Enhancing Smart Grids for Sustainable Energy Transition and Emission Reduction with Advanced Forecasting Techniques by Farah Rania, Farou Brahim, Kouahla Zineddine and Seridi Hamid

“…Smart grids are modernized, intelligent electricity distribution systems that integrate information and communication technologies to improve the efficiency, reliability, and sustainability of the electricity network. …”
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Neuromorphic system using capacitor synapses by Reon Oshio, Takumi Kuwahara, Takeru Aoki, Mutsumi Kimura, Yasuhiko Nakashima

“…Abstract Artificial intelligences are indispensable social infrastructures, neural networks are embodiment methodologies, and neuromorphic systems are promising solutions for compact size and low energy. …”
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A Multi-Objective Path-Planning Approach for Multi-Scenario Urban Mobility Needs by Zhaohui Wang, Meng Zhang, Shanqing Liang, Shuang Yu, Chengchun Zhang, Sheng Du

“…With the development of smart cities and intelligent transportation systems, path planning in multi-scenario urban mobility has become increasingly complex. …”
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High-performance federated continual learning algorithm for heterogeneous streaming data by Hui JIANG, Tianliu HE, Min LIU, Sheng SUN, Yuwei WANG

“…Aiming at the problems of poor model performance and low training efficiency in training streaming data of AI models that provide intelligent services, a high-performance federated continual learning algorithm for heterogeneous streaming data (FCL-HSD) was proposed in the distributed terminal system with privacy data.In order to solve the problem of the current model forgetting old data, a model with dynamically extensible structure was introduced in the local training stage, and an extension audit mechanism was designed to ensure the capability of the AI model to recognize old data at the cost of small storage overhead.Considering the heterogeneity of terminal data, a customized global model strategy based on data distribution similarity was designed at the central server side, and an aggregation-by-block manner was implemented for different modules of the model.The feasibility and effectiveness of the proposed algorithm were verified under various data increment scenarios with different data sets.Experimental results show that, compared with existing works, the proposed algorithm can effectively improve the model performance to classify old data on the premise of ensuring the capability to classify new data.…”
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Research on Multistage Rotor Assembly Optimization Methods for Aeroengine Based on the Genetic Algorithm by Yue Chen, Jiwen Cui, Xun Sun, Shihai Cui

“…It often needs to be tested and disassembled repeatedly to meet the double-objective requirements at the same time. Therefore, an intelligent assembly method is urgently needed to directly predict the optimal assembly orientations of the rotors at each stage to meet the double-objective requirements simultaneously. …”
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Multi-Objective Portfolio Optimization Strategy Using the SPEA-II Algorithm by Alireza Azarberahman, Malihe Tohidinia, Hossein Aliakbarzadeh

“…This study explores the application of intelligent algorithms, particularly the multi-objective of Strength Pareto Evolutionary Algorithm II (SPEA-II), alongside traditional methods to determine optimal portfolios. …”
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Exploring the factors driving the sustainable consumer intentions for over-the-air updates in electric vehicles by Shanshan Wang, Asif Khan

“…With the development of intelligent and connected vehicles, over-the-air (OTA) updates empower cars with continuous evolution capabilities, leading to an accelerated penetration rate and steady market share growth. …”
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Jean-Clet Martin, Logique de la science-fiction : de Hegel à Philip K. Dick (2017) by Jean-Loup Héraud

“…Through this confrontation, the aim of the author is to confer new forms of intelligibility to this literary genre, and in an other way to reactualise the hegelian ontological project to write a logic of the world. …”
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Practice of comorbidity management based on community chronic disease health management support centers: an introduction and discussion by Mengyun SUI, Sheng ZHANG, Yuheng WANG, Qinghua YAN, Fei WU, Chen FU, Minna CHENG, Yan SHI

“…Shanghai city has developed a comprehensive and closed-loop chronic disease health management system, which includes pre-diagnosis risk assessment and identification with tagged classification, intra-diagnosis standardized monitoring, data sharing integration, multidisciplinary collaboration, decision support, and post-diagnosis complication screening, intelligent follow-up, patient self-management, standardized health education, and re-evaluation. …”
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A Framework for Integrating Vision Transformers with Digital Twins in Industry 5.0 Context by Attila Kovari

“…In this work, the emergent role of ViTs and digital twins in the development of intelligent, dynamic, and human-centric industrial ecosystems is discussed.…”
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Selection of Construction Methods: A Knowledge-Based Approach by Ximena Ferrada, Alfredo Serpell, Miroslaw Skibniewski

“…This paper proposes a knowledge management approach that will enable the intelligent use of corporate experience and information and help to improve the selection of construction methods for a project. …”
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A big data framework for short-term power load forecasting using heterogenous data by Haibo ZHAO, Zhijun XIANG, Linsong XIAO

“…The power system is in a transition towards a more intelligent, flexible and interactive system with higher penetration of renewable energy generation, load forecasting, especially short-term load forecasting for individual electric customers plays an increasingly essential role in future grid planning and operation.A big data framework for short-term power load forcasting using heterogenous was proposed, which collected the data from smart meters and weather forecast, pre-processed and loaded it into a NoSQL database that was capable to store and further processing large volumes of heterogeneous data.Then, a long short-term memory (LSTM) recurrent neural network was designed and implemented to determine the load profiles and forecast the electricity consumption for the residential community for the next 24 hours.The proposed framework was tested with a publicly available smart meter dataset of a residential community, of which LSTM’s performance was compared with two benchmark algorithms in terms of root mean square error and mean absolute percentage error, and its validity has been verified.…”
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A new miniaturized multi-band transparent antenna for V2X communication by Ourahou Omar, Belahrach Hassan, Ghammaz Abdelilah

“…Intelligent transportation services are being developed to enhance road safety, increase traffic efficiency, achieve higher speeds, and alleviate traffic congestion. …”
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Le défi des outils numériques dans la scolarisation des élèves avec autisme : entre les besoins cognitifs des élèves et les approches pédagogiques des enseignants by Camelia-Mihaela Dascalu, Philippe Garnier

“…The grounded theory approach makes the process of inserting the information technology tools into a special teaching for students with autism, more intelligible.…”
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Research on Design and Application of National Fitness System by Shengyou Wang

“…On this basis, through the collection of users’ fitness data rating data, the data are transformed into fitness data rating matrix, and the matrix is analyzed and calculated to realize the intelligent recommendation of fitness data and complete the design of national fitness data recommendation algorithm. …”
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GAD:topology-aware time series anomaly detection by Qi QI, Runye SHEN, Jingyu WANG

“…To solve the problems of anomaly detection,intelligent operation,root cause analysis of node equipment in the network,a graph-based gated convolutional codec anomaly detection model was proposed for time series data such as link delay,network throughput,and device memory usage.Considering the real-time requirements of network scenarios and the impact of network topology connections on time series data,the time dimension features of time series were extracted in parallel based on gated convolution and the spatial dependencies were mined through graph convolution.After the encoder composed of the spatio-temporal feature extraction module encoded the original input time series data,the decoder composed of the convolution module was used to reconstruct the time series data.The residuals between the original data and the reconstructed data were further used to calculate the anomaly score and detect anomalies.Experiments on public data and simulation platforms show that the proposed model has higher recognition accuracy than the current time series anomaly detection benchmark algorithm.…”
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Pulsions et significations de la douceur. A partir de « Puissance de la douceur », d’Anne Dufourmantelle by Nicolas Couégnas

“…Se dessine ainsi l’un des chemins possibles entre sémiotique et pragmatique à partir de la tensivité et de sa capacité à nouer ensemble le sensible et l’intelligible.…”
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Art Online Design Based on Digital Simulation Technology by Song Gao

“…Finally, this paper uses the intelligent system constructed in this paper to conduct multiple sets of simulation experiments to evaluate the digital effect and artistic design effect of the system constructed in this paper. …”
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Reconceptualizing the Role of the University Language Teacher in Light of Generative AI by Mark Tutton, Doron Cohen

“…We call for a reconceptualization of this role based on two factors: the unique social interactivity of the university language classroom and the need for effective instruction on how to use Intelligent Computer-Assisted Language Learning (ICALL) tools outside of the classroom. …”
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Maple leaf-based triboelectric nanogenerator for efficient energy harvesting and precision monitoring in ping-pong training by He Yu, Zheng Li

“…Triboelectric technology, with its renewable, low-cost, and eco-friendly advantages, offers new possibilities for intelligent motion-sensing equipment and sports monitoring. …”
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