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检索条件"丛书名=Lecture Notes in Networks and Systems"

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Improving the Performance of Permanent Magnet Synchronous Motors Based on the Model Predictive Current Control Method 7th

Improving the Performance of Permanent Magnet Synchronous Mo...

引用

7th International Conference on Green Technology and Sustainable Development

作者： Nhi Van Thi Kieu Thanh Quy Bach Dai Le Van Ind Univ Hochiminh City Hochiminh Vietnam

ISBN: (纸本)9783031762314;9783031762321

This research suggests a model predictive current control (MPCC) method to enhance the efficiency of permanent magnet synchronous motors (PMSM). In the suggested method, the system model forecasts stator current for all three-phase two-level voltage source inverter voltage vectors. The predictive current cost function, along with the reference current, is utilized to assess the current error at the subsequent sampling time. PMSM selects the voltage vectors with the lowest error function. MATLAB/Simulink is used to test the suggested MPCC method on a 1.5KW motor. The simulation result demonstrates that implementing the suggested MPCC method for controlling the PMSM leads to enhancements in current ripple reduction and torque response time when compared to both the field-oriented control (FOC) and the standard MPCC methods.

关键词： permanent magnet synchronous motor (PMSM) voltage source inverter model predictive current control (MPCC) field-oriented control (FOC)

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Assessing Inference Time in Large Language Models 19th

Assessing Inference Time in Large Language Models

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19th International Conference on Dependability of Computer systems (DepCoS-RELCOMEX)

作者： Walkowiak, Bartosz Walkowiak, Tomasz Wroclaw Univ Sci & Technol Wroclaw Poland

ISBN: (纸本)9783031618567;9783031618574

Large Language Models have transformed the field of artificial intelligence, yet they are often associated with elitism and inaccessibility. This is primarily due to the large number of their parameters, ranging from 1 billion to 70 billion, making inference on these models costly and resource intensive. To tackle this challenge, various solutions have emerged with the goal of enabling efficient, fast, and resource-constrained inference. This study aims to review and compare these available solutions. The authors conducted a series of experiments that compared the inference speed of the basic HuggingFace transformers library, the HuggingFace Text Generation Inference server, and the open source vLLM library. The findings reveal that vLLM outperforms the other approaches examined. Additionally, the results highlight how relatively straightforward techniques, such as continuous batching, can significantly accelerate inference for large batch sizes.

关键词： Large language models model deployment continous batching

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Method of Fitting a Nonlinear Function to Measurement Data, Its Uncertainty and as Example the Application in Thermistor Circuits 28th

Method of Fitting a Nonlinear Function to Measurement Data, ...

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2024 International Conference Automation

作者： Puchalski, Jacek Warsza, Zygmunt L. Cent Off Measures PL-00139 Warsaw Poland Polish Metrol Soc Warsaw Poland

ISBN: (纸本)9783031782657;9783031782664

The paper presents a method of determining parameters and uncertainty bands of a specific non-linear function fitted to given examined measured data. One or both of the variables of this non-linear function are changed so as to linearize it. Using the linear regression method, fined are the most favorable parameters of this straight line for its adjustment to the measured values of the coordinates of points tested according to the weighted total mean square WTLS criterion. Their autocorrelation and cross-correlation coefficients as well as uncertainties estimated according to the rules of the GUM guide [1] are considered. The parameters and the uncertainty band of the non-linear function result from the parameters of this straight line and its uncertainty band. In the part 2 numerical examples of determining the parameters and uncertainty bands for the characteristic of thermistor (two methods) alone and with resistance twoport sensor are given.

关键词： Linear regression of non-linear functions fit uncertainty and its band correlation weighted total least squares method characteristic function of thermistor

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Predicting Households' Short-Term Power Consumption Utilizing LSTM 10th

Predicting Households' Short-Term Power Consumption Utilizin...

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International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Vrbancic, Grega Podgorelec, Vili Brezocnik, Lucija Univ Maribor Intelligent Syst Lab Fac Elect Engn & Comp Sci Koroska Cesta 46 Maribor 2000 Slovenia

ISBN: (纸本)9783031662706;9783031662713

Due to the growing trend of power consumption, its efficient planning plays a vital role not only in households but also on a national level and beyond. Numerous methods and approaches have been proposed to tackle the complexities associated with power consumption predictions, yet the challenges persist. In this paper, we focus on short-term household power consumption prediction. For that, we briefly present the current techniques that solve this problem, along with their weaknesses - they are usually highly dependent on the nature of the problem and, more precisely, the data on which they are trained. To address this problem, we propose the LSTM model, which was tested on a real-life household power consumption dataset. The results show that the proposed model performs better than the ARIMA method, one of the most common methods for addressing such tasks regarding MAE, MSE, and RMSE metrics, thus providing more accurate and reliable predictions.

关键词： machine learning electrical energy consumption short-term prediction LSTM

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The Application of Artificial Intelligence in Recommendation systems Reinforced Through Assurance of Learning in Personalized Environments of e-Learning 1

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Fresneda-Bottaro, Fernando Santos, Arnaldo Martins, Paulo Reis, Leonilde Univ Tras Os Montes & Alto Douro Vila Real Portugal Univ Aberta Lisbon Portugal Inst Syst & Comp Engn Technol & Sci Porto Portugal Polytech Inst Setubal Setubal Portugal

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

Learning environments unquestionably enable learners to develop their pedagogical and scientific processes efficiently and effectively. Thus, considering the impossibility of not having conditions of autonomy over the routine underlying the studies and, consequently, not having guarantees of the learning carried out makes the learners experience gaps in the domain of materials adequate to their actual needs. The paper's objective is to present the relevance of the applicability of Artificial Intelligence in Recommendation systems, reinforced through the Assurance of Learning, oriented towards adaptive-personalized practice in corporate e-learning contexts. The research methodology underlying the work fell on Design Science Research, as it is considered adequate to support the research, given the need to carry out the design phases, development, construction, evaluation, validation of the artefact and, finally, communication of the results. The main results instigate the development of an Adaptive-Personalized Learning framework for corporate e-learning, provided with models of Artificial Intelligence and guided using the Assurance of Learning process. It becomes central that learners can enjoy adequate academic development. In this sense, the framework has an implicit structure that promotes the definition of personalized attributes, which involves recommendations and customizations of content per profile, including training content that will be suggested and learning activity content that will be continuously monitored, given the specific needs of learners.

关键词： Artificial Intelligence Recommendation systems Assurance of Learning Adaptive-Personalized Learning Learning Analytics

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Variational Quantum Algorithms in Finance 9th

Variational Quantum Algorithms in Finance

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9th International Congress on Information and Communication Technology (ICICT)

作者： Cong, Thanh N. N. Thi, Hiep. L. Duy Tan Univ Inst Res & Dev Da Nang City 550000 Vietnam Thu Dau Mot Univ Fac Educ Thu Dau Mot City 75000 Binh Duong Vietnam

ISBN: (纸本)9789819732982;9789819732999

The quantum processors' performance is predicted to surpass the traditional systems during this decade in computational performance and capabilities. This disruptive technology can significantly impact many industrial sectors in the long term. Other than communication and mathematics, we expect the finance sector to be one of the first to receive the prosperity of this new cutting-edge technology. This paper provides a review of the current progress on quantum algorithms for financial applications, specifically focusing on the use cases that can be addressed through machine learning.

关键词： Quantum computing Quantum machine learning Variational quantum algorithms

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Innovating Corporate Social Responsibility Integration in Human Resource Practices: A Systematic Review 4th

Innovating Corporate Social Responsibility Integration in Hu...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Larbi, Rania Alami, Nada Kasri, Laila Alami Akioud, Malika Sidi Mohamed Ben Abdellah Univ Fes Morocco

ISBN: (纸本)9783031686498;9783031686504

In this systematic literature review, an in-depth exploration of the interaction between corporate social responsibility (CSR) and human resource management (HRM) is undertaken. These two crucial elements play a fundamental role in achieving organizational excellence and adopting sustainable practices. The methodology of Tranfield, Denyer, and Smart (2003) is utilized, following a methodical approach from the identification to the detailed analysis of sources to extract key lessons. CSR is viewed as a business philosophy that deliberately integrates social and environmental concerns beyond mere financial considerations, while HRM focuses on the strategic management of talent within the company. The integration of CSR and HRM is recognized as an increasingly relevant area of research, suggesting that ethically rooted HRM practices can stimulate employee engagement and contribute to the sustainable development of the company. The Scopus database was leveraged for its wealth of research, and the analysis commenced with a broad examination of articles. These were progressively narrowed down to 215 relevant studies through rigorous selection criteria focusing on CSR and HRM. Further examination resulted in 41 studies being retained for more detailed analysis. This exploration revealed a complex landscape of interactions, where CSR initiatives intertwine closely with HRM strategies, creating corporate cultures that value employee engagement and strengthen the corporate brand. The strategic merging of HRM and CSR practices is identified as a marker of the modern orientation of organizations, underlining the importance of simultaneously achieving organizational objectives and societal well-being.

关键词： Corporate Social Responsibility Human Resources Innovation Prisma Statement Systematic Review

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Enhancing Educational Outcomes Through Learning Pathways and Artificial Intelligence-Driven Learning Analytics 21st

Enhancing Educational Outcomes Through Learning Pathways and...

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21st International Conference on Smart Technologies and Education (STE) on Smart Technologies for a Sustainable Future

作者： Trommer, Martin Franke, Susanne Teich, Tobias Riedel, Ralph Hellbach, Sven Franke, Daniel Univ Appl Sci Zwickau WHZ Kornmarkt 1 D-08056 Zwickau Germany

ISBN: (纸本)9783031618901;9783031618918

This paper explores the implementation of personalized learning pathways using Learning Analytics to enhance educational quality. It addresses the challenges posed by learner heterogeneity, varying learning speeds, and different learning styles, emphasizing the need for individualized learning approaches to optimize learning outcomes. Especially in the context of e-learning, the integration of Learning Analytics and Artificial Intelligence (AI) allows enhancing educational quality through the definition and dynamic adaption of learning pathways. This is achieved by adapting learning content, questions and difficulty levels in real-time based on the students' performance and behaviors. The paper includes the design of a platform architecture for data acquisition, preparation, and utilization in dynamically adjusting course content.

关键词： Learning Analytics xAPI Learning Platform Architecture

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Approach to Real-Time Simulation and Hardware-In-The-Loop for Microgrid Battery Management systems 4th

Approach to Real-Time Simulation and Hardware-In-The-Loop fo...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： El Qasery, Mouna Mahir, Oumaima Laamim, Mohamed Rochd, Abdelilah Barkouki, Bouthaina E. L. Abbou, Ahmed Mohammed V Univ Mohamadia Sch Engineers Dept Elect Engn Rabat Morocco Univ Sidi Mohamed Ben Abdallah Lab Signals Syst & Components Fes Morocco Fac Sci & Tech Mohammedia Lab Engn Sci & Biosci LSIB Mohammadia Morocco Hassan II Univ Mohammedia Elect Engn & Intelligent Syst Lab ENSET Mohammadia Morocco Green Energy Pk Benguerir Morocco

ISBN: (纸本)9783031686740;9783031686757

Real-time energy management is vital to address the intermittency of renewable energy resources. Assuming that the state of charge (SOC) availability of the battery is favorable, this paper will focus on achieving optimal integrated control to accomplish the utilization of solar power generation, battery energy storage, and grid interaction. This paper presents the offline modeling in MATLAB/Simulink study and the model validation through HIL (Hardware-in-the-Loop) on real-time simulation using OPAL-RT. Furthermore, the methodology is tested with residential datasets measured in Green & Smart Building Park (GSBP) in Ben-Guerir, Morocco. The analysis and evaluation of battery management systems (BMS), this research aims to contribute insights into enhancing system performance and reliability. This work seeks to understand how to improve system performance and reliability. The collected results show the performance of the battery energy management system and the contribution to the penetration of renewable resources through the Moroccan energy mix. This study is vital to developing renewable energy and advancing the global energy transition to cleaner energy sources.

关键词： Battery Energy Management System State of Charge Real-Time Simulation Hardware in the loop

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Energy Characteristics of Solar Arrays of the University Microsatellite for Remote Sensing of the Earth

Energy Characteristics of Solar Arrays of the University Mic...

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International Scientific and Technical Conference on Integrated Computer Technologies in Mechanical Engineering - Synergetic Engineering (ICTM)

作者： Pohudin, Andrii Gubin, Sergii Shepetov, Yurii Babakova, Larysa Dzvonyskyi, Oleksii Natl Aerosp Univ Kharkiv Aviat Inst 17 Chkalova St UA-61070 Kharkiv Ukraine

ISBN: (纸本)9783031614149;9783031614156

The article evaluates the illumination and temperature of sol-nex batteries of youth microsatellite of remote sensing of the Earth in the radio band. The assessment was carried out using a mathematical model adapted for the design of university spacecraft, describing the orbital parameters of the satellite in the sun vector. The model is implemented in the MathCAD application and tested on known parameters of operating micro-spacecraft. With the help of the model, numerical experiments were conducted to determine the dynamics of the illumination and temperature of the solar panels of the planned university microsatellite with geometric forms CubeSat 3U and orientation to the Earth with the largest axis of inertia.

关键词： microsatellite remote sensing orbit solar battery light temperature mathematical model

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