A Antropologia Estrutural de Lévi-Strauss e suas reverberações geográficas by Cláudio Luiz Zanotelli

“…It is observed that the structural method developed by Claude Lévi- Strauss allows us to associate the outer space to inner space of man, dealing with the sensitive immanent form and intelligible. Thus the structuralist method appears to be of great fertility to the geographic method and understanding of the environment in interaction with society in a dialectical process.…”
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ICT infrastructure based on intent-based network and service orchestration by Jie ZHANG, Jianhong XU, Yongjian ZHAO, Yunxiang GAO, Xun CHEN

“…Considering the complexity of communication networks and the requirement of communication business innovation, operators should upgrade their ICT infrastructure.Based on the study of intent-based network and service orchestration technology, a new ICT architecture that combines the automatic transformation of business intention and the automatic correlation of network service models were proposed.As an automatic and intelligent upgrade of the operator BOSS IT system, it aims to accelerate the process of comprehensive digital transformation of operators.…”
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Research status and development trend of NB-IoT enhancement technology by Furong XU, Weiwen WENG, Chao ZHANG, Tingting BIAN, Xinli MA, Xiangdong GAO, Xin LI, Lei CAO

“…NB-IoT,which is the key technology of the Internet of things,has received widespread attention from global operators.Firstly,the commercial technologies of NB-IoT was outlined,then the research status of NB-IoT enhancement technology was introduced in detail from the aspects of mobile IoT enhancement technology,positioning enhancement technology,mobility enhancement technology and intelligent network optimization technology,and finally,future evolution of NB-IoT technology was introduced.…”
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Impacts of meteorology and emission reductions on haze pollution during the lockdown in the North China Plain by L. Liu, L. Liu, X. Long, Y. Li, Y. Li, Z. Zang, Z. Zang, F. Wang, Y. Han, Z. Bao, Y. Chen, T. Feng, J. Yang

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Study on a cable jumper method for offshore floating photovoltaic systems with multiple floating bodies by Xiangyu KONG, Yangping SHAO, Qiang FU, Lujie YU, Hongbin LIU

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Joint Resource Allocation for V2X Sensing and Communication Based on MADDPG by Zhiyong Zhong, Zhangyou Peng

“…Vehicle-to-Everything (V2X) communication is expected to play a critical role in enabling Intelligent Transportation Systems (ITS) within sixth-generation (6G) networks. …”
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Variational Autoencoder-Based Framework for Retail Sales Prediction by Fuyu Li, Lei Wang, Bo Jin

“…Accurate retail sales prediction is crucial for supporting the intelligent operations and management of a retail sales organization. …”
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Considering the Characteristics of Traffic Risk Factors and the Method of Establishing a Flexible Traffic System by Lingling Chen, Yuanyuan Zhang

“…It can relieve traffic congestion and provide a smooth and orderly traffic environment using intelligent transportation systems to control and direct traffic flow. …”
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SMART AGENT-BASED FRAMEWORK FOR MULTIPLE SIMULTANEOUS BILATERAL NEGOTIATIONS TO SUPPORT BUSINESS PROCESSES by Adina-Georgeta CREȚAN

“…This paper introduces an innovative agent-based intelligent framework aimed at modelling and facilitating simultaneous and parallel negotiations among organisations operating within the same industrial sector. …”
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Research of problems and prospects of development of public control in the information and communication space by D. A. Okolyshev

“…It is substantiated that in the long term, intelligent systems will become a fundamental part of the communication flows analysis system. …”
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Delay-sensitive traffic intellisense scheduling based on optimal decision tree by Xuerong WANG, Zhengzhi TANG, Yinchuan LI, Meiyu QI, Jianbo ZHU, Liang ZHANG

“…Currently, network traffic scheduling strategy cannot be intelligent and on-demand, especially in the congestion caused by sudden network failures and escort scenarios of high-value services.They cannot guarantee latency-sensitive service experience on demand.The delay-sensitive attribute requirements of different network traffic were analyzed and studied, and the internal correlation between the behavior characteristics of varying network traffic and its delay sensitivity requirements was explored.Then, AI technology was used to learn this inherent relationship and construct its mapping relationship, realizing a traffic scheduling technical solution based on the intelligent awareness of delay-sensitive traffic.At the same time, considering the practical issues of interpretability and deploy-ability of AI models, reinforcement learning (RL) technology was used to prune and optimize the interpretable decision tree model, which improved the robustness of the model and made model lighter and easier to implement in equipment deployment.Through experiments by the collected real network traffic, the decision tree model optimized by reinforcement learning could improve the awareness accuracy by 1.75% in a single inference case, and the inference performance was improved by about 30%.The experiment also proved that using micro-statistical features for multiple inferences could help improve the model accuracy; in all experiments, the scale of the decision tree model optimized by RL was reduced by about 60.0%～87.2%, and the Saras had better optimization performance than Q-learning.…”
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Data Imputation for Detected Traffic Volume of Freeway Using Regression of Multilayer Perceptron by Xiang Wang, Yingying Ma, Shengwen Huang, Yu Xu

“…Traffic volume data are the important part of research and application of intelligent transportation systems (ITS). However, data loss often happens due to various factors in the real world, which may cause large deviations in prediction or bad accuracy of optimizations. …”
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A Wireless Emergency Telemedicine System for Patients Monitoring and Diagnosis by M. Abo-Zahhad, Sabah M. Ahmed, O. Elnahas

“…Recently, remote healthcare systems have received increasing attention in the last decade, explaining why intelligent systems with physiology signal monitoring for e-health care are an emerging area of development. …”
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Trust evaluation model of social internet of things based on implicit social relationship by Hongbin ZHANG, Fan FAN, Dongmei ZHAO, Bin LIU, Yan YIN, Jian LIU

“…The social internet of things （SIoT） is a new paradigm that combines social networks and the internet of things to enhance network scalability and navigability.However, with increased openness and mobility of intelligent objects, there are rising security risks related to information security and reliable service delivery, which poses a significant challenge to the SIoT.Trust is a critical factor in providing secure and reliable services.Therefore, a new trust assessment model was proposed from the perspective of social relationships.A trust transfer algorithm was proposed based on the explicit social relationships and potential features between nodes.The algorithm can tap and establish the implicit social relationships among nodes to solve the SIoT sparsity and cold start problem.Additionally, the social relations were fine-grained and divided to build a single-relationship sub-network.Multiple single-relationship sub-networks were fused to build a multiple-relationship composite network.Thus, the impact of multiple dynamically changing social relationships among nodes on trust evaluation can be effectively fused.The comprehensive trust assessment of intelligent objects was conducted based on three indicators: direct trust, indirect recommendation trust, and service satisfaction.The experimental results on real smart city datasets demonstrate the model’s robustness in non-sparse and sparse network scenarios.It can effectively evaluate trusted and untrusted objects in the network and improve the accuracy and convergence of trust evaluation.…”
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Multiobjective Core Reloading Pattern Optimization of PARR-1 Using Modified Genetic Algorithm Coupled with Monte Carlo Methods by Nadeem Shaukat, Ammar Ahmad, Bukhtiar Mohsin, Rustam Khan, Salah Ud-Din Khan, Shahab Ud-Din Khan

“…It has been observed that the developed intelligent strategy performs these tasks with a reasonable computational cost.…”
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Innovative Smart Road Stud Sensor Network Development for Real-Time Traffic Monitoring by Zhimin Tao, Wei Quan, Hua Wang

“…Intelligent transportation infrastructure has gained significant research attention recently. …”
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FAULT DIAGNOSIS OF PLANETARY GEAR BOX BASED ON SENSITIVE TRANSIERT IMPACT FEATURE EXTRACTION AND HIERARCHICAL EXTREME LEARNING MACHINE by QIN Bo, YIN Heng, WANG Zhuo, ZHAO WenJun, MA Tao, WANG JianGuo

“…In the intelligent diagnosis of planetary gearbox faults,the issue of "difficult extraction"of the vibration signal characteristics,the"quality difference"of the constructed eigenvector set and the"low precision"of the fault classification model based on the extreme learning machine. …”
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Fault Diagnosis Method of Distribution Equipment Based on Hybrid Model of Robot and Deep Learning by Shan Rongrong, Ma Zhenyu, Ye Hong, Lin Zhenxing, Qiu Gongming, Ge Chengyu, Lu Yang, Yu Kun

“…In view of the poor effect of most fault diagnosis methods on the intelligent recognition of equipment images, a fault diagnosis method of distribution equipment based on the hybrid model of robot and deep learning is proposed to reduce the dependence on manpower and realize efficient intelligent diagnosis. …”
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A Wi-Fi sensing method for complex continuous human activities based on CNN-BiGRU by Yang LIU, Anming DONG, Jiguo YU, Kai ZHAO, You ZHOU

“…Human activity sensing based on Wi-Fi channel state information (CSI) has an important application prospect in future intelligent interaction scenarios such as virtual reality, intelligent games, and the metaverse.Accurate sensing of complex and continuous human activities is an important challenge for Wi-Fi sensing.Convolutional neural network (CNN) has the ability of spatial feature extraction but is poor at modeling the temporal features of the data.While long short-term memory (LSTM) network or gated recurrent unit (GRU) network, which are suitable for modeling time-series data, neglect learning spatial features of data.In order to solve this problem, an improved CNN that integrates bidirectional gated recurrent unit (BiGRU) network was proposed.The bi-directional feature extraction ability of BiGRU was used to capture the correlation and dependence of the front and back information in the time series data.The extraction of the spatiotemporal features of the time series CSI data was realized, and then the mapping relationship between the action and the CSI data was present.Thus the recognition accuracy of the complex continuous action was improved.The proposed network structure was tested with basketball actions.The results show that the recognition accuracy of this method is above 95% under various conditions.Compared with the traditional multi-layer perceptron (MLP), CNN, LSTM, GRU, and attention based bidirectional long short-term memory (ABLSTM) baseline methods, the recognition accuracy has been improved by 1%～20%.…”
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Improvement of flipped classroom teaching in colleges and universities based on virtual reality assisted by deep learning by Wenxia Dai, Qinqing Kang

“…This paper aims to enhance personalized learning experience, improve teaching efficiency and autonomous learning effect through VR technology and intelligent feedback, and promote the innovation of interactive teaching mode.…”
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