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predictive Energy Management for Battery Electric Vehicles with Hybrid models 6th

Predictive Energy Management for Battery Electric Vehicles w...

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6th EAI international conference on Intelligent Transport Systems, INTSYS 2022

作者： Huang, Yu-Wen Prehofer, Christian Lindskog, William Puts, Ron Mosca, Pietro Kauermann, Göran DENSO Automotive Eching Germany LMU München Munich Germany

ISBN: (纸本)9783031308543

this paper addresses the problem of predicting the energy consumption for the drivers of Battery electric vehicles (BEVs). Several external factors (e.g., weather) are shown to have huge impacts on the energy consumption of a vehicle besides the vehicle or powertrain dynamics. thus, it is challenging to take all of those influencing variables into consideration. the proposed approach is based on a hybrid model which improves the prediction accuracy of energy consumption of BEVs. the novelty of this approach is to combine a physics-based simulation model, which captures the basic vehicle and powertrain dynamics, with a data-driven model. the latter accounts for other external influencing factors neglected by the physical simulation model, using machine learning techniques, such as generalized additive mixed models, random forests and boosting. the hybrid modeling method is evaluated with a real data set from TUM and the hybrid models were shown that decrease the average prediction error from 40% of the pure physics model to 10%. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Energy utilization

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Computer Simulation of Velocity Fields in the Flow of Plate models With a Given Roughness

Computer Simulation of Velocity Fields in the Flow of Plate ...

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international Youth conference on Radio Electronics, Electrical and Power engineering (REEPE)

作者： Dmitryi Chernykh National Research University “MPEI” Moscow Russian Federation

the need to develop a software package and conduct theoretical modeling of flow patterns with its help is dictated by the complexity of using the laser anemometry method on particle images. With the help of computer simulation of flows, it becomes possible to accelerate laboratory experiments, compare theoretical results with practical ones, further create new and modernize old structured materials with improved mechanical, thermal and aerodynamic properties. this article examines the principle of creating models of plates with a roughness class $\mathrm{P}100$ and with a fractal roughness distribution of similar sizes. For the roughness class $\mathrm{P}100$ , the characteristic size and distribution of surface irregularities are set according to the model of dimensionless equivalent “sand” roughness. the average height of the irregularities is $150 \pm 27,5$ microns. Fractal roughness modeling was performed in accordance with the Foss iterative algorithm. After the plate models were created, the influence of roughness on the flow pattern in the region $ = 1{{\ mm}}$ from the plate surface was analyzed under the following conditions: the rarefaction of the medium corresponds to $35{{\ km}}$ above the earth's surface, the initial flow velocity is $11{{\ m}}/\mathrm{s}$ , the angle of attack is ${0^ \circ }$ , the incoming flow is laminar.

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Simulation for sustainable agri-food production: From efficiency optimization to waste reuse 6

Simulation for sustainable agri-food production: From effici...

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6th international conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Fusto, Caterina Solina, Vittorio Grasso, Maria Lucrezia Magarò, Umile Mazziotti, Mattia Francesco Tripudio, Ettore Algieri, Angelo Corigliano, Orlando Department of Mechanical Energy and Management Engineering University of Calabria Ponte Pietro Bucci 45C Rende87036 Italy

this study analyzes the application of simulation in the agri-food production processes, with a focus on integrating Industry 4.0 technologies to improve efficiency, flexibility, product quality and environmental sustainability. the growing interest in simulation applications, their use in the agri-food sector is still in an initial phase compared to other industries, especially in terms of circular economy practices and waste reuse. this research addresses this gap by focusing on sustainable waste reuse in citrus production processes. Using Siemens Tecnomatix Plant Simulation software, a model was developed to simulate the production of citrus products, such as juices, jams, icings and alcoholic drinks, allowing bottlenecks to be identified and resources to be optimized. Minitab 17 software was used for statistical analysis of the results, confirming the benefits of optimization, including reduced production times and operating costs. the innovative aspect of this study lies in the development of a second model, which emphasizes sustainability through renewable energy generation from production waste. the sustainable model enabled the plant to meet 30% of its energy needs independently, and production time in the juice line was reduced from 4 days to just over 1 day. A second sustainability-oriented model introduces the reuse of production waste to generate renewable energy and by-products, fostering a circular economy. the results highlight how the integration of simulation and statistical tools can promote significant improvements in production performance and energy sustainability, contributing to the evolution of the agri-food sector toward more sustainable and competitive practices. © 2024 the Authors. Published by Elsevier B.V.

关键词： Circular economy

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Project Management Issues While Using Agile Methodology 6th

Project Management Issues While Using Agile Methodology

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6th international conference on Lean and Agile software Development (LASD)

作者： Butt, Shariq Aziz Pineres-Espitia, G. Ariza-Colpas, Paola Tariq, Muhammad Imran Univ Lahore Dept Comp Sci & Informat Technol Lahore Pakistan Univ Costa CUC Barranquilla Barranquilla Colombia Super Univ Lahore Pakistan

ISBN: (纸本)9783030942380;9783030942373

software engineering has many software development life cycle (SDLC) models to develop a software application and the latest SDLC models have been provided by agile methods. the agile methodology has been introduced due to some existing lacks in software development. Now agile methodology is used to overcome these deficiencies and improve software development. the use of the agile methodology is increased within software industries due to its distinctive features such as enabling change requests from the client at any stage of a project, client satisfaction, iterative development, and client-developer interaction. Another reason for agile adoption is the methods that are being used for agile software development. these methods include Scrum, Feature drive development, Extreme programming, and Dynamic system development methods. However, the agile methodology has some issues for project development and management. In this study, we discuss all these issues which are related to agile methods and individuals (i.e. team and developer). Further, we suggest the possible improvements that need to be introduced in the agile methodology. We believe such improvements is to make the agile methodology more productive for development environments.

关键词： Agile methodology software development Methods of agile Challenges

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EIF: A Mediated Pass-through Framework for Inference as a Service 21

EIF: A Mediated Pass-Through Framework for Inference as a Se...

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21st IEEE international Symposium on Parallel and Distributed Processing with Applications, 13th IEEE international conference on Big Data and Cloud Computing, 16th IEEE international conference on Social Computing and Networking and 13th international conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Gao, Yiming Wang, Zhen Wu, Weili Lam, Herman University of Florida Department of Electrical & Computer Engineering GainesvilleFL United States The University of Texas at Dallas Department of Electrical & Computer Engineering RichardsonTX75080 United States The University of Texas at Dallas Department of Computer Science RichardsonTX75080 United States

ISBN: (纸本)9798350329223

In order to effectively provide INaaS (Inference-as-a-Service) for AI applications in resource-limited cloud environments, two major challenges must be overcome: achieving low latency and providing multi-tenancy. this paper presents EIF (Efficient INaaS Framework), which uses a heterogeneous CPU-FPGA architecture to provide three methods to address these challenges (1) spatial multiplexing via software-hardware co-design virtualization techniques, (2) temporal multiplexing that exploits the sparsity of neural-net models, and (3) streaming-mode inference which overlaps data transfer and computation. the prototype EIF is implemented on an Intel PAC (shared-memory CPU-FPGA) platform. For evaluation, 12 types of DNN models were used as benchmarks, with different size and sparsity. Based on these experiments, we show that in EIF, the temporal multiplexing technique can improve the user density of an AI Accelerator Unit from 2 × to 6 × , with marginal performance degradation. In the prototype system, the spatial multiplexing technique supports eight AI Accelerators Unit on one FPGA. By using a streaming mode based on a Mediated Pass-through architecture, EIF can overcome the FPGA on-chip memory limitation to improve multi-tenancy and optimize the latency of INaaS. To further enhance INaaS, EIF utilizes the MapReduce function to provide a more flexible QoS. Together with the temporal/spatial multiplexing techniques, EIF can support 48 users simultaneously on a single FPGA board in our prototype system. In all tested benchmarks, cold-start latency accounts for only approximately 5% of the total response time. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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the executable digital twin: merging the digital and the physics worlds 30

The executable digital twin: merging the digital and the phy...

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30th international conference on Noise and Vibration engineering, ISMA 2022 and 9th international conference on Uncertainty in Structural Dynamics, USD 2022

作者： Van der Auweraer, H. Hartmann, D. Siemens Industry Software NV Strategy & Innovation Interleuvenlaan 68 LeuvenB-3001 Belgium Siemens Industry Software GmbH Strategy & Innovation Otto-Hahn-Ring 6 Munich81739 Germany KU Leuven Department of Mechanical Engineering Celestijnenlaan 300 HeverleeB-3001 Belgium

ISBN: (纸本)9789082893151

While the digital twin has become an intrinsic part of the product creation process, its true power lies in the connectivity of the digital representation with its physical counterpart. Data acquired on the physical asset can validate, update and enrich the digital twin. the knowledge contained in the digital representation brings value to the physical asset itself. When a dedicated encapsulation is extracted from the digital twin to model a specific set of behaviors in a specific context, delivering a stand-alone executable representation, such instantiated and self-contained model is referred to as an Executable Digital Twin. In this contribution, key building blocks such as model order reduction, real-time models, state estimation and co-simulation are reviewed, and a number of characteristic use cases are presented. these include virtual sensing, hybrid testing and hardware-in-the loop, model-based control and model-based diagnostics. © 2022 proceedings of ISMA 2022 - international conference on Noise and Vibration engineering and USD 2022 - international conference on Uncertainty in Structural Dynamics. All rights reserved.

关键词： Structural dynamics

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Development of 3D Building Model Using Augmented Reality 6

Development of 3D Building Model Using Augmented Reality

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6th IEEE international conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2022

作者： Sundari, A.M. Anjana Bhatt, Devam Bhagya, R. R.V. College of Engineering Department of Electronics and Telecommunication Bangalore India

ISBN: (纸本)9781665456982

Augmented reality (AR) is one of the interactive user interface technology which enhances the real physical world through digital elements. From industrial solutions to tourism, marketing and education, AR has become one of the most widely used technologies in recent years. Over the decade, the field of architecture has been evolving from the traditional practices. the visualization of architectural blueprints has always been a perplexing task for the general public and architects. therefore, the developed AR application provides a 360-degree view of custom made 3D building models over the blueprints when scanned through an Android device. this makes it a cost-effective business tool for architects to show their clients what their future buildings will look like. this application involves the use of Marker-based AR Technology with Unity Real-Time Development Platform software and Vuforia. © 2022 IEEE.

关键词： Augmented reality

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Predicting Momentum: A Model Based on Wavelet Neural Network and PSO Algorithm

Predicting Momentum: A Model Based on Wavelet Neural Network...

引用

Electronics and Communication, Network and Computer Technology (ECNCT), international conference on

作者： Xinxuan Li Xinxuan Li School of Engineering Shantou University Shantou Guangdong

ISBN: (数字)9798350366143

ISBN: (纸本)9798350366150

this paper presents a predictive model based on Wavelet Neural Networks (WNN) and Particle Swarm Optimization (PSO) to forecast momentum in competitive environments. Initially, data related to player performance is analyzed using various machine learning algorithms, including Random Forest, XGBoost, SVC, MLP, and Logistic Regression. these models are validated using a 5-fold cross-validation method to determine their efficacy. Following this, a WNN model is constructed to map one-dimensional input to output, utilizing “momentum” as the key predictive feature. the model's accuracy is enhanced through the integration of PSO, which optimizes the combination of neural network models. Experimental results demonstrate that the WNN combined with PSO significantly improves prediction accuracy, making it a robust tool for forecasting in dynamic and complex systems.

关键词： Machine learning algorithms Accuracy Neural networks Static VAr compensators predictive models Prediction algorithms Robustness Particle swarm optimization Complex systems Random forests

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Analysis and Evaluation of Impact Reliability for Automotive Wheel Hub Based on Load Spectrum

Analysis and Evaluation of Impact Reliability for Automotive...

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Robotics and Computer Vision (ICRCV), international conference on

作者： Yao Liu Xiaoying Zhang Xintian Liu Xu Wang Shanghai University of Engineering Science School of Mechanical and Automotive Engineering Shanghai China

ISBN: (数字)9798331527426

ISBN: (纸本)9798331527433

Based on the road load spectrum, the vulnerable parts of the automobile wheel hub are analyzed for load characteristics and their fatigue life is predicted under actual service conditions, which provides a basis for the subsequent determination of model parameters. Considering the possible impact failure of the automobile wheel hub in service, a time-varying failure threshold model is established, and the model parameters are determined based on the actual physical significance. then, the impact reliability model of the wheel hub is established, and the remaining model parameters are estimated by the great likelihood estimation method.

关键词： Analytical models Roads Computational modeling Wheels Estimation predictive models Fatigue Reliability Automobiles Load modeling

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Proposed Conceptual Design of Artificial Intelligence Integration into a Pressure Oxidation Facility 6

Proposed Conceptual Design of Artificial Intelligence Integr...

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6th international conference on software and e-Business, ICSeB 2022

作者： De Los Santos, Breine C. Intal, Grace Lorraine D. School of Industrial Engineering and Management Mapua University Intramuros Manila Philippines School of Information Technology Mapua University Intramuros Manila Philippines

ISBN: (纸本)9798400700095

Research on Artificial Intelligence has substantially increased in various disciplines to address safety and operation difficulties such as the mineral processing Industry. the control system of a Pressure Oxidation facility was evaluated to determine potential opportunities for the integration of Artificial Intelligence. Several challenges were identified during the start-up operations of the Autoclave including typographical errors, possible non-compliance with Standard Operating Procedures, and the need for expertise to manage the operations. these conditions satisfy the need to explore an AI system that can potentially minimize human intervention. through related reviews, this study suggested a hybrid approach through incorporation of safe oxygen operation limits as part of supervised learning and to develop predictive models using historical data to predict the optimal oxygen requirement to achieve maximum oxidation results thereby making the POX process an ideal candidate for Artificial Intelligence system integration. A data flow diagram and user interface prototype were developed to illustrate the role of the proposed Artificial Intelligence system in controlling the Autoclave, which can significantly minimize human errors that can potentially improve safety and boost productivity. © 2022 ACM.

关键词： Optimization

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