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International Conference on Communication, Computing and Digital Systems (C-CODE)

作者： Zawar Khan Muhammad Aamir Electrical & Computer Engineering Department Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology Haripur Pakistan

In this paper, the consensus model predictive control (MPC)-based hierarchical control scheme is presented for the primary and secondary layers of an islanded AC microgrid (MG). The secondary control is designed on the tracker consensus method, in this way a distributed controller in collaboration with the finite time observer will set the referenced values of voltage magnitude and frequency by significantly speeding up the method of synchronous convergence. Furthermore, the primary control has been implemented for each DG separately and comprises Finite Control Set-Model Predictive control (FCS-MPC), and droops control. FCS-MPC regulates PCC reference voltages for each DG unit. Droop Control regulates power exchange within and among DG units. In the proposed hierarchical control approach, information sharing is accomplished by a neighbouring node creating a sparse communication network while fully eliminating the requirement for a centralized controller. The controller effectiveness have been validated against unbalanced load, transients, and load plug-and-play capabilities. The simulation result shows that MG operates effectively using FCS-MPC for parallel inverters of DG units, and the consensus algorithm based distributed secondary controller in MG effectively delivers the anticipated power, voltage, and frequency.

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Explaining BERT model decisions for near-duplicate news article detection based on named entity recognition

Explaining BERT model decisions for near-duplicate news arti...

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International Conference on Semantic Computing

作者： Anne Stockem Novo Fatih Gedikli Institute of Computer Science University of Applied Sciences Ruhr West Mülheim an der Ruhr Germany

While it is a straight-forward task to detect lexically identical documents, it is challenging to do this on documents that are semantically similar. This work deals with the detection of near-duplicate news articles on various websites. The detection of documents of related content is especially interesting for search engines and recommender systems. Search engines aim at eliminating duplicates to prevent the user from seeing the same document in different versions. Recommender systems filter out items that are too similar to those the user already knows to tackle the problem of overspecialization. A near-duplicate is in some cases a mere paraphrasing of a previous article, in other cases it contains corrections or added content as a follow-up article. In this work, we investigate, among other things, the extent to which named entities such as people, places, and organisations that appear in the article text can be used to detect near-duplicates. Evaluating a fine-tuned BERT model on common named entities in an article pair, performance measures greater than 97 % are achieved. The SHAP library is then used to get insight into the model decisions and feature importance, which is the individual words in a text document. Overall, the results show that named entities are very suitable for the detection of near-duplicates. Furthermore, the explanations are in agreement with an intuitive human interpretation.

关键词： Deep learning Measurement Bit error rate Semantics Search engines Data models Libraries

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Supporting the Requirements-Based Selection of Suitable Communication Protocols in Smart Grids

Supporting the Requirements-Based Selection of Suitable Comm...

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2022 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2022

作者： Hanna, Sebastian Rohjans, Sebastian Heeren, Philipp Rolink, Johannes Institute for Information Technology Division of Energy Offis Oldenburg Germany Jade University of Applied Sciences Civil Engineering Geoinformation and Health Technology Oldenburg Germany University of Applied Sciences Emden/Leer Electrical Engineering and Computer Science Emden Germany

ISBN: (数字)9781665480321

ISBN: (纸本)9781665480321

The implementation of the smart grid and the related use cases requires the interaction of a wide variety of systems from many manufacturers. The selection of suitable communication protocols is a key factor in achieving the necessary interoperability and avoiding vendor lock-ins. Considering the large number of possible protocols, this selection process is becoming increasingly difficult and time-consuming. To simplify and accelerate this process, the use of a morphological box is presented. The partial aspects defined in the morphological box are chosen in such a way that they can describe both the requirements of a use case and the possibilities of the protocol under assessment. Applying the box eventually results in reusable profiles that allow the comparison of use cases and protocols in a quick and simple way. The utilization is demonstrated by evaluating the MQTT protocol for the realization of a given use case. © 2022 IEEE.

关键词： Smart power grids

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Fewer Faces Displayed Simultaneously, Less Videoconference Fatigue in Distance Learning? An Experimental Study 43

Fewer Faces Displayed Simultaneously, Less Videoconference F...

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43rd International Conference on Information Systems: Digitization for the Next Generation, ICIS 2022

作者： Li, Jiaqi Lamers, Maarten H. Riedl, René Leiden Institute of Advanced Computer Science Leiden University Leiden Netherlands University of Applied Sciences Upper Austria Johannes Kepler University Linz Steyr Linz Austria

ISBN: (纸本)9781713893615

In the last two years, there has been a massive use of videoconferencing tools for distance learning all over the world. However, a feeling of fatigue has been found among students. Researchers have proposed multiple problems in the online interaction with human faces that may contribute to videoconference fatigue (VCF). To contribute to this upcoming new research domain, this study investigates whether VCF can be reduced if we change the unnatural interaction with multiple enlarged faces on videoconferencing tools. We compare Zoom's "speaker view" with "gallery view", and based on theoretical insights from the information processing and brain research domains, we argue that Zoom "gallery view" leads to higher fatigue and stress levels than "speaker view". Moreover, we investigate whether the face manipulation ("gallery view" vs. "speaker view") affects learning outcome and learning satisfaction, as well as the role of fatigue and stress as mediators in this relationship. © 2022 International Conference on Information Systems, ICIS 2022: "Digitization for the Next Generation". All Rights Reserved.

关键词： COVID-19

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Real-Time Human Fall Detection using a Lightweight Pose Estimation Technique

arXiv

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arXiv 2024年

作者： Alam, Ekram Sufian, Abu Dutta, Paramartha Leo, Marco Department of Computer Science Gour Mahavidyalaya West Bengal India Department of Computer Science University of Gour Banga India Department of Computer and System Sciences Visva-Bharati University India National Research Council of Italy Institute of Applied Sciences and Intelligent Systems Lecce73100 Italy

The elderly population is increasing rapidly around the world. There are no enough caretakers for them. Use of AI-based in-home medical care systems is gaining momentum due to this. Human fall detection is one of the most important tasks of medical care system for the aged people. Human fall is a common problem among elderly people. Detection of a fall and providing medical help as early as possible is very important to reduce any further complexity. The chances of death and other medical complications can be reduced by detecting and providing medical help as early as possible after the fall. There are many state-of-the-art fall detection techniques available these days, but the majority of them need very high computing power. In this paper, we proposed a lightweight and fast human fall detection system using pose estimation. We used 'Movenet' for human joins key-points extraction. Our proposed method can work in real-time on any low-computing device with any basic camera. All computation can be processed locally, so there is no problem of privacy of the subject. We used two datasets 'GMDCSA' and 'URFD' for the experiment. We got the sensitivity value of 0.9375 and 0.9167 for the dataset 'GMDCSA' and 'URFD' respectively. The source code and the dataset GMDCSA of our work are available online to access. © 2024, CC BY-NC-ND.

关键词： Fall detection

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Detrended fluctuation analysis of sentiment patterns in literary texts

Detrended fluctuation analysis of sentiment patterns in lite...

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37th ECMS International Conference on Modelling and Simulation, ECMS 2023

作者： Gaża, Lukasz Drożdż, Stanislaw Oświęcimka, Pawel Stanuszek, Marek Faculty of Computer Science and Telecommunications Cracow University of Technology Kraków31-155 Poland Institute of Nuclear Physics Polish Academy of Sciences Kraków31-342 Poland Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Kraków30-348 Poland

ISBN: (纸本)9783937436807

Temporal correlations of the sentiment content in consecutive sentences are studied based on a large corpus of the world-famous literary texts in four major European languages (English, French, German, and Spanish). For quantifying the related characteristics in terms of the Hurst exponents the Detrended Fluctuation Analysis (DFA) is employed. The results obtained provide a clear indication for the existence of persistent correlations as revealed by the Hurst exponents significantly larger than 1/2 in all the four languages studied. An interesting result that requires a deeper study is the identified fact that in many texts the DFA indicates two different regimes of scaling and thus two different Hurst exponents. In those cases - quite universally - the cross-over occurs at the scale corresponding to about 200 sentences and the Hurst exponents at the scales above this value are even larger which indicates the presence of stronger long-range temporal correlations than those at the shorter scales. © ECMS Enrico Vicario, Romeo Bandinelli, Virginia Fani, Michele Mastroianni (Editors) 2023.

关键词： Sentiment analysis

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Fuzzy Querying in the Cloud-based Environment for Data Stream-driven Predictive Maintenance in AGV-enabled Smart Factories

Fuzzy Querying in the Cloud-based Environment for Data Strea...

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IEEE International Conference on Big Data

作者： Bożena Małysiak-Mrozek Dominik Romanów Piotr Grzesik Paweł Benecki Alexandre Niyomugaba Theodore Habimana Daniel Kostrzewa Krzysztof Tokarz Che-Lun Hung Dariusz Mrozek Department of Distributed Systems and Informatics Devices Silesian University of Technology Gliwice Poland Department of Applied Informatics Silesian University of Technology Gliwice Poland Department of Computer Science INES Ruhengeri - Institute of Applied Sciences Rwanda Department of Graphics Computer Vision and Digital Systems Silesian University of Technology Gliwice Poland Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei Taiwan

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

Fuzzy data processing enables data enrichment and increases data interpretation in industrial environments. In the cloud-based IoT data ingestion pipelines, fuzzy data processing can be implemented in several locations, closer to the IoT events gateways, stream processors, or the persistence layer before the data is visualized. Since Automated Guided Vehicles (AGV)-enabled manufacturing can produce vast amounts of data, the decision on the placement of the fuzzy data processing can be important for secondary processes performed on the enriched data, like the predictive maintenance inferencing. In this paper, we analyze two locations of fuzzy data processing in the cloud-based environment built for monitoring AGVs in smart factories - by formulating fuzzy queries against data streams on stream processing units and data at rest in a database. The querying scenarios cover fuzzy filtering with simple and complex criteria, fuzzy filtering through assignment to a linguistic variable, and joining data streams by representing joining attributes as fuzzy numbers. The experimental results show that querying the data stream can be more efficient and profitable in the scalable environment of many AGVs. However, the enrichment provided for the data at rest is also beneficial when gathering data for building future predictive maintenance models.

关键词： Remotely guided vehicles Program processors Filtering Pipelines Predictive models Logic gates Data processing Monitoring Predictive maintenance Smart manufacturing

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Mesh-based Object Tracking for Dynamic Semantic 3D Scene Graphs via Ray Tracing

arXiv

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arXiv 2024年

作者： Niecksch, Lennart Mock, Alexander Igelbrink, Felix Wiemann, Thomas Hertzberg, Joachim German Research Centre for Artificial Intelligence Plan-Based Robot Control Osnabrück Germany Osnabrück University Institute of Computer Science Knowledge-Based Systems Osnabrück Germany Fulda University of Applied Sciences Department of Applied Computer Science Robotics in Computer Science Fulda Germany

In this paper, we present a novel method for 3D geometric scene graph generation using range sensors and RGB cameras. We initially detect instance-wise keypoints with a YOLOv8s model to compute 6D pose estimates of known objects by solving PnP. We use a ray tracing approach to track a geometric scene graph consisting of mesh models of object instances. In contrast to classical point-to-point matching, this leads to more robust results, especially under occlusions between objects instances. We show that using this hybrid strategy leads to robust self-localization, pre-segmentation of the range sensor data and accurate pose tracking of objects using the same environmental representation. All detected objects are integrated into a semantic scene graph. This scene graph then serves as a front end to a semantic mapping framework to allow spatial reasoning. Copyright © 2024, The Authors. All rights reserved.

关键词： Mesh generation

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Analysing Student Depression through Cyber-Activity Patterns Using Heterogeneous Graph Attention Networks 1

Analysing Student Depression through Cyber-Activity Patterns...

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1st International Conference on Software, Systems and Information Technology, SSITCON 2024

作者： Shukla, Tushar Dhar Vanyan, Diana Rizvi, Qaim Mehdi George, Geogen Bhosale, Aryaraj Dattatraya Bhoopathy, V. University Institute of Physical Education & Sports Chandigarh University Department of Physical Education Mohali India Kuban State University Krasnodar Russia Kolkata India University of Technology and Applied Sciences College of Computing and Information Sciences Middle East Ibri Oman Indian Institute of Information Technology Pune India Sree Rama Engineering College Department of Computer Science and Engineering Tirupathi India

ISBN: (纸本)9798350352931

This study focusses on the crucial matter of identifying student sadness by analysing patterns of cyberactivity. The technology utilizes Heterogeneous Graph Attention Networks (HGATs) to represent and examine intricate connections within the data. The dataset used for training and testing the model was obtained from Kaggle. The model achieved an accuracy of 9 6. 8 %, a precision of 9 5. 4 %, a recall of 94.7 %, and an AUC-ROC of 98.3 %. The findings of this study demonstrate a substantial improvement over current models, indicating the high efficacy of HGATs in accurately capturing complex patterns in cyber-activity data. The results indicate that this method can function as a potent instrument for identifying depression at an early stage, with wide-ranging implications for monitoring the mental health of students and implementing intervention techniques. © 2024 IEEE.

关键词： Graph neural networks

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"I Show You How I Solved It!": Empowering Novice University Students to Learn Programming and Mathematics Through Self-produced Videos to Potentially Teach to Their Peers 4th

"I Show You How I Solved It!": Empowering Novice University ...

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4th EAI International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2022

作者： Inglese, Terry Fässler, Lukas E. Christen, Patrik Institute for Information Systems FHNW University of Applied Sciences and Arts Northwestern Switzerland Basel4002 Switzerland Department of Computer Science ETH Zurich Zurich8092 Switzerland Institute for Information Systems FHNW University of Applied Sciences and Arts Northwestern Switzerland Olten4600 Switzerland

ISBN: (纸本)9783031181221

A relevant concern of Java programming and mathematics instructors is that first-year college students usually have difficulties in grasping the abstract concepts of these two disciplines. Consequently, a meaningful part of students may fail to pass their core exams in BIT, Business Information Technology. To overcome this issue, two maths and programming instructors and a researcher in psychology of education, implemented the so-called exploratory video-based instructional intervention, through which BIT students were asked to explain specific Java programming concepts and to describe how to solve three maths exercises using self-produced videos. From a diagnostic perspective, the instructors were able: a) to recognise the correctness of the syntactic knowledge, the conceptual knowledge and the strategic knowledge of Java programming and b) to distinguish whether students were correctly applying the foundations of mathematics, which are essential skills for becoming a good programmer. The results of this experimental study showed that first-year students appreciated the production of these self-explaining videos, resulting in mastering complex abstract concepts in mathematics and in programming. © 2022, ICST institute for computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Students

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