Mechanisms for Secure Access to Data of Scientometric Systems Using Virtual DBMS by Alexander Kozitsin, Maxim Zanchurin

“…The paper discusses ways to ensure secure access to data when integrating scientometric systems with external systems, based on the use of virtual databases. …”
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Interpretable Reinforcement Learning for Sequential Strategy Prediction in Language-Based Games by Jun Zhao, Jintian Ji, Robail Yasrab, Shuxin Wang, Liang Yu, Lingzhen Zhao

“…To address these challenges, this study proposes an interpretable reinforcement learning framework based on an Enhanced Deep Deterministic Policy Gradient (Enhanced-DDPG) algorithm. By leveraging a custom simulation environment and integrating key linguistic features word frequency, letter frequency, and repeated letter patterns (rep) the model dynamically predicts the number of attempts needed to solve <b>Wordle</b> puzzles. …”
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Machine learning algorithms to predict khat chewing practice and its predictors among men aged 15 to 59 in Ethiopia: further analysis of the 2011 and 2016 Ethiopian Demographic and... by Mequannent Sharew Melaku, Lamrot Yohannes, Eliyas Addisu Taye, Nebebe Demis Baykemagn

“…Effective khat prevention strategies should focus on the following: preserving rural norms that discourage khat use and expanding these to urban areas; targeted interventions for young and middle-aged men, including youth programs and economic empowerment initiatives as alternative opportunities; strengthening family values through marriage counseling and spouse involvement to help reduce khat chewing; integrating khat education into reproductive health programs and engaging religious leaders in awareness efforts; and, finally, implementing media campaigns, school-based education, and policy measures—such as restricting sales near schools and enforcing community bylaws—to further curb khat consumption while promoting healthier economic alternatives.…”
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Integrating Machine Learning, SHAP Interpretability, and Deep Learning Approaches in the Study of Environmental and Economic Factors: A Case Study of Residential Segregation in Las... by Jingyi Liu, Yuxuan Cai, Xiwei Shen

“…Among the tested algorithms, LGBM (Light Gradient Boosting) delivered the highest predictive accuracy and robustness. …”
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Technological Culture and Politics: Artificial Intelligence as the New Frontier of Political Communication by Daniele Battista, Emiliana Mangone

“…One of the issues under discussion is whether the integration of AI in the political context represents a promising opportunity to improve the efficiency of democratic participation and policy-making processes, as well as increase institutional accountability. …”
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The sustainable energy development dilemma in European countries: a time-series cluster analysis by Víctor Dugo, David Gálvez-Ruiz, Pilar Díaz-Cuevas

“…Conclusions The diversity of energy and environmental performance among European countries underlines the need for concrete policies that integrate the specific socioeconomic, energy and environmental contexts of each country. …”
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Low-Power-Management Engine: Driving DDR Towards Ultra-Efficient Operations by Zhuorui Liu, Yan Li, Xiaoyang Zeng

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THE ROLE OF ORGANIZATIONAL AND ECONOMIC MECHANISM OF STRATEGIC COMPANY MANAGEMENT IN THE NATIONAL ECONOMY by О. Parfentieva, А. Grechan, A. Bezuglyi, К. Kompanets, О. Salimon

“…The mechanism of strategic company management based on investment activity is suggested. An algorithm for improving strategic investment management is suggested. …”
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Realizing the promise of machine learning in precision oncology: expert perspectives on opportunities and challenges by Vasileios Nittas, Kelly E. Ormond, Effy Vayena, Alessandro Blasimme

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The Impact Prediction of Income Tax Standards on Company Performance: A Hybrid Spatial Artificial Intelligence Approach by Sawsan Kareem Abdullah

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Observer-Based Deep Reinforcement Learning for Robust Missile Guidance and Control by Wenwen Wang, Zhihua Chen

“…This study presents a deep reinforcement learning (DRL)-based missile guidance system that integrates an extended state observer (ESO) using a leaky proximal policy optimization algorithm. …”
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Machine Learning with Administrative Data for Energy Poverty Identification in the UK by Lin Zheng, Eoghan McKenna

“…This research demonstrates that machine learning, trained on existing administrative datasets, offers a feasible, scalable, and interpretable alternative for energy poverty identification, enabling new opportunities for efficient targeted policy interventions. This study also aligns with recent UK government discussions on the potential for integrating administrative data sources to enhance policy implementation. …”
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Machine Learning in Public Governance: A Systematic Review of Applications, Trends and Challenges by Y. Nuruly, G. N. Sansyzbayeva, L. Z. Ashirbekova, S. K. Tazhiyeva

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From Land Conservation to Famers’ Income Growth: How Advanced Livelihoods Moderate the Income-Increasing Effect of Land Resources in an Ecological Function Area by Xinyu Zhang, Yiqi Zhang, Yanjing Yang, Wenduo Wang, Xueting Zeng

“…This study investigates how ecological land resources influence farmers’ incomes in ecological function areas (EFAs), with a focus on the moderating role of advanced livelihoods (ALI). Using an integrated Fixed-Effects–SVM–Genetic Algorithm framework, we quantify nonlinear policy-livelihood interactions and simulate multi-scenario governmental interventions (e.g., ecological investment, returning farmland to forest/RFF) across Beijing’s EFA, which can obtain the key findings as follows: (a) Ecological land resources have a significant positive effect on farmers’ incomes due to production-manner adjustment guided by governmental green strategy and corresponding TSP in an ecological restoration area of an EFA, while they have a non-significant impact in the core ecological reserve areas on account of the strict environmental protection restrictions on economic activities. …”
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Changing social citizenship through information technology by Karolina Sztandar-Sztanderska, Marianna Zielenska

“…Instead, the access to services and benefits is determined on the basis of multiple non-transparent and seemingly technical criteria (for similar accounts, see van Berkel 2011; Dubois 2009) inscribed in the IT tool: the profiling programme scores personal characteristics and attitudes towards work - the so called"employment potential" - according to a hidden algorithm. This computer-integrated assessment has significant consequences as those who are classified as lacking"employment potential" (i.e. approximately 33% of the unemployed population) have no possibility to appeal against the decision and become formally excluded from most forms of active labour market programmes (Niklas et al. 2015). …”
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Evolution of machine learning applications in medical and healthcare analytics research: A bibliometric analysis by Samuel-Soma M. Ajibade, Gloria Nnadwa Alhassan, Abdelhamid Zaidi, Olukayode Ayodele Oki, Joseph Bamidele Awotunde, Emeka Ogbuju, Kayode A. Akintoye

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Ethical, Legal, and Socioeconomic Aspects of Implementing Artificial Intelligence in Tax Administration by Artur Bogucki

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Artificial Intelligence for Drug Discovery Accelerating the Development of New Pharmaceuticals by Basri T. Syeda Jeelani, Kulkarni Adokshaja Krishnarao, K Renuka, B Yamini Supriya, R V Kavya, A Buckshumiyan

“…However, despite its potential, current AI can cause several challenges, including small-scale validation, AI bias, data privacy, regulatory compliance, as well as scalability and integration into clinical practice. These challenges can be addressed through large-scale real-world validations, fairness-aware algorithms and privacy-preserving techniques building a next-gen AI framework enabling our research. …”
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Simulation-based deep reinforcement learning for multi-objective identical parallel machine scheduling problem by Sohyun Nam, Young-in Cho, Jong Hun Woo

“…In the training phase of the scheduling agent, the Proximal Policy Optimization algorithm is applied to learn the scheduling policy, which is approximated by deep neural networks. …”
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Blockchain-Enhanced Attribute-Based Encryption Architecture With Feasibility Analysis by Agustin Ferrer-Rojas, Bodhaswar T. Maharaj, Mduduzi C. Hlophe

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