Validating an Electronic Health Record Algorithm for Diabetes Screening Eligibility in the Emergency Department by Mary H. Smart, Janet Y. Lin, Brian T. Layden, Yuval Eisenberg, Kirstie K. Danielson, Ruth Pobee, Chuxian Tang, Brett Rydzon, Anjana Bairavi Maheswaran, A. Simon Pickard, Lisa K. Sharp, Angela Kong

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Algorithms Facilitating the Observation of Urban Residential Vacancy Rates: Technologies, Challenges and Breakthroughs by Binglin Liu, Weijia Zeng, Weijiang Liu, Yi Peng, Nini Yao

“…Algorithms can handle complex spatial data, integrate diverse data sources, and explore the social and economic factors behind vacancy rates. …”
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Two-layer Optimization Scheduling for Off-grid Microgrids Based on Multi-agent Deep Policy Gradient by Huicong FAN, Zhiguo DUAN, Zhiyong CHEN, Shijia ZHU, Hang LIU, Wenxiao LI, Yang YANG

“…The lower-level model optimizes slow-regulating discrete devices based on mixed-integer second-order cone programming, while the upper-level model optimizes fast-regulating continuous devices using a multi-agent deep policy gradient algorithm. The two-layer model coordinates both active and reactive power flows of the microgrid, enabling real-time monitoring of the microgrid's status and online decision-making for the optimization of device regulation, without reliance on precise power flow models or complex communication systems. …”
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Integration of theoretical and methodological developments in the field of sustainable development into regional management by Tatiana V. Alferova

“…The study applies the methods of analysis and synthesis, conceptual and functional modelling to build logical-semantic and descriptive models of scientific developments’ integration into regional management. As a result of the research, the authors transform analytical support structure of political decisions, which now involves the creation of scientific missions; develop tools for measuring the sustainable development of a region to be introduced into key management functions at all stages of the management cycle; create an algorithm for preparing decisions that comprises four stages: conceptualisation, modelling, measurement, and assessment. …”
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Foreign Economic Cooperation between Russia and Vietnam in the Context of Regional Integration by N. O. Yakushev

“…The development of foreign economic cooperation with friendly countries is one of the key priorities of Russia’s economic and foreign policy. This study aims to determine the specific characteristics and promising directions for Russian-Vietnamese foreign economic cooperation in the context of regional integration. …”
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Forwarding efficiency aware traffic scheduling algorithm based on deep reinforcement learning by Zongxuan SHA, Ru HUO, Chuang SUN, Shuo WANG, Tao HUANG

“…The software defined network separates the control plane from the data plane to achieve flexible traffic scheduling, which can use network resources more efficiently.However, with the increase of the number of flow entries, load rate, the number of connected hosts, and other factors, the forwarding efficiency of the SDN switch will be reduced, which will affect the end-to-end transmission delay.To solve the above problems, the forwarding efficiency aware traffic scheduling algorithm based on deep reinforcement learning was proposed.First, the switch state was integrated into the perception model, and the mapping relationship between switch state information and forwarding efficiency was established based on neural network.Then, combined with network state and traffic information, traffic scheduling policy was generated through deep reinforcement learning.Finally, the expert samples generated by the shortest path and load balance algorithms could guide the model training, which enabled the model to learn knowledge from expert samples to improve performance and accelerated the training process.The experimental results show that the proposed algorithm not only reduces the average end-to-end transmission delay by 15.31%, but also ensures the overall load balance of the network, compared with other algorithms.…”
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Forwarding efficiency aware traffic scheduling algorithm based on deep reinforcement learning by Zongxuan SHA, Ru HUO, Chuang SUN, Shuo WANG, Tao HUANG

“…The software defined network separates the control plane from the data plane to achieve flexible traffic scheduling, which can use network resources more efficiently.However, with the increase of the number of flow entries, load rate, the number of connected hosts, and other factors, the forwarding efficiency of the SDN switch will be reduced, which will affect the end-to-end transmission delay.To solve the above problems, the forwarding efficiency aware traffic scheduling algorithm based on deep reinforcement learning was proposed.First, the switch state was integrated into the perception model, and the mapping relationship between switch state information and forwarding efficiency was established based on neural network.Then, combined with network state and traffic information, traffic scheduling policy was generated through deep reinforcement learning.Finally, the expert samples generated by the shortest path and load balance algorithms could guide the model training, which enabled the model to learn knowledge from expert samples to improve performance and accelerated the training process.The experimental results show that the proposed algorithm not only reduces the average end-to-end transmission delay by 15.31%, but also ensures the overall load balance of the network, compared with other algorithms.…”
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Optimization model for enterprise financial management utilizing genetic algorithms and fuzzy logic by Sujuan Wang, Musadaq Mansoor

“…To improve predictive accuracy, the study integrates genetic algorithms with back-propagation (BP) neural networks, leveraging genetic algorithms to optimize the neural network’s parameters and structure. …”
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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

“…By adopting scalable AI models and fostering interdisciplinary collaborations, healthcare systems can overcome existing barriers, integrating AI seamlessly into infection control policies and ultimately enhancing patient safety and care quality. …”
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Exploring “Many Objective Robust Decision Making” for managing uncertainty in climate policy analysis for the transport sector by Albin Engholm, Ida Kristoffersson

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Multivariate machine learning algorithms for energy demand forecasting and load behavior analysis by Farhan Hussain, M. Hasanuzzaman, Nasrudin Abd Rahim

“…For strategic planning, medium- and long-term electricity projections integrate ANN and ANFIS with an econometric approach aligned with national policy, providing area-wide development-consistent forecasts. …”
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The Role of Misclassification and Carbon Tax Policies in Determining Payment Time and Replenishment Strategies for Imperfect Product Shipments by Chun-Tao Chang, Yao-Ting Tseng

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An improved hybrid policy optimization method for economic-preference dispatch considering cross time-scales collaboration by Qianli Zhang, Hao Tang, Duanchao Li

“…In this paper, we present an improved DRL algorithm, called distributed partial-modulation proximal policy optimization (DPMPPO), to address this issue. …”
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Evaluating end-to-end autonomous driving architectures: a proximal policy optimization approach in simulated environments by Ângelo Morgado, Kaoru Ota, Mianxiong Dong, Nuno Pombo

“…The study uses the Proximal Policy Optimization (PPO) algorithm within the CARLA simulation environment. …”
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An amalgamated load shifting cum curtailing policy with smart charging of PHEV for economic operation of microgrid system by Bishwajit Dey, Srikant Misra, Arnab Pal, Fausto Pedro Garcia Marquez

“…This research aims to implement integrated load shifting and curtailment algorithms inside a microgrid with a low voltage category system to distribute energy resources that are optimally scheduled, hence minimizing overall operating costs. …”
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COMPARATIVE ANALYSIS OF DOUBLE DEEP Q-NETWORK AND PROXIMAL POLICY OPTIMIZATION FOR LANE-KEEPING IN AUTONOMOUS DRIVING by Ariful Islam Sabbir

“…This article gives a comparative examination of two reinforcement learning (RL) algorithms—Double Deep Q-Network and Proximal Policy Optimization—for lanekeeping across discrete and continuous action spaces. …”
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The battle for TNCs in Latin America: navigating policy trends and sociotechnical controversies in the regulation of ride-hailing platforms by Ronald Sáenz-Leandro

“…Findings reveal that while policy frameworks predominantly emphasize market access and innovation-driven consumer protection measures, other crucial sociotechnical controversies, such as driver misclassification, environmental impacts, algorithmic transparency, and data-sharing obligations, remain marginal or neglected. …”
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A multi-site study of clinician perspectives in the lifecycle of an algorithmic risk prediction tool by Rita Dexter, Kristin Kostick-Quenet, Jennifer Blumenthal-Barby

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Organizational and methodical approaches to disclosure of income distribution in integrated reporting by Legenchyk S.F., Polishchuk I.R.

“…The issue of the necessity of conducting the external audit of the data verification of the integrity reporting is highlighted. The algorithm of profit distribution depending on the chosen strategy of enterprise development is proposed. …”
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Large Language Model-Guided SARSA Algorithm for Dynamic Task Scheduling in Cloud Computing by Bhargavi Krishnamurthy, Sajjan G. Shiva

“…State Action Reward Action (SARSA) learning, a policy variant of Q learning, which learns the value function based on the current policy action, has been utilized in task scheduling. …”
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