Comparative Analysis of Dedicated and Randomized Storage Policies in Warehouse Efficiency Optimization by Rana M. Saleh, Tamer F. Abdelmaguid

“…Given the complexity of the combined problem, a tailored Non-dominated Sorting Genetic Algorithm (NSGA-II) was developed to assess the performance of the two storage policies across various randomly generated test instances of differing sizes. …”
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AI IN CYBER DEFENSE: PRIVACY RISKS, PUBLIC TRUST, AND POLICY CHALLENGES by Abdullah Azizi, Mohammad Qias Mohammadi, Abdul Wahid Samadzai

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The phenomenon of digital paternalism as a factor in the transformation of state youth policy by  S. V. Polyakov

“…The scientific novelty lies in the conceptualization of «digital paternalism» as a qualitatively new stage in the evolution of state youth policy, synthesizing elements of traditional paternalism with the capabilities of digital platforms and algorithmic governance. …”
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Detecting unsafe behavior in neural network imitation policies for caregiving robotics by Andrii Tytarenko

“…While leveraging advancements in deep learning and control algorithms, the study focuses on training neural network policies using offline demonstrations. …”
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Policy Efforts to Promote the Adoption of Autonomous Vehicles: Subsidy and AV Lanes by Chao Liu, Hongfei Jia, Yu Lin, Guanfeng Wang, Jingjing Tian, Ruiyi Wu, Heyao Gao

“…To promote the adoption of AVs, it would be crucial for the government to take policy measures. This paper develops a two-stage model to explore the effects of subsidy and AV lanes’ policies on AV adoption. …”
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Algorithmic Techniques for GPU Scheduling: A Comprehensive Survey by Robert Chab, Fei Li, Sanjeev Setia

“…In this survey, we provide a comprehensive classification of GPU task scheduling approaches, categorized by their underlying algorithmic techniques and evaluation metrics. We examine traditional methods—including greedy algorithms, dynamic programming, and mathematical programming—alongside advanced machine learning techniques integrated into scheduling policies. …”
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Disinformation optimised: gaming search engine algorithms to amplify junk news by Samantha Bradshaw

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Optimization and Trends in EV Charging Infrastructure: A PCA-Based Systematic Review by Javier Alexander Guerrero-Silva, Jorge Ivan Romero-Gelvez, Andrés Julián Aristizábal, Sebastian Zapata

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POLICY FOR THE ASSESSMENT AND COMPENSATION OF DAMAGES FROM THE RUSSIAN FEDERATION’S AGGRESSION AGAINST UKRAINE by Valerii Zhuk, Yuliia Bezdushna, Nataliia Zhuk, Olena Hryschenko

“…This mechanism will enable businesses to assess both their direct and indirect losses resulting from the war. It includes an algorithm for recording and reporting indirect losses, with subsequent integration into national statistics and the system of national accounts. …”
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Optimal control of manipulator with joint clearance compensation via generalized policy learning by Wenting Liu, Qingliang Zeng, Zhiwen Wang, Jun Zhao, Lin Kong

“…To implement the optimal control strategy, a generalized policy learning algorithm is developed, which reduces the dependency on known system dynamics. …”
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Optimizing Robotic Arm Learning: Curiosity-Driven Deep Deterministic Policy Gradient by Liu Jiarun

“…This study explores the application of the Reinforcement Learning (RL) in training robotic arms, particularly using the Deep Deterministic Policy Gradient (DDPG) algorithm enhanced by a curiosity- driven mechanism. …”
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Intelligent policy framework: Natural resource conservation, knowledge and big data analytics by Nina Xiao, Xianhe Qu

“…Bayesian inference constructs a conditional probability network to model and analyze complex relationships in a multi-factor environment, allowing for dynamic updates of the influences of various factors and providing precise evaluations of natural resource protection policies. This approach integrates prior information and observational data to ensure the continuity and accuracy of predictions. …”
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Ethical and legal considerations in healthcare AI: innovation and policy for safe and fair use by Tuan Pham

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A policy conflict detection mechanism for multi-controller software-defined networks by You Lu, Qiming Fu, Xuefeng Xi, Zhenping Chen, Encen Zou, Baochuan Fu

“…First, it quantifies and classifies the software-defined policy conflict itself to provide the basis for detection mechanism; then, it proposes a conflict detection model and its deployment scheme for multi-controller software-defined networks; finally, based on the software-defined flow policy’s structure, a multi-branch tree-based policy conflict detection algorithm is proposed to accurately detect the universal types of conflicts. …”
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An Efficient Fine-Grained Access Control Scheme Based on Policy Protection in SGs by Xiaoqing Guo, Huayi Wu, Zhen Qin, Ruonan Ying, Jilai Yang

“…We propose an efficient fine-grained access control scheme for secure information processing with policy protection to address this issue. By integrating the cuckoo filter, the proposed scheme achieves complete attribute hiding, thereby improving system privacy and security. …”
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Climate risk and low-carbon policies: implications for sports economics and global events by Siyu Fu, Chen Kong

“…ICSF, on the other hand, leverages game theory and optimization algorithms to enhance decision-making in areas such as resource allocation, salary cap management, and sustainability-oriented strategic planning.ResultsEmpirical results from multiple datasets and experiments confirm that the integration of climate risk and low-carbon policy variables significantly improves the predictive accuracy and resilience of economic planning in the sports sector.DiscussionThis research provides theoretical advancements and practical insights for policymakers, sports managers, and investors seeking to navigate the complex interplay between sustainability and profitability in a rapidly changing global environment.…”
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A Small-Sample Scenario Optimization Scheduling Method Based on Multidimensional Data Expansion by Yaoxian Liu, Kaixin Zhang, Yue Sun, Jingwen Chen, Junshuo Chen

“…Firstly, based on spatial correlation, the daily power curves of PV power plants with measured power are screened, and the meteorological similarity is calculated using multicore maximum mean difference (MK-MMD) to generate new energy output historical data of the target distributed PV system through the capacity conversion method; secondly, based on the existing daily load data of different types, the load historical data are generated using the stochastic and simultaneous sampling methods to construct the full historical dataset; subsequently, for the sample imbalance problem in the small-sample scenario, an oversampling method is used to enhance the data for the scarce samples, and the XGBoost PV output prediction model is established; finally, the optimal scheduling model is transformed into a Markovian decision-making process, which is solved by using the Deep Deterministic Policy Gradient (DDPG) algorithm. The effectiveness of the proposed method is verified by arithmetic examples.…”
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AI-driven assistive technologies in inclusive education: benefits, challenges, and policy recommendations by Chokri Kooli, Rim Chakraoui

“…Additionally, the paper highlights limitations related to accuracy, infrastructure needs, educator readiness, and ethical concerns such as data privacy and algorithmic bias.To address these challenges, the study proposes policy recommendations and practical strategies for equitable and responsible AI adoption in education, including targeted educator training, funding for inclusive infrastructure, and development of ethical and technical standards. …”
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An algorithm to generate correlated input-parameters to be used in probabilistic sensitivity analyses by Mohamed Neine, Desmond Curran

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From algorithms to negotiations: Why health diplomacy must adapt. by Brian Li Han Wong, Garry Aslanyan, Warisa Panichkriangkrai, Ricardo Baptista Leite, Jemilah Mahmood, Anders Nordström

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