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Simulation Winter Conference

作者： Mahdi Darvishi Abdolreza Abhari Fac. of Eng. and Architectural Scie. Toronto Metropolitan University Toronto ON CANADA Dept. of Computer Science Eng Toronto Metropolitan University Toronto ON CANADA

ISBN: (数字)9798331534202

ISBN: (纸本)9798331534219

Photovoltaic (PV) systems are pivotal in the global energy transition, where accurate solar power forecasting is critical. Traditional forecasting has leaned heavily on solar irradiance data, yet such reliance carries inherent uncertainties and measurement complexities, presenting significant forecasting challeng.s. This paper introduces a novel hybrid/ensemble model that reduces dependence on solar irradiance data, utilizing geographic, meteorological, and temporal data to predict solar power output. Combining the streng.hs of XGBoost and LightGBM algorithms through a linear regression meta-model, our approach demonstrates improved prediction accuracy, evidenced by a mean absolute error (MAE) of 0.033, and an R-squared value of 0.693. This study advances solar power forecasting, enhancing PV system efficiency, and reliability, and promoting sustainable energy investments.

关键词： Training Solar irradiance Analytical models Adaptation models Accuracy Uncertainty Linear regression Predictive models Reliability Forecasting

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Elasticity Measurements of Expanded Foams using a Collaborative Robotic Arm

arXiv

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arXiv 2023年

作者： Beber, Luca Lamon, Edoardo Palopoli, Luigi Fambri, Luca Saveriano, Matteo Fontanelli, Daniele Dept. of Eng. and Computer Science University of Trento Trento Italy Dept. of Industrial Engineering University of Trento Trento Italy

Medical applications of robots are increasingly popular to objectivise and speed up the execution of several types of diagnostic and therapeutic interventions. Particularly important is a class of diagnostic activities that require physical contact between the robotic tool and the human body, such as palpation examinations and ultrasound scans. The practical application of these techniques can greatly benefit from an accurate estimation of the biomechanical properties of the patient's tissues. In this paper, we evaluate the accuracy and precision of a robotic device used for medical purposes in estimating the elastic parameters of different materials. The measurements are evaluated against a ground truth consisting of a set of expanded foam specimens with different elasticity that are characterised using a high-precision device. The experimental results in terms of precision are comparable with the ground truth and suggest future ambitious developments. Copyright © 2023, The Authors. All rights reserved.

关键词： Diagnosis

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WIP: (Almost) Anywhere Virtual Computing Learning Environment: Student Technology Acceptance

WIP: (Almost) Anywhere Virtual Computing Learning Environmen...

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Frontiers in Education (FIE) Conference

作者： Patrick Seeling Michael P. McGarry Department of Computer Science Central Michigan University Mount Pleasant MI USA Dept. of Electrical and Computer Eng. University of Texas at El Paso El Paso TX USA

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This work in progress innovative practice paper details our open source approach, which directly addresses new challeng.s to equitable access and privacy originating from increased technology-driven learning. We provide results from the Technology Acceptance Model's anonymous survey approach for a second-year introductory networking and a fourth-year operating systems course that employed the environment with comparable respondent characteristics. Although perceived ease of use and perceived use are in the middle of possible ranges, we find an interesting reversal for the network course, where student attitudes are low despite high perceptions. Future work will be directed at further refinements of the framework and a more in-dept. evaluation of the privacy concerns that students might have and whether these could be included in the Technology Accentance Model.

关键词： Surveys Privacy Data privacy Technology acceptance model Operating systems Computational modeling Data models

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WIP: From Passive to Passionate: Using Genuine Projects to Motivate Students

WIP: From Passive to Passionate: Using Genuine Projects to M...

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Frontiers in Education (FIE) Conference

作者： Michael P. McGarry Patrick Seeling Dept. of Electrical and Computer Eng. University of Texas at El Paso El Paso TX USA Department of Computer Science Central Michigan University Mount Pleasant MI USA

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This innovative practice WIP paper presents our work to increase student motivation and eng.gement using real-world projects. Specifically, we assigned final projects to students that came from a genuine need from our research program on campus. The team projects were assigned in a networking course offered to undergraduate and graduate students. Anecdotally, the students seemed more motivated to complete the projects because they knew the requested designs were novel and provided local utility. Student performance toward project completion was, anecdotally, exceptional compared to traditional projects. We surveyed students to assess their perceptions of their mo-tivation and subsequent eng.gement. The survey results suggest that the students perceived what we also perceived: students had more motivation from these types of projects than the typical contrived recycled projects typically assigned. In this paper, we provide the details behind these projects, how we managed the students to complete them, how we attempted to make the process mirror a commercial environment, and analyze the results of the student survey data. We also outline our experimental design to be executed in future course offerings to better understand how student motivation and eng.gement is affected by these types of projects in comparison with typical contrived recycled projects. Lastly, we outline how we intend to scale up across campuses and to create an experiential learning environment outside of formal course work.

关键词： Surveys Heuristic algorithms Mirrors Particle swarm optimization Logistics

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WIP: Evolution of a Networking Course - Attitude Changes a Decade and a Pandemic Later

WIP: Evolution of a Networking Course - Attitude Changes a D...

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Frontiers in Education (FIE) Conference

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This work in progress research paper describes the findings of an anonymous survey modeled after the persistence in eng.neering survey instrument that we conducted a decade apart in 2014 and 2024. Significant changes in the mid-2010s to the mid-2020s have altered course delivery and resulting student perceptions, and we find statistically significant differences for program persistence, student self-perceived performance, perceived course value, course enjoyment, self-perceived learning gains, and self-perceived learning material eng.gement efforts. Interestingly, we did not find significant differences between the two groups with respect to self-reported time spent on different course activities or general student population characteristics, such as self-reported credits, GPA, work hours, or commutes. When considering the averaged changes, we note that students in the more recent blended and virtualized environments exhibit a higher level of persistence than their peers. This showcases the overall increase of blended and decentralized/virtualized instruction having a positive impact on student attitudes based on the feedback collected.

关键词： Surveys Pandemics Instruments Active learning Position measurement Market research

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SCHC over DtS-IoT: Performance of SCHC Confirmation Modes in Satellite IoT

SCHC over DtS-IoT: Performance of SCHC Confirmation Modes in...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Rodrigo Munoz-Lara Sandra Céspedes Marcos Diaz Dept.of Electrical Engineering University of Chile Santiago Chile Dept. of Computer Science & Software Eng. Concordia University Montreal QC Canada

ISBN: (数字)9798350373011

ISBN: (纸本)9798350373028

Static Context Header Compression and Fragmentation (SCHC) is a standard defined as an adaptation layer for supporting IPv6, UDP, and CoAP protocols in low power wide area network (LPWAN) technologies. SCHC has fragmentation modes that use confirmation mechanisms to deliver reliable communications. Direct-to-satellite Internet of Things (DtS-IoT) directly communicates between end devices and the satellite in an IoT environment. If SCHC is implemented in a DtSIoT environment, applications using IPv6 could have global coverage through the Internet of Things (IoT). Unfortunately, it is not known whether SCHC can operate with the current acknowledgement mechanisms in a DtS-IoT environment, and if so, it is not known which one performs better. This work evaluates SCHC acknowledgement modes for ACK-on-Error fragmentation mode, including the new SCHC Compound ACK mode. It determines which mode has the lowest transfer delay for different LoRa data rates and frame error rates in a DtS-IoT environment with LEO satellites.

关键词： Satellites Protocols Low earth orbit satellites Delays Internet of Things Compounds Reliability IP networks Standards Low-power wide area networks

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Issues with Input-Space Representation in Nonlinear Data-Based Dissipativity Estimation

arXiv

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arXiv 2024年

作者： LoCicero, Ethan J. Penne, Alexander Bridgeman, Leila Dept. of Mechancial Eng. and Materials Science Duke Univeristy DurhamNC27708 United States Dept. of Electrical and Computer Engineering Duke Univeristy United States

In data-based control, dissipativity can be a powerful tool for attaining stability guarantees for nonlinear systems if that dissipativity can be inferred from data. This work provides a tutorial on several existing methods for data-based dissipativity estimation of nonlinear systems. The interplay between the underlying assumptions of these methods and their sample complexity is investigated. It is shown that methods based on δ-covering result in an intractable trade-off between sample complexity and robustness. A new method is proposed to quantify the robustness of machine learning-based dissipativity estimation. It is shown that this method achieves a more tractable trade-off between robustness and sample complexity. Several numerical case studies demonstrate the results. © 2024, CC BY.

关键词： Adversarial machine learning

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Machine Learning Applications in Market Basket Analysis: A Case Study on elec.ric Vehicle Sales in India

Machine Learning Applications in Market Basket Analysis: A C...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Rachna Rathore Ashish Singh Chauhan Kailash Aseri J. Balaji Praveen Gaurav Sethi Ankur Mishra Dept. of Mathematics Jiwaji University Gwalior India Dept. of Pharmaceutical Sciences Uttaranchal University Dehradun India Dept. of Computer Science D.A.V. College Sri Ganganagar Rajasthan Dept. Civil Eng. Dhanalakshmi Srinivasan College of Eng. Coimbator India Dept. of Electronics and Electrical Eng. Lovely Professional University Punjab India Dept. of CSE (AIML) CSE-APEX Chandigarh University Chandigarh India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

This study explores the potential of Market Basket Analysis (MBA) to enhance elec.ric vehicle (EV) recommendations in India. By analyzing transactional data and identifying common item sets and association rules, MBA can provide valuable insights into customer preferences and purchasing behavior. This information can be utilized to develop personalized recommendation systems that effectively guide customers toward EV solutions tailored to their specific needs and preferences. These include discussions on key drivers of EV purchases in India, steps for implementing MBA, and challeng.s/concerns about the application of MBA. Specific factors in buying decisions can be traced through the analysis of unique characteristics in the Indian EV market. Finally, potential benefits are presented with the implementation of an MBA-driven recommendation system to both the manufacturer and the consumers of elec.ric vehicles in India. The study will delve deep into the application of MBA in the Indian EV market and contribute toward more effective and customized recommendation systems for the industry at large.

关键词： elec.ric potential Time series analysis Predictive models elec.ric vehicles Market research Data models Association rule learning Vehicle dynamics Usability Recommender systems

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Mixed Energy and Production Scheduling in an Eco-Industrial Park

Mixed Energy and Production Scheduling in an Eco-Industrial ...

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Simulation Winter Conference

作者： Shufang Xie Tao Zhang Oliver Rose Tobias Uhlig Björn Vollack Dept. of Computer Science University of the Bundeswehr Munich Munich GERMANY Chair of Logistics Eng. TUD Dresden University of Technology Dresden GERMANY

ISBN: (数字)9798331534202

ISBN: (纸本)9798331534219

In recent times, eco-industrial parks (EIP) have taken on a significant role in addressing environmental challeng.s and supporting sustainable practices. To enhance the efficient utilization of energy within the park and ensure the achievement of production targets among its members, the implementation of energy and production scheduling is imperative. This paper addresses this optimization challeng. by formulating it into a constraint programming (CP) model. The optimized scheduling solutions generated by the CP model will be directly used to guide the operations within the simulation environment of the EIP. The paper compares the CP results with the results of another method which we developed in our previous research stage. The outcomes of CP solver demonstrate its effectiveness in optimizing energy utilization and meeting production targets. This research contributes to developing a practical decision support system for resolving real-life scheduling problems in industry parks.

关键词： Constraint handling Industries Job shop scheduling Green products Production Search problems Problem-solving Optimization Faces eng.nes

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Performance Monitoring and Controlling of Multicore Shared-Memory Parallel Processing Systems 3

Performance Monitoring and Controlling of Multicore Shared-M...

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3rd Information Technology to Enhance e-Learning and Other Application, IT-ELA 2022

作者： Haji, Lailan M Zeebaree, Subhi R. M. Ageed, Zainab Salih Ahmed, Omar M. Sadeeq, Mohammed A. M. Shukur, Hanan M. University of Zakho Faculty of Science Computer Science Dep. Duhok Iraq Technical College of Engineering Duhok Polytechnic University Energy Eng. Dept. Duhok Iraq College of Science Nawroz University Computer Science Dept. Duhok Iraq Zakho Technical Institute Duhok Polytechnic University Information Technology Dept. Duhok Iraq Technical College of Administration Duhok Polytechnic University ITM Dept. Duhok Iraq Al-Kitab University Computer Engineering Dept. Kirkuk Iraq

ISBN: (纸本)9798350334968

The field of research known as 'parallel processing' examines architectural and algorithmic methods for increasing the efficiency and other desirable qualities (such as cost-effectiveness and reliability) of computers by exploiting many forms of concurrency. The development of multi-core CPUs has opened the door to novel strategies for boosting system performance via parallelism. Increasing the number of concurrent threads greatly affects the time cost. While increased parallelism might reduce calculation time, the associated synchronization costs would likely be prohibitive for most applications. In this article, we'll go through the first half of the process, which involves gathering requirements and designing a prototype;the second half, which involves monitoring and managing a program that can run on a wide range of multicore system architectures, including those with (2, 4, and 8 CPUs). A shared-memory parallel processing method was proposed and built to show off the system's full potential. The implications of multi-core systems on overall program execution time and parallel processing in shared-memory systems provide the backbone of this investigation. © 2022 IEEE.

关键词： Cost effectiveness

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