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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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A New Encryption Mechanism Supporting the Update of Encrypted Data for Secure and Efficient Collaboration in the Cloud Environment

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 813-834页

作者： Chanhyeong Cho Byeori Kim Haehyun Cho Taek-Young Youn department of Cyber security Dankook UniversityYongin16890Republic of Korea department of Software Soongsil UniversitySeoul07027Republic of Korea

With the rise of remote collaboration,the demand for advanced storage and collaboration tools has rapidly ***,traditional collaboration tools primarily rely on access control,leaving data stored on cloud servers vulnerable due to insufficient *** paper introduces a novel mechanism that encrypts data in‘bundle’units,designed to meet the dual requirements of efficiency and security for frequently updated collaborative *** bundle includes updated information,allowing only the updated portions to be reencrypted when changes *** encryption method proposed in this paper addresses the inefficiencies of traditional encryption modes,such as Cipher Block Chaining(CBC)and Counter(CTR),which require decrypting and re-encrypting the entire dataset whenever updates *** proposed method leverages update-specific information embedded within data bundles and metadata that maps the relationship between these bundles and the plaintext *** utilizing this information,the method accurately identifies the modified portions and applies algorithms to selectively re-encrypt only those *** approach significantly enhances the efficiency of data updates while maintaining high performance,particularly in large-scale data *** validate this approach,we conducted experiments measuring execution time as both the size of the modified data and the total dataset size *** show that the proposed method significantly outperforms CBC and CTR modes in execution speed,with greater performance gains as data size ***,our security evaluation confirms that this method provides robust protection against both passive and active attacks.

关键词： Cloud collaboration mode of operation data update efficiency

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A Grid Cell Based Distribution Network Planning Method Adapting to the Increasing Permeability of Distributed Resources

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Dianwang Jishu/Power System Technology 2025年第1期49卷 306-315页

作者： Zhou, Yang Wang, Zhuding Zhang, Man Yang, Jie Shu, Dongsheng State Key Laboratory of Power Transmission Equipment & System security and New Technology Chongqing University Shapingba District Chongqing 400044 China Chongqing Electric Energy Star Inc Jiulongpo District Chongqing 400039 China economic Research Institute of State Grid Hubei Electric Power Company Hubei Province Wuhan 430000 China

Based upon the existing research findings of distribution network planning，and based on the optimization division of power areas (or grid cells), a heuristic method of distribution network planning, i.e., the grid cell based distribution network planning method, is proposed to adapt to the gradual increase in the penetration rate of distributed resources, wherein the power balancing method involves differential approaches of different space-time-resources and two typical operating modes. The optimization division of grid cells is carried out by the principles of nearby use for distributed power resources and "nearby backup supply", resulting in the regional grid cell, substation grid cell, medium-voltage and low-voltage grid cell in terms of space, and also the energy output type, energy input type and balance type in terms of resources. The real planning example shows that the proposed method has relatively strong operability. © 2025 Power System Technology Press. All rights reserved.

关键词： Power distribution planning

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Smart Gas Sensors:Recent Developments and Future Prospective

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Nano-Micro Letters 2025年第3期17卷 55-86页

作者： Boyang Zong Shufang Wu Yuehong Yang Qiuju Li Tian Tao Shun Mao College of Environmental Science and Engineering Biomedical Multidisciplinary Innovation Research InstituteShanghai East HospitalState Key Laboratory of Pollution Control and Resource ReuseTongji University1239 Siping RoadShanghai 200092People’s Republic of China Shanghai Institute of Pollution Control and Ecological security Shanghai 200092People’s Republic of China Microbiome Medicine Center Department of Laboratory MedicineZhujiang HospitalSouthern Medical UniversityGuangzhou 510280People’s Republic of China

Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,*** the development of sensor technology,wireless communication,smart monitoring terminal,cloud storage/computing technology,and artificial intelligence,smart gas sensors represent the future of gassensing due to their merits of real-time multifunctional monitoring,earlywarning function,and intelligent and automated *** electronicand optoelectronic gas sensors have been developed for high-performancesmart gas *** the development of smart terminals and the maturityof integrated technology,flexible and wearable gas sensors play an increasingrole in gas *** review highlights recent advances of smart gassensors in diverse *** structural components and fundamentalprinciples of electronic and optoelectronic gas sensors are described,andflexible and wearable gas sensor devices are ***,sensorarray with artificial intelligence algorithms and smart gas sensors in“Internet of Things”paradigm are ***,the challengesand perspectives of smart gas sensors are discussed regarding the future need of gas sensors for smart city and healthy living.

关键词： Smart gas sensor Electronic sensor Optoelectronic sensor Flexible and wearable sensor Artificial intelligence

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Enhancing Deepfake Detection:Proactive Forensics Techniques Using Digital Watermarking

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Computers, Materials & Continua 2025年第1期82卷 73-102页

作者： Zhimao Lai Saad Arif Cong Feng Guangjun Liao Chuntao Wang School of Automation Guangdong University and TechnologyGuangzhou510006China School of Immigration Administration(Guangzhou) China People’s Police UniversityGuangzhou510663China department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl Ahsa31982Saudi Arabia Cyber Police Division Guangzhou Public Security BureauGuangzhou510030China School of Forensic Science and Technology Guangdong Police CollegeGuangzhou510320China College of Mathematics and Informatics South China Agricultural UniversityGuangzhou510642China

With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly *** paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking *** detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic *** contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake *** offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal ***,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking *** systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.

关键词： Deepfake proactive forensics digital watermarking traceability detection techniques

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Maximizing biomass utilization: An integrated strategy for coproducing multiple chemicals

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Journal of Energy Chemistry 2025年第1期100卷 180-191页

作者： Byeongchan Ahn Sua Jo Jonggeol Na J.Jay Liu Young-Ju Kim Wangyun Won department of Chemical and Biological Engineering Korea University department of Chemical Engineering (Integrated process) Kyung Hee University department of Chemical Engineering and Materials Science Ewha Womans University department of Chemical Engineering Pukyong National University Resources Engineering Plant Research department Korea Institute of Geoscience and Mineral Resources

Lignocellulosic biomass is one of the viable solutions to alleviate the global warming. However, the limited utilization of biomass majorly focused on cellulose and hemicellulose restricts the economic and environmental feasibilities. To cope with this issue, we proposed an integrated process of co-producing 1,6-hexanediol（1,6-HDO） with tetrahydrofuran and adipic acid from biomass, referred to as Strategy A. To compare the impacts of lignin upgrading and feedstock, Strategy B, which co-produces tetrahydrofuran alone, and Strategy C, which is the traditional route to produce 1,6-HDO from fossil fuels, were used. Heat networks are also designed to reduce operating costs and indirect carbon emissions due to energy consumption, saving 87% and 83% of the heat and cooling requirements, respectively, in Strategy A. The market competitiveness of Strategy A was evaluated by determining the minimum selling price through techno-economic analysis, and sustainability was thoroughly investigated by quantifying the environmental impacts through both midpoint and endpoint life-cycle assessments（LCAs）.Strategy A was found to be the most favorable both economically（USRDSCHARDOLLAR3,402/ton） and environmentally（-26.9 kg CO2eq.）. This indicates that lignin valorization is not only economically but also environmentally preferred. Finally, changes in economic and environmental feasibilities depending on economic, process, and environmental parameters were investigated using sensitivity and uncertainty analyses. The results of these analyses provide valuable insight into bio-based chemical production.

关键词： Carbon capture and utilization

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Localized characteristics of lump and interaction solutions to two extended Jimbo–Miwa equations

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Chinese Physics B 2020年第12期29卷 174-180页

作者： Yu-Hang Yin Si-Jia Chen Xing Lü department of Mathematics Beijing Jiaotong UniversityBeijing 100044China Beijing Laboratory of National economic security Early-warning Engineering Beijing Jiaotong UniversityBeijing 100044China

We focus on the localized characteristics of lump and interaction solutions to two extended Jimbo–Miwa *** on the Hirota bilinear method and the test function method,we construct the exact solutions to the extended equations including lump solutions,lump–kink solutions,and two other types of interaction solutions,by solving the underdetermined nonlinear system of algebraic equations for associated ***,analysis and graphical simulation are presented to show the dynamical characteristics of our solutions and the interaction behaviors are revealed.

关键词： Hirota bilinear method test function method lump solution interaction solution symbolic computation

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A Text Sentiment Classification Modeling Method Based on Coordinated CNN-LSTM-Attention Model

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Chinese Journal of Electronics 2019年第1期28卷 120-126页

作者： ZHANG Yangsen ZHENG Jia JIANG Yuru HUANG Gaijuan CHEN Ruoyu Institute of Intelligent Information Processing Beijing Information Science and Technology University Beijing Laboratory of National economic security Early-Warning Engineering

The major challenge that text sentiment classification modeling faces is how to capture the intrinsic semantic, emotional dependence information and the key part of the emotional expression of text. To solve this problem, we proposed a Coordinated CNNLSTM-Attention(CCLA) model. We learned the vector representations of sentence with CCLA unit. Semantic and emotional information of sentences and their relations are adaptively encoded to vector representations of *** used softmax regression classifier to identify the sentiment tendencies in the text. Compared with other methods, the CCLA model can well capture the local and long distance semantic and emotional *** results demonstrated the effectiveness of CCLA model. It shows superior performances over several state-of-the-art baseline methods.

关键词： Coordinated CNN-LSTM-Attention Sentiment analysis Text modeling Semantic information

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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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Dynamic behaviors of the lump solutions and mixed solutions to a(2+1)-dimensional nonlinear model

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Communications in Theoretical Physics 2023年第5期75卷 52-61页

作者： Si-Jia Chen Xing Lü Yu-Hang Yin department of Mathematics Beijing Jiaotong UniversityBeijing 100044China Beijing Laboratory of National economic security Early-warning Engineering Beijing Jiaotong UniversityBeijing 100044China

In this paper,we propose a combined form of the bilinear Kadomtsev-Petviashvili equation and the bilinear extended(2+1)-dimensional shallow water wave equation,which is linked with a novel(2+1)-dimensional nonlinear *** model might be applied to describe the evolution of nonlinear waves in the *** the effect of a novel combination of nonlinearity and dispersion terms,two cases of lump solutions to the(2+1)-dimensional nonlinear model are derived by searching for the quadratic function solutions to the bilinear ***,the one-lump-multi-stripe solutions are constructed by the test function combining quadratic functions and multiple exponential *** one-lump-multi-soliton solutions are derived by the test function combining quadratic functions and multiple hyperbolic cosine *** behaviors of the lump solutions and mixed solutions are analyzed via numerical *** result is of importance to provide efficient expressions to model nonlinear waves and explain some interaction mechanism of nonlinear waves in physics.

关键词： bilinear form test function mixed solutions dynamic behaviors

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