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Deep Learning in Automated Tests for the Automotive Industry 15th

Deep Learning in Automated Tests for the Automotive Indus...

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15th International Conference on Soft computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired computing, NaBIC 2023

作者： Branco, Beatriz C. Barbosa, Ramiro S. Porto Portugal GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development ISEP/IPP Porto Portugal

ISBN: (纸本)9783031810824

The automotive industry is one of the biggest industries nowadays, representing almost 80% of the projects in Capgemini eng.neering Portugal, where this work was developed. In this paper, a new approach for automated tests in this sector is presented, based on the application of Deep Learning (DL) algorithms. Experimental results show that the new solution reduces the frameworks needed for testing, as well as the human interaction, improving the efficiency in HMI testing for the company. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Automated tests Automotive industry Deep learning

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Knowledge Retrieval Mechanism for Smart Buildings Based on IoT Devices Data 1

引用

9th International Conference on Energy and Environment research, ICEER 2022

作者： Teixeira, Nuno Gomes, Luis Vale, Zita GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto Rua Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (数字)9783031435591

ISBN: (纸本)9783031435584

The use of smart building solutions can bring advantages to both a building and its users. The main motivation of this work is to propose a solution based on internet of things devices to retrieve knowledge from historic data and, using the knowledge gained, contribute to the comfort of the user and the building’s sustainability. The use of internet of things devices enables the easy deployment of the proposed system in today’s buildings, where this kind of devices are commonly found. The knowledge regarding the role of each device and how they interact or impact each other will be studied by the proposed solutions that will deploy a continuous mechanism. The designed software architecture was developed in python, to allow easy implementation of different features. To test the proposed solution, it was used real data from a research building where several types of sensors were correlated to assess relations among data. The results show significant correlations between celling light consumption and the room’s light intensity sensor, and between the operation of air conditioning units and the room’s temperature, for example, data from 2 months, regarding air conditioner unit in room N102, demonstrates a − 0.85 correlation with the room temperature, when operating in cooling mode. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Internet of things

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Flexibility Provision from Residential Houses: a Sensitive Analysis on Net Consumption Limits

Flexibility Provision from Residential Houses: a Sensitive A...

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Mediterranean Electrotechnical Conference (MELECON)

作者： Ricardo Faia Pedro Faria Luis Gomes Zita Vale Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) Intelligent Systems Associate Laboratory (LASI) Porto Portugal

ISBN: (数字)9798350387025

ISBN: (纸本)9798350387032

This paper explores the potential for flexibility provision a residential house equipped with 12 different loads, integrated with a battery storage system and photovoltaic panels. The study employs a sensitive analysis framework to examine the net consumption limits associated with total flexibility provision throughout different periods of the day. By incorporating renewable energy sources such as PV panels and energy storage via batteries, the research addresses the load management in modern households. The use of shifting properties to the loads enhances the potential for flexibility provision. The findings offer valuable insights into optimizing energy consumption, balancing loads, and improving the overall efficiency of residential energy systems. This work contributes to the advancement of smart grid technologies, sustainable energy practices, and the integration of renewable sources in residential settings.

关键词： Photovoltaic systems Renewable energy sources Costs Load management Linear programming Mathematical models Batteries

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Using simulation to evaluate a concept drift detector for condition based maintenance 48

Using simulation to evaluate a concept drift detector for co...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Lourenco, Afonso Fernandes, Marta Marreiros, Goreti Corchado, Juan Manuel Gecad-Res. Group on Intelligent Engineering and Computing for Advanced Innovation and Development Porto Portugal Bisite-Research Group on Bioinformatics Intelligent Systems and Educational Technology Salamanca Spain

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

Industry 4.0. has empowered the integration of real-time sensor readings and process knowledge for early identification of faults. In this paper, simulation was used to evaluate the process of classifying data streams as drifting towards defective behavior. Focusing on the challeng.s imposed by real-word, unlabeled and non-stationary data, the proposed method was assessed by conducting a case-study in the plastic extrusion domain. The knowledge gained from initial tests on generated synthetic data sets was used to isolate symptoms of a clogged screen pack from the concept drifts detected by the Adaptive Windowing algorithm. Experimental results for 40 days of running time of an extruder show that the proposed method helped in identifying a defective screen pack state upon the appearance of defects in the extrudate. © 2022 IEEE.

关键词： Industry 4.0

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Federated Genetic Programming: A Study About the Effects of Non-IID and Federation Size 20th

Federated Genetic Programming: A Study About the Effects of ...

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20th International Symposium on Distributed computing and Artificial Intelligence, DCAI 2023

作者： Ribeiro, Bruno Gomes, Luis Faia, Ricardo Vale, Zita GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9783031383328

The privacy and security of users’ data have been a concern in the last few years. New techniques like federated learning have appeared to allow the training of machine learning models without sharing the users’ personal data. These systems have a lot of variables that can change the outcome of the models. Studies have been made to explore the effect of these variables and their importance. However, those studies only focus on machine learning models, namely deep learning. This paper explores the impact of the federation size in unbalanced data using a genetic programming model for image classification. The results show that the federation size can have impact on the contributions of each client, and the dataset size can influence the quality of the individuals. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image classification

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Hourly uncertainty applied to optimal expansion planning considering energy storage and seasonal network impacts

Hourly uncertainty applied to optimal expansion planning con...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Castro, Fábio Canizes, Bruno Soares, João Vale, Zita GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI – Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9798350396782

The prevalence of renewable energy on most networks has grown exponentially in recent years. This introduces previously unknown issues, such as how unpredictable output may be and the fact that it is not continuous, necessitating extra preparation for network planning. This study presents a stochastic methodology to enable the network to consider investments in new lines and any energy storage systems it sees fit. Sixteen alternative situational scenarios are produced by segmenting the study into seasonal phases, which are then broken into four circumstances (morning, peak, afternoon, and night) for each of the four seasons. However, these are divided into hourly scenarios (totaling 8760), with different states for generation, load, storage, and electric vehicles. The model is evaluated on a 180-bus network in Portugal that includes distributed generation, a substation, and a number of the distribution operator's biomass generators in addition to the distributed generation. © 2023 IEEE.

关键词： Distribution Networks Energy Storage Systems Optimal Planning Renewable Energy Seasonal Impacts Uncertainty

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A Novel Approach to Network Traffic Analysis: the HERA tool

A Novel Approach to Network Traffic Analysis: the HERA tool

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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Daniela Pinto Ivone Amorim Eva Maia Isabel Praça Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) Porto School of Engineering Polytechnic of Porto (ISEP-IPP) Porto Portugal Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) PORTIC – Porto Research Technology & Innovation Center Polytechnic of Porto (IPP) Porto Portugal

ISBN: (数字)9798331506209

ISBN: (纸本)9798331506216

Cybersecurity threats highlight the need for robust network intrusion detection systems to identify malicious behaviour. These systems rely heavily on large datasets to train machine learning models capable of detecting patterns and predicting threats. In the past two decades, researchers have produced a multitude of datasets, however, some widely utilised recent datasets generated with CICFlowMeter contain inaccuracies. These result in flow generation and feature extraction inconsistencies, leading to skewed results and reduced system effectiveness. Other tools in this context lack ease of use, customizable feature sets, and flow labelling options. In this work, we introduce HERA, a new open-source tool that generates flow files and labelled or unlabelled datasets with user-defined features. Validated and tested with the UNSW-NB15 dataset, HERA demonstrated accurate flow and label generation.

关键词： Data privacy Accuracy Network intrusion detection Telecommunication traffic Machine learning Predictive models Feature extraction Labeling Computer security

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A Novel Framework for Multiagent Knowledge-Based Federated Learning Systems 21st

A Novel Framework for Multiagent Knowledge-Based Federated L...

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21st International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2023

作者： Ribeiro, Bruno Gomes, Luis Barbarroxa, Rafael Vale, Zita GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9783031376153

Multiagent systems promote a decentralized and distributed approach that enable the division of complex problems into smaller parts. The use of multiagent systems also enables the representation of physical entities, such as persons, pursuing their own goals in an active and proactive society. Currently developments are promoting the idea of having machine learning models in agents to enable intelligent decisions in agents-side. However, machine learning, required assess to large datasets that cannot be available locally to individual agents, demanding the sharing of data or the use of public available datasets to training models for a given agent. To address this issue, this paper proposes the use of federated learning to enable the existence of a collaborative learning model that respects the data privacy, security, and ownership and can be in compliance with the European General Data Protection Regulation (EU GDPR). This paper proposes a novel framework called Python-based framework for agent-based communities powered by federated learning (PEAK FL) that will provide all the necessary tools to build powerful federated learning solutions based on agent communities. This framework provides the users the ability to implement and test hybrid solutions (multiagent-based federated learning systems) in a simple-to-use way, removing the unnecessary boilerplates. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Multi agent systems

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Energy Community Integration of a Smart Home Based on an Open Source Multiagent System 21st

Energy Community Integration of a Smart Home Based on an Ope...

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21st International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2023

作者： Ribeiro, Bruno Faia, Ricardo Gomes, Luis Vale, Zita GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9783031376153

Smart grid is a revolutionary concept that came to renew the way the power systems are thought. However, for these systems to be possible it is necessary and recommended that the consumers have the right technology integrated in their houses, in other words, have smart homes. This paper describes the demonstration of a smart home solution based on multiagent systems for the optimization of the house energy usage. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Multi agent systems

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Chatbot Architecture for a Footwear E-Commerce Scenario 20th

Chatbot Architecture for a Footwear E-Commerce Scenario

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20th International Symposium on Distributed computing and Artificial Intelligence, DCAI 2023

作者： Rodrigues, Vasco Santos, Joaquim Carrasco, Pedro Jesus, Isabel Barbosa, Ramiro Matos, Paulo Marreiros, Goreti GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto Porto4200-072 Portugal LASI - Intelligent Systems Associate Laboratory Guimarães4800-058 Portugal UC - University of Coimbra Coimbra Portugal

ISBN: (纸本)9783031383328

The amount of information accessible to businesses grows as more individuals get access to the internet. This information can be used by businesses to make corporate decisions that can highly affect them. E-commerce is the result of businesses starting to export their operations to the internet as a result of taking advantage of this reality. To help a footwear e-commerce platform keep up with the current demands of the market in terms of accessibility and customer service, a chatbot was created to help on this request. To build this chatbot, datasets were created leading to Intent Classification and Named-Entity Recognition pre-trained models, utilizing Bert-Large, getting fine-tuned with those datasets. These models achieved a F1-score of 0.90 and 0.88 respectively in their tasks. The Sentiment Analysis functionality of TextBlob was also utilized to help the chatbot comprehend user’s text polarity to reply appropriately. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

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