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检索条件"任意字段=11th International Conference on Intelligent Data Engineering and Automated Learning"

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(WIP) Evaluation of a Cloud-Based System for Delivering Adaptive Micro Open Education Resource to Fresh Learners 11

(WIP) Evaluation of a Cloud-Based System for Delivering Adap...

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11th IEEE international conference on Cloud Computing, CLOUD 2018

作者： Sun, Geng Cui, Tingru Dong, Fang Xu, Dongming Shen, Jun Chen, Shiping Lin, Jiayin School of Computing and Information Technology University of Wollongong Australia School of Computer Science and Engineering Southeast University China UQ Business School University of Queensland Australia CSIRO Data61 Australia

ISBN: (纸本)9781538672358

In this paper, we present an online computation approach implemented in a cloud-based system to assist open education resource (OER) providers and instructors dealing with the sparsity of data in micro OER recommendation. An algorithmic framework is provided to realize the novel micro OER recommendation system based on heuristic rules. these rules can also optimize the approaches to blending new-coming micro OERs into established learning paths. Comparing with different widely used recommender systems, our evaluation shows the proposed heuristic algorithms for online computation performs satisfactorily in terms of precision and recall values. © 2018 IEEE.

关键词： Recommender systems

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Case-Based Decision Support System with Contextual Bandits learning for Similarity Retrieval Model Selection 11th

Case-Based Decision Support System with Contextual Bandits L...

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11th international conference on Knowledge Science, engineering and Management (KSEM)

作者： Sekar, Booma Devi Wang, Hui Ulster Univ Sch Comp Jordanstown Campus Newtownabbey North Ireland

ISBN: (纸本)9783319993652;9783319993645

Case-based reasoning has become one of the well-sought approaches that supports the development of personalized medicine. It trains on previous experience in form of resolved cases to provide solution to a new problem. In developing a case-based decision support system using case-based reasoning methodology, it is critical to have a good similarity retrieval model to retrieve the most similar cases to the query case. Various factors, including feature selection and weighting, similarity functions, case representation and knowledge model need to be considered in developing a similarity retrieval model. It is difficult to build a single most reliable similarity retrieval model, as this may differ according to the context of the user, demographic and query case. To address such challenge, the present work presents a case-based decision support system with multi-similarity retrieval models and propose contextual bandits learning algorithm to dynamically choose the most appropriate similarity retrieval model based on the context of the user, query patient and demographic data. the proposed framework is designed for DESIREE project, whose goal is to develop a web-based software ecosystem for the multidisciplinary management of primary breast cancer.

关键词： Case-based reasoning Clinical decision support system Similarity retrieval Contextual bandits learning

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Technology-Needs Assessment data Analysis using PCA for the Design of a WLAN-based Hybrid Classroom Response and learning Management System Android Application

Technology-Needs Assessment Data Analysis using PCA for the ...

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international conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)

作者： Joseph Bryan Ibarra Meo Vincent Caya Arnold Paglinawan Jerry Turingan Sarah Alma Bentir Jim Joseph Monta Jumarie Mocon Analyn Yumang Lilibeth Sabino Mariciel Teogangco School of Electrical Electronics and Computer Engineering Mapúa University Manila Philippines Senior High School Department Mapua University Manila Philippines College of Engineering University of Perpetual Help DALTA Molino Cavite Philippines

ISBN: (数字)9781728130446

ISBN: (纸本)9781728130453

the influence of technology in the evolution of modern-day education grows significantly as more educational institutions attempt to improve the quality of education. this study aims to develop a hybrid of a classroom response system and learning management system web and android applications without the use of the internet. A technology-needs assessment (TNA) was administered on 213 high school students. the TNA questionnaire was comprised by 16 closed-ended questions, 15 of which required Likert scale-based responses and one required a yes/no response. the TNA data was analyzed with the help of principal component analysis (PCA). the results of the PCA became the basis for the configuration of a wireless local area network of devices connected to a central server through a wireless router dedicated for the implementation of the web and android applications designed for the needs identified by the study. the web and android applications were developed using a test-driven development (TDD) approach. the system configuration was based on the system capacity requirements to enable simultaneous wireless connection of up to 100 mobile devices. Two groups of high school students were identified by the school to be part of the field testing of the web/android app since these students were of significantly similar academic standing in their respective classes. the study group (n=7) used the web/android app in their statistics class and a control group (n=10) were subjected to the traditional classroom set-up. the field testing lasted for two weeks covering various teaching and learning activities including exams. the exam results were subjected to Analysis of Variance using two-sample F-test and t-test. the results show that at 5% significance level, a p-value of 0.0026 was obtained, which indicates that the means between the summative test results data sets are significantly different. the performance of the students in the study group is significantly different from the

关键词： Principal component analysis learning management systems Androids Humanoid robots Wireless LAN Testing

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A Real-Time Detection Framework for On-Tree Mango Based on SSD Network 11th

A Real-Time Detection Framework for On-Tree Mango Based on S...

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11th international conference on intelligent Robotics and Applications (ICIRA)

作者： Liang, Qiaokang Zhu, Wei Long, Jianyong Wang, Yaonan Sun, Wei Wu, Wanneng Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China Hunan Univ Hunan Key Lab Intelligent Robot Technol Elect Mfg Changsha 410082 Hunan Peoples R China Natl Engn Lab Robot Vis Percept & Control Changsha 410082 Hunan Peoples R China

ISBN: (纸本)9783319975894;9783319975887

On-tree fruit detection in orchards is important for yield estimation, mapping and automatic harvesting in modern agriculture. this paper proposes a real-time detection framework for on-tree mango based on SSD (Single shot Multi Box Detector) network, a state-of-the-art object detection algorithms based on deep learning. the mango image dataset used in this paper was gathered from outdoor mango orchards. Firstly, the dataset was annotated and converted to a trainable dataset for SSD network. Secondly, the author designed new sampling strategies and image distortions at the image pre-processing stage to optimize data augmentation techniques. Moreover, the default box proposal methods of SSD network were improved by redesigning the shapes of default boxes on multiple feature maps according to our own dataset. Finally, to explore which classification network is most suitable for mango detection, an experiment was presented to compare the detection performance of SSD network with the VGG16 and ZFNet as base network respectively. Almond dataset was also used to verify our proposed method. Experimental results demonstrated that, with optimization of data augmentation techniques and default box proposals, our improved VGG16-based SSD network can achieve higher performance than Faster R-CNN in on-tree mango detection, with F1 score of 0.911 at 35 FPS for 400 x 400 input image, which is a real-time detection.

关键词： Mango Detection SSD Deep learning

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Problem Solving Olympics: An Inclusive Education Model for learning Informatics 11th

Problem Solving Olympics: An Inclusive Education Model for L...

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11th international conference on Informatics in Schools - Situation, Evolution, and Perspectives (ISSEP)

作者： Borchia, Roberto Carbonaro, Antonella Casadei, Giorgio Forlizzi, Luca Lodi, Michael Martini, Simone Ist Tecn Ind Q Sella Biella Italy Univ Bologna Dip Informat Sci & Ingn Bologna Italy Univ Aquila Dip Ingn & Sci Informaz & Matemat Laquila Italy INRIA Sophia Antipolis Valbonne France

ISBN: (纸本)9783030027506;9783030027490

the paper presents the Olimpiadi di Problem Solving, a mild and inclusive competition aimed to promote computational thinking and general problem-solving in Italian schools. We describe motivation, teaching strategies behind the initiative, as well as its structure, organization and give some sample of the problems proposed to students. We also present some data that show the broad participation of Italian schools to the initiative, and a preliminary analysis of the results obtained by the students in the last 5 editions, which suggests that the competition fosters deep learning of computational thinking knowledge and skills.

关键词： Inclusive competitions Computational thinking Problem-solving

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11th EAI international conference on Communications and Networking in China, ChinaCom 2016

11th EAI International Conference on Communications and Netw...

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11th EAI international conference on Communications and Networking in China, ChinaCom 2016

ISBN: (纸本)9783319666242

the proceedings contain 105 papers. the special focus in this conference is on Communications and Networking in China. the topics include: Transceiver optimization in full duplex SWIPT systems with physical layer security;robust secure transmission scheme in MISO interference channel with simultaneous wireless information and power transfer;an effective limited feedback scheme for FD-MIMO based on noncoherent detection and kronecker product codebook;two-stage precoding based interference alignment for multi-cell massive MIMO communication;adaptive energy-saving mechanism for SMAC protocol in wireless sensor network;a transmission rate optimized cooperative MAC protocol for wireless sensor networks;heterogeneous control and data split network for precision formation flying of distributed spacecraft;a novel feedback method to enhance the graphical slotted ALOHA in M2M communications;a hybrid automatic repeat reQuest scheme based on maximum distance separable codes;energy-efficient resource allocation in distributed antenna systems;applications of genetic algorithms in BGP-based interdomain traffic engineering;performance analysis of routing algorithms based on intelligent optimization algorithms in cluster Ad Hoc network;incentive mechanism for crowdsensing platforms based on multi-leader stackelberg game;master controller election mechanism based on controller cluster in software defined optical networks;performance evaluation of black hole attack under AODV in smart metering network;an entropy-based DDoS defense mechanism in software defined networks;protecting location privacy through crowd collaboration;a measurement and security analysis of SSL/TLS deployment in mobile applications and two degree forest based LT codes with feedback.

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Two-step training and mixed encoding-decoding for implementing a generative chatbot with a small dialogue corpus

Two-step training and mixed encoding-decoding for implementi...

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2018 Workshop on intelligent Interactive Systems and Language Generation, 2IS and NLG 2018, collocated with the 11th international conference on Natural Language Generation, INLG 2018

作者： Kim, Jintae Lee, Hyeon-Gu Kim, Harksoo Lee, Yeonsoo Kim, Young-Gil Kangwon National University Computer and Communication Engineering Korea Republic of NCSOFT Corp. Korea Republic of Electronics and Telecommunications Research Institute Korea Republic of

ISBN: (纸本)9781948087889

Generative chatbot models based on sequence-to-sequence networks can generate natural conversation interactions if a huge dialogue corpus is used as training data. However, except for a few languages such as English and Chinese, it remains difficult to collect a large dialogue corpus. To address this problem, we propose a chatbot model using a mixture of words and syllables as encoding-decoding units. In addition, we propose a two-step training method, involving pre-training using a large non-dialogue corpus and re-training using a small dialogue corpus. In our experiments, the mixture units were shown to help reduce out-of-vocabulary (OOV) problems. Moreover, the two-step training method was effective in reducing grammatical and semantical errors in responses when the chatbot was trained using a small dialogue corpus (533,997 sentence pairs). © 2018 Association for Computational Linguistics

关键词： Mixtures

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Machine learning Based Skill-level Classification for Personal Mobility Devices Using Only Operational Characteristics

Machine Learning Based Skill-level Classification for Person...

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25th IEEE/RSJ international conference on intelligent Robots and Systems (IROS)

作者： Huang, Yifan Kamezaki, Mitsuhiro Mori, Taiga Manawadu, Udara E. Ishihara, Tatsuya Nakano, Masahiro Koshiji, Kohjun Higo, Naoki Tubaki, Toshimitsu Sugano, Shigeki Waseda Univ Grad Sch Creat Sci & Engn Dept Modern Mech Engn Shinjuku Ku 17 Kikui Cho Tokyo 1620044 Japan Waseda Univ RISE Shinjuku Ku 17 Kikui Cho Tokyo 1620044 Japan NTT Corp NTT Serv Evolut Labs Network Robot & Gadget Project 1-1 Hikarinooka Yokosuka Kanagawa 2390847 Japan NTT Corp Network Architecture Innovat Project NTT Network Technol Labs 3-9-11 Midori Cho Musashino Tokyo 1808585 Japan Waseda Univ Dept Modern Mech Engn Sch Creat Sci & Engn Shinjuku Ku 3-4-1 Okubo Tokyo 1698555 Japan

ISBN: (纸本)9781538680940

Some electric-powered wheelchairs are recently redefined as personal mobility devices. their users are not only elderly or handicapped people, but also passengers with large baggage or pedestrians going from station to destination, i.e., last-mile transport. Consequently, people with different operation skills and expectations on personal mobility would become new users of this kind of devices. Safe and comfort travel in human co-existing environment such as sidewalks and airports is a social expectation for personal mobility. In order to realize this, understanding the operation skill of each user by a practical and simple method is essential. this paper thus introduced a skill level classification method by machine learning using only joystick data as input. In order to determine the number of skill level clusters, basic 26 features of joystick operation data are used for unsupervised clustering (single-linkage). We then made evaluation indexes by using speed, speed control, and direction control. For a five-level classification by using gradient boosting as supervised learning, we achieved a 67% accuracy (tolerance: 0) and a 98% accuracy (tolerance: 1). Further analysis of the feature importance of gradient boosting revealed key features to a good operation. Results also show that skill level differed among people with different driving experiences.

关键词： Boosting Vehicles Sensors Feature extraction Acceleration

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Distributed cooperative hierarchical control for DC microgrid 11

Distributed cooperative hierarchical control for DC microgri...

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11th IET international conference on Advances in Power System Control, Operation and Management, APSCOM 2018

作者： Guo, Chunyuan Qiu, Li Zhang, Bo Yuan, Jianping College of Mechatronics and Control Engineering Shenzhen University Shenzhen China Intelligent Operation Laboratory Research Institute of Northwestern Polytechnical University in Shenzhen Shenzhen China

ISBN: (纸本)9781839530043

this paper proposes a distributed cooperative hierarchical control scheme for DC microgrid based on consensus algorithm. the control architecture includes primary control, secondary control and tertiary control, which secondary controller uses a consensus algorithm. Four power generators are a cooperative relationship with each other through the control layer. the controller of each converter only exchanges data with the adjacent converter on the cyber layer communication network. When the internal power of the microgrid is higher than the external system, the tertiary controller can be used to deliver energy to the external power grid and achieve power optimization between the microgrids. Finally, through the experimental simulation, it is verified that hierarchical control can effectively regulate the DC microgrid bus voltage in the target range and achieve power exchange management with the external power grid. © 2018 Institution of engineering and Technology. All rights reserved.

关键词： Controllers

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Accurate measurement of lexical sophistication with reference to ESL learner data 11

Accurate measurement of lexical sophistication with referenc...

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11th international conference on Educational data Mining, EDM 2018

作者： Naismith, Ben Han, Na-Rae Juffs, Alan Hill, Brianna Zheng, Daniel University of Pittsburgh Department of Linguistics 4200 Fifth Ave PittsburghPA15260 United States University of Pittsburgh School of Computing and Information 4200 Fifth Ave PittsburghPA15260 United States University of Pittsburgh Department of Electrical and Computer Engineering 4200 Fifth Ave PittsburghPA15260 United States

One commonly used measure of lexical sophistication is the Advanced Guiraud (AG;[9]), whose formula requires frequency band counts (e.g., COCA;[13]). However, the accuracy of this measure is affected by the particular 2000-word frequency list selected as the basis for its calculations [27]. For example, possible issues arise when frequency lists that are based solely on native speaker corpora are used as a target for second language (L2) learners (e.g., [8]) because the exposure frequencies for L2 learners may vary from that of native speakers. Such L2 variation from comparable native speakers may be due to first language (L1) culture, home country teaching materials, or the text types which L2 learners commonly encounter. this paper addresses the aforementioned problem through an English as a Second Language (ESL) frequency list validation. Our validation is established on two sources: (1) the New General Service List (NGSL;[4]) which is based on the Cambridge English Corpus (CEC) and (2) written data from the 4.2 million-word Pitt English Language Institute Corpus (PELIC). Using open-source data science tools and natural language processing technologies, the paper demonstrates that more distinct measurable lexical sophistication differences across levels are discernible when learner-oriented frequency lists (as compared to general corpora frequency lists) are used as part of a lexical measure such as AG. the results from this research will be useful in teaching contexts where lexical proficiency is measured or assessed, and for materials and test developers who rely on such lists as being representative of known vocabulary at different levels of proficiency. this research applies data-driven exploration of learner corpora to vocabulary acquisition and pedagogy, thus closing a loop between educational data mining and classroom applications. © 2018 international Educational data Mining Society. All rights reserved.

关键词： data mining

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