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engineering Pedagogy in Chilean Context: Some Results from the PEDING-Project 2nd

Engineering Pedagogy in Chilean Context: Some Results from t...

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22nd international conference on Interactive Collaborative learning (ICL) / 48th IGIP international conference on engineering Pedagogy - Impact of the 4th Industrial Revolution on engineering Education

作者： Gormaz-Lobos, Diego Galarce-Miranda, Claudia Hortsch, Hanno Kersten, Steffen Univ Talca Talca Chile Univ Talca Chile CIEI IGIP Zentrum Talca Chile Tech Univ Dresden IGIP Int Soc Engn Pedag Dresden Germany Tech Univ Dresden Dresden Germany

ISBN: (纸本)9783030402716;9783030402709

This paper presents the results of the research project "Pedagogy in engineering in Chilean Universities" (PEDING-Project). The aim of the PEDING-Project was the development and testing of training modules for teaching qualifications of teaching staff in academic engineering Education based in the IGIP Curriculum offered for the TU Dresden. The project was led by Prof. Hortsch (Chair of Didactics of Vocational learning of the TU Dresden and President of IGIP) and funded by the German Academic Exchange Service (DAAD). The PEDING-Project is a binational university effort - Germany and Chile and consisted of a group of academics from the Chair of Didactics of Vocational Education, Faculty of Education of the TU Dresden and engineering Faculties of three Chilean Universities: Universidad Autonoma de Chile (UA), Universidad de Magallanes (UMAG) and Universidad de Talca (UTALCA).

关键词： engineering Pedagogy engineering Pedagogy in Chilean Universities PEDING research project

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Trading Cryptocurrency with Deep Deterministic Policy Gradients 21st

Trading Cryptocurrency with Deep Deterministic Policy Gradie...

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21st international conference on intelligent data engineering and automated learning

作者： Tummon, Evan Raja, Muhammad Adil Ryan, Conor Avaya Galway Ireland Univ Limerick Dept Comp Sci & Informat Syst Limerick Ireland

ISBN: (纸本)9783030623616;9783030623623

The volatility incorporated in cryptocurrency prices makes it difficult to earn a profit through day trading. Usually, the best strategy is to buy a cryptocurrency and hold it until the price rises over a long period. This project aims to automate short term trading using Reinforcement learning (RL), predominantly using the Deep Deterministic Policy Gradient (DDPG) algorithm. The algorithm integrates with the BitMEX cryptocurrency exchange and uses Technical Indicators (TIs) to create an abundance of features. Training on these different features and using diverse environments proved to have mixed results, many of them being exceptionally interesting. The most peculiar model shows that it is possible to create a strategy that can beat a buy and hold strategy relatively effortlessly in terms of profit made.

关键词： Reinforcement learning Cryptocurrency Trading

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HACK: A Hierarchical Model for Fake News Detection 22nd

HACK: A Hierarchical Model for Fake News Detection

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22nd international conference on Web Information Systems engineering (WISE)

作者： Li, Yanqi Ji, Ke Ma, Kun Chen, Zhenxiang wu, Jun Li, Yidong Xu, Guandong Univ Jinan Sch Informat Sci & Engn Jinan 250022 Peoples R China Univ Jinan Shandong Prov Key Lab Network Based Intelligent C Jinan 250022 Peoples R China Beijing Jiaotong Univ Sch Comp & Informat Technol Beijing 100044 Peoples R China Univ Technol Sydney Data Sci & Machine Intelligence Lab Adv Analyt Inst Ultimo Australia

ISBN: (纸本)9783030908881;9783030908874

Online social media sites have become the most powerful platform to share news nowadays. However, all kinds of unauthenticated news that are released online without strict limits may lead to the spread of fake news, which has become a synonym for social and political threats. The existing solutions to the fake news issue are mostly trying to construct a social graph network by integrating the news content and social context of the news, which may be restricted when lacking social context information. In this paper, we propose a model for text only, regardless of contextual information, and named it HACK (HierArchical deteCtion for faKe news), which can construct high-level combined features of spatial capsule vectors from low-level character features and phrase features by fusing a pre-trained language model and convolution network. The experimental results on real-life data show that the classification accuracy is significantly improved by our method comparing with the state-of-the-art methods.

关键词： Fake news Hierarchical framework Feature extraction Pre-trained LM CapsNet

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Preface

Preface

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Industry 4.0 - Nascent Technologies and Sustainability for 'Make in India' Initiative, Sardar Patel international conference on

作者： Santosh Rane Sardar Patel International Conference SPICON 2022 India

It brings me great joy to present the proceedings of the Sardar Patel international conference on Industry 4.0 - Nascent Technologies and Sustainability for ‘Make in India’ Initiative (SPICON 2022) held at Sardar Patel College of engineering, Mumbai, on 22nd and 23rd December 2022. SPICON-2022 is sponsored by SERB, AICTE, CSIR, Indian Institution of Industrial engineering � IIIE Mumbai Chapter , Turnitin, Apex Subscriptions and is in association with Sardar Patel Institute of Technology, Mumbai, Capgemini, SAE India-WS, Institution of Engineers, Federation for Educational Leaders and Administrators Foundation (FELA). Further SPICON2022 has technical collaboration with American Institute of Physics (AIP) and IEEE Bombay Section for publishing proceedings of the conference. The aim of this conference was to provide an interdisciplinary platform for leading and young researchers, engineers, academicians, industrialists and practitioners working in the domain of Industry 4.0 - Nascent Technologies and ‘Make in India’ Initiative and Atmanirbhar Bharat. The conference also emphasised on sustainability and is also in alignment with 17 sustainable goals of United Nations. The conference enabled participants to disseminate their innovations and contemporary research in the field of Civil engineering, Electrical engineering, Mechanical engineering, Electronics and Telecommunication, VLSI and Signal Processing, Mechatronics, Information Technology, Computer Science and engineering (AI, ML and data Science) and related fields. The conference featured paper presentation and keynote speeches by eminent speakers who focused on stateof-the-art development in the field of industry 4.0 like, green technology, lean manufacturing, Supply chain, innovative business processes, cloud deliver, network virtualization, network security, big data analysis, machine learning and prediction analytics, IoT, Blockchain and their recent trends in various verticals of engineering. This conference al

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Development of Research-Based RRSDI learning Model for Telecommunication engineering Education 2nd

Development of Research-Based RRSDI Learning Model for Telec...

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作者： Intarawiset, Nattapong Noulnoppadol, Sivadol Jeenawong, Rattapon Akatimagool, Somsak King Mongkuts Univ Technol North Bangkok Bangkok Thailand Rajamangala Univ Technol Srivijaya Rattaphum Coll Songkhla Thailand Rajamangala Univ Technol Lanna Chiang Mai Thailand

ISBN: (纸本)9783030402747;9783030402730

The paper presents the development of an instructional package using a research-based model for learning in telecommunication engineering. The model includes 5 steps (requirement, reviewing, solution, discussion and improvement) has been tested on a student group and has been assessed by several course instructors. The developed RRSDI learning model can encourage learners to have more participation in learning activities and highly learning achievement. The active RRSDI learning model can promote students to research and develop novel knowledge and to solve the problems by themselves using research results and methodology. The research results of the developed RRSDI learning model was assessed by five experts and then was implemented on 15 undergraduate students of microwave engineering course. The quality of the developed RRSDI learning model was appropriate (mean = 4.10, S.D. = 0.22) and was efficient with regards to Meguigans' theory. The student's satisfaction for the developed RRSDI learning model was at a high level. Moreover, the research results can be applied in order to create an effective innovation for learning and teaching of higher education.

关键词： Research-based learning RRSDI learning model Telecommunication engineering education

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A New Hybrid Particle Swarm Optimization and Evolutionary Algorithm with Self-Adaptation Mechanism 1

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22nd international conference on Artificial Intelligence and Soft Computing, ICAISC 2023

作者： Dziwiński, Piotr Bartczuk, Lukasz Department of Intelligent Computer Systems Czȩstochowa University of Technology Czȩstochowa Poland

ISBN: (数字)9783031425059

ISBN: (纸本)9783031425042

Particle Swarm Optimization (PSO) has demonstrated remarkable convergence capabilities in various optimization problems. It is increasingly employed in conjunction with gradient-based methods to enhance the learning process of deep neural networks. However, PSO suffers from a significant drawback, namely the propensity to become trapped in local minima, particularly in challenging multi-modal problems. To address this issue, this study introduces a novel Hybrid Particle Swarm Optimization and Genetic Algorithm with a Self-Adaptation mechanism. Self-adaptation mechanism enables the hybrid algorithm to dynamically adjust its behavior according to the current state of the global best solution search. Initial simulations conducted in this research validate the effectiveness of the proposed approach. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Genetic algorithms

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XTuning: Expert database Tuning System Based on Reinforcement learning 22nd

XTuning: Expert Database Tuning System Based on Reinforcemen...

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22nd international conference on Web Information Systems engineering (WISE)

作者： Chai, Yanfeng Ge, Jiake Chai, Yunpeng Wang, Xin Zhao, BoXuan Renmin Univ China Key Lab Data Engn & Knowledge Engn MOE Beijing Peoples R China Renmin Univ China Sch Informat Beijing Peoples R China Taiyuan Univ Sci & Technol Coll Comp Sci & Technol Taiyuan Shanxi Peoples R China Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China

ISBN: (纸本)9783030908881;9783030908874

database performance optimization has become a hot issue in recent years. Some works deeply reconstruct the database to achieve specified goals like throughput or latency. The others focus on the database's configuration knobs with reinforcement learning (RL) to improve the performance without any empirical knowledge. But the exhaustive offline training process costs plenty of time and resources due to the large inefficient configuration knobs combinations with trial-and-error methods. The most time-consuming part of the process is not the RL network training, but the database performance evaluation for acquiring the reward values of target performance like throughput or latency. So we propose an expert database tuning system (XTuning) which contains a correlation knowledge model to remove unnecessary training costs and a multi-instance mechanism (MIM) to support fine-grained tuning for diverse workloads. The models define the importance and correlations among these configuration knobs for the user's specified target. Then we implement the models as Progressive Expert Knowledge Tuning (PEKT) algorithm with an abstracted architectural optimization integrated into XTuning. Experiments show that XTuning can effectively reduce the training time and achieves extra performance promotion compared with the state-of-the-art tuning methods.

关键词： database optimization Auto tuning Expert knowledge rules Reinforcement learning Reduce training time

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Poster: Intensive learning Technologies as a Trend in Education Digitalization 2nd

Poster: Intensive Learning Technologies as a Trend in Educat...

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作者： Aksyanova, Anna, V Barabanova, Svetlana, V Kraysman, Natalia, V Nasonkin, Vladimir V. Nikonova, Nataliya, V Kazan Natl Res Technol Univ Kazan Russia Russian Peoples Friendship Univ Moscow Russia

ISBN: (纸本)9783030402747;9783030402730

An important task of engineering education is to ensure high quality training on the basis of fundamental approaches to training and taking into account the current and future needs of science and industry. The basic higher education in a modern university should combine both classical educational technologies and modern ones, related to the rapid digitalization process, i.e. information technologies including not only the technological infrastructure of auditoriums, but also various online courses, latest e-books, original e-courses, adapted for a specific audience, taking into account the fields of study;videos, training programs, simulators, etc. At a number of Kazan National Research Technological University departments, with the participation of stakeholders, learning and teaching support kits were developed for solving the problem. The structure and content of these meets the requirements of the distance education system. They can be used in any engineering university, as well as in the system of supplementary vocational education.

关键词： Universal didactic kit Intensive learning technologies Education digitalization

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Generating Synthetic Tabular data for DDoS Detection Using Generative Models

Generating Synthetic Tabular Data for DDoS Detection Using G...

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IEEE international conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Samed Saka Ali Al-Ataby Valerio Selis Department of Electrical Engineering and Electronics University of Liverpool Liverpool UK

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Distributed denial-of-service (DDoS) attacks are a type of cyber attack that overwhelms a target server, service or network with a flood of malicious traffic, making it unavailable to legitimate users. These attacks have become a major threat to the security of computer networks and systems, and effective intrusion detection systems (IDSs) are essential for detecting and mitigating these attacks. IDSs are used to monitor network traffic for malicious activity and can help detect and prevent DDoS attacks. Most IDSs are often designed to identify diverse types of attacks, but their efficacy can be limited when faced with attacks that exhibit extensive variations and sophisticated techniques, such as DDoS. In order to establish an effective IDS capable of identifying DDoS attacks, the acquisition of substantial volumes of labelled network data becomes crucial. This study aims to evaluate the performance of recent generative models in synthesising realistic tabular data to accurately emulate DDoS attack patterns. To achieve this, we used the CIC-DDOS2019 dataset, a comprehensive and modern collection of real-world DDoS attack scenarios. Leveraging state-of-the-art generative models, namely CTGAN, TVAE, and CopulaGAN, we synthesised realistic tabular data that emulated the characteristics and patterns observed in DDoS attack flow. We utilised various statistical metrics such as correlation scores, similarity and distance metrics, along with machine learning performance metrics, to quantitatively measure the performance of the generative models. The findings indicate that all three models have the ability to accurately emulate the patterns found in the real database, resulting in the generation of useful synthetic data. Specifically, among the classification methods used, the Random Forest method showed the most successful performance in detecting attacks with an accuracy of 99% when applied to the original dataset. In comparison, it achieved accuracy levels of 98%, 99%,

关键词： Measurement data privacy Computational modeling Intrusion detection Telecommunication traffic Denial-of-service attack data models

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engineering Slam as a Project of Popularizing Sciences and engineering Competencies 2nd

Engineering Slam as a Project of Popularizing Sciences and E...

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作者： Kadeeva, Zulfiya Kaybiyaynen, Alla A. Lisina, Olga Turner, Elena Kazan Natl Res Technol Univ Kazan Russia

ISBN: (纸本)9783030402747;9783030402730

This paper deals with the engineering Slam Project that was conceived and is being implemented at the engineering university in order to awake students' interest in engineering professions and in new trends in science, engineering, and applied areas. engineering Slam represents sessions with experts, in the course of which informal communication takes place, as well as direct dialogs, discussions, and answers to questions. The speakers present their developments and their businesses. This is a kind of a "battle" among the speakers, resulting in assessing all presentations and identifying the best ones. engineering Slam allows demonstrating to young people all the facets of scientific and engineering activities in the context of the digitalization of economy and industry 4.0, push the boundaries of research and project-related thought in engineering areas, and involve school, college and university students into the process of technology entrepreneurship and in commercializing the results obtained.

关键词： engineering Slam Project of popularization of science Project of popularization of engineering competencies

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