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10th International Conference Machine and Industrial Design in Mechanical engineering, KOD 2018

作者： Tropp, M. Brumerčík, F. Šteininger, J. Weis, P. Glowacz, A. Univerzity of Žilina Faculty of Mechanical Engineering Department of Design and Mechanical Elements Univerzitná 1 Žilina010 26 Slovakia AGHUniversity of Science and Technology Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics Al. A. Mickiewicza 30 Kraków30-059 Poland

The subject of the article is a simulation of heat affected components of a device for deep drawing by extreme conditions in vacuum by high temperatures required for forming of crystallization containers made from thin molybdenum sheets. The simulation is focused on the distribution of heat in particular components in relation with their shape. There are presented the design of working components and the boundary conditions of transient thermal simulations with the results. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Deep drawing

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IT'S ALL IN THE EMBEDDING! FAKE NEWS DETECTION USING DOCUMENT EMBEDDINGS

arXiv

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arXiv 2023年

作者： Truicǎ, Ciprian-Octavian Apostol, Elena-Simona Computer Science and Engineering Department Faculty of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania

With the current shift in the mass media landscape from journalistic rigor to social media, personalized social media is becoming the new norm. Although the digitalization progress of the media brings many advantages, it also increases the risk of spreading disinformation, misinformation, and malformation through the use of fake news. The emergence of this harmful phenomenon has managed to polarize society and manipulate public opinion on particular topics, e.g., elections, vaccinations, etc. Such information propagated on social media can distort public perceptions and generate social unrest while lacking the rigor of traditional journalism. Natural Language Processing and Machine Learning techniques are essential for developing efficient tools that can detect fake news. Models that use the context of textual data are essential for resolving the fake news detection problem, as they manage to encode linguistic features within the vector representation of words. In this paper, we propose a new approach that uses document embeddings to build multiple models that accurately label news articles as reliable or fake. We also present a benchmark on different architectures that detect fake news using binary or multi-labeled classification. We evaluated the models on five large news corpora using accuracy, precision, and recall. We obtained better results than more complex state-of-the-art Deep Neural Network models. We observe that the most important factor for obtaining high accuracy is the document encoding, not the classification model's complexity. © 2023, CC BY-NC-ND.

关键词： Embeddings

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The Development of an ERP Application within a computer Integrated Manufacturing Laboratory

The Development of an ERP Application within a Computer Inte...

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Chinese control Conference (CCC)

作者： Stefan Dumbrava Faculty of Automatic Control and Computer Engineering “Gh. Asachi” Technical University of Iasi Iasi Romania

Enterprise control applications are becoming more and more complex, exploiting distributed object technology in multi-tier architectures. For educational purposes, the development of a manufacturing control laboratory that may emphasize the new control techniques and the overall integration of the system activities with business processes is a complex and challenging task. In the paper, an educational enterprise application that integrates the ERP concept together with a flexible manufacturing system in a computer integrated laboratory is presented. It contains modularized, distributed subsystems in configurable and maintainable software, covering the business processes, from the customer order, to planned order dispatch. The software architecture contains the ERP components that are implemented using Enterprise Java Beans, deployed in a J2EE application server. It enables transactions with the business environment, shop-floor system and the database. The application is conceptually designed and analyzed using a visual model developed in unified modeling language.

关键词： Enterprise resource planning Application software computer integrated manufacturing Laboratories control systems Software maintenance computer architecture Manufacturing processes Flexible manufacturing systems computer aided manufacturing

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An optimization method based on evolutionary computation used for estimating the energy consumption for heating in a building

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and computer Science 2016年第3期78卷 265-276页

作者： Cǎruţaşiu, Mihail-Bogdan Stegaru, Silvia Cristina Ionescu, Constantin Sluşanschi, Emil Ioan Badea, Adrian Ţǎpuş, Nicolae University Politehnica of Bucharest Faculty of Power Engineering Romania Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Romania Faculty of Power Engineering University Politehnica of Bucharest Romania

Simplified mathematical models that can describe the real behavior of a building with relative small errors can provide useful information about the best operational methods of the HVAC (Heating, Ventilating and Air Conditioning) systems, energy demand for heating and cooling, etc. We developed a simplified mathematical model for computing the energy demand for heating and optimized it with a Genetic Algorithm, in order to minimize the error between the model and real data. The tested period (a month) showed that the optimization method is suitable for this type of applications and the relative error was 0.14 kWh.

关键词： Energy utilization

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Hierarchical Classification of Transversal Skills in Job Ads Based on Sentence Embeddings

arXiv

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arXiv 2024年

作者： Leon, Florin Gavrilescu, Marius Floria, Sabina-Adriana Minea, Alina-Adriana Faculty of Automatic Control and Computer Engineering Romania Faculty of Materials Science and Engineering "Gheorghe Asachi" Technical University of Iași Romania

This paper proposes a classification framework aimed at identifying correlations between job ad requirements and transversal skill sets, with a focus on predicting the necessary skills for individual job descriptions using a deep learning model. The approach involves data collection, preprocessing, and labeling using ESCO (European Skills, Competences, and Occupations) taxonomy. Hierarchical classification and multi-label strategies are used for skill identification, while augmentation techniques address data imbalance, enhancing model robustness. A comparison between results obtained with English-specific and multi-language sentence embedding models reveals close accuracy. The experimental case studies detail neural network configurations, hyperparameters, and cross-validation results, highlighting the efficacy of the hierarchical approach and the suitability of the multi-language model for the diverse European job market. Thus, a new approach is proposed for the hierarchical classification of transversal skills from job ads. © 2024, CC BY-NC-ND.

关键词： Embeddings

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A Distributed automatic Domain-Specific Multi-Word Term Recognition Architecture using Spark Ecosystem

A Distributed Automatic Domain-Specific Multi-Word Term Reco...

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International Symposium on Parallel and Distributed Computing

作者： Ciprian-Octavian Truică Neculai-Ovidiu Istrate Elena-Simona Apostol Computer Science and Engineering Department Faculty of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania

automatic Term Recognition is used to extract domain-specific terms that belong to a given domain. In order to be accurate, these corpus and language-dependent methods require large volumes of textual data that need to be processed to extract candidate terms that are afterward scored according to a given metric. To improve text preprocessing and candidate terms extraction and scoring, we propose a distributed Spark-based architecture to automatically extract domain-specific terms. The main contributions are as follows: (1) propose a novel distributed automatic domain-specific multi-word term recognition architecture built on top of the Spark ecosystem; (2) perform an in-depth analysis of our architecture in terms of accuracy and scalability; (3) design an easy-to-integrate Python implementation that enables the use of Big Data processing in fields such as Computational Linguistics and Natural Language Processing. We prove empirically the feasibility of our architecture by performing experiments on two real-world datasets.

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Genetic Multiobjective Optimisation with Elite Insertion for EEG Feature Selection

Genetic Multiobjective Optimisation with Elite Insertion for...

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IEEE International Conference on Intelligent computer Communication and Processing (ICCP)

作者： Lavinia Ferariu Corina Cîmpanu Faculty of Automatic Control and Computer Engineering Gheorghe Asachi Technical University of Iasi Iaşi Romania

Embedded Feature Selection (FS) ensures the selection of few, relevant features, by directly re-designing the classifier for subsets of features. Naturally, this problem is formulated as a multi-objective optimization (MOO) addressing to the accuracy of the classifier and the parsimony of the feature vector. In MOOs, common ranking techniques use dominance analysis for providing a partial sorting of the solutions. Unfortunately, dominance analysis can also promote solutions less useful for the application. In order to gradually guide the search towards a user-preferred area set around the middle of the best fronts, this paper proposes an adaptive ranking algorithm with insertion of elites (ARE), which could be integrated in any MOO genetic algorithm. ARE incorporates two new procedures proposed for labeling the preferred solutions and for inserting elites in the less populated areas, whenever a biased exploration is detected. The experimental investigations illustrate that GA with ARE offers better results than NSGAII, both for electroencephalogram (EEG) feature selection problem (which likely involves weakly conflicting objectives) and MOOs with strongly conflicting objectives.

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Monocular visual self-localization for humanoid soccer robots

Monocular visual self-localization for humanoid soccer robot...

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International Conference on Electronics, Communications and computers (CONIELECOMP)

作者： J.M. Ibarra Zannatha R. Cisneros Limón A.D. Gómez Sánchez E. Hernández Castillo L.E. Figueroa Medina F.J.K. Lara Leyva Departament of Automatic Control Cinvestav Engineering Faculty La Salle University Departament of Computer Systems Cinvestav

In this paper a visual self-localization method for a humanoid robot is presented. This one is based on monocular information. The goal of this method is to obtain the position (x; y) and orientation θ of the humanoid robot inside the field of play. The methods proposed include some digital image processing algorithms and geometric interpretation to perform a 3D monocular reconstruction, that allows to measure the relative position between the robot and some known objects (goals and beacons), and to use them to obtain the robot's absolute position, by means of a triangulation method. Finally, the results obtained in Webots and in the real platform are presented.

关键词： Image color analysis Feature extraction Image segmentation Three dimensional displays Robots Image edge detection Pixel

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Prototype of Turbine Propulsion System with controllable Thrust Vector for Long-Range Unmanned VTOL Aircraft 21st

Prototype of Turbine Propulsion System with Controllable Thr...

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21st Polish control Conference, PCC 2023

作者： Czyba, Roman Lemanowicz, Marcin Domin, Jaroslaw Grzybowski, Jacek Stępień, Izabela Ungier, Lukasz Rosiek, Radoslaw Bialas, Piotr Niemiec, Michal Department of Automatic Control and Robotics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology ul. Akademicka 16 Gliwice44-100 Poland Department of Chemical Engineering and Process Design Faculty of Chemistry Silesian University of Technology ul. Ks. M. Strzody 7 Gliwice44-100 Poland Department of Mechatronics Faculty of Electrical Engineering Silesian University of Technology ul. Akademicka 10a Gliwice44-100 Poland

ISBN: (纸本)9783031351723

The aim of the project was to build a prototype of a turbine drive with a controllable thrust vector for a long-range vertical take-off and landing (VTOL) aircraft. The construction of the prototype required the development of a vectoring system for the tail propulsion system and a dedicated VTOL aircraft stabilization and control system. The prototype of the turbine drive system was based on energy-efficient electric motors. Research also involved modeling the turbine propulsion aerodynamics with usage of computational fluid dynamics (CFD) analysis. As a result of the design stage, a prototype of the propulsion system was created, on which flight tests were carried out. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computational fluid dynamics

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Multiple-Layer Classifier with Label Correction for Semantic Segmentation

Multiple-Layer Classifier with Label Correction for Semantic...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Lavinia Ferariu Simona Caraiman Faculty of Automatic Control and Computer Engineering Gheorghe Asachi Technical University of Iasi Iaşi Romania

Semantic segmentation (SS) provides the meaning of visual scenes, thus being a key stage for navigation and environment's perception. This paper presents a solution for SS compatible with assistive wearable systems equipped with color and depth cameras. In order to ensure a compact and robust description of input color-based images, both 2D and 3D features are extracted at superpixel level, after correcting the displacements of the camera by means of adequate rectifications. Random Forests (RF) are called for solving the classification problem. In this context, this paper introduces a multilayer RFbased classifier, including a separate layer for label correction. Additional two other correcting methods are proposed for the first layers of the classifier, i.e. a fast method investigating the majority label around each object, and several customizations of the graph cut algorithm using convenient cue weights. The performance of the suggested approach is experimentally verified on diverse urban street scenes.

关键词： Three-dimensional displays Feature extraction Cameras Image segmentation Image color analysis Radio frequency Two dimensional displays

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