Resource allocation mechanism in the TWDM-PON and C-RAN joint architecture with hybrid energy supply by Ruyan WANG, Ningning XU

“…Aiming at the problems of low resource utilization rate,high energy consumption and poor user service quality in the existing virtualized Cloud Radio Access Network,an energy-aware virtualized resource allocation mechanism with hybrid energy supply was proposed.According to the energy sources and energy consumption of different network devices,energy arrival and energy consumption models were established.Furthermore,under the premise of guaranteeing the quality of user services,considering proportional fairness and energy consumption optimization,distributed algorithms based on asynchronous update were used to allocate resources and harvested energy for different types of virtual cloud radio access networks and user virtual base stations to effectively improve the energy efficiency of network.The simulation results show that the proposed resource allocation mechanism can reduce energy consumption while effectively reducing the latency and improving the throughput.…”
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Revolutionizing Diabetes Management Through Nanotechnology-Driven Smart Systems by Aayush Kaushal, Aanchal Musafir, Gourav Sharma, Shital Rani, Rajat Kumar Singh, Akhilesh Kumar, Sanjay Kumar Bhadada, Ravi Pratap Barnwal, Gurpal Singh

“…Diabetes is a global health challenge, and while current treatments offer relief, they often fall short in achieving optimal control and long-term outcomes. …”
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Decentralized Energy Swapping for Sustainable Wireless Sensor Networks Using Blockchain Technology by Umar Draz, Tariq Ali, Sana Yasin, Mohammad Hijji, Muhammad Ayaz, EL-Hadi M. Aggoune

“…The system is built using NS-3 to simulate node behavior, energy usage, and network dynamics, while Python manages the blockchain architecture, cryptographic security, and trading algorithms. …”
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A Comprehensive Survey on AI in Counter-Terrorism and Cybersecurity: Challenges and Ethical Dimensions by Ioannis Syllaidopoulos, Klimis S. Ntalianis, Ioannis Salmon

“…This paper provides a comprehensive overview of AI methodologies, such as predictive analytics, Natural Language Processing (NLP), and machine learning architectures (e.g., Support Vector Machines – SVM and Long Short-Term Memory – LSTM), and optimization algorithms (e.g., Particle Swarm Optimization – PSO), assessing their effectiveness in security applications. …”
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A stacked ensemble machine learning model for the prediction of pentavalent 3 vaccination dropout in East Africa by Meron Asmamaw Alemayehu, Shimels Derso Kebede, Agmasie Damtew Walle, Daniel Niguse Mamo, Ermias Bekele Enyew, Jibril Bashir Adem

“…Hyperparameter optimization (HPO) and comparisons were conducted using grid search and random search. …”
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Review of the Research on Underwater Explosion Ice-Breaking Technology by Xiao Huang, Zi-Xian Zhong, Xiao Luo, Yuan-Dong Wang

“…Key findings establish that shock waves initiate brittle fracture via stress superposition while bubble pulsation drives crack propagation through pressure oscillation; optimal ice fragmentation depends critically on charge weight, standoff distance, and ice thickness. …”
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Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices? by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith

“…Accurate and reliable crop yield prediction is essential for optimizing agricultural management, resource allocation, and decision-making, while also supporting farmers and stakeholders in adapting to climate change and increasing global demand. …”
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AI powered blockchain framework for predictive temperature control in smart homes using wireless sensor networks and time shifted analysis by Cong Feng, Ahmed Kateb Jumaah Al-Nussairi, Mustafa Habeeb Chyad, Narinderjit Singh Sawaran Singh, Jianyong Yu, Amirfarhad Farhadi

“…Abstract In the context of smart homes, efficiently managing temperature control while optimizing energy consumption and ensuring data security remains a significant challenge. …”
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Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis by Ali Nabavi, Mohammad Kashkooli, Sara Sadat Nabavizadeh, Farimah Safari

“…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”
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Machine Learning Modeling of Foam Concrete Performance: Predicting Mechanical Strength and Thermal Conductivity from Material Compositions by Leifa Li, Wangwen Sun, Askar Ayti, Wangping Chen, Zhuangzhuang Liu, Lauren Y. Gómez-Zamorano

“…The predictive model used in this study provides reliable technical support for the optimization and engineering application of foam concrete, enhancing both prediction accuracy and practical efficiency.…”
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Blending Ensemble Learning Model for 12-Lead Electrocardiogram-Based Arrhythmia Classification by Hai-Long Nguyen, Van Su Pham, Hai-Chau Le

“…Experiments conducted with seven diverse machine learning algorithms (Adaptive Boosting, Extreme Gradient Boosting, Decision Trees, k-Nearest Neighbors, Logistic Regression, Random Forest, and Support Vector Machine) demonstrate that the proposed blending solution, utilizing an LR meta-model with three optimal base models, achieves a superior classification accuracy of 96.48%, offering an effective tool for clinical decision support.…”
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Two Power Allocation and Beamforming Strategies for Active IRS-aided Wireless Network via Machine Learning by Q. Cheng, J. Bai, X. Wang, B. Shi, W. Gao, F. Shu

“…Simulation results show that the proposed algorithms can effectively improve the rate performance compared to fixed PA strategies, only optimizing PA factor, aided by passive IRS, and without IRS.…”
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Subtidal seagrass and blue carbon mapping at the regional scale: a cloud-native multi-temporal Earth Observation approach by Mar Roca, Chengfa Benjamin Lee, Avi Putri Pertiwi, Alina Blume, Isabel Caballero, Gabriel Navarro, Dimosthenis Traganos

“…We developed a satellite-based workflow to complement in situ seagrass monitoring efforts in the Balearic Islands (Western Mediterranean), reducing field expenses while covering regional spatial scales. Our synoptic tool uses Sentinel-2 A/B satellite imagery at 10 m spatial resolution to generate a multi-temporal composite (2016–2022) of the Balearic Islands’ coastal waters within the Google Earth Engine cloud computing platform, optimizing image processing and highlighting the importance of a high-resolution bathymetric dataset to increase seagrass mapping accuracies. …”
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Biobjective Scheduling for Joint Parallel Machines with Sequence-Dependent Setup by Taking Pareto-Based Approach by Wichai Srisuruk, Kanchala Sudtachat, Paramate Horkaew

“…Modern factories have been moving toward just-in-time manufacturing paradigm. Optimal resource scheduling is therefore essential to minimize manufacturing cost and product delivery delay. …”
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A Review of Enhancement Techniques for Cone Beam Computed Tomography Images by Hassn Mazin Al-alaaf, Mohammed Sabah Jarjees

“…These methods encompass various mathematical algorithms, machine learning approaches, and hybrid models, which aim to mitigate the imperfections present in CBCT data while preserving diagnostically relevant information. …”
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Deep Clustering of Student Code Strategies Using Multi-View Code Representation (CMVAE) by Zhengting Tang, Shizhou Wang, Liangyu Chen

“…The model captures structural features by transforming code into tree graphs and extracting centrality measures, while CodeBERT provides semantic embeddings. Through a joint optimization of reconstruction loss and clustering loss, the model effectively integrates multiple code representations. …”
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Integrated Waste Management in the Circular Economy Era: Insights from Research and Practice by Charisios Achillas, Christos Vlachokostas

“…Technological advancements, such as AI-driven waste sorting and route optimization algorithms, are highlighted alongside policy frameworks supporting circular economy principles. …”
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Revolutionizing Supply Chain Management With AI: A Path to Efficiency and Sustainability by Kassem Danach, Ali El Dirani, Hassan Rkein

“…Through an in-depth analysis of various AI techniques—such as machine learning, predictive analytics, and optimization algorithms—this study offers novel insights into their applicability in solving complex supply chain problems like demand forecasting, inventory management, and logistics optimization. …”
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Privacy-preserving method for face recognition based on homomorphic encryption. by Zhigang Song, Gong Wang, Wenqin Yang, Yunliang Li, Yinsheng Yu, Zeli Wang, Xianghan Zheng, Yang Yang

“…To overcome this limitation, this paper introduces an optimization scheme based on clustering algorithms to accelerate the facial recognition process within the HE_FaceNet framework. …”
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A Solution for Predicting the Timespan Needed for Grinding Roller Bearing Rings by Cezarina Chivu, Mitica Afteni, Gabriel Radu Frumusanu, Florin Susac

“…The optimal management of manufacturing processes can be achieved through a set of optimal decisions, which must be made to choose the best method to follow every time the process planner reaches a point when several potential manufacturing paths branch off. …”
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