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Investigating the Impact of Semi-Supervised Methods with Data Augmentation on Offensive Language Detection in Romanian Language

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Procedia computer science 2024年 246卷 3447-3456页

作者： Elena-Beatrice Nicola Dumitru-Clementin Cercel Florin Pop Faculty of Automatic Control and Computers National University of Science and Technology POLITEHNICA Bucharest Romania National Institute for Research and Development in Informatics (ICI) Bucharest Romania Academy of Romanian Scientists Bucharest Romania

Offensive language detection is a crucial task in today’s digital landscape, where online platforms grapple with maintaining a respectful and inclusive environment. However, building robust offensive language detection models requires large amounts of labeled data, which can be expensive and time-consuming to obtain. Semi-supervised learning ofers a feasible solution by utilizing labeled and unlabeled data to create more accurate and robust models. In this paper, we explore a few different semi-supervised methods, as well as data augmentation techniques. Concretely, we implemented eight semi-supervised methods and ran experiments for them using only the available data in the RO-Offense dataset and applying five augmentation techniques before feeding the data to the models. Experimental results demonstrate that some of them benefit more from augmentations than others.

关键词： Semi-Supervised Learning Romanian Language Offensive Language Data Augmentation

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Comparative Study of Neural Networks Used in Halyomorpha Halys Detection*

Comparative Study of Neural Networks Used in Halyomorpha Hal...

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Mediterranean Conference on control and Automation (MED)

作者： Dan Popescu Loretta Ichim Mihai Dimoiu Raluca Trufelea Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

The paper’s purpose was to investigate some methods based on neural networks for the detection and classification of harmful insects for agriculture as the Halyomorpha Halys. The implementation of different object detection networks for image categorization was analyzed. Images from the Maryland Biodiversity database were used for neural network training and testing. Rotation, scaling, blurring, mirroring, and other techniques were employed for data augmentation. For the detection and classification of Halyomorpha Halys, some neural networks that include multiple smaller networks were implemented and investigated. The networks used are the following: YOLOv5s, SSD with different backbones such as MobileNet V1, MobileNet V2, and ResNet-50, Faster R-CNN with ResNet-50 backbone, and EfficientDet-D0. Moreover, neural networks were evaluated and compared based on performance metrics such as accuracy and time. Performances like accuracy between 0.49 – 0.86 and time between 36 ms – 55 ms were obtained. The best results were obtained for YOLOv5s, in terms of accuracy, and EfficientDet-D0, in terms of time.

关键词： Training Insects Neural networks Transfer learning Object detection Real-time systems Agriculture

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MPPT techniques application and comparison for photovoltaic panels 23

MPPT techniques application and comparison for photovoltaic ...

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23rd International Conference on control Systems and computer science Technologies, CSCS 2021

作者： Dobrea, Marius-Alexandru Arghira, Nicoleta Vasluianu, Mihaela Neculoiu, Giorgian Moldoveanu, Ana-Maria Cristiana University POLITEHNICA of Bucharest Faculty of Automatic Control and Computer Science Romania Technical University of Civil Engineering Faculty of Hidrotechnics Bucharest Romania

ISBN: (纸本)9781665439398

Photovoltaic (PV) panel modelling and control is very important in renewable energy systems. Due to it variability, PV panel generation power should be maximized for the given climate conditions. This paper considers three Maximum Power Point Tracking (MPPT) algorithms: Perturb Observe, Incremental Conductance and Fuzzy Logic. After a clear description for each algorithm, modelling, testing and validation is conducted on real experimental data for a 250W PV panel. Over one day period, a comparison between the 3 control MPPT algorithms show that Perturb Observe gives the best results, close to Incremental Conductance algorithm application. © 2021 IEEE.

关键词： Fuzzy logic

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Investigating the Impact of Semi-Supervised Methods with Data Augmentation on Offensive Language Detection in Romanian Language

arXiv

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arXiv 2024年

作者： Nicola, Elena-Beatrice Cercel, Dumitru-Clementin Pop, Florin Faculty of Automatic Control and Computers National University of Science and Technology POLITEHNICA Bucharest Romania Bucharest Romania Academy of Romanian Scientists Bucharest Romania

Offensive language detection is a crucial task in today’s digital landscape, where online platforms grapple with maintaining a respectful and inclusive environment. However, building robust offensive language detection models requires large amounts of labeled data, which can be expensive and time-consuming to obtain. Semi-supervised learning offers a feasible solution by utilizing labeled and unlabeled data to create more accurate and robust models. In this paper, we explore a few different semi-supervised methods, as well as data augmentation techniques. Concretely, we implemented eight semi-supervised methods and ran experiments for them using only the available data in the RO-Offense dataset and applying five augmentation techniques before feeding the data to the models. Experimental results demonstrate that some of them benefit more from augmentations than others. © 2024, CC BY-NC-SA.

关键词： Self-supervised learning

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Estimating Chlorophyll Content from Hyperspectral Data Using Gradient Features 23rd

Estimating Chlorophyll Content from Hyperspectral Data Usin...

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23rd International Conference on Computational science, ICCS 2023

作者： Ruszczak, Bogdan Wijata, Agata M. Nalepa, Jakub Faculty of Electrical Engineering Automatic Control and Informatics Department of Informatics Opole University of Technology Opole Poland Faculty of Biomedical Engineering Silesian University of Technology Zabrze Poland Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Gliwice Poland KP Labs Gliwice Poland

ISBN: (纸本)9783031360206

Non-invasive estimation of chlorophyll content in plants plays an important role in precision agriculture. This task may be tackled using hyperspectral imaging that acquires numerous narrow bands of the electromagnetic spectrum, which may reflect subtle features of the plant, and inherently offers spatial scalability. Such imagery is, however, high-dimensional, therefore it is challenging to transfer from the imaging device, store and investigate. We propose a machine learning pipeline for estimating chlorophyll content from hyperspectral data. It benefits from the Savitzky-Golay filtering to smooth the (potentially noisy) spectral curves, and from gradient-based features extracted from such a smoothed signal. The experiments revealed that our approach significantly outperforms the state of the art according to the widely-established estimation quality metrics obtained for four chlorophyll-related parameters. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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An e-Business Services Composition Framework 14

An e-Business Services Composition Framework

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14th International Conference on Communications, COMM 2022

作者： Pop, Eugen Gifu, Daniela University 'Politehnica' of Bucharest R&d Institute for Automation-IPA Sa Faculty of Automatic Control and Computers Automatics and Industrial Informatics Department Bucharest Romania Institute of Computer Science Romanian Academy Iasi Branch Faculty of Computer Science of Alexandru Ioan Cuza University of Iasi Iasi Romania

ISBN: (纸本)9781665494854

E-business offers to economic agents the opportunity to increase the efficiency of their activity, promote and offer their products and services on a large and diversified market. Often a single service, separately, does not meet all the needs of various categories and groups of customers. In such a situation, service composition can provide more technical, commercial, informational facilities than each separate component service can offer. There are many web-based frameworks used for e-business, but still with limitations. The paper presents a Services Composition Framework and a wise algorithm for e-business models, based on REST and SOAP web services. It is intended to be used for the development of e-business models, comprising stock market exchange, e-commerce, e-banking, etc. The customers can access the framework services, through Smartphones, on mobile and wireless communication channels. Within a Quality-of-Service performance analysis of the e-business Service Composition Framework, the response time and throughput for multiuser access simultaneous requests were evaluated. A stock market exchange service is considered, as an e-business service example, while bucharest Stock Exchange information is the digital content source for data transactions. © 2022 IEEE.

关键词： Web services

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Solutions for Digital Interaction of a Resilient Energy Community in a Service-oriented Framework 12

Solutions for Digital Interaction of a Resilient Energy Comm...

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12th International Conference and Exposition on Electrical and Power Engineering, EPE 2022

作者： Sanduleac, Mihai Ionescu, Constantin Mandis, Alexandru Gropa, Victor Efremov, Cristina Sanduleac, Vlad Department of Power Systems Faculty of Energy Engineering University Politehnica of Bucharest Bucharest Romania Dep. of Energy Generation and Use Faculty of Energy Engineering University Politehnica of Bucharest Bucharest Romania Faculty of Energetics and Electrical Engineering Technical University of Moldova Chisinau Moldova Department of Computer Science and Engineering Faculty of Automatic Control and Computers University Politehnica of Bucharest Romania

ISBN: (数字)9781665489942

ISBN: (纸本)9781665489942

Energy communities are emerging entities which need their own Information and Communication System. Resilience is a key metric of such communities, and it has to be implemented for both energy supply versus public network outages and for its information system versus cyber-attacks, acting as cyber-citadels which have to resist external malicious attacks while having also digital interactions with external entities. The paper presents solutions for a resilient energy community with appropriate implementations of digital interaction for data exchange, in order to acquire external energy service for specialized companies and to deliver also information and communication-related services for external users. Principles of a Contractual Data Protection Regulation are presented, as an adaptation of data protection tailored for automated energy services and based on secure data exchange. The principles are verified in a demonstration project which has also external entities with digital interaction. © 20XX IEEE.

关键词： Cybersecurity

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A deep learning architecture for audience interest prediction of news topic on social media 24

A deep learning architecture for audience interest predictio...

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Advances in Database Technology - 24th International Conference on Extending Database Technology, EDBT 2021

作者： Truică, Ciprian-Octavian Apostol, Elena-Simona Stefu, Teodor Karras, Panagiotis Faculty of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania Department Computer Science Aarhus University Aarhus Denmark

ISBN: (纸本)9783893180844

Personalized social media offer communication opportunities that mass media could not afford, yet also raise novel challenges. A prime challenge arising from this shift in digital communication is to detect topics and events of interest. In this paper, we propose and deploy a novel Deep Learning architecture that predicts if a news topic becomes viral by analyzing social media diffusion and audience interest in current news events. The proposed solution: (i) analyzes news articles, (ii) extracts associated topics and events, (iii) matches the topics and events to filter and extract developing topics, (iv) extracts current events from Twitter and matches them to the filtered news topics, and (v) predicts audience interest in news topics using Twitter likes and retweets. We employ several feature engineering techniques to improve prediction by integrating user metadata into the training set. In our experiments, we correlate two datasets collected over several months in the same time period. The first dataset contains news articles collected from different news venues, while the second one contains tweets regarding the news. The experimental results from our real-world deployment prove that the proposed system achieves high accuracy when integrating influencers metadata and the day of the week. Thus, proving that the news topics virality prediction is improved under the assumptions that spreaders and the day of the week play a huge role in information diffusion. © 2021 Copyright held by the owner/author(s).

关键词： Metadata

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DESIGN OF PID controlLER FOR NONLINEAR MAGNETIC LEVITATION SYSTEM USING FUZZY-TUNING APPROACH

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

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UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2022年第2期84卷 45-62页

作者： Ismail, Laith S. Lupu, Ciprian Alshareefi, Hamid Luu, Duc Lich Dept. of Automatic Control University POLITEHNICA of Bucharest Romania Computer Technology Engineering Department Al Turath University Collage Baghdad Iraq Faculty of Mechanical Dynamics Vinh University of Technology Education Nghe an Viet Nam

This paper presents a dynamic model of a magnetic levitation system (Maglev) and suggests a Fuzzy Tuning of a proportional—integral--derivative controller (PID) that uses a fuzzy approach system to determine the PID controller's settings. The controller allows a steel ball to be suspended in free fall in the chosen position in reference to the electromagnet bottom end. The electromagnet levitation system can be controlled with a traditional PID controller, however because of the highly nonlinear of this system, it is unpredictable in the case of load and air gap changes. The fuzzy rules are developed to fuzzy tune PID while considering the control response and behavior of the system to find a solution to this problem. This paper shows excellent stability, rising time, settling time overshoot, and robust response results. The results reveal that this fuzzy PID controller solution can stabilize the ball's location and has strong disturbance rejection. The real time platform is designed for educational laboratory and test all the proposed control systems. © 2022, Politechnica University of bucharest. All rights reserved.

关键词： controllers

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EMG Mapping Technique for Pinch Meter Robot Extension 23rd

EMG Mapping Technique for Pinch Meter Robot Extension

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Proceedings of the 23rd Polish Conference on Biocybernetics and Biomedical Engineering, PCBEE 2023

作者： Smolinski, Marcel Mikulski, Michal Śmieja, Jaroslaw EGZOTech Sp. z o.o. Gliwice44-100 Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

ISBN: (纸本)9783031384295

Rehabilitation of patients with impaired grip functions involves standard exercise that should be repeated in a predefined sequence. They are aimed to gradually improve patients’ ability to grip and operate objects used in daily life. Rehabilitation robots, employing surface EMG (sEMG) as a diagnostic and feedback signal may be used to support these exercises and trace the rehabilitation progress. However, to properly employ exercise regimen, information about what force should be used to hold and operate various objects is needed. This work is focused on finding the correlation between the value of sEMG signal and the force required to grip a particular object. Calibration plots obtained that way will reduce the need for additional equipment, such as specialized gloves, and at the same time provide information needed for better exercise protocols. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mapping

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