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IEEE Education engineering (EDUCON)

作者： Sergio Martin Manuel Castro Elio Sancristobal Gabriel Diaz Felix Garcia-Loro Clara Perez Blanca Quintana Rosario Gil Pedro Plaza Africa Lopez German Carro Antonio Robles Llanos Tobarra Miguel Rodriguez-Artacho Jose A. Ruiperez-Valiente Electrical and Computer Engineering Department Universidad Nacional de Educación a Distancia Madrid Spain Dep. Sistemas de Comunicación y Control Universidad Nacional de Educación a Distancia Madrid Spain Dep. Lenguajes y Sistemas Informáticos Universidad Nacional de Educación a Distancia Madrid Spain Teaching Systems Lab Masschusetts Institute of Technology USA

This paper describes the organization and results of several MOOCs delivered about technical topics (i.e., digital electronics, VHDL design on FPGAs, open education and OERs repositories and the use of STEAM technologies to encourage diversity and inclusion), where online laboratories have been used in some of them. An analysis of the enrollment, students participating on tasks or quizzes, drop-out rate and certifications requests have been done.

关键词： VHDL Laboratories Organizations Task analysis engineering education Field programmable gate arrays Certification

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Smart Human Resource Management System to Maximize Productivity

Smart Human Resource Management System to Maximize Productiv...

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2020 International computer Symposium, ICS 2020

作者： H.a.s.s, Hewage K.u, Hettiarachchi K.m.j.b, Jayarathna K.p.c., Hasintha Senarathne, A.N. Wijekoon, J. Sri Lanka Institute of Information Technology Dep. of Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Dep. of Computer Systems Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Dep. of Information Technolgy Malabe Sri Lanka

ISBN: (纸本)9781728192550

Human resource is one of the most valuable assets in an organization. They are bounded to develop the unique and dynamic aspects that strengthen their competitive advantage to persist in an always changing market environment. In order to recruit a quality candidate for an organization, reducing human involvement and verifying details of the candidate is important in recruitment process. Furthermore, having an idea about how well or poor the employees perform, and how likely the employee attrition can occur is vital in human resource management process. This paper is an attempt to introduce smart human resource management system that can maximize the productivity of an organizational environment using machine learning and blockchain technologies. The end goal of this research is a smart human resource management system that reduces human judgment, time in the candidate selection process and predicts employee performance and attrition to motivate current employers to maximize productivity with minimal financial loss in the workplace environment. Skill assessment and resume classification have been done using unsupervised learning algorithms and natural language processing after extracting raw data from employee resumes using Object Character Recognition. Candidate details verification is done by comparing the hashes of the records which are stored in the blockchain. Employee performance and attrition are predicted using supervised machine learning classification techniques with high accuracy and the result of the final performance is generated as a score for each employee considering the multiple attributes that has been standardized and regulated by some specifically considered e-competence frameworks. © 2020 IEEE.

关键词： Human resource management

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Enhancements to the 5G-NR 2-Step RACH: an Unsourced Multiple Access Perspective

Enhancements to the 5G-NR 2-Step RACH: an Unsourced Multiple...

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IEEE Conference on Standards for Communications and Networking (CSCN)

作者： Patrick Agostini Jean-Francois Chamberland Federico Clazzer Johannes Dommel Gianluigi Liva Andrea Munari Krishna Narayanan Yury Polyanskiy Slawomir Stanczak Zoran Utkovski Fraunhofer Heinrich-Hertz-Institut Berlin Germany Dep. of Electrical and Computer Engineering College Station Texas A&M University TX USA German Aerospace Center (DLR) Inst. of Communications and Navigation Wessling Germany Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA USA

ISBN: (数字)9798331507428

ISBN: (纸本)9798331507435

The ever increasing demand for massive connectivity, combined with the specific characteristics of machinegenerated wireless traffic, is pushing the existing solutions for device registration and data transfer beyond their operational limits. In this paper, we target specifically the 3GPP 5G New Radio random access channel, proposing some enhancements inspired by recent research results in the field of unsourced multiple access (UMAC). Aiming to enable massive grant-free connectivity for large machine-type and Internet of things terminals, we focus on modifications of the two-step random access procedures originally introduced in 3GPP Release 16. By means of simulations, we show that remarkable gains in both energy and spectral efficiency can be attained while retaining a strong resemblance to the legacy protocol.

关键词： Wireless communication Fading channels Protocols Spectral efficiency Simulation New Radio 3GPP Internet of Things Standards Signal to noise ratio

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Interference Estimation via Model-Based Deep Learning in Grant-Free Networks

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IEEE Wireless Communications Letters 2025年第6期14卷 1663-1667页

作者： Pereira, Diogo Oliveira, Rodolfo da Costa, Daniel Benevides Kim, Hyong Instituto de Telecomunicações Lisbon1049-001 Portugal Universidade Nova de Lisboa Dep. de Engenharia Electrotécnica e de Computadores Faculdade de Ciências e Tecnologia Caparica2829-516 Portugal Interdisciplinary Research Center for Communication Systems and Sensing Department of Electrical Engineering Dhahran31261 Saudi Arabia Carnegie Mellon University Electrical and Computer Engineering PittsburghPA United States

This paper presents a novel approach for estimating interference distribution parameters in grant-free access networks using a model-based deep learning (DL) framework. Our method integrates the precision of analytical models with the adaptability of deep learning algorithms. Specifically, we employ an analytical model to generate labeled data, which enhances the deep learning model’s ability to estimate interference levels. Through extensive validation, we demonstrate that our approach accurately estimates interference across a broad range of scenarios, including operating regions not covered during the model’s training. Moreover, our method also estimates the spatial density of interfering nodes, making it a valuable tool for interference management in grant-free access networks. This methodology offers a robust solution for improving interference estimation accuracy, aiding decision-making at the Medium Access Control (MAC) and physical layers in grant-free access schemes. © 2025 IEEE. All rights reserved.

关键词： Contrastive Learning

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Electronic Energy System and Energy Management Algorithm for FutureHAUS

Electronic Energy System and Energy Management Algorithm for...

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IEEE Conference on Power Electronics and Renewable Energy (CPERE)

作者： Vladimir Mitrovic Igor Cvetkovic Dushan Boroyevich Joseph Wheeler Robert Vance The Bradley Dep. of Electrical and Computer Engineering College of Engineering Center for Power Electronics Systems Virginia Polytechnic Institute and State University Blacksburg VA USA Center for Design Research School of Architecture + Design College of Architecture and Urban Studies Virginia Polytechnic Institute and State University Blacksburg VA USA

Technology advancements that happened in the last two decades have changed the way how people live, interact, and work more than any technology did in the past 100 years or so. Not only little “gadgets” enabled this enormous paradigm shift, the new innovative concepts have been well integrated into the design and manufacturing of computers, appliances, automobiles, airplanes, and ships, and it was about time to start seeing these concepts applied to the homes where building practices, by contrast, experienced a very slow, if not resistant effort to advance. At least they did before Virginia Tech demonstrated the use of advanced manufacturing concepts, prefabricated structures, and a great number of power electronics to redefine the conventional practice of modern home design. Its FutureHAUS won first place at the international competition in Dubai, UAE, validating an enormous societal desire to see this change finally happening. This paper will describe details of the electronic energy system implementation as well as an energy management algorithm developed to successfully achieve a net-positive energy balance in the FutureHAUS.

关键词： Resistance computers Renewable energy sources Home appliances Decision making Inverters Manufacturing

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Smart Harvesting based on Image Processing

Smart Harvesting based on Image Processing

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2020 International computer Symposium, ICS 2020

作者： Joseph, S.P Wijerathna, L.L.M.C. Epa, K.G.R.D. Egalla, E.K.W.A.P.K. Abeygunawardhana, P.W.K. De Silva, R Sri Lanka Institute of Information Technology Dep. of Computer Systems Engineering Faculty of Computing Malabe10115 Sri Lanka Sri Lanka Institute of Information Technology Dep. of Software Engineering Faculty of Computing Malabe10115 Sri Lanka

ISBN: (纸本)9781728192550

Vision device is a critical component of fruit harvesting mobile robot which is designed for recognizing and harvesting of tomato fruits. The system of vision device of the moving robot, for a dedicated path identification with the use of colour detection algorithms and contour detection algorithms could be stated as an additional usage of the image-based technology. When the robot operates in real life, varying environmental parameters would not affect its activity, since the robot will be functioning mainly indoors, specifically in a greenhouse. Robust fruit segmentation algorithms for the visual system and the fruit plucking mechanism using a readymade robot arm with a soft gripper where it operates with basic hardware components like motors, controlled by a microcontroller with the intervention of kinematic theories, is being used with the goal of collecting fruit objects efficiently in the natural world. Plucking only the ripe and healthy object fruit without damaging both the fruit and the tree is the intended task of the system. The aim is to reduce human effort by promoting automation concepts in agriculture in developing countries like Sri Lanka with great potential, where agriculture plays a vital role in the development of the economy while indoor plantation and harvesting mechanism are also being developing to cater to the economy of the country as well. The way that this system is implemented will be discussed in this paper. © 2020 IEEE.

关键词： Fruits

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Development of a Low-Cost Interrogation System Using a MEMS Fabry-Pérot Tunable Filter 5

Development of a Low-Cost Interrogation System Using a MEMS ...

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5th International Conference on Applications of Optics and Photonics, AOP 2022

作者： Araújo, João C. C. Dias, Bernardo Dos Santos, Paulo S. S. De Almeida, J.M.M.M. Coelho, Luís C. C. INESC TEC - Institute for Systems and Computer Engineering Technology and Science FCUP Univ. of Porto R. Do Campo Alegre Porto4169-007 Portugal FCUP University of Porto Rua do Campo Alegre Porto4169-007 Portugal Dep. of Physics Univ. of Trás-os-Montes e Alto Douro Vila Real5001-801 Portugal

The interrogation of optic fiber sensors usually relies in complex and costly equipment with low portability due to their size such as Optical Spectrum Analyzers (OSA) or high-resolution spectrometers. Because of this, micro spectrometer devices, such as Micro-Electromechanical systems (MEMS) with Fabry-Pérot tunable filters, are emerging as simpler and compact alternatives capable of being used to acquire spectral information in a wide wavelength band. In this work it is described the development of an interrogation system capable of infrared spectroscopy using a MEMS Fabry-Pérot Interferometer (MEMS-FPI) with a spectral response in the 1350nm to 1650nm range. Its performance is tested with the interrogation of long period fiber gratings both as a refractive index sensor and as a temperature sensor. Deconvolution techniques such as Wiener filtering are used to reduce the impact of the tunable filter's impulse response in the measured signal. Results are comparable to those obtained using a typical OSA which shows the system's potential as a cheaper and more transportable alternative. © Published under licence by IOP Publishing Ltd.

关键词： Fiber optic sensors

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Five actions fit for 55: streamlining energy savings calculations

Five actions fit for 55: streamlining energy savings calcula...

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2022 ECEEE Summer Study on Energy Efficiency: Agents of Change

作者： van Maris, Kelsey Renders, Nele Böck, Elisabeth Fonseca, Paula Moura, Pedro Patrão, Carlos López Arias, María VITO/Energyville Boeretang 200 MolBE-2400 Belgium AEA - Austrian Energy Agency Mariahilfer Straße 136 ViennaAT-1150 Austria Institute of Systems and Robotics Dep. of Electrical and Computer Engineering University of Coimbra Polo II Coimbra3030-290 Portugal CIRCE Parque Empresarial Dinamiza Avda. Ranillas 3D 1ª Planta Zaragoza50018 Spain

ISBN: (纸本)9789198827002

The "energy efficiency first principle" is key when defining energy policies and making relevant investment decisions within Europe to encourage actions in energy efficiency and energy demand management. In a first round, the H2020 project streamSAVE targeted five Priority Actions or measures with high energy savings potential and being considered as priority issues by the Member States. The project streamlines energy savings calculations, in frame of Article 3 and 7 of the Energy Efficiency Directive (EED) covering energy efficiency targets and national energy savings obligations, respectively. Given the importance of deemed savings approaches in Member States' EED reporting, streamSAVE focuses on bottom-up calculation methodologies of standardized technical actions. Despite their high energy savings potential, policy officers indicated that a lack of experience, practices and reliable data sources is hindering the adoption of the following Priority actions by several Member States: Heat Recovery;Building Automation and Control systems (BACS);Commercial and Industrial Refrigeration systems;Electric Vehicles and Road Lighting. The project developed standardized calculation methodologies and provided EU-wide indicative values for each of these Priority Actions. These bottom-up approaches for calculating energy savings consider all essential impacts on the energy consumption of an appliance or system (e.g., equipment efficiency, operating hours) and compare the baseline scenario with the situation after implementation. This paper presents the developed methodologies, considering Article 3 and Article 7 reporting requirements as well. Moreover, lessons learned, collected during the testing and validation of the methodologies when translating the streamSAVE methodology guidance into Member States' EED practices, are explained to illustrate the role of standardized calculations in supporting energy efficiency policy. © 2022 European Council for an Energy Efficient Econom

关键词： Energy efficiency

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Segmentation of Foetus Brain MRI Based on K-nn Algorithm, A Case Study 12th

Segmentation of Foetus Brain MRI Based on K-nn Algorithm, A ...

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12th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2020 and 16th International Conference on Information Assurance and Security, IAS 2020

作者： Salgado, Paulo Azevedo Perdicoúlis, Teresa-Paula CITAB-Dep. de Engenharias ECT UTAD Quinta de Prados Vila Real5000-801 Portugal Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Rua Silvio Lima-Polo II Coimbra3030-290 Portugal

ISBN: (纸本)9783030736880

The segmentation of magnetic resonance images of the fetal brain has been emerging as a clinical tool to detect abnormalities during the development of the foetus. Since the brain is still in development, a mixture of regions of white matter, grey matter and transition structures that are related to brain growth are still associated with it. In this work, two versions of the K-nearest neighbour algorithm are proposed as the core method for the recognition of different regions of an image;the first one is a refinement of the standard algorithm since some statistics are associated with the pixel, and the second a reinforcing iterative version of the same method. Both versions are used to identify 3 apriori selected regions—the brain, the intracranial region and the remaining part of the foetus. The effectiveness of the method has been demonstrated in a magnetic resonance image segmentation that was first pre-processed with digital filters for feature extraction. The present study illustrates the capabilities of this type of method to support obstetricians and general practitioners to assess the foetus and, in particular, its brain. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image segmentation

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Automating Public Announcement Logic with Relativized Common Knowledge as a Fragment of HOL in LogiKEy

arXiv

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arXiv 2021年

作者： Benzmüller, Christoph Reiche, Sebastian University of Bamberg AI Systems Engineering Bamberg Germany FU Berlin Dep. of Mathematics and Computer Science Berlin Germany

A shallow semantical embedding for public announcement logic with relativized common knowledge is presented. This embedding enables the first-time automation of this logic with off-the-shelf theorem provers for classical higher-order logic. It is demonstrated (i) how meta-theoretical studies can be automated this way, and (ii) how non-trivial reasoning in the target logic (public announcement logic), required e.g. to obtain a convincing encoding and automation of the wise men puzzle, can be realized. Key to the presented semantical embedding is that evaluation domains are modeled explicitly and treated as an additional parameter in the encodings of the constituents of the embedded target logic;in previous related works, e.g. on the embedding of normal modal logics, evaluation domains were implicitly shared between meta-logic and target logic. The work presented in this article constitutes an important addition to the pluralist LogiKEy knowledge engineering methodology, which enables experimentation with logics and their combinations, with general and domain knowledge, and with concrete use cases - all at the same *** Codes 03B42, 03B60, 03B62, 68T27, 68T30 Copyright © 2021, The Authors. All rights reserved.

关键词： Formal logic

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