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

共 2255 条记录，以下是1171-1180 订阅

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Poster: Creative, Mental, and Innovation Competences Formation in engineering Education: Systemic Pattern of Labor Productivity Increase in Industry 2nd

Poster: Creative, Mental, and Innovation Competences Formati...

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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： Redin, Lev, V Galikhanov, Mansur F. Kazan Natl Res Technol Univ Dept Engn Pedag & Psychol Kazan Russia Kazan Natl Res Technol Univ Inst Addit Profess Educ Kazan Russia

ISBN: (纸本)9783030402747;9783030402730

The actual rule of intellectual property creation, labor productivity increase in contemporary innovative economy is shown. Author's conception of innovation educational cluster MIMIM (3*MI) should be reliable base for innovation, mental, creative competences formation and development by engineering education. In MIMIM (3*MI) suggest new definition, sense, and content of basic categories "creativity", "creative thinking", "strong", effective solution, "modality of thinking", and three modalities of thinking - binitarian, triune (poly-unity), quaterian.

关键词： Creativity Creative thinking Competence Innovation Labor productivity engineering education

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A Collaborative Approach in Designing Curriculum for Industry 4.0 Software Integration Implementation 2nd

A Collaborative Approach in Designing Curriculum for Industr...

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作者： Centea, Dan Srinivasan, Seshasai Singh, Ishwar Wanyama, Tom McMaster Univ Hamilton ON Canada

ISBN: (纸本)9783030402716;9783030402709

Working in Industry 4.0 enabled environments requires multidisciplinary skills. Academic programs that produce graduates who are ready to support Industry 4.0 concepts need to offer curricula that prepare students to implement different aspects of Industry 4.0 as soon as they enter the workforce. Designing a full new curriculum or modifying an existing curriculum are challenging due to the multidisciplinary nature of the Industry 4.0 implementation. A possible approach involves collaboration between teams of academics specialized in hardware and in software who often belong to distinct academic programs, and include topics that generally belong to different academic specializations. Although such collaboration can be defined in theory, implementing it in an academic program brings a series of challenges. This paper presents a collaborative work that addresses the challenge of integrating software-specific topics in automation engineering and software engineering programs, and describes an experiential learning environment that demonstrate physical implementation of several Industry 4.0 concepts.

关键词： Industry 4.0 Curriculum design Internet of Things learning factory

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Application of Machine learning to Automatic Gear Shift Schedule Design of Alternative Drive Systems

Application of Machine Learning to Automatic Gear Shift Sche...

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international Symposium on Electrical Apparatus and Technologies (SIELA)

作者： Adrienn Dineva Á dá m Zsuga Szabolcs Kocsis Szü rke Vehicle Industry Research Center Sz&#x00E9 chenyi Istv&#x00E1 n University Gy&#x00F6 r Hungary K&#x00E1 lm&#x00E1 n Kand&#x00F3 Faculty of Electrical Engineering &#x00D3 buda University Budapest Hungary

ISBN: (数字)9781665411394

ISBN: (纸本)9781728186702

intelligent automatic transmission shift schedule design has been well established in the last decade. However, due to the paradigm change is currently taking place in mobility sector, which resulted in a rapid progress of Electric Vehicles and Autonomous Vehicles, intelligent automatic gear shift strategies are still in the focus of much research. In addition, the proper transmission shift schedule generation is especially important from the viewpoint of energy efficiency optimizing algorithms, which is affected by the driving style, power losses, etc. Fundamentally, conventional shift schedule design relies on lookup tables obtained from test-bench measurements and real-world driving measurements. During real time test data collection, the measurement of some variables may be impractical and/or patterns of important driving conditions may be unavailable during short-distance routes neglecting the comprehensive effects of the transient operation. Machine learning methods in combination with model-based data generation is a promising alternative, which allows a significant reduction in development time and a more precise calibration by using rich historical data rich. Such models can be easily fitted to alternative drive systems also, which may raise more specific requirements regarding gear shift scheduling issues coupled with efficiency. In this paper the performances of Machine learning models are investigated in automatic gear shift schedule generation based on simulated driving cycle test data. Results of simulation investigations validate the applicability and efficiency of the proposed approach.

关键词： Schedules Power measurement Gears Energy measurement Machine learning Prediction algorithms data models

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Converting Big Video data into Short Video: Using 360-Degree Cameras for Searching Students Location and Judging Students learning Style 22nd

Converting Big Video Data into Short Video: Using 360-Degree...

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11th international conference on intelligent Networking and Collaborative Systems (INCoS) / 22nd international conference on Network-Based Information Systems (NBiS)

作者： Yamamoto, Noriyasu Fukuoka Inst Technol Dept Informat & Commun Engn Higashi Ku 3-30-1 Wajiro Higashi Fukuoka 8110295 Japan

ISBN: (纸本)9783030290290;9783030290283

In general, at the universities the lecturers use the grades to evaluate the students' performance. However, the grades do not show the accumulated knowledge. Thus, the students can't understand whether they have studied enough to understand all the topics of the lecture. Recently, with the advancement with as IoT technology and applications, we can record students' study for every lecture using video images in all directions (360-degree). We can display high quality image for students. However, by recording many lectures, we will have big data. Therefore, we need to convert these data into short video and show to the students in order that students easily understand their study style. In this paper, we use 360-degrees cameras for searching the students' location and judge their learning style.

关键词： Students

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engineering Education: Elite Training at a Technological University 2nd

Engineering Education: Elite Training at a Technological Uni...

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作者： Khatsrinova, Olga Yurievna Tarasova, Ekaterina Nikolaevna Ovsienko, Lyubov' Vasilievna Yushko, Sergey Vladimirovich Galikhanov, Mansur Floridovich KNRTU Dept Engn Educ & Psychol Kazan Russia KNRTU Kazan Russia KNRTU Inst Continuous Profess Educ Kazan Russia

ISBN: (纸本)9783030402747;9783030402730

The article addresses to elite training of A-level-students at an engineering university. It is caused by the necessity to improve the quality of education to train the future innovation-oriented professionals. This type of elite training is exemplified by the additional professional education school "Technolider". The fulfil the educational tasks a curriculum was developed that includes specialized, basic, innovational, professionally oriented and creative training modules. The program is called "Innovational technological projects management". On the final stage of the program students present their scientific researches or technological projects to potential investors and industries for the projects to be implemented into practice.

关键词： engineering education Elite training Additional professional education school

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Proposal of an Interactive IPTV Platform to Improve the Quality of Service of E-learning Platforms 2nd

Proposal of an Interactive IPTV Platform to Improve the Qual...

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作者： Boko, Ulrich Hermann Semevo Degboe, Bessan Melckior Ouya, Samuel Mendy, Gervais Univ Cheikh Anta Diop Dakar Higher Polytech Sch Lab LIRT Dakar Senegal

ISBN: (纸本)9783030402747;9783030402730

The objective of this paper is to contribute to improve the interactivity and quality of service of the e-learning platforms by using the power of IPTV. To do this, we propose a highly interactive elearning platform. This platform, based on FFmpeg, Tvheadend and Verto-FreeSwitch, allows the teacher to deliver an online course with a better quality of service. The FFmpeg streaming server performs MPEG-TS encoding and allows the teacher to broadcast the multimedia (audio/video) stream from his webcam in unicast to the Tvheadend server. This interactive IPTV's server carries out a multicast of the stream for learners. With a web browser or an IPTV client, students can follow the teacher's explanations and interact in real time;thanks to the Verto-FreeSwitch module. The use of this solution allowed students to go to any Open Digital Space (ENO) of the Virtual University of Senegal (UVS) and follow a quality online courses without buying an internet package.

关键词： E-learning Interactive IPTV FreeSwitch

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engineering Education over the Course of Time A Technical and Didactic Journey over Four Decades: From Manual Road Map Navigation to Electronic Navigation Systems to Autonomous Cars 2nd

Engineering Education over the Course of Time A Technical an...

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作者： Michler, Oliver Schwarzbach, Paul Richter, Robert Tech Univ Dresden Dresden Germany

ISBN: (纸本)9783030402747;9783030402730

The mastery of the theoretical and applied basics and their deepening are indispensable for engineering students. Over the last decades, many technical systems have changed in a revolutionary way, mostly from simplicity to complexity. This technological change shapes the engineering didactics in terms of contents and goals as well as methodology in the form of implementation and organization of engineering education in a revolutionary and evolutionarily way. This paper analyzes the subject- and domain-specific change in the learning and teaching processes over several decades in transport related engineering education using the teaching example "car navigation". It turns out that the teaching material of lectures continuously evolved from general subject-related content to subject-specific content.

关键词： engineering training Study program contents Academic tools Teaching example Car navigation Transport engineering

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A CONVOLUTIONAL NEURAL NETWORK And SEQUENCE-TO-SEQUENCE MODEL BASED ENERGY DISAGGREGATION ALGORITHM FOR NON-INTRUSIVE LOAD MONITORING 22

A CONVOLUTIONAL NEURAL NETWORK AND SEQUENCE-TO-SEQUENCE MODE...

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22nd international Symposium on High Voltage engineering, ISH 2021

作者： Lian, Wenli Wu, Tuo He, Ying Shan, Zihan Si, Gangquan Smart Grid Xian Electric Power Supply Company Xi'an China Smart Grid Shanxi Electric Power Company Xi'an China School of Electrical Engineering Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9781839536052

With the achievement of the sensing technology and communication network, the smart monitoring and computing equipment becomes more and more common, which generates the massive data of different types and sampling frequency. The detailed information in the collected electricity usage data shows the load features and residents' electricity utilizing style, and the achievement of artificial intelligence and machine learning algorithms provide better ways for process and analysis. The appliance-level energy consumption information obtained by non-intrusive load monitoring is a great benefit for energy saving by scientific management. For this purpose, this paper adopted an energy disaggregation algorithm based on CNN and Seq2Seq model to analyse the appliances' energy consumption information. We use the local attention mechanism in decoding to process the information in the long source sequence, expected to reduce the information compression and computational complexity. The proposed method for non-intrusive load monitoring succeeds in disaggregation from the total power profiles to target appliance power profiles very close and provides more effective performance than the traditional CNN and LSTM method. © 2021 The Institution of engineering and Technology.

关键词： Energy utilization

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Analysis Dropout Situation of Business Computer Students at University of Phayao 2nd

Analysis Dropout Situation of Business Computer Students at ...

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作者： Nuankaew, Pratya Nuankaew, Wongpanya Phanniphong, Kanakarn Fooprateepsiri, Rerkchai Bussaman, Sittichai Univ Phayao Phayao Thailand Rajabhat Mahasarakham Univ Maha Sarakham Thailand Rajamangala Univ Technol Tawan Ok Chon Buri Thailand

ISBN: (纸本)9783030402747;9783030402730

This paper aims to analyze the situation of dropout of business computer students at University of Phayao. The composition of the goal consists of 3 main points, including summarizing the situation from the past to the present, statistical analysis and machine learning analysis. data collection is 1,888 students from the Department of Business Computer at University of Phayao from the academic year 2001-2016. The research tools are percentages, decision tree, cross-validation methods, and confusion matrix performance. The results showed that the dropout rate of learners in business computer program tended to increase even though the number of new students decreased. It was found that the academic results had a significant influence on dropout, which most of the students who dropped out were obviously in their first academic year. Which, the model received is a high-performance prediction level with an accuracy of 87.21%. It was found that factors affecting the dropout consisted of seven courses: 221110, 221120, 001103, 128221, 005171, 122130 and 128221. Based on research findings, it represents a situation that has entered into a crisis in which the stakeholders need to focus on the above problems.

关键词： Student dropout prediction Analysis dropout situation Educational data mining Personal learning pathway

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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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