Study on incentive mechanism of reward and punishment on work efficiency of PCB welder based on recurrence quantification analysis and electroencephalogram signals by Zhang Qian, Mingyue Guo, Fuwang Wang

“…By comparing the EEG signals of workers with and without reward and punishment incentives (control group vs. experimental group), key features such as deterministic (DET) and average diagonal line length (DLL) are extracted to reveal how incentives regulate work efficiency. …”
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Efficient energy management and temperature control of a high-tech greenhouse using an improved data-driven model predictive control by Farhat Mahmood, Rajesh Govindan, Tareq Al-Ansari

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A fast physics-based perturbation generator of machine learning weather model for efficient ensemble forecasts of tropical cyclone track by Jingchen Pu, Mu Mu, Jie Feng, Xiaohui Zhong, Hao Li

“…Although emerging artificial intelligence (AI)-based weather models offer high forecast accuracy and improved computational efficiency, they still face considerable challenges in ensemble forecasting applications, due to the unclear error growth dynamic and the lack of suitable ensemble methods in AI-based models. …”
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Deep Reinforcement Learning for RIS-Assisted Multi-UAV MU-MISO Communication Networks: Sum-Rate and Energy Efficiency Maximization by Alif Rahmatullah Umar, Hasan Albinsaid, Chia-Po Wei, Chih-Peng Li

“…We formulate separate optimization problems for sum-rate and energy efficiency, and address them using deep reinforcement learning (DRL) algorithms, namely proximal policy optimization (PPO) and deep deterministic policy gradient (DDPG). …”
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Efficient IP address retrieval using a novel octet based encoding technique for high speed lookup to improve network performance by Veeramani Sonai, Indira Bharathi, Sajjad Shaukat Jamal, Zaid Bassfar, Sameer Abdullah Nooh

“…This paper proposes an efficient deterministic approach to encoding IP prefixes that reduces storage complexity. …”
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Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning by Charilaos Latinopoulos, Efstathios Zavvos, Dimitrios Kaklis, Veerle Leemen, Aristides Halatsis

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Identification and Valuation of Economic Activities Reserves as a Priorityin Strategic Analysis by Svetlana Evgen’evna Egorova, Natal’ya Nikolaevna Kistaeva

“…Comparative characteristics of the major methods of reserves valuation: method of direct evaluation, method of comparison, deterministic factor analysis, correlation and regression analysis, value analysis, mathematical programming are provided. …”
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Reinforcement learning for autonomous underwater vehicles (AUVs): navigating challenges in dynamic and energy-constrained environments by Mohab M. Eweda, Karim ElNaggar

“…Reinforcement Learning (RL) has arisen as a revolutionary method for tackling these challenges. This paper examines significant progress in reinforcement learning algorithms, emphasizing their application in the training of autonomous underwater vehicles in both simulated and real-world environments. …”
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Secure THz Communication in 6G: A Two-Stage DRL Approach for IRS-Assisted NOMA by Muhammad Shahwar, Manzoor Ahmed, Touseef Hussain, Muhammad Sheraz, Wali Ullah Khan, Teong Chee Chuah

“…Utilizing the deep deterministic policy gradient (DDPG) algorithm, we introduce a two-stage policy learning approach designed to optimize secrecy energy efficiency (SEE) while ensuring secure communication, even in the presence of multiple eavesdroppers (Eves). …”
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Integrated estimation of parameters of radio transmitter power amplifier with automatic mode adjustment by two-frequency test signal by P. V. Sak

“…Method is proposed for calculation of energy gain and efficiency factor (efficiency) when applying automatic control of supply voltage of output cascades of shortwave transmitters intended for modulation with speech signals. …”
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Maximizing theoretical and practical storage capacity in single-layer feedforward neural networks by Zane Z. Chou, Jean-Marie C. Bouteiller, Jean-Marie C. Bouteiller, Jean-Marie C. Bouteiller, Jean-Marie C. Bouteiller

“…We derive analytical expressions for maximum theoretical memory capacity and introduce a grid-based construction and sub-sampling method for pattern generation that takes advantage of the full storage potential of the network. …”
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MM3: Multimodal framework for regional-scale quantitative landslide risk analysis by William Pollock, Joseph Wartman

“…However, to date, no readily transferable, regional-scale method for PLRA exists. In this work, we expand an existing deterministic multimodal method for landslide risk analysis developed in the country of Lebanon into a linked framework of code-based modules that are location-agnostic and computationally efficient for regional end-to-end risk estimation. • Use of near-global, remote-sensing-based inputs enables risk estimates almost anywhere in the world • Modular computational framework facilitates upgrades of component models as new research becomes available • Probabilistic implementation through a Monte Carlo approach…”
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Maximum a posteriori estimation for high-throughput peak fitting in X-ray photoelectron spectroscopy by Tarojiro Matsumura, Naoka Nagamura, Shotaro Akaho, Kenji Nagata, Yasunobu Ando

“…The computation is performed efficiently by the spectrum-adapted expectation–conditional maximisation algorithm with deterministic annealing. …”
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A comparative approach of analyzing data uncertainty in parameter estimation for a Lumpy Skin Disease model by Edwiga Renald, Miracle Amadi, Heikki Haario, Joram Buza, Jean M. Tchuenche, Verdiana G. Masanja

“…This has driven the interest to research efficient mitigating measures towards controlling the transmission of LSD. …”
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A novel explicit scheme for stochastic diffusive SIS models with treatment effects by Muhammad Shoaib Arif

“…The scheme is designed as an explicit two-stage method, where only the time-dependent terms are discretized, ensuring computational efficiency. …”
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A two-stage computational approach for stochastic Darcy-forchheimer non-newtonian flows by Muhammad Shoaib Arif, Muhammad Shoaib Arif, Kamaleldin Abodayeh, Yasir Nawaz

“…The proposed two-stage numerical method integrates a modified time integrator with a second-stage Runge-Kutta scheme, ensuring second-order accuracy in time for deterministic problems. …”
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A Proposed Stochastic Finite Difference Approach Based on Homogenous Chaos Expansion by O. H. Galal

“…Galerkin projection is used in converting the original stochastic partial differential equation (PDE) into a set of coupled deterministic partial differential equations and then solved using finite difference method. …”
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RELIABILITY-BASED DESIGN OPTIMIZATION USING OPTIMUM SAFETY FACTORS FOR LARGE-SCALE PROBLEMS by Gh. Kharmanda, I. R. Antypas

“…A numerical application on a large scale problem under  fatigue  loading  shows  the  efficiency of the developed RBDO method relative to the Deterministic Design Optimization (DDO). …”
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Stochastic carbon footprint tracing for power systems with uncertainty by Jiashuo Hu, Mengge Shi, Xiao‐ping Zhang, Youwei Jia

“…Recognizing that the CEF network complexity increases with higher DER penetration, the second method extends the initial approach to enhance computational efficiency while maintaining accuracy, thus ensuring scalability for large‐scale power system topologies. …”
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Local and global sensitivity analysis of key durability parameters of concrete under chloride environment by Lingjie Wu, Chengjian Yu, Fenfei Shi, Xuping Ni

“…By integrating the One-At-a-Time (OAT) method for local sensitivity analysis with the extended Fourier Amplitude Sensitivity Test (EFAST) and Sobol methods for global sensitivity analysis, a systematic evaluation is conducted to identify distinct influence mechanisms of these parameters under deterministic and time-dependent durability life prediction models. …”
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