Fuzzy System for the Quality Assessment of Educational Multimedia Edition Design by Vsevolod Senkivskyy, Liubomyr Sikora, Nataliia Lysa, Alona Kudriashova, Iryna Pikh

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Energy evolution and key parameters of coal breaking by flexible cutting tools by Yong LIU, Zhikang ZHANG, Jianping WEI, Xiangyu XU, Yingjun GAO

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Numerical Study on the Influence of Rudder Fillets on Submarine Wake Field and Noise Characteristics by Hao Yuan, Eryun Chen, Xingsheng Liu, Ailing Yang

“…Compared with the crossed rudder, the “X” layout shows better flow control performance, with the maximum reduction in the axial relative velocity of the propeller plane surface reaching 49.34%, which is 24.25% higher than that of the SUBOFF baseline model, and the addition of two distributions of rudder fillets can reduce the hydrodynamic noise of the submarine by 4.6 dB vs. 5.6 dB at most. …”
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Evolutionary game-based cooperative strategy for effective capacity of multiple-input-multiple-output communications by Jianhua Liu, Jiadi Yu, Minglu Li, Luqun Li, Dazhi Li, Shigen Shen

“…In this article, we propose a game theoretical framework for mobile two-dimensional multiple-input-multiple-output communication networks to achieve optimal relay selection and cooperative control. A source node, relay, and destination node can make service-selection decisions dynamically in a two-level network, based on the mobile-channel satisfaction parameters (e.g. spatial-temporal correlation and relay survivability). …”
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A Novel Vehicle Lateral Velocity Observer With Adaptive Feedback Gain via Deep Learning by Minchang Kwak, Wanki Cho, Seung-Han You

“…Based on these ground truth values, we developed an AI model capable of predicting optimal observer feedback gains through supervised learning techniques. …”
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Deep learning-driven IoT solution for smart tomato farming by Akshit Saxena, Aayushi Agarwal, Bhavya Nagrath, Carmel Sanjana Jayavanth, Shamita Thulasidoss, S. Maheswari, P. Sasikumar

“…Model optimizations, including quantization, pruning, and TensorRT, improved inference speed by 35% while maintaining 52.8% classification accuracy during our initial stage of the project. …”
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HYPERTEXTUAL KNOWLEDGE FOR MINIMIZING RISKS OF BIOCHEMISTRY AND BIOPHYSICS STRUCTURES AND HEALTH SUSTAINABILITY ACHIEVEMENT by Ioana-Andreea, MARINESCU

“…It concludes that in order to minimize the biochemical and biophysical risk, the socio-economic value of the perpetual nature must be protected, and use of knowledge in the economy on quasi-continuous and dense net management control for optimized structures. That is fully legitimate pragmatic, positive.…”
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Thermal performance analysis of a heat exchanger with a novel turbulator insert by using machine learning method by Jiangbo Wang, Chenzhe Li, Liangcai Zeng, Ting Fu, Kai Liu

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Depth-dependent contributions of various vascular zones to cerebral autoregulation and functional hyperemia: An in-silico analysis. by Hadi Esfandi, Mahshad Javidan, Rozalyn M Anderson, Ramin Pashaie

“…To determine relative contributions of distinct vascular zones across different cortical depths in CBF regulation, we developed a simplified yet detailed and computationally efficient model of the mouse cerebrovasculature. The model integrates multiple simplifications and generalizations regarding vascular morphology, the hierarchical organization of mural cells, and potentiation/inhibition of MT in vessels. …”
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Cost-Effectiveness Analysis of a Latent Tuberculosis Screening Program Among Healthcare Personnel by Niludi Ranwanee Yasaratna MD, Manuj Chrishantha Weerasinghe MD

“…Screening high-risk groups for Latent Tuberculosis Infection (LTBI) is crucial for TB elimination, as the large global reservoir of Mycobacterium tuberculosis bacilli poses a significant challenge to TB control globally. Assessing the cost-effectiveness of LTBI screening strategies is also crucial in determining the optimal approach. …”
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Neural network based clinical decision support system for the calculation the initial continuous subcutaneous insulin infusion settings by D. N. Laptev, D. Y. Sorokin

“…BACKGROUND: Despite existing recommendations for the initial calculation of insulin pump settings, the process is largely subjective and depends on the physician’s personal experience.AIM: Development of a clinical decision support system (CDSS) that determines the initial settings of the insulin pump, which would have satisfactory agreement with the expert opinion of physicians.MATERIALS AND METHODS: Neural network model developed using data (continuous subcutaneous insulin infusion (CSII) settings, age, weight, total daily dose, and HbA1c) from 2850 children with T1D who were switched to CSII and achieved optimal glycemic control according to glucose levels. …”
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Resting-state EEG microstate features for Alzheimer's disease classification. by Xiaoli Yang, Zhipeng Fan, Zhenwei Li, Jiayi Zhou

“…The results show that in the Alpha (8-13 Hz) sub-band, the microstate feature set as model input to SVM is optimal for the recognition of AD, with a classification accuracy of 99.22%. …”
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High-precision segmentation and quantification of tunnel lining crack using an improved DeepLabV3+ by Zhutian Pan, Xuepeng Zhang, Yujing Jiang, Bo Li, Naser Golsanami, Hang Su, Yue Cai

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Designing Personalized Multimodal Mnemonics With AI: A Medical Student’s Implementation Tutorial by Noor Elabd, Zafirah Muhammad Rahman, Salma Ibrahim Abu Alinnin, Samiyah Jahan, Luciana Aparecida Campos, Ovidiu Constantin Baltatu

“…The process involves (1) template development, (2) refinement, (3) personalization, (4) mnemonic specification, and (5) quality control. The implementation time typically ranges from 2 to 5 minutes per concept, with 1 to 3 iterations needed for optimal results. …”
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Homogeneous and Heterogeneous Photo-Fenton-Based Photocatalytic Techniques for the Degradation of Nile Blue Dye by Georgia Papadopoulou, Eleni Evgenidou, Dimitra Lambropoulou

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Prediction of Metal Additively Manufactured Bead Geometry Using Deep Neural Network by Min Seop So, Mohammad Mahruf Mahdi, Duck Bong Kim, Jong-Ho Shin

“…The DNN model architecture consists of multiple hidden layers with varying neuron counts, trained using backpropagation, and optimized using the Adam optimizer. …”
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AdjcorT-RBFNN for Air Quality Classification: Mitigating Multicollinearity with Real and Simulated Data by Siti Khadijah Arafin, Nor Azura Md Ghani, Marshima Mohd Rosli, Nurain Ibrahim

“…However, multicollinearity in air quality data can hindermodel performance.To address this issue, this study introduces theAdjcorT-RBFNN, a two-stage feature selection method, to classify air quality in Klang, Selangor. The AdjcorT-RBFNN model selects the optimal combination of 9 feature combinations from 10 variables and outperforms the RBFNN model, which uses all 10 variables. …”
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Deployable Deep Learning for Cross-Domain Plant Leaf Disease Detection via Ensemble Learning, Knowledge Distillation, and Quantization by Mohammad Junayed Hasan, Suvodeep Mazumdar, Sifat Momen

“…Strategic data augmentation and ADASYN-based balancing mitigate the severe 75:1 class imbalance, while systematic hyperparameter tuning optimizes model configurations. Our four-model ensemble (DenseNet-121, ResNet-101, DenseNet-201, EfficientNet-B4) achieves 99.15% accuracy via soft-voting. …”
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Investigating the compaction and the mechanical behaviors of coal gangue as subgrade filler and constructing highway subgrade in practice by Zong-Tang Zhang, Guan-Ming Zhou

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Investigation on Broadening Compressor Surge Margin by Using Active Magnetic Bearing by Yingzhe Lin, Gen Bai, Yunkai Huang, Jin Zhou, Xudong Guan, Jiyong Dong

“…For every 1% rise in CR, the surge margin would improve by 7.8%. A control method of changing the reference suspension position according to the optimal efficiency fitting model is proposed. …”
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