Trajectory Optimization for High-Speed and Long-Range Interceptor Based on Improved Adaptive hp Pseudospectral Method by Changxin Luo, Chijun Zhou, Jiong Li, Humin Lei

“…On the other hand, the curvature of the system state curve is used as the criterion to segment the original mesh nonuniformly so that more mesh points can be allocated where the curvature is large. These two points together ensure that the collocation point resources can be used more efficiently in the mesh refinement process. …”
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Dynamic energy consumption monitoring and scheduling for green buildings: A comprehensive approach by Hua Zheng, Pengming Wang

“…The scheduling strategy adopts a dynamic approach based on priority to flexibly allocate energy resources to ensure the coordinated operation of various energy systems in the building. …”
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Leveraging deep neural network and language models for predicting long-term hospitalization risk in schizophrenia by Yihang Bao, Wanying Wang, Zhe Liu, Weidi Wang, Xue Zhao, Shunying Yu, Guan Ning Lin

“…Abstract Early warning of long-term hospitalization in schizophrenia (SCZ) patients at the time of admission is crucial for effective resource allocation and individual treatment planning. …”
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Preventing Health Risks Through Intelligent Medical Appointment Management Using Disease and Attendance Propensity by Fredy Troncoso-Espinosa, Guillermo Latorre-Nunez, Catalina Valenzuela-Nunez, Juan San Martin-Duran

“…Patients scheduled by the intelligent model show higher mean propensities to attend appointments and to develop diseases, ensuring that medical resources are allocated efficiently to those in greatest need. …”
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Sequential Hybrid Beamforming for Radio Stripes by Joumana JOUMANA, Daniel Castanheira, Adao Silva, Rui Dinis, Atilio Gameiro

“…By eliminating conventional cell boundaries, CF mMIMO deploys a large number of distributed access points (APs), enabling seamless connectivity across a wide area, more flexible resource allocation, and enhanced overall system performance. …”
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Informatics-driven unsupervised learning of comorbidity clusters for COVID-19 reinfection risk: A finite mixture modeling approach by Grant B. Morgan, Andreas Stamatis, Chelsea C. Yager, Ali Boolani

“…The findings may support targeted prevention, data-driven resource allocation, and precision medicine strategies by highlighting subgroups at elevated risk. …”
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MDE-Net: Multi-Layer Depth Extraction Network With Attention Mechanism for Medical Image Segmentation by Xiaokang Ding, Ling Dong, Yingyu Ji, Ke'Er Qian

“…MDE-Net’s contribution can significantly streamline diagnostic processes, minimize human error, and optimize resource allocation in clinical settings, making it a valuable tool in advancing healthcare.…”
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IRS-Assisted Wireless Sensor Networks With Hybrid TDMA-NOMA by Haitham Al-Obiedollah, Haythem Bany Salameh, Kanapathippillai Cumanan

“…To demonstrate the performance of such a system, we formulate a resource allocation framework that aims to minimize the total transmit power in the system while meeting a set of quality of service (QoS) requirements. …”
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A Privacy-Preserving Polymorphic Heterogeneous Security Architecture for Cloud–Edge Collaboration Industrial Control Systems by Yukun Niu, Xiaopeng Han, Chuan He, Yunfan Wang, Zhigang Cao, Ding Zhou

“…The architecture introduces three key innovations: (1) a hybrid event–time triggered scheduling algorithm with credibility assessment and heterogeneity metrics to mitigate common-mode escape scenarios, (2) an adaptive privacy budget allocation mechanism that balances privacy protection effectiveness with system availability based on attack activity levels, and (3) a unified framework that organically integrates privacy-preserving arbitration with heterogeneous redundancy management. …”
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Optimising test intervals for individuals with type 2 diabetes: A machine learning approach. by Sasja Maria Pedersen, Nicolai Damslund, Trine Kjær, Kim Rose Olsen

“…<h4>Objective</h4>To demonstrate the potential of ML to guide resource allocation and tailored disease management, this study aims to predict the optimal testing interval for monitoring blood glucose (HbA1c) for patients with Type 2 Diabetes (T2D). …”
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Protocol of a parallel group Randomized Control Trial (RCT) for Mobile-assisted Medication Adherence Support (Ma-MAS) intervention among Tuberculosis patients. by Zekariyas Sahile, Lua Perimal-Lewis, Paul Arbon, Anthony John Maeder

“…A total of 186 participants (93 per group) will be individually randomized into one of the two groups with a 1:1 allocation ratio by a computer-generated algorithm. …”
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Modelling geographical accessibility to urban centres in Kenya in 2019. by Peter M Macharia, Eda Mumo, Emelda A Okiro

“…Therefore, marginalised populations should be prioritised during resource allocation and policies should be formulated to enhance equitable access to public services and opportunities in urban areas.…”
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Modeling Energy Access Challenges in Europe: A Neural Network Approach to Predicting Household Heating Inadequacy Using Macro-Energy Indicators by Monika Kulisz, Justyna Kujawska, Michał Cioch, Wojciech Cel

“…The findings highlight the potential of machine learning to predict the percentage of the population unable to keep their houses adequately warm, enabling policymakers to allocate resources more efficiently and target vulnerable populations. …”
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Advances in Deep Learning Applications for Plant Disease and Pest Detection: A Review by Shaohua Wang, Dachuan Xu, Haojian Liang, Yongqing Bai, Xiao Li, Junyuan Zhou, Cheng Su, Wenyu Wei

“…To address these challenges, deep learning technologies have emerged as a promising solution for the accurate and timely identification of plant diseases and pests, thereby reducing crop losses and optimizing agricultural resource allocation. By leveraging its advantages in image processing, deep learning technology has significantly enhanced the accuracy of plant disease and pest detection and identification. …”
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Two-layer energy optimization of HVAC system in a cement factory building by Xiaoquan Lu, Kaijie Fang, Yuqi Zhou, Ju Sheng, Hanmiao Chen

“…Finally, a typical case of a double-story model of a cement factory office building using the GA algorithm was compared and verified, showing the effectiveness of the proposed model.…”
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Artificial intelligence in project management: A bibliometric analysis by Nurkhat Ibadildin, Zhaxat Kenzhin, Gaukhar Yeshenkulova, Rymkul Ismailova, Assel Nurguzhina, Samalgul Nassanbekova, Aiman Kadyrova

“…The analysis maps the evolution of AI-driven project management practices, focusing on resource allocation, risk management, and scheduling optimization. …”
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Dynamic SOFA component scores-based deep learning for short to long-term mortality prediction in sepsis survivors by Juan Wei, Feihong Lin, Tian Jin, Qian Yao, Sheng Wang, Di Feng, Xin Lv, Wen He

“…Early identification of those at high risk of mortality following discharge may optimize healthcare resource allocation. We sought to feed common clinical available data to a deep learning algorithm for predicting short to long-term mortality in sepsis survivors. …”
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Bayesian optimization of hybrid quantum LSTM in a mixed model for precipitation forecasting by Yumin Dong, Huanxin Ding

“…Accurate forecasting is of great significance for reducing the impact of floods, optimizing crop planting plans, rationally allocating water resources, and ensuring traffic safety. …”
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Customer Clustering and Marketing Optimization in Hospitality: A Hybrid Data Mining and Decision-Making Approach from an Emerging Economy by Maryam Deldadehasl, Houra Hajian Karahroodi, Pouya Haddadian Nekah

“…It also provides managers with appropriate tools to allocate resources efficiently. This study extends the traditional Recency, Frequency, and Monetary (RFM) model by incorporating duration, an overlooked dimension of customer engagement. …”
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Integrating IT and OT for Cybersecurity: A Stochastic Optimization Approach via Attack Graphs by Gonzalo Martinez Medina, Krystel K. Castillo-Villar, Tanveer Hossain Bhuiyan

“…The defense strategies identified by our approach demonstrate that robust security protection can be achieved with optimal resource allocation, providing robust protection while minimizing implementation costs across the most critical vulnerabilities in the manufacturing network.…”
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