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检索条件"任意字段=22nd International Conference on Intelligent Data Engineering and Automated Learning"

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The tags are alright: Robust large-scale RFID clone detection through federated data-augmented radio fingerprinting 21

The tags are alright: Robust large-scale RFID clone detectio...

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22nd international Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, MobiHoc 2021

作者： Piva, Mauro Maselli, Gaia Restuccia, Francesco Department of Computer Science Sapienza University Italy Department of Electrical and Computer Engineering Northeastern University United States

ISBN: (纸本)9781450385589

Millions of RFID tags are pervasively used all around the globe to inexpensively identify a wide variety of everyday-use objects. One of the key issues of RFID is that tags cannot use energy-hungry cryptography, and thus can be easily cloned. For this reason, radio fingerprinting (RFP) is a compelling approach that leverages the unique imperfections in the tag's wireless circuitry to achieve large-scale RFID clone detection. Recent work, however, has unveiled that time-varying channel conditions can significantly decrease the accuracy of the RFP process. Prior art in RFID identification does not consider this critical aspect, and instead focuses on custom-tailored feature extraction techniques and data collection with static channel conditions. For this reason, we propose the first large-scale investigation into RFP of RFID tags with dynamic channel conditions. Specifically, we perform a massive data collection campaign on a testbed composed by 200 off-the-shelf identical RFID tags and a software-defined radio (SDR) tag reader. We collect data with different tag-reader distances in an over-the-air configuration. To emulate implanted RFID tags, we also collect data with two different kinds of porcine meat inserted between the tag and the reader. We use this rich dataset to train and test several convolutional neural network (CNN)-based classifiers in a variety of channel conditions. Our investigation reveals that training and testing on different channel conditions drastically degrades the classifier's accuracy. For this reason, we propose a novel training framework based on federated machine learning (FML) and data augmentation (DAG) to boost the accuracy. Extensive experimental results indicate that (i) our FML approach improves accuracy by up to 48%;(ii) our DAG approach improves the FML performance by up to 19% and the single-dataset performance by 31%. To the best of our knowledge, this is the first paper experimentally demonstrating the efficacy of FML and DAG

关键词： data acquisition

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Transformers fault identification by frequency response analysis using intelligent classifiers

Transformers fault identification by frequency response anal...

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22nd international Symposium on High Voltage engineering (ISH 2021)

作者： R. S. A. Ferreira H. Ezzaidi I. Fofana P. Picher Research Chair on the Aging of Power Network Infrastructure (ViAHT) Université du Québec à Chicoutimi Saguenay Canada Institut de recherche d'Hydro-Québec (IREQ) Varennes Canada

Failures in power transformers generates high financial loss inherent to equipment cost and power interruption. Thus, the industry has been working into developing efficient and reliable monitoring techniques with the objective of detecting incipient faults. Frequency Response Analysis (FRA) is among well-known methods to detect faults in transformers' active parts. FRA is very sensitive to changes in the winding geometry and a comparison between healthy and faulty measurements can present deviations that leads to the fault identification. However, until now, FRA interpretation is performed with the aid of experts. The development of FRA and the spreading of its application in transformers' diagnostics, have led studies to focus on the advancement of objective interpretation techniques. To contribute to this matter, intelligent classifiers are evaluated over its capabilities to classify transformers faults. For this purpose, a database of measurements performed on a laboratory winding model including different faults is used. Numerical indices are used as input for machine learning classifiers. This analysis indicated that the use of one individual index is appropriate for a good classification performance using Radial Basis Function neural network. Meanwhile Support-vector machine and Backpropagation neural network performed better with a combination of indices.

关键词： backpropagation condition monitoring fault diagnosis frequency response pattern classification power engineering computing power system faults power system reliability radial basis function networks support vector machines

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Infret: Enhancing a Tool for Explorative learning of Information Retrieval Concepts 2nd

Infret: Enhancing a Tool for Explorative Learning of Informa...

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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： Bobic, Aleksandar Cheong, Christopher Filippou, Justin Cheong, France Guetl, Christian Graz Univ Technol Graz Austria RMIT Univ Melbourne Vic Australia Univ Melbourne Melbourne Vic Australia

ISBN: (纸本)9783030402747;9783030402730

To help students better understand abstract information retrieval (IR) concepts and encourage students to explore new concepts, an existing Web-based IR tool called Infret was enhanced. Based on the feedback from a previous evaluation, the need for additional IR concepts and user tracking functionality was identified. The expanded Infret version was evaluated in a class of experienced students who were studying an information search and retrieval course and a class of novice students who were studying a database design and development course. Both groups were working in different learning environments and were given two similar text statistics-based learning activities and four term weighting-based learning activities. At the end of the activities, both groups completed a multi-part survey. The results indicate that the novice students were more inclined to explore unrelated IR concepts after using Infret. Additionally, both groups agreed that exploring the concepts using visualisations helped them more than just calculating the formulae manually. Furthermore, the results show that Infret successfully helps students understand concepts of text statistics and term weighting and was seen as useful by most students. The average system usability score (SUS) for the experienced students was 69.8 and for novice students 57.7. These results indicate that Infret supports exploration and helps students get a better understanding of concepts, however, further improvements are required.

关键词： Information retrieval Active learning Interactive visualisation tool Web-based learning Explorative learning

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Background of the Revision of the Secondary School engineering Curriculum in the Context of the Society 4.0 2nd

Background of the Revision of the Secondary School Engineeri...

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作者： Malach, Josef Vicherkova, Dana Univ Ostrava Fac Educ Dept Pedag & Andrag Ostrava Czech Republic

ISBN: (纸本)9783030402716;9783030402709

The study responds to the characteristics of Society 4.0, which links industry, services, science, research, innovation and new digital technologies. Education 4.0 must ensure the preparation for the digital age and the expansion of digital skills across generations while increasing the use of digital technology in school and in-service training. Digitization, robotics and the potency of artificial intelligence also significantly influence engineering production, which requires a different qualification of workers. European Qualifications Frameworks are a suitable tool for revising engineering study. The revision must be based on trends in engineering, analysis of the educational needs of this sector, current educational concept and knowledge of the specifics of the current young generation. The revised curriculum should integrate professional competences with key competences and transversal (cross-curricular) skills, allowing school leavers to enter the production or production practice and excellent students a higher level of engineering education. The authors of the study deal with the research grant of the Technological Agency of the Czech Republic entitled "Education in engineering fields and its optimisation for the labour market", which will be one of the research starting points for the commenced review of the curriculum. Research uses a number of empirical methods to identify unnecessary parts of the curriculum and to identify new components in terms of learning goals and learning outcomes in both the vocational and general education fields. Research findings will be compared with foreign results and discussed with engineering companies as purchasers of graduates and educators at secondary engineering schools to meet the needs of the emerging Industry 4.0 and the real educational potential of schools. The study presents the results of analyses of trends in the engineering industry, its human resources needs and requirements for the professional profile of w

关键词： Curriculum of engineering education Curriculum revision European qualification framework Educational needs Industry 4.0 Digitization Robotics Artificial intelligence

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How to Enlighten Novice Users on Behavior of Machine learning Models?

How to Enlighten Novice Users on Behavior of Machine Learnin...

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ACIS international conference on Software engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD)

作者： Hiroto Mizutani Masateu Tsunoda Keitaro Nakasai Kindai University Higashi-Osaka Japan Kagoshima College National Institute of Technology Kirishima Japan

ISBN: (纸本)9781665447324

Background: Machine learning models are sometimes embedded in software to implement the required functions. As a result, non-experts in machine learning are becoming familiar with the models. However, the interpretability of the built models is often low in machine learning, such as deep learning, and the recognition process of such models is very different from that of humans. Therefore, it is not easy for novice users, such as end-users and beginners, to anticipate the behavior of models that they will use or build. Aim: We assist novice users to realize an aspect of the behavior of machine learning models relating to robustness intuitively. Method: We formalized and evaluated quiz-based analysis, which is often applied by practitioners to test the robustness of machine learning models arbitrarily. To generate test cases of the models, the analysis converts images towards the boundary of classification for both machine learning and humans. It can be regarded as a type of boundary value analysis of software development. Results: In the experiment, we evaluated whether the analysis quantitatively clarified the aspects of the models. The analysis clarified the robustness of the model for image conversion and misclassification quantitatively. Conclusion: The analysis is expected to enlighten novice users on the behavior of machine learning models. This may promote behavioral changes in the evaluation of models for novice users.

关键词： Knowledge engineering Deep learning Analytical models Machine learning Robustness Software data models

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Emergency Clinical Procedure Detection With Deep learning 42

Emergency Clinical Procedure Detection With Deep Learning

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42nd Annual international conference of the IEEE-engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Li, Lingfeng Paris, Richard A. Pinson, Conner Wang, Yan Coco, Joseph Heard, Jamison Adams, Julie A. Fabbri, Daniel, V Bodenheimer, Bobby Vanderbilt Univ Dept Elect Engn & Comp Sci 221 Kirkland Hall Nashville TN 37235 USA Vanderbilt Univ Med Ctr Nashville TN USA Rochester Inst Technol Dept Elect & Microelect Engn Rochester NY 14623 USA Oregon State Univ Collaborat Robot & Intelligent Syst Inst Corvallis OR 97331 USA

ISBN: (纸本)9781728119908

Information about a patient's state is critical for hospitals to provide timely care and treatment. Prior work on improving the information flow from emergency medical services (EMS) to hospitals demonstrated the potential of using automated algorithms to detect clinical procedures. However, prior work has not made effective use of video sources that might be available during patient care. In this paper we explore the use convolutional neural networks (CNNs) on raw video data to determine how well video data alone can automatically identify clinical procedures. We apply multiple deep learning models to this problem, with significant variation in results. Our findings indicate performance improvements compared to prior work, but also indicate a need for more training data to reach clinically deployable levels of success.

关键词： Hospitals

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Educational and Career Guidance Cloud-Based System to Improve learning Outcomes 2nd

Educational and Career Guidance Cloud-Based System to Improv...

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作者： El-Sofany, Hosam Farouk El-Seoud, Samir A. King Khalid Univ Abha Saudi Arabia Cairo Higher Inst Engn Comp Sci & Management Cairo Egypt British Univ Egypt BUE Fac Informat & Comp Sci Cairo Egypt

ISBN: (纸本)9783030402747;9783030402730

Choosing a career or specialization is an important goal for students in the early stage of their life. The decision for choosing right career will affect positively or negatively on the academic level of students and professional life of the graduates. There are many factors affect career guidance process for students and graduates, some difficulties in this process have motivated the researchers to use a variety of scientific methodologies to propose career guidance systems and to solve related problems. In this research, the cloud-based career guidance system that helps and support students for transferring to the professional world is introduced. From cloud computing point of view, we introduce the proposed system as Career-as-a-Service (CAAS) model. On other hands, the identification of system inputs, outputs, and rules are controlled by fuzzy logic operations. The main objectives of the proposed system include: help students to choose appropriate colleges that matching with their desires, help graduates to choose the appropriate career that matching with their, scientific skills, and practical experiences, and provide graduates with the required training courses for specific career. This research introduces the implementation and use of career guidance system that provides career guidance services to students and graduates and improves the learning outcomes.

关键词： learning outcomes Cloud computing Career and educational guidance Fuzzy logic

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Innovative Technical Drawing Simulation Application for Higher-Order Thinking Skills in Teaching and learning of Technical Graphic Communication for Upper Secondary School 2nd

Innovative Technical Drawing Simulation Application for High...

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作者： Latip, Mohd Amir Abdul Salleh, Shaharuddin Md Idrus, Aminah Binti Univ Teknol Malaysia UTM Fac Social Sci & Humanities Johor Baharu Malaysia Univ Malaysia Sabah UMS Fac Psychol & Educ Kota Kinabalu Sabah Malaysia

ISBN: (纸本)9783030402747;9783030402730

Higher-order thinking skills (HOTS) has become a focus on Teaching and learning in Malaysia in recent years and this has raised concern among Technical Graphic Communication (TGC) teachers. The development of an innovation known as Technical Drawing Simulation (TDS) application responds to the challenge. TDS was developed using Visual Basic Application (VBA) as the programming language and ADDLE as the design model. The research aims to study the effectiveness of the TDS application into applying HOTS during learning process using TDS. An experimental approached included pre-test and post-test were conducted to compare students' scores on using HOTS questions while applying TDS and as in standard practice. Students' motivation and perception were measured using the questionnaire after the pre-test and post-test. The research has been conducted in a rural school in Sabah and samples were among moderate achieving students. The results indicated that TDS helped improve students' performance in answering HOTS questions and increase students' motivation in learning the subject. Hence, TDS offers a potential tool to help students in applying HOTS in learning technical drawing. In a nutshell, the findings implied that using TDS in Teaching and learning helps infuse HOTS effectively, time saving and practical.

关键词： Innovation Simulation Technical Graphics Communication HOTS VBA

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Development of a "Smart Materials" Master's Degree Module for Chemical engineering Students 2nd

Development of a "Smart Materials" Master's Degree Module fo...

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作者： Bezrukov, Artem Sultanova, Dilbar Kazan Natl Res Technol Univ Kazan Russia

ISBN: (纸本)9783030402716;9783030402709

This paper describes development of an interdisciplinary "Smart Materials" module in English for Master's students in a Russian chemical engineering university. The module is intended for promoting English proficiency of engineering students and internationalizing education by attracting foreign students within the framework of short-term academic exchange. The research stage of project implementation included comparative analysis of international engineering education in Germany and Russia in a form of survey included 30 faculty members and 100 students. Germany was selected because it offers excellent engineering education in English and is originally non-English speaking. The visits to universities in four different regions of Germany allowed for planning the structure of the module and the content of lectures and practicums. The survey results contributed to the implementation of the second stage of the project that was focused on developing three disciplines for the module: "Introduction to smart Materials", "Research Methods for Smart Materials" as lecture courses and "Practical Course in Smart Materials" as the laboratory practicum. The module is ready for introduction into the education process of a Russian chemical engineering university starting from the 2019-2020 academic year and is selected as the core for a new Master's degree program "Molecular Materials engineering".

关键词： Master's program engineering education internationalization Smart materials

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Application of Microfluidic Tools for Training Chemical Engineers 2nd

Application of Microfluidic Tools for Training Chemical Engi...

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作者： Bezrukov, Artem Sultanova, Dilbar Kazan Natl Res Technol Univ Kazan Russia

ISBN: (纸本)9783030402716;9783030402709

Microfluidics operates flows of fluids on a micrometer scale. It offers more economically friendly solutions for universities as microfluidic chips cost orders of magnitude lower than conventional laboratory equipment. The "Lab on a Chip" approach offers easily reproducible solutions for simulating chemical processes in a microfluidic confinement. This paper describes development of experimental practicums with microfluidic tools for various chemical processes and their implementation to the education process of Master's degree students in Polymer engineering program. The following processes are realized: purification of polymer solutions, synthesis of nanoparticles from polymers and surfactants and control of polymer conformations. Within these practicums, students are involved in entire engineering cycle including all stages from design and fabrication of their experimental tools to final product characterization. They first apply fundamental physical and chemical aspects to the design of new microfluidic devices, then fabricate them, practice chemical processes in microfluidic chips and finally characterize products they obtained. The practicums are strongly interdisciplinary and students need to apply knowledge from physics, hydrodynamics, physical chemistry, polymer engineering and computer-aided design to successfully fabricate and work with microfluidic chips. Not limited to polymer engineering, these practicums are suitable for Master's students in materials science, nanotechnology and biotechnology.

关键词： Microfluidics Polymer engineering Experimental practicums

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