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检索条件"任意字段=23rd International Conference on Control Systems and Computer Science Technologies, CSCS 2021"

共 285 条记录，以下是151-160 订阅

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Using Open Source technologies and Generalizable Procedures in Conversational and Affective Intelligent Tutoring systems 23rd

Using Open Source Technologies and Generalizable Procedures ...

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23rd international conference on Artificial Intelligence in Education (AIED)

作者： Albornoz-De Luise, Romina Soledad Arevalillo-Herraez, Miguel Arnau, David Univ Valencia Sch Engn Valencia Spain Dept Didact Math Valencia Spain

ISBN: (纸本)9783031116476;9783031116469

In the last years, the educational field has been influenced by technological advances. The digital transformation in educational environments allows the incorporation of virtual teaching-learning environments, which allow or facilitate learning opportunities for students, showing, for example, where they make mistakes and providing personalized help whenever they require it. In addition, these systems provide permanent access availability whenever it is possible to access the Internet. Traditionally, simultaneously many students learn word problem-solving skills in the classroom through instruction from only one educational professional. The Intelligent Tutoring System (ITS) Hypergraph Based Problem Solver (HBPS) is capable of tutoring the whole process of solving arithmetic-algebraic word problems, in a personalized way and without imposing any restrictions on the resolution path. Nevertheless, the student-system interaction is performed through a traditional interface by selecting items from a drop-down menu and clicking on buttons. Since dialogue is the fundamental communication mechanism for human-human, we propose use a framework to improve the interaction of the HBPS using a conversational user interface that allows performing the same actions more easily using natural language as the main means of interaction. My thesis research focuses on two main topics. The first one is related to the incorporation of a conversational agent using an open source machine learning framework that is fully configurable. The second one in concerned with testing and modifying different neural architectures to improve performance in intent classification and entity extraction, in such a way that it can be exported to other mathematical domains.

关键词： Intelligent tutoring systems (ITS) Interactive learning environments (ILE) Conversational agents Natural language processing (NLP) Affective support Algebraic word problems

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Database-Conscious End-to-End Testing for Reactive systems using Containerization 23

Database-Conscious End-to-End Testing for Reactive Systems u...

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23rd international conference on Enterprise Information systems, ICEIS 2021

作者： Wood, Denton Černý, Tomáš Department of Computer Science Baylor University WacoTX United States

ISBN: (纸本)9789897585098

Reactive systems are a relatively new paradigm in computer science architecture with important implications for computer science. While much attention has been paid to effectively running end-to-end (E2E) tests on these architectures, little work has considered the implications of tests which modify the database. We propose a framework to group and orchestrate E2E tests based on data qualities across a series of parallel containerized application instances. The framework is designed to run completely independent tests in parallel while being mindful of system costs. We present a conceptual version of the framework and discuss future directions with this work. Copyright © 2021 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Database systems

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RISC-V Processor technologies for Aerospace Applications in the ISOLDE Project 23rd

RISC-V Processor Technologies for Aerospace Applications in ...

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23rd international conference on Embedded computer systems: Architectures, Modeling, and Simulation, SAMOS 2023

作者： Fornaciari, William Reghenzani, Federico Agosta, Giovanni Zoni, Davide Galimberti, Andrea Conti, Francesco Tortorella, Yvan Parisi, Emanuele Barchi, Francesco Bartolini, Andrea Acquaviva, Andrea Gregori, Daniele Cognetta, Salvatore Ciancarelli, Carlo Leboffe, Antonio Serri, Paolo Burrello, Alessio Pagliari, Daniele Jahier Urgese, Gianvito Martina, Maurizio Masera, Guido Di Carlo, Rosario Sciarappa, Antonio Politecnico di Milano Milan Italy University of Bologna Bologna Italy E4 Computer Engineering SpA Scandiano Italy Thales Alenia Space Italia S.p.A Turin Italy Politecnico di Torino Torino Italy Leonardo SpA Rome Italy

ISBN: (纸本)9783031460760

Modern space applications impose significant challenges to the design of hardware and software platforms. Beyond traditional applications such as avionics, Attitude Orbit control, and signal/telemetry processing, new developments increasingly leverage Machine Learning models to enhance the autonomy of spacecraft. Such AI-based functional-ities promise significant advantages, but require computing power beyond what can be provided by current on-board platforms. At the same time, the challenge of technological sovereignty requires a move towards open hardware and software. To achieve these objectives, within the KDT ISOLDE project started in 2023, we propose the development of a new family of processors for AI-based applications to be deployed on board of satellites. In this paper, we showcase some examples of space applications with their requirements, and highlight the possible solutions as well as the corresponding work that will be carried out in ISOLDE, and the expected results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Space applications

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A Survey of Semantic Web Based Recommender systems for E-Learning 23rd

A Survey of Semantic Web Based Recommender Systems for E-Lea...

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23rd international conference on Computational science and its Applications (ICCSA)

作者： Aktas, Cevat Ciloglugil, Birol Ege Univ Inst Nat Sci Dept Comp Engn TR-35100 Izmir Turkiye Ege Univ Dept Comp Engn TR-35100 Izmir Turkiye

ISBN: (纸本)9783031371042;9783031371059

Recommender systems have been widely used in various domains such as e-commerce, e-learning and the entertainment sector especially for movie and music recommendation. E-learning has gained more attention recently, as the Covid-19 pandemic forced a mandatory shift from face-to-face education to online education. In this regard, taking into consideration the individual differences of learners such as learning styles, prior knowledge level, and motivation level play a vital role in acceptance and usage levels of e-learning systems by the learners and academic success levels of students using these e-learning systems. Semantic web technologies enable modeling these individual differences with ontologies and provide a valuable foundation for knowledge based recommender systems. Various learning resource or learning object ontologies that model learning materials and learner model ontologies that model learner profiles have been developed and used successfully in different educational recommender systems. These ontologies and interaction data of learners with e-learning systems provide valuable data for recommender systems to operate on. Collaborative filtering and content based filtering approaches have been used to analyze these data and implement educational recommender systems. Therefore, in this paper, we provide a review of semantic web based recommender systems conducted at the e-learning domain. We surveyed different aspects of educational recommender systems such as the data sources used for recommendations and the approaches utilized for implementation. Finally, we present the implications, limitations and future work directions in the field of educational recommender systems.

关键词： E-Learning Recommender systems Semantic Web Ontology

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How University Students in "Informatics and computer sciences" would like to Use Video Games for Learning 22

How University Students in "Informatics and Computer Science...

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23rd international conference on computer systems and technologies, CompSysTech 2022

作者： Antonova, Albena Bontchev, Boyan Dankov, Yavor Department of Information Technologies Faculty of Mathematics and Informatics Sofia University St. Kliment Ohridski Sofia Bulgaria

ISBN: (纸本)9781450396448

The game-based learning and serious games are researched mainly, especially in school education and lifelong learning. At the same time, in university settings, serious games and simulations are reserved for specific domains such as medicine, business, and engineering fields. Do University students from the Informatics and computer sciences Bachelor's Programs play games, how do they perceive game-based learning, and do they play video games for educational purposes? The present research investigates the IT students' attitudes and perceptions of using video games for learning. The empirical study is based on the responses from 122 students from the Faculty of Mathematics and Informatics of Sofia University, Bulgaria. It is conducted in November 2021 and March 2022. A detailed questionnaire developed within the project APOGEE examines video game personalization and adaptation opportunities. On one side, it investigates the students' dominating learning style (VARK) and playing style. On the other side, it surveys students' preferences for using video games for learning and their attitudes about video game personalization. The discussion part reflects on the recommendations and key findings, proposing a conceptual model for smart services for lecturers and students, supporting learning personalization and game-based adaptation in University settings. © 2022 ACM.

关键词： Serious games

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Human Research in Technology Design 9th

Human Research in Technology Design

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9th international conference on Culture and Computing (C&C) part of the 23rd international conference on Human-computer Interaction (HCI)

作者： Saariluoma, Pertti Jyvaskyla Univ Jyvaskyla 40014 Finland

ISBN: (纸本)9783030774301;9783030774318

Modern technology design processes in intelligent societies are different from the classic electromechanical technology design processes. Future technology design must be based as much on human research as on natural scientific thinking. Today one can find technologies such as social media applications which are created with minimal technical effort. Thus, understanding the human dimension of technologies is becoming much more important today than in the time of electromechanical technologies. The change in focus motivates to pay attention to the foundational differences between natural science and human research in technology design. The differences between the two traditions have been discussed over the last century, but today the differences between human research and natural science get new forms in designing intelligent technologies.

关键词： Designing Human research Natural science

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Efficient Dynamic Routing in Elastic Optical Networks Based on Traffic Prediction and Bandwidth Reservation

Efficient Dynamic Routing in Elastic Optical Networks Based ...

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international conference on Transparent Optical Networks

作者： Róża Goścień Department of Systems and Computer Network Faculty of Information and Communication Technologies Wrocław University of Science and Technology Wroclaw Poland

In this paper, we study the problem of efficient dynamic routing in elastic optical networks. We propose a novel resource allocation strategy that benefits from the bandwidth reservation in advance based on the analysis of the traffic prediction. We also propose a mechanism for the strategy's partial implementation to provide its high flexibility and the possibility to control both the efficiency and processing time. Next, we perform numerical experiments on representative European network topology. Their aim is the selection of the strategy’s beneficial configuration as well as its performance evaluation. The results prove its high efficiency – the approach reduces the bandwidth blocking probability up to 0.85%, corresponding to 16.925 Tbps of more served traffic (compared to the allocation without traffic-aware bandwidth reservation).

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Prediction based Auto-Pilot Interface for Drone to Object Chasing using Historical TSPI Data

Prediction based Auto-Pilot Interface for Drone to Object Ch...

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international conference on control, Automation and systems ( ICCAS)

作者： Shinhyoung Jang Byeonghwi Park Juheon Jeong Jack Mahedy Nebey Gebreslassie Minji Lee Eric T. Matson Department of Computer Science and Engineering Chungnam National University Daejeon Republic of Korea Daejeon Korea Department of Computer and Information Technology Purdue University West Lafayette IN USA Department of Technology Purdue University West Lafayette IN USA

Replacing military aircraft with Unmanned Aerial Vehicles (UAV) offers advantages such as reducing costs and risks associated with conventional military aircraft. To defend against enemy UAV attacks, anti-drone systems are used. While most technologies focus on drone detection, this paper proposes a process of tracking targets using arbitrary UAV to enhance camera data quality or directly engage and neutralize targets. The system comprises drone detection, movement prediction, and chasing. Devices such as radar are used to detect drones, and they provide Time-Space-Position Information (TSPI) using suitable data formats. Using Machine Learning (ML) techniques make it feasible to predict an object's future location, represented with equations. Utilizing trained machine learning models, the Auto-pilot Application Programming Interface (API) of the drone is employed to track based on the predicted results. Through experiments, the feasibility of predicting an object's future location using various ML techniques has been confirmed. Furthermore, verification has been conducted to establish the attainability of implementing the Auto-pilot API through the utilization of DJI's API.

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Application of Machine Learning Methods for Cross-Matching Astronomical Catalogues 23rd

Application of Machine Learning Methods for Cross-Matching A...

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23rd international conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2021

作者： Kulishova, Aleksandra Briukhov, Dmitry Lomonosov Moscow State University Moscow Russia Federal Research Center "Computer Science and Control" of Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9783031122842

The paper presents an approach for the application of machine learning methods for cross-matching astronomical catalogues. Related works on the cross-matching are analyzed and machine learning methods applied are briefly discussed. The approach is applied for cross-matching of three catalogues: Gaia, SDSS and ALLWISE. Experimental results of application of several machine learning methods for cross-matching these catalogues are presented. Recommendations for the application of the approach in astronomical information systems are proposed. © 2022, Springer Nature Switzerland AG.

关键词： Machine learning

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Multi-object Multi-sensor Tracking Simulation Using Poisson Multi-Bernoulli Mixture Filter 23

Multi-object Multi-sensor Tracking Simulation Using Poisson ...

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23rd international conference on Digital Signal Processing and its Applications, DSPA 2021

作者： Thanh, Le Ba Alexandrovich, Pogibelsky Dmitry Ruben, Paliyan Moscow Institute of Physics and Technology Department of Microprocessor Technologies in Intelligent Control Systems Dolgoprudniy Russia

ISBN: (纸本)9781728195513

Multi-object tracking and multi-sensor fusion algorithms are used in many areas of science and technology. For example, in an advanced field such as autonomous vehicles, multi-object tracking and multi-sensor fusion are indispensable technologies. The purpose of these technologies is to processing noisy measurements from different sensors to determine the number and state of objects with high accuracy. Some of the algorithms frequently used in multi-object tracking applications are Global Nearest Neighbor Filter (GNN), Joint Probabilistic Data Association Filter (JPDA), Multiple Hypothesis Tracking (MHT), Probability Hypothesis Density Filter (PHD), and other algorithms. These algorithms are very effective for estimating the state of objects and can combine measurements from multiple sensors to improve estimation accuracy [1,2]. But an even more powerful tool for multi-object tracking is the Poisson multi-Bernoulli mixture filter (PMBM Filter) [1]. In this paper, we will introduce the PMBM filter and simulate an algorithm using a PMBM filter that combines measurements from multiple automotive sensors to estimates object's states. At the same time, we also compare the performance of the aforementioned algorithms in some specific simulation scenarios. © 2021 IEEE.

关键词： Mixtures

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