High-voltage defibrillator unit with increased energy output from a controlled capacitor storage by E. E. Gorokhov-Miroshnikov, G. V. Slyusarev

“…It has been established that it is possible to form a pulse with a virtually constant output energy in a wide range of patient resistances. The model of the proposed high-voltage unit shows the possibility of increasing the energy output from the capacitor bank when forming a pulse of optimal duration with a flat front. …”
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Adversarial Sample Generation Method Based on Frequency Domain Transformation and Channel Awareness by Yalin Gao, Dongwei Xu, Huiyan Zhu, Qi Xuan

“…To solve these problems, we propose a super-resolution denoising residual network (SDRNet), which combines the advantages of the super-resolution convolutional neural network (SRCNN) and the denoising convolutional neural network (DnCNN) to construct a pilot-based OFDM signal model, train SDRNet using OFDM pilot data containing Gaussian noise, and optimize its feature enhancement ability in frequency-selective fading channels. …”
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Application of business analysis tools in company management by A. Yu. Orlova, A. A. Sorokin, D. G. Lovyannikov

“…We have developed an algorithm for the implementation of a business intelligence system and for this purpose built models in the EPC AS-IS and TO-BE notation. …”
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Information and methodological aspects of developing platforms of spatial management of natural assets in resource limitations by V.V. Mykytenko, I.V. Dragan

“…It is planned to build, within the subsystems of functional and decision-making and development of communicative metaspace, which is included in the spatial management system, sustainable theoretical-analytical and applied models with a high degree of approximation of characteristics and comparative assessment of optimal natural assets for involvement within business ecosystems of Ukraine, available natural resources in the context of the formation of a national economy of the platform type as a result of strengthening the competitive positions of participants in sustainable management and increasing the effectiveness of spatial management. …”
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Development of PYMUS+ Code for Quantitative Evaluation of Nuclear Material Accounting (NMA) System by Byung Hee Won, Hee-Sung Shin, Se Hwan Park, Seong-Kyu Ahn

“…It is also important to quantitatively evaluate the performance of NMA system including NRTA from the standpoints of Safeguards and Security by Design (SSBD) prior to construction of nuclear-material-handling facilities. Such evaluation improves safeguards effectiveness and efficiency. Modeling and Simulation (M&S) work is a good way to evaluate performance for various NMA systems and to determine the optimal one among different options. …”
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Automated Body Condition Scoring in Dairy Cows Using 2D Imaging and Deep Learning by Reagan Lewis, Teun Kostermans, Jan Wilhelm Brovold, Talha Laique, Marko Ocepek

“…The study recommends improvements in algorithmic feature extraction, dataset expansion, and multi-view integration to enhance accuracy. …”
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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…Artificial intelligence (AI) offers promising potential for improving HAIs prevention through advanced predictive capabilities.ObjectiveTo evaluate the effectiveness, usability, and challenges of AI models in preventing, detecting, and managing HAIs.MethodsThis integrative review synthesized findings from 42 studies, guided by the SPIDER framework for inclusion criteria. …”
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Innovative approach for gauge-based QPE in arid climates: comparing neural networks and traditional methods by Bayan Banimfreg, Ernesto Damiani, Vesta Afzali Gorooh, Duncan Axisa, Luca Delle Monache, Youssef Wehbe

“…These improvements highlight the model’s ability to assimilate diverse climatic and topographical inputs for more accurate rainfall prediction, particularly in areas where conventional methods fall short due to sparse or irregular precipitation. …”
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The artificial intelligence revolution in gastric cancer management: clinical applications by Runze Li, Jingfan Li, Yuman Wang, Xiaoyu Liu, Weichao Xu, Runxue Sun, Binqing Xue, Xinqian Zhang, Yikun Ai, Yanru Du, Jianming Jiang

“…The integration of artificial intelligence, from optimizing the diagnosis process and enhancing diagnostic efficiency to promoting the practice of precision medicine, demonstrates its promising prospects for reshaping the treatment model of gastric cancer. …”
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Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT by Hao-Nan Zhu, Yi-Fan Guo, YingMin Lin, Zhi-Chao Sun, Xi Zhu, YuanZhe Li

“…Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. …”
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An Enhanced Phenology Dataset for Global Drylands from 2001 to 2019 by Yuqi Dong, Yu Zhou, Li Zhang, Feng Tian, Qiaoyun Xie, Yiyang Chen, Linlin Ruan, Bo Zhang

“…Existing land surface phenology (LSP) products exhibit low accuracy in drylands due to coarse spatiotemporal data sources and algorithms optimized for other ecosystems. Here we present the Global Dryland Phenology Dataset (GDPD) for 2001–2019, derived from daily 500-m two-band Enhanced Vegetation Index using MODIS NBAR data and an improved retrieval algorithm with dynamic, pixel-wise amplitude thresholds. …”
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Unraveling C-to-U RNA editing events from direct RNA sequencing by Adriano Fonzino, Caterina Manzari, Paola Spadavecchia, Uday Munagala, Serena Torrini, Silvestro Conticello, Graziano Pesole, Ernesto Picardi

“…Using in vitro synthesized and human ONT reads, our model optimizes the signal-to-noise ratio improving the detection of C-to-U editing sites with high accuracy, over 90% in all samples tested. …”
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Tire Pressure Monitoring System Using Feature Fusion and Family of Lazy Classifiers by Arpit Pandey, Sridharan Naveen Venkatesh, Prabhakaranpillai Sreelatha Anoop, B. R. Manju, Vaithiyanathan Sugumaran

“…The study examines autoregressive moving average (ARMA), histogram, and statistical features individually and in combinations (statistical‐histogram, histogram‐ARMA, statistical‐ARMA, and statistical‐histogram‐ARMA) to improve predictive accuracy. By integrating these features, the study aims to optimize predictive modeling of TPMS. …”
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A lightweight knowledge graph-driven question answering system for field-based mineral resource survey by Mingguo Wang, Chengbin Wang, Jianguo Chen, Bo Wang, Wei Wang, Xiaogang Ma, Jiangtao Ren, Zichen Li, Yicai Ye, Jiakai Zhang, Yue Wang

“…The results also suggest that further studies on geoscience pre-trained models, an informative library of question templates, and multimodal knowledge graphs are necessary to improve the performance of the knowledge graph-driven question-answering system.…”
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A Rapid Artificial Intelligence-Based Computer-Aided Diagnosis System for COVID-19 Classification from CT Images by Hassaan Haider Syed, Muhammad Attique Khan, Usman Tariq, Ammar Armghan, Fayadh Alenezi, Junaid Ali Khan, Seungmin Rho, Seifedine Kadry, Venkatesan Rajinikanth

“…The proposed method includes four core steps: (i) preparing a database of three different classes such as COVID-19, pneumonia, and normal; (ii) modifying three pretrained deep learning models such as VGG16, ResNet50, and ResNet101 for the classification of COVID-19-positive scans; (iii) proposing an activation function and improving the firefly algorithm for feature selection; and (iv) fusing optimal selected features using descending order serial approach and classifying using multiclass supervised learning algorithms. …”
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Integrated pixel-level crack detection and quantification using an ensemble of advanced U-Net architectures by Rakshitha R, Srinath S, N Vinay Kumar, Rashmi S, Poornima B V

“…Binary Focal Loss proved particularly effective in addressing class imbalance across four benchmark datasets. To further improve segmentation performance, two ensemble strategies were applied: stochastic reordering using logical operations (AND, OR, and averaging) and a weighted average ensemble optimized through grid search. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…We enhance the model’s diagnostic capability through complex image preprocessing techniques, such as improved noise reduction and morphological approaches. …”
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Effect of tool angle in nanocutting of single crystal GaN using diamond cutter by Yongqiang WANG, Hao XIA, Zhihang HU, Shuaiyang ZHANG, Shaohui YIN

“…Large-scale MD simulations are meticulously performed to model the nanoscale cutting process of single-crystal GaN using a diamond tool. …”
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Duck Egg Crack Detection Using an Adaptive CNN Ensemble with Multi-Light Channels and Image Processing by Vasutorn Chaowalittawin, Woranidtha Krungseanmuang, Posathip Sathaporn, Boonchana Purahong

“…In current practice, human inspectors use standard white light for crack detection, and many researchers have focused primarily on improving detection algorithms without addressing lighting limitations. …”
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Investigating employment patterns and determinants in the European Union through panel data insights by Vasilescu Maria Denisa, Stănilă Larisa, Crivoi Silvana, Belu Maria Berta

“…The clustering algorithm identified the heterogeneity of the countries, indicating an optimal number of three clusters for the grouping of EU states, considering the set of variables used. …”
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