Enhanced Mamba model with multi-head attention mechanism and learnable scaling parameters for remaining useful life prediction by Fugang Liu, Shenyang Liu, Yuan Chai, Yongtao Zhu

“…In this paper, we propose a remaining useful life (RUL) prediction model based on Mamba, which incorporates learnable parameters and a multi-head attention mechanism; to address the issues faced by traditional algorithms, which struggle to efficiently capture dependencies in long sequences and parallelize the processing of these sequences. …”
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Influence of wearable biometric sensors on performance indicators of volleyball players by Guoqing Jia

“…Two classification algorithms—K Nearest Neighbour (KNN) and Linear Discriminant Analysis (LDA)—are combined with two separate cross-valuation methods. …”
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Development of Advanced Machine Learning Models for Predicting CO₂ Solubility in Brine by Xuejia Du, Ganesh C. Thakur

“…Using a comprehensive database of 1404 experimental data points spanning temperature (−10 to 450 °C), pressure (0.098 to 140 MPa), and salinity (0.017 to 6.5 mol/kg), the research evaluates the predictive capabilities of five ML algorithms: Decision Tree, Random Forest, XGBoost, Multilayer Perceptron, and Support Vector Regression with a radial basis function kernel. …”
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Optimization of microwave components using machine learning and rapid sensitivity analysis by Slawomir Koziel, Anna Pietrenko-Dabrowska

“…On the other hand, the most widely used nature-inspired algorithms require large numbers of system simulations to yield a satisfactory design. …”
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A hybrid extraction model for semantic knowledge discovery of water conservancy big data by Yanna Feng, Feng Zhang, Yongheng Zhang, Jiangang Dong, PengJu Wang

“…To address the growing demand for efficient public opinion analysis in water conservancy and related domains, as well as the inefficiencies and limited scalability of existing automated web data extraction algorithms for multi-source datasets, this research integrates advanced technologies including big data analytics, natural language processing, and deep learning. …”
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Syllable-, Bigram-, and Morphology-Driven Pseudoword Generation in Greek by Kosmas Kosmidis, Vassiliki Apostolouda, Anthi Revithiadou

“…Pseudowords are essential in (psycho)linguistic research, offering a way to study language without meaning interference. …”
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Low-Power-Management Engine: Driving DDR Towards Ultra-Efficient Operations by Zhuorui Liu, Yan Li, Xiaoyang Zeng

“…Our research strategy encompasses real-time monitoring of the DDR subsystem’s operational states, traffic intervals, and Quality of Service (QoS) metrics. …”
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Platform Employment — the Scale and Evidence of Instability by V. N. Bobkov, E. A. Chernykh

“…Platforms are digital (virtual) technological devices-software, algorithms, control systems using artificial intelligence and other digital means of labour. …”
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Carbon reduction analysis of power system based on carbon emission flow theory: a case study of Shenzhen power grid by Yinjie Li, Ningrui Zhou, Zeqi Zhang

“…To address these challenges, this study proposes an integrated framework combining carbon emission flow theory with a low carbon demand response mechanism, accompanied by corresponding computational algorithms. Utilizing operational data from the Shenzhen power grid, we conducted a comprehensive empirical study featuring three key innovations. …”
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Advancing cardiovascular care through actionable AI innovation by Giuseppe Biondi-Zoccai, Arjun Mahajan, Dylan Powell, Mariangela Peruzzi, Roberto Carnevale, Giacomo Frati

“…Indeed, offline RL refers to a class of ML algorithms that learn optimal decision-making policies from a fixed dataset of previously collected experiences—such as electronic health records or registries—without the need for active, real-time interaction with the clinical environment. …”
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Analyzing the compressive performance of lightweight foamcrete and parameter interdependencies using machine intelligence strategies by Wang Guoyuan, Fan Wenbo, Shi Qingbin, Luo Yingqi

“…Nevertheless, there is still a lack of practical applications, which calls for more research, especially in strength studies, to increase its use in the actual world. …”
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A Comparative study of the Envisaged and Definite Stock Prices of BSE SMEs Using RNN during the COVID-19 Pandemic by S. Kaur, A. Munde, A. K. Goyal

“…The stock market is unstable, but the use of machine learning algorithms allows to predict its future dynamics before spending. …”
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Remote sensing semantic segmentation based on multimodal feature alignment and fusion by B. Chang, T. Balz

“…The accurate semantic segmentation of remote sensing data is of paramount importance to the success of geoscience research and applications. In comparison to traditional single-modal segmentation techniques, models based on multi-modal fusion have demonstrated superior performance and have been the subject of considerable attention in recent years. …”
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Robust design of bicycle infrastructure networks by Christoph Steinacker, Mads Paulsen, Malte Schröder, Jeppe Rich

“…In this paper, we approach the problem from two perspectives: direct optimization methods, which generate near-optimal solutions using operations research techniques, and conceptual heuristics, which offer intuitive and scalable algorithms grounded in network science. …”
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Introduction of self-control of enterprise information system through accounting documentation process of by K.О. Volskа

“…The research is devoted to determining the possibility of implementing self-control of an enterprise information system, describing the criteria for building an information system in an enterprise that will be self-organized and capable of self-analysis. …”
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Non-Profiled Partial Nibble Recovery on Power Attack Resilient Adiabatic PRESENT Block Cipher Through AI Vulnerability Assessment by Anjana Jyothi Banu, A. A.

“…Artificial Intelligence (AI) techniques, by eliminating the need for prior knowledge of cryptographic algorithms, have emerged as powerful tools for executing effective SCAs on secure implementations. …”
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TECHNOLOGIES FOR DEVELOPING DECISION SUPPORT SYSTEMS FOR THE DIAGNOSIS OF BLOOD DISORDERS USING CONVOLUTIONAL NEURAL NETWORKS by U. V. Maslikova, A. A. Supilnikov

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A review of ultrasound monitoring applications in agriculture by Muhammad Awais Sattar, Dina Shona Laila

“…Finally, the review also discusses the current limitations and future research directions of how ultrasound-based monitoring can catalyse a new paradigm of sustainable data-driven agriculture that meets food security needs.…”
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An Integrated Supply Chain Model for Predicting Demand and Supply and Optimizing Blood Distribution by Pooria Bagher Niakan, Mehdi Keramatpour, Behrouz Afshar-Nadjafi, Alireza Rashidi Komijan

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Fault Diagnosis in a Four-Arm Delta Robot Based on Wavelet Scattering Networks and Artificial Intelligence Techniques by Claudio Urrea, Carlos Domínguez

“…This study compares time-domain signal features and wavelet scattering networks, applied by classification algorithms including wide neural networks (WNNs), efficient linear support vector machine (ELSVM), efficient logistic regression (ELR), and kernel naive Bayes (KNB). …”
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