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检索条件"任意字段=International Conference on Advances in Data-driven Computing and Intelligent Systems, ADCIS 2022"

共 558 条记录，以下是311-320 订阅

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English-Chinese Translation Online Teaching System Based on data Mining Algorithm

English-Chinese Translation Online Teaching System Based on ...

引用

Advanced Technologies in intelligent Control, Environment, computing & Communication Engineering (ICATIECE), international conference on

作者： Chenxi Li Department of Public Foreign Language Teaching and Research Jilin University of Finance and Economics ChangchunJilin China International School of Chinese Studies Northeast Normal University ChangchunJilin China

ISBN: (纸本)9781665493970

With the rapid development of modern communication technology, mobile phones, as an indispensable communication tool for people, record the trajectory of people's activities, not only in the real space, but also in the network space. The analysis and mining of all kinds of information data has been very. data mining, which plays a crucial role in many scenarios, can help us discover a lot of valuable knowledge and anomaly patterns. The cultivation of translation ability is the core goal of current translation teaching, and the research on the composition of translation ability and the methods to improve translation ability is increasingly becoming the focus of translation teaching research. The development of translation ability is a dynamic interactive process, not a linear process guided by gradual input, but a dyna mic systematic behavior full of peaks, valleys, advances, reversals, stagnation, and even leaps forward, since it is composed of multiple sub-abilities and the multi-sub-abilities do not develop synchronously. The characteristics of dynamic assessment coincide with the dynamic change and complexity of the development of translation ability. In this paper, data mining algorithms are used to study the existing English-Chinese translation online systems.

关键词： Microwave integrated circuits Systematics Heuristic algorithms Education Mobile handsets Regression analysis Windows

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data-driven model for state of health estimation of lithium-ion battery

Data-driven model for state of health estimation of lithium-...

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international conference on Computational Methods and data Engineering, ICMDE 2020

作者： Singh, Rupam Kurukuru, V. S. Bharath Khan, Mohammed Ali Department of Electrical Engineering Delhi Technological University New Delhi India New Delhi India

ISBN: (纸本)9789811579066

The trend of electrification within the automotive industry has resulted in the development of electric vehicles (EVs) due to their sustainable and environment-friendly feature. One of the major components of these cars is their energy storage device, as its performance is very crucial for the success of the EV. But the major concern is the properties of the energy storage or battery change with time and usage. Therefore, the degradation of battery properties is interesting, especially the capacity decline. To understand and counter this degradation, it must be measured with high precision. This paper develops a data-driven approach to estimate the health of the batteries by using the support vector machine model. The proposed method identifies the keen points of the operation of an EV battery under aging conditions by performing accelerated aging and trains them with the adapted data-driven approach. To access the aging conditions, an equivalent electrical model of a cell of EV battery is simulated and operated for various current pulses. Further, when tested with unkown operation of a battery, the developed estimator predicted its health with an accuracy of 96.25%. The results depicted that the proposed concept gives an improved measure of the battery state and a pattern on how the capacity degradation occurs with time. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Lithium-ion batteries

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Discovering the diverse types of multi-degree valence relations combined with their context

Discovering the diverse types of multi-degree valence relati...

引用

international conference on Applications and Techniques in Cyber Intelligence, ATCI 2020

作者： Zhang, Qianqian Sun, Yang Liu, Weidong College of Computer Science Inner Mongolia University Hohhot China

ISBN: (纸本)9783030539795

With the promotion of the innovation-driven development strategy, patent data mining is receiving increasing attention, especially patent relation mining. Most current works mine some simple types of patent relations. However, the types of relation in patent are more complex than these simple types. Since realizing technical objectives needs to innovate technical functions in structure, function, application, testing or processing of products, the types of relations are formed by verbs and nouns as well. We propose a model to discover of multi-degree valence relations combined with their context. In the model, The noun/verb association relations are obtained by their contextual similarity. Combined with these association relations, the model discovers diverse patent relation types. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： data mining

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A Trust Level Evaluation Method for intelligent Numerical Control systems driven by Edge Intelligence

A Trust Level Evaluation Method for Intelligent Numerical Co...

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international conference on Computer and Communications (ICCC)

作者： Zheng Zhou Dong Yu Yi Hu Lipeng Zhang Wuwei He Haoyu Yu University of Chinese Academy of Sciences Shenyang Institute of Computing Technology Chinese Acadamy of Sciences Shenyang P.R. China Shenyang Institute of Computing Technology Chinese Acadamy of Sciences Shenyang P.R. China Digital Workshop Department Shenyang CASNC Technology Co.Ltd Shenyang P.R. China

With the increase in the number of networking devices in the industrial field, the total amount of data increases, resulting in huge broadband pressure and power consumption, making the traditional centralized processing outdated, and giving rise to the development of edge computing in the industrial field. To ensure the security of the overall network, the trust concept of the access terminal computer numerical control (CNC) system is introduced as an important basis for improving the manufacturing capability of CNC machine tools, so the inclusion of computing power and trust mechanism in the intelligent CNC system is a good solution to the lack of computing and analysis resources and the ability to reduce the security risks of the CNC system. In this paper, we mainly design a trust level evaluation method for the intelligent CNC system based on edge intelligence, which incorporates the trust evaluation in the edge computing environment, and effective plans and coordinates the cloud, edge, and final resources in the intelligent CNC system. We designed the trust degree model evaluation and constructed the security trust level of the CNC intelligent system with the collaboration between the cloud and the edge. Finally, the experimental scheme is validated and tested in a real environment.

关键词： Power demand Computational modeling Collaboration Numerical models Manufacturing Machine tools Computer numerical control

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OASIS: An Ontology-driven Autonomic Management System for intelligent Substations

OASIS: An Ontology-Driven Autonomic Management System for In...

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Xiaodong Xie Jianxu Yang Xiong Hua Qianru Zhou STATE GRID Corporation of China Beijing China NARI Group Corporation State Grid Electric Power Research Institute Hefei China School of Compute Science and Engineering Nanjing University of Science and Technology Nanjing China

With the soar of the demand for electricity all over the so-ciety, an intelligent autonomic management system for substations is in urgent need. Ontology driven knowledge based system plays a vital role in achieving a truly autonomic, zero-touch substation management system. This paper proposes OASIS, an ontology driven autonomic management system for intelligent substations, which is able to organize first-nary devices and verify human operations to prevent mis-operation in real-time. The ontology used and develop procedures are presented in detail. OASIS has been tested in a real-life substation, and the test results are presented in detail. It is evident that OASIS is competent for autonomic substation management, including device power status calculation, main device running status retrieval, interval organization, general faulty check and single operation mis-operation verification, in a efficient way, with the responding time less than two seconds in general. At last, several lessons learnt during the developing procedure are discussed as a conclusion.

关键词： Substations Inference mechanisms Knowledge based systems Organizations Ontologies Programming Real-time systems

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A data-driven ROM Based on HODMD 14th

A Data-Driven ROM Based on HODMD

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14th international conference on Soft computing Models in Industrial and Environmental Applications (SOCO)

作者： Beltran, Victor Le Clainche, Soledad Vega, Jose M. Univ Politecn Madrid Sch Aerosp Engn E-28040 Madrid Spain

ISBN: (纸本)9783030200558;9783030200541

A preliminary version of a data driven reduced order model (ROM) for dynamical systems is presented in this Chapter. This ROM synergically and adaptively combines a black-box full model (FM) of the system and extrapolate conveniently using a recent extension of standard dynamic mode decomposition called higher order dynamic mode decomposition (HODMD). These two are applied in interspersed time intervals, called the FM-intervals and the HODMD-intervals, respectively. The data for the each HODMD-interval is obtained from the application of the FM in the previous FM-interval. The main question is when extrapolation from HODMD is no longer valid and switching to a new FM-interval is necessary. This is made attending to two criteria, ensuring that an estimate of the extrapolation error and a measure of consistency are both conveniently small. In this sense, the present method is similar to a previous method called POD on the Fly, which was not a purely data driven method. Instead, POD on the Fly was based on a Galerkin projection of the governing equations that thus should be known. The new method presented in this paper is illustrated with several transient dynamics for the complex Ginzburg-Landau equation that converges to either periodic or quasi-periodic attractors. The resulting CPU accelerations factors (compared to the full model) are quite large.

关键词： Higher order dynamic mode decomposition Adaptive reduced order model data driven reduced order model Complex dynamics

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A data-driven Study of the Productivity of English-Originated Loanwords in Contemporary Chinese

A Data-Driven Study of the Productivity of English-Originate...

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international conference on Cyber Security Intelligence and Analytics, CSIA 2021

作者： Li, Jie College of Literature and Journalism Sichuan University Chengdu Sichuan610065 China School of Foreign Languages Southwest Petroleum University Chengdu Sichuan610500 China

ISBN: (纸本)9783030700416

In this paper, the word formation ability of English loanwords and morphemes in Chinese is measured and calculated. Number of syllables, positioning in a new word, degree of dependence, and number of semantic domain are the four factors to influence a morpheme’s word formation ability. We quantify the characteristics of the four aspects with numbers and then use SPSS to do correlation analysis and multivariate linear regression analysis. As a result, an equation is established to calculate and predict the productivity of English loanwords and morphemes. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Productivity

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Artificial Intelligence-Based New Material Design 10th

Artificial Intelligence-Based New Material Design

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10th international conference on Theory and Application of Soft computing, computing with Words and Perceptions (ICSCCW)

作者： Babanli, M. B. Azerbaijan State Univ Oil & Ind Azadlig Ave 20 AZ-1010 Baku Azerbaijan

ISBN: (纸本)9783030352493;9783030352486

For a long time, design of new materials was implemented on the basis of costly and time-consuming experimental approach. Nowadays machine learning, data mining and Big data techniques allow to develop a new approach, a so-called data-driven design of new materials. In this paper, we consider an approach to alloy discovery that is based on a synergy of deep learning and fuzzy logic methods. The approach allows to design materials with predefined characteristics by computer-aided generation of the underlying crystal structures and optimization of their parameters. An example is provided to illustrate the approach.

关键词： Crystal structure Material properties Fuzzy logic Deep learning Big data

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3rd international conference on Innovative computing and Communication, ICICC 2020

3rd International Conference on Innovative Computing and Com...

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3rd international conference on Innovative computing and Communication, ICICC 2020

ISBN: (纸本)9789811551123

The proceedings contain 196 papers. The special focus in this conference is on Innovative computing and Communication. The topics include: A Primer on Opinion Mining: The Growing Research Area;a Generic Framework for Evolution of Deep Neural Networks Using Genetic Algorithms;multimodal Medical Image Fusion Based on Discrete Wavelet Transform and Genetic Algorithm;driver Fatigue and Distraction Analysis Using Machine Learning Algorithms;a Hybridized Auto-encoder and Convolution Neural Network-Based Model for Plant Identification;curaBand: Health Monitoring and Warning System;optimization Algorithm-Based Artificial Neural Network Control of Nonlinear systems;mHealth for Mental Health;elman and Jordan Recurrence in Convolutional Neural Networks Using Attention Window;state of Charge Estimation Using data-driven Techniques for Storage Devices in Electric Vehicles;Application of Stochastic Approximation for Self-tuning of PID in Unmanned Surface Vehicles;dark web Activity on Tor—Investigation Challenges and Retrieval of Memory Artifacts;A Heterogeneous Dynamic Scheduling Minimize Energy—HDSME;face Recognition-Based Automated Attendance System;Human Emotion Recognition from Spontaneous Thermal Image Sequence Using GPU Accelerated Emotion Landmark Localization and Parallel Deep Emotion Net;delay Based Multi-controller Placement in Software Define Tactical Network;security in Cloud computing for Sensitive data: Challenges and Propositions;Utility of Game Theory in Defensive Wireless Sensor Networks (WSNs);robust Approach for Emotion Classification Using Gait;routing in Internet of Things Using Cellular Automata;depression Detection Among Social Media Users Using Machine Learning;Security-Based LEACH Protocol for Wireless Sensor Network;Design of High-Speed FPGA Based CASU Using CBNS Arithmetic: Extension to CFFT Processor;blockchain-Based Boothless E-Voting System;preface.

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Smart Driver Assistance for Traffic Sign, Pothole, Vehicle Malfunction, and Accident Detection

Smart Driver Assistance for Traffic Sign, Pothole, Vehicle M...

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international conference on advances in ICT for Emerging Regions

作者： Warna Vithanage Hasanka Madushan Tharinda Madushanka Tharushi Lokuliyana Janaka Wijekoon Sanjeevi Chandrasiri Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

Reducing ever-increasing road accidents is a big concern worldwide. Sri Lanka had the highest rate of road fatalities in the past few years, rapidly increasing daily. Among many factors, traffic signs, potholes, and vehicle mechanical malfunctions significantly impact road safety. Most accidents result from a lack of awareness, ignorance, and negligence of drivers. While many high-end vehicles are equipped with technologies such as intelligent road sign recognition systems and air suspension systems, most cars in the market only come with basic driving instruments. Therefore, there is a need for a universal driver assistance system that can be plugged into any vehicle to assist drivers in minimising road casualties. To this end, this study discusses Neural Networks, Machine Learning and IoT technologies to develop an intelligent system that is capable of detecting and analysing road signs, road potholes, vehicles’ internal system malfunctions, and road accidents and notifying drivers in real-time and inform authorities such as hospitals and police stations to be aware of accidents to minimise further casualties. This portable device is based on a Raspberry Pi microprocessor. It uses a web camera, an onboard diagnostic tool (OBD) and an accelerometer to process traffic sign footages, vehicle sensor data and movement data of the vehicle. Yielded results showed that the proposed system was 90% accurate.

关键词： Suspensions (mechanical systems) Road accidents Machine learning algorithms Law enforcement Microprocessors Neural networks Machine learning

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