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Federated Learning’s Role in Next-Gen TV Ad Optimization

Computers, Materials & Continua 2025年第1期82卷 675-712页

作者： Gabriela Dobrita Simona-Vasilica Oprea Adela Bâra department of economic Informatics and Cybernetics Bucharest University of Economic StudiesBucharest010374Romania

In the rapidly evolving landscape of television advertising,optimizing ad schedules to maximize viewer engagement and revenue has become *** methods often operate in silos,limiting the potential insights gained from broader data analysis due to concerns over privacy and data *** article introduces a novel approach that leverages Federated Learning(FL)to enhance TV ad schedule optimization,combining the strengths of local optimization techniques with the power of global Machine Learning(ML)models to uncover actionable insights without compromising data *** combines linear programming for initial ads scheduling optimization with ML—specifically,a K-Nearest Neighbors(KNN)model—for predicting ad spot *** into account the diversity and the difficulty of the ad-scheduling problem,we propose a prescriptivepredictive approach in which first the position of the ads is optimized(using Google’s OR-Tools CP-SAT)and then the scheduled position of all ads will be the result of the optimization ***,this output becomes the target of a predictive task that predicts the position of new entries based on their characteristics ensuring the implementation of the scheduling at large scale(using KNN,Light Gradient Boosting Machine and Random Forest).Furthermore,we explore the integration of FL to enhance predictive accuracy and strategic insight across different broadcasting networks while preserving data *** FL approach resulted in 8750 ads being precisely matched to their optimal category placements,showcasing an alignment with the intended diversity ***,there was a minimal deviation observed,with 1133 ads positioned within a one-category variance from their ideal placement in the original dataset.

关键词： Ad scheduling prescriptive-predictive approach federated learning KNN

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Decision making module based on stochastic magnetic tunnel junctions

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 202-209页

作者： Yifan Miao Li Zhao Yajun Zhang Zhe Yuan Center for Advanced Quantum studies and department of Physics Beijing Normal University Institute for Nanoelectric Devices and Quantum Computing Fudan University Interdisciplinary Center for Theoretical Physics and Information Sciences Fudan University

In biological neural systems, noise is ubiquitous but does not affect the correct decisions made in the complex cognitive ***-making in biological neural system is typically achieved by accumulating input information over a period of *** by recent developments in neurosciences, we design a decision-making module based on spintronic devices, utilizing superparamagnetic tunnel junctions as artificial neurons. The feasibility of this decision-making module is verified through circuit simulations. Taking a multi-layer perceptron as an example, the module significantly improves the accuracy of the perceptron in the handwritten digit recognition task. Furthermore, the spintronic decision-making module offers advantages over the conventional pooling methods, such as adaptive decision time, high performance and the absence of analog-to-digital conversion. The decision-making module is flexible to be integrated into artificial neural networks and provides a general yet effective solution to enhance performance against device noise.

关键词： neuromorphic computing spintronics magnetic tunnel junction neural networks

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Detecting Malicious Uniform Resource Locators Using an Applied Intelligence Framework

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Computers, Materials & Continua 2024年第6期79卷 3827-3853页

作者： Simona-Vasilica Oprea Adela Bara department of economic Informatics and Cybernetics Bucharest University of Economic StudiesBucharest010572Romania

The potential of text analytics is revealed by Machine Learning(ML)and Natural Language Processing(NLP)*** this paper,we propose an NLP framework that is applied to multiple datasets to detect malicious Uniform Resource Locators(URLs).Three categories of features,both ML and Deep Learning(DL)algorithms and a ranking schema are included in the proposed *** apply frequency and prediction-based embeddings,such as hash vectorizer,Term Frequency-Inverse Dense Frequency(TF-IDF)and predictors,word to vector-word2vec(continuous bag of words,skip-gram)from Google,to extract features from ***,we apply more state-of-the-art methods to create vectorized features,such as ***,feature engineering that is specific to URL structure is deployed to detect scams and other *** framework assessment,four ranking indicators are weighted:computational time and performance as accuracy,F1 score and type error *** the computational time,we propose a new metric-Feature Building Time(FBT)as the cutting-edge feature builders(like doc2vec or GloVe)require more *** applying the proposed assessment step,the skip-gram algorithm of word2vec surpasses other feature builders in ***,eXtreme Gradient Boost(XGB)outperforms other *** this setup,we attain an accuracy of 99.5%and an F1 score of 0.99.

关键词： Detecting malicious URL classifiers text to feature deep learning ranking algorithms feature building time

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An Enhanced Lung Cancer Detection Approach Using Dual-Model Deep Learning Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 835-867页

作者： Sumaia Mohamed Elhassan Saad Mohamed Darwish Saleh Mesbah Elkaffas department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandria21526Egypt College of Computing and Information Technology Arab Academy for ScienceTechnology and Maritime TransportAlexandriaP.O.Box 1029Egypt

Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic *** detection of lung tumors significantly increases the chances of successful treatment and ***,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung ***-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate ***,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor *** overcome these disadvantages,dual-model or multi-model approaches can be *** research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of *** automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung ***8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single *** is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to ***,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive *** combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applicati

关键词： Lung cancer detection dual-model deep learning technique data augmentation CNN YOLOv8

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Impact of Pollutant Concentration and Particle Deposition on the Radiative Flow of Casson-Micropolar Fluid between Parallel Plates

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 665-690页

作者： Ghaliah Alhamzi Badr Saad T.Alkahtani Ravi Shanker Dubey Vinutha Kalleshachar Neelima Nizampatnam department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11564Saudi Arabia department of Mathematics College of ScienceKing Saud UniversityRiyadh11989Saudi Arabia department of Mathematics Amity School of Applied SciencesAmity University RajasthanJaipur302002RajasthanIndia department of studies in Mathematics Davangere UniversityDavangere577002India department of Electronics and Communication Engineering Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluru560035India

Assessing the behaviour and concentration of waste pollutants deposited between two parallel plates is essential for effective environmental *** the effectiveness of treatment methods in reducing pollution scales is made easier by analysing waste discharge *** waste discharge concentration analysis is useful for assessing how effectively wastewater treatment techniques reduce pollution *** study aims to explore the Casson micropolar fluid flow through two parallel plates with the influence of pollutant concentration and thermophoretic particle *** explore the mass and heat transport features,thermophoretic particle deposition and thermal radiation are *** governing equations are transformed into ordinary differential equations with the help of suitable similarity *** Runge-Kutta-Fehlberg’s fourthfifth order technique and shooting procedure are used to solve the reduced set of equations and boundary *** integration of a neural network model based on the Levenberg-Marquardt algorithm serves to improve the accuracy of predictions and optimize the analysis of *** outcomes are displayed to analyze the characteristics of the relevant dimensionless parameters in the current *** reveal that concentration upsurges as the micropolar parameter *** concentration reduces with an upsurge in the thermophoretic *** upsurge in the external pollutant source variation and the local pollutant external source parameters enhances mass *** surface drag force declines for improved values of porosity and micropolar parameters.

关键词： Micropolar fluid thermal radiation porous medium thermophoretic particle deposition waste discharge concentration

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The emerging role of nitric oxide in the synaptic dysfunction of vascular dementia

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Neural Regeneration Research 2025年第2期20卷 402-415页

作者： Xiaorong Zhang Zhiying Chen Yinyi Xiong Qin Zhou Ling-Qiang Zhu Dan Liu department of Pathology Affiliated Hospital of Jiujiang UniversityJiujiangJiangxi ProvinceChina Jiujiang Clinical Precision Medicine Research Center JiujiangJiangxi ProvinceChina Center for Cognitive Science and Transdisciplinary studies Jiujiang UniversityJiangxi ProvinceChina department of Neurology Affiliated Hospital of Jiujiang UniversityJiujiangJiangxi ProvinceChina department of Rehabilitation Affiliated Hospital of Jiujiang UniversityJiujiangJiangxi ProvinceChina department of Pathophysiology School of Basic MedicineTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei ProvinceChina

With an increase in global aging,the number of people affected by cerebrovascular diseases is also increasing,and the incidence of vascular dementia-closely related to cerebrovascular risk-is increasing at an epidemic ***,few therapeutic options exist that can markedly improve the cognitive impairment and prognosis of vascular dementia *** in Alzheimer’s disease and other neurological disorders,synaptic dysfunction is recognized as the main reason for cognitive *** oxide is one of the ubiquitous gaseous cellular messengers involved in multiple physiological and pathological processes of the central nervous ***,nitric oxide has been implicated in regulating synaptic plasticity and plays an important role in the pathogenesis of vascular *** review introduces in detail the emerging role of nitric oxide in physiological and pathological states of vascular dementia and summarizes the diverse effects of nitric oxide on different aspects of synaptic dysfunction,neuroinflammation,oxidative stress,and blood-brain barrier dysfunction that underlie the progress of vascular ***,we propose that targeting the nitric oxide-sGC-cGMP pathway using certain specific approaches may provide a novel therapeutic strategy for vascular dementia.

关键词： endoplasmic reticulum stress endothelial nitric oxide synthase gene therapy nitric oxide NO-sGC-cGMP pathway synaptic dysfunction vascular dementia

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A NECESSARY AND A SUFFICIENT CONDITION FOR THE EXISTENCE OF THE POSITIVE RADIAL SOLUTIONS TO HESSIAN EQUATIONS AND SYSTEMS WITH WEIGHTS

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Acta Mathematica Scientia 2017年第1期37卷 47-57页

作者： Dragos-Patru COVEI department of Applied Mathematics The Bucharest University of Economic StudiesBucharest 010374Romania

In this article, we consider the existence of positive radial solutions for Hessian equations and systems with weights and we give a necessary condition as well as a sufficient condition for a positive radial solution to be large. The method of proving theorems is essentially based on a successive approximation technique. Our results complete and improve a work published recently by Zhang and Zhou（existence of entire positive k-convex radial solutions to Hessian equations and systems with weights. Applied Mathematics Letters,Volume 50, December 2015, Pages 48–55）.

关键词： existence Keller-Osserman condition k-Hessian equation and system

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Deepening Collaboration China and Africa need to further align development strategies to realise the immense potential of economic cooperation

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ChinAfrica 2025年第1期17卷 24-26页

作者： EHIZUELEN MICHAEL MITCHELL OMORUYI Centre for Nigerian studies Institute of African StudiesZhejiang Normal University

Humming factories,bustling ports,and shuttling merchants highlight the vibrancy of China-Africa economic and trade *** the years,this partnership has grown significantly,optimising trade structures and fostering mutual *** deepening collaboration is evident in China’s role as Africa’s largest bilateral trading partner for 15 consecutive *** the first seven months of 2024,trade between China and African countries reached$167 billion,reflecting a 5.5-percent increase compared to the same period in *** to the International Monetary Fund,approximately 20 percent of Africa’s exports now go to China,while 16 percent of its imports originate there.

关键词： trading deepening Africa

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A three-stage approach for resilience-constrained scheduling of networked microgrids

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Journal of Modern Power Systems and Clean Energy 2019年第4期7卷 705-715页

作者： Saeed TEIMOURZADEH Osman Bulent TOR Mahmut Erkut CEBECI Adela BARA Simona Vasilica OPREA Engineering ProcurementResearch and Analysis(EPRA)Electric Energy Co.AnkaraTurkey department of economic Informatics and Cybernetics Faculty of CyberneticsStatistics and Economic InformaticsBucharest University of Economic Studies(BUES)BucharestRomania

This paper deals with optimal scheduling of networked microgrids(NMGs)considering resilience *** proposed scheme attempts to mitigate the damaging impacts of electricity interruptions by effectively exploiting NMG capabilities.A three-stage framework is *** Stage 1,the optimal scheduling of NMGs is studied through determining the power transaction between the NMGs and upstream network,the output power of distributed energy resources(DERs),commitment status of conventional DERs as well as demand-side *** Stage 2,the decisions made at Stage 1 are realized considering uncertainties pertaining to renewable generation,market price,power consumption of loads,and unintentional islanding of NMGs from the upstream network and *** 3 deals with uncertainties of unintentional islanding of each MG from the rest of islanded NMGs and *** problem is formulated as a mixed-integer linear programming problem and its effectiveness is assured by simulation studies.

关键词： Networked microgrid(NMG) Distributed energy resource(DER) Power system resilience Point estimate method

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Stakeholder and Public Involvement in Risk Governance

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International Journal of Disaster Risk Science 2015年第1期6卷 8-20页

作者： Ortwin Renn economic and Social Sciences department and Stuttgart Research Center for Interdisciplinary Risk and Innovation studies University of Stuttgart

Stakeholder involvement has been a major requirement for effective, efficient, and fair risk *** risk management includes uncertain outcomes that affect different parts of the population to different degrees it is essential to integrate the knowledge, values, and interests of stakeholders into the risk policy making *** article provides insights into how to structure and organize stakeholder participation and how to cope with the challenges of complexity, uncertainty, and ambiguity. For each of the three challenges there is a need for specific input from stakeholders. The article describes these requirements and explains the formats that have been tested for providing this input to the risk governance process.

关键词： Participatory formats Public participation Risk governance Stakeholder involvement

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