Impulse Noise Parameter Assessment in a Batch Radio Channel by A. Yu. Bekkiev, V. A. Makoviy

“…Formulas that allow synthesizing the device operation algorithms are obtained. The structure chart of the measurer is developed; the algorithms used to assess measured parameters are given.…”
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Machine learning Techniques for Spondylolisthesis Diagnosis: a review by Rahma Rabee Aziz, Mohammed S. Jarjees, Mohammad R. Aziz, Ali Asim Hameed

“…Methodologies, sample sizes, algorithms, and measurement accuracy are the main topics of interest. …”
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THE POSTMODERN CITY TEXT IN SERHIY ZHADAN’S POETICS by Tetiana M. Starostenko., Ianina V. Gurtova

“…The purpose of the research paper is to distinguish and analyze the main categories of the Postmodern city as a text in poetry and prose by Serhiy Zhadan. …”
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A Novel RMS-Driven Deep Reinforcement Learning for Optimized Portfolio Management in Stock Trading by Asma Sattar, Amna Sarwar, Saira Gillani, Maryam Bukhari, Seungmin Rho, Muhammad Faseeh

“…The findings of this research indicate that the integrated model, mainly the DDPG_RMS effectively outperforms the baseline ^DJI index in many risk-return analyses in ratios showing better risk management, and profitability. …”
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Nailfold videocapillaroscopy in patients with deficiency of adenosine deaminase 2 (DADA2): a case-control study by Pietro Francesco Bica, Caterina Matucci-Cerinic, Elvis Hysa, Andrea Cere, Silvia Rosina, Stefano Volpi, Roberta Caorsi, Alberto Sulli, Sabrina Paolino, Vanessa Smith, Maurizio Cutolo, Marco Gattorno

“…Abstract Background Deficiency of adenosine deaminase 2 (DADA2) is a rare monogenic autoinflammatory disease mainly characterized by the presence of systemic inflammation and vascular manifestations such as vasculitis and early-onset stroke. …”
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Improving the efficiency of the automated process of drying flotation concentrate in a drum drying furnace by Kovalev Igor, Kulmurodova Nafisa, Kulmurodov Zarifjon, Voroshilova Anna, Kadirov Yorkin, Ibodullaeva Dinara

“…The study focuses on three main areas of optimization: managing humidity conditions, increasing energy efficiency and increasing the service life of equipment. …”
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A Short-Term Power Output Forecasting Model Based on Correlation Analysis and ELM-LSTM for Distributed PV System by Deng Yongsheng, Jiao Fengshun, Zhang Jie, Li Zhikeng

“…Firstly, the basic information of distributed PV system is introduced, and the main influence factors affecting the power output of distributed PV system are determined. …”
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MACHINE LEARNING MODELS FOR PERFORMANCE PREDICTION OF YOUNG PLAYERS IN FOOTBALL ACADEMIES – A REVIEW by Armand Florin Bertea, Cezar Honceriu

“…The main characteristics of these categories are reviewed. …”
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The ‘Implicit Intelligence’ of artificial intelligence. Investigating the potential of large language models in social science research by Ottorino Cappelli, Marco Aliberti, Rodrigo Praino

“…This paper addresses this gap. Our main hypothesis is that existing Artificial Intelligence Large Language Models (LLMs) can closely align with human expert assessments in specialized social science surveys. …”
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Artificial intelligence in soil science: Where do we go now? by Jose Pablo Castro, Caley K. Gasch, Paulo Flores

“…Abstract Recognizing the fast advancement of artificial intelligence (AI) in soil science, the main objective of this commentary paper is to discuss how this technology is being incorporated into the discipline, focusing on the most common algorithms and their applications. …”
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YOLO-SAR: An Enhanced Multi-Scale Ship Detection Method in Low-Light Environments by Zihang Xiong, Mei Wang, Ruixiang Kan, Jiayu Zhang

“…In low-illumination scenes, traditional ship detection algorithms often struggle due to poor visibility and blurred details in RGB video streams. …”
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A Review of Approaches for Rapid Data Clustering: Challenges, Opportunities, and Future Directions by Mahnoor, Imran Shafi, Mahnoor Chaudhry, Elizabeth Caro Montero, Eduardo Silva Alvarado, Isabel de la Torre Diez, Md Abdus Samad, Imran Ashraf

“…The paper includes a brief introduction to clustering, discussing various clustering algorithms, improvements in handling various data types, and appropriate evaluation metrics. …”
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NeuroMorse: a temporally structured dataset for neuromorphic computing by Ben Walters, Yeshwanth Bethi, Taylor Kergan, Binh Nguyen, Amirali Amirsoleimani, Jason K Eshraghian, Saeed Afshar, Mostafa Rahimi Azghadi

“…This eliminates the need for a synchronisation clock and minimises power consumption when no data is present. However, many benchmarks for neuromorphic and spiking algorithms primarily focus on spatial features, neglecting the temporal dynamics that are inherent to most sequence-based tasks. …”
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The principles of oncological alertness at the outpatient therapeutic stage by A. S. Sycheva, A. L. Kebina, A. V. Nosova, A. L. Vertkin

“…In such a situation, the main task of the therapist and general practitioner is to identify suspicious symptoms of malignant neoplasms using an algorithmized approach and refer the patient to a specialized institution.…”
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Artificial intelligence, generative artificial intelligence and research integrity: a hybrid systemic review by Khalid H. Arar, Hamit Özen, Gülşah Polat, Selahattin Turan

“…Abstract Current advances in academic research stem from two main sources: artificial intelligence technologies and the specific field of generative artificial intelligence. …”
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Socioeconomic and Cultural Determinants of the Development of Artificial Intelligence by Sorin Paul Lazăr, Iustin Atanasiu Pop, Maria Mortan

“…This technology is evaluated both globally and in terms of its components: qualified users, technical capabilities, regulations, societal support, academic support, algorithms and platforms, support from public authorities, and private economic initiatives. …”
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The Improvement of Energy Harvesting Efficiency of Constant Current Source by Martynyuk V.V., Kosenkov V.D., Fedula M.V.

“…The presented approach allows developing the maximum power point tracking algorithms based on the estimation of the equivalent current source parameters that provide improvement of the energy harvesting efficiency.…”
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Predictive Analytics in Finance Using the Arima Model. Application for Bucharest Stock Exchange Financial Companies Closing Prices by Spulbar Cristi, Ene Cezar Cătălin

“…Stock markets can be volatile, thus accurate predictions can greatly help investors and stakeholders to make wise financial choices. The main goal of this paper is to test how well the Autoregressive Integrated Moving Average (ARIMA) model can capture and predict changes in closing prices. …”
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The role of neurovisualization in monitoring stroke risk among athletes: a review by Bauyrzhan Omarov, Akbayan Aliyeva

“…Discussion: the findings were consistent with previous studies that supported the use of multimodal imaging and computational tools in stroke risk evaluation. however, data heterogeneity and algorithmic transparency were identified as persistent challenges across the reviewed literature. …”
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Neutrosophic Fuzzy Power Management (NFPM): Tackling Uncertainty in Energy Harvesting for Sensor Networks by Musallam M. AlZubi, Mohamed A. Mohamed, Hanan M. Amer, A. A. Salama

“…This paper presents a novel approach known as Neutrosophic Fuzzy Power Management (NFPM) aimed at addressing the critical challenge of uncertain energy availability in Energy Harvesting Sensor Networks (EHWSNs). The main objective of this research is to enhance the management of energy resources within these networks, which traditional fuzzy logic methods often fail to do, leading to power failures and reduced reliability. …”
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