined with a binary cross-entropy loss function, making it highly effective for binary segmentation tasks with an IoU score of 0.94, highlighting its effectiveness for practical environmental applications.…”
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UAV-Based Multispectral Winter Wheat Growth Monitoring with Adaptive Weight Allocation by Lulu Zhang, Xiaowen Wang, Huanhuan Zhang, Bo Zhang, Jin Zhang, Xinkang Hu, Xintong Du, Jianrong Cai, Weidong Jia, Chundu Wu

“…Based on the optimal growth inversion model for winter wheat, spatial distribution of wheat growth in the study area is obtained. …”
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Flow Cytometric Assessment of FcγRIIIa-V158F Polymorphisms and NK Cell Mediated ADCC Revealed Reduced NK Cell Functionality in Colorectal Cancer Patients by Phillip Schiele, Stefan Kolling, Stanislav Rosnev, Charlotte Junkuhn, Anna Luzie Walter, Jobst Christian von Einem, Sebastian Stintzing, Wenzel Schöning, Igor Maximilian Sauer, Dominik Paul Modest, Kathrin Heinrich, Lena Weiss, Volker Heinemann, Lars Bullinger, Marco Frentsch, Il-Kang Na

“…Samples were collected from healthy donors and metastatic colorectal cancer (mCRC) patients from the FIRE-6-Avelumab phase II study. The machine learning model accurately predicted the FcγRIIIa-V158F polymorphism in 94% of samples. …”
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Integrative radiomics of intra- and peri-tumoral features for enhanced risk prediction in thymic tumors: a multimodal analysis of tumor microenvironment contributions by Liang zhu, Jiamin Li, Xuefeng Wang, Yan He, Siyuan Li, Shuyan He, Biao Deng

“…These selected features were then used to train machine learning models, which were optimized on the training dataset and assessed for predictive performance. …”
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A Robust Heuristics for the Online Job Shop Scheduling Problem by Hugo Zupan, Niko Herakovič, Janez Žerovnik

“…The probabilistic rule defines a model which is not unlike the spin glass models that are closely related to quantum computing. …”
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A recurrent multimodal sparse transformer framework for gastrointestinal disease classification by V. Sharmila, S. Geetha

“…The approach integrates clinical text and WCE images using a robust multi-modal fusion strategy that incorporates Bio-RoBERTa for textual feature extraction, a graph vision spatial channel attention transformer network for image feature learning, and cross-attention mechanisms for modality alignment. Further, the model employs principal component analysis (PCA) for dimensionality reduction and gradient boosting machines (GBMs) for semantic conflict resolution. …”
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Preliminary Assessment of Electromagnetic Field Effects Induced by High and Medium Voltage Power Lines on Carbon Assimilation in Maize and Sunflower Crops by Viorel Fătu, Vasilică Savu, Agripina Șapcaliu, Roxana Zaharia, Iulian Voicea

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Assessment of Global and Detailed Chemical Kinetics in Supercritical Combustion for Hydrogen Gas Turbines by Sylwia Oleś, Jakub Mularski, Halina Pawlak-Kruczek, Abhishek K. Singh, Artur Pozarlik

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Advancing Hyperspectral Image Classification with Deep Features Learning and Evolutionary Algorithms by M. B. Amri, M. B. Amri, D. Yedjour, M. E. A. Larabi, F. Berrichi

“…In addition, the experiments conducted on simulated benchmarks validate the superior performance of the proposed approach compared to the baseline ML model in terms of prediction accuracy and F1-score.…”
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From digitized whole‐slide histology images to biomarker discovery: A protocol for handcrafted feature analysis in brain cancer pathology by Xuanjun Lu, Yawen Ying, Jing Chen, Zhiyang Chen, Yuxin Wu, Prateek Prasanna, Xin Chen, Mingli Jing, Zaiyi Liu, Cheng Lu

“…Among the 72 models combining nine feature selection methods and eight machine learning classifiers, the optimal model combination achieved discriminative performance with an average area under the curve (AUC) of 0.615 over 100 iterations under five‐fold cross‐validation. …”
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The Value of PET/CT-Based Radiomics in Predicting Adrenal Metastases in Patients with Cancer by Qiujun He, Xiangxing Kong, Xiangxi Meng, Xiuling Shen, Nan Li

“…Based on the selected features, the optimal model was chosen from ten machine learning algorithms, and the nomogram was constructed. …”
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Nano-coolants for thermal enhancement in heat exchangers: A review of prospects, challenges and applications by E.T. Bello, A. Nasir, A.S. Abdulkareem, M.M. Muhammadu, N.A. Musa, J.O. Tijani, Samson Oluwaseyi Bada

“…Furthermore, it outlines emerging prospects, including life cycle assessment, integration with renewablelar energy and the use of artificial intelligence and machine learning for predictive modeling and optimization, offering sustainable pathways for deployment and system miniaturization. …”
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Prediction of individual treatment allocation between electroconvulsive therapy or ketamine using the Personalized Advantage Index by Benjamin S. C. Wade, Ryan Pindale, James Luccarelli, Shuang Li, Robert C. Meisner, Stephen J. Seiner, Joan A. Camprodon, Michael E. Henry

“…We adapted the Personalized Advantage Index (PAI) using machine learning to predict optimal treatment assignment to ECT or ketamine using EHR data on 2506 ECT and 196 ketamine patients. …”
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Enhancing electric vehicle powertrain energy efficiency using robust nonlinear control approaches by Ilyass El Myasse, Mohamed Lmouradi, Abdelmounime El Magri, Rachid Lajouad, Pankaj Kumar

“…Firstly, a speed control loop is implemented to achieve precise tracking of the driver’s speed reference. Secondly, the machine current is optimized to generate maximum torque. …”
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Deception detection based on micro-expression and feature selection methods by Shusen Yuan, Zilong Shao, Zhongjun Ma, Ting Cao, Hongbo Xing, Yong Liu, Yewen Cao

“…Two feature selection methods are applied to optimize these features. Specifically, facial action units (AUs), eye gaze, and head pose were extracted using the OpenFace toolkit, while micro-expression information was obtained via the SOFTNet model, trained on the CAS(ME) $$^{2}$$ 2 data set. …”
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Calibration of soil contact parameters for planting sand shrubs in the desert regions of Inner Mongolia by Zhang Nannan, Pei Chenghui, Zhang Yantang, Cui Shaoyu, Liang Lingzhi, Liu Zhigang

“…Subsequently, a Box–Behnken experiment was conducted to establish a regression model for these significant factors, aiming to identify the optimal combination. …”
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