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检索条件"任意字段=International Conference on WWW/Internet 2017 and Applied Computing 2017"

共 177 条记录，以下是51-60 订阅

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Factors favoring the development of educational apps. Usability study of mobile applications to teach programming

Factors favoring the development of educational apps. Usabil...

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international conference on www/internet 2017 and applied computing 2017

作者： García-Iruela, Miguel Hijón-Neira, Raquel Department of Computing Science Universidad Rey Juan Carlos Mostoles Madrid Spain

ISBN: (纸本)9789898533692

The use of smart-phones and tablets has had a big impact on our habits of handling interactive applications. These devices provide us with plenty of information to consult whenever we want. Developing an application is not difficult even lacking a high level of programming. However, creating high-quality application with good usability and the capacity of engaging the users is doubtless a more demanding task. This article shows the usability study of two educational apps created to teach programming and the experiences carried out with students from university and vocational training. The experiences took place in two countries, within an interval of three years. Through the experiences, we identified several very suitable factors in the development of educational apps, especially in teaching programming. © 2017.

关键词： Smartphones

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Message from the CPSCom-2017 Program Chairs

Proceedings - 2017 IEEE International Conference on Internet...

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Proceedings - 2017 IEEE international conference on internet of Things, IEEE Green computing and Communications, IEEE Cyber, Physical and Social computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017 2018年 2018-January卷 xix页

作者： Ni, Qiang Choudhary, Alok N. Ntalianis, Klimis Yu, Hui Lancaster University United Kingdom Northwestern University United States Athens University of Applied Sciences Greece University of Portsmouth United Kingdom

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An Energy-image based Multi-unit Power Load Forecasting System 1

An Energy-image based Multi-unit Power Load Forecasting Syst...

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IEEE international conference on Industrial internet (ICII)

作者： Tang, Chengpei Wang, Shanqing Zhou, Chancheng Zheng, Xiaolong Li, Hua Shi, Xiangjian Sun Yat Sen Univ Sch Engn Guangzhou Peoples R China Sun Yat Sen Univ Sch Data & Comp Sci Guangzhou Peoples R China Beijing Univ Posts & Telecommun Sch Comp Sci Beijing Peoples R China NR Elect Co Ltd Nanjing Peoples R China

ISBN: (纸本)9781538677711

Electric energy is one of the most important energy sources for modern industry. The electrical power system is expected to achieve the dynamic balance between electricity generation and electricity consumption, to avoid thriftless excessive generation or power shortage. In this paper, we propose EM-MY, an energy-image based multi-unit power load forecasting system that applies internet of Things (IoT) techniques on traditional electricity industry. To solve the inaccuracy caused by the diversity of unit power consumption, EM-PLE exploits multiple models to predict the power loads of different units in a factory. To gather the prediction supporting data, we design an embedded device platform to collect the fine-grained power consumption as energy-image snapshots. We also propose the power load prediction algorithm based on Long Short-Term Memory (LSTM) neural network, taking the time correlation of power loads into consideration. We implement and run our system in a real-world factory for more than one year and evaluate its performance with a 500-day real operation data set. The results demonstrate that EM-PLE significantly improves the prediction accuracy.

关键词： Terms Electric data Energy-image system Long Short-Term Memory neural network Cloud computing

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A lexical and semantical analysis on REST cloud computing APIs 1

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7th international conference on Cloud computing and Service Science, CLOSER 2017

作者： Petrillo, Fabio Merle, Philippe Palma, Francis Moha, Naouel Guéhéneuc, Yann-Gaël Concordia University Montréal Canada Inria Lille - Nord Europe Villeneuve d’Ascq France Linnaeus University Växjö Sweden Université du Québec à Montréal Montréal Canada

ISBN: (数字)9783319949598

ISBN: (纸本)9783319949581

Cloud computing is a popular internet-based computing paradigm that provides on-demand computational services and resources, generally offered by Cloud providers’ REpresentational State Transfer (REST) APIs. Developers use REST APIs by invoking these APIs by their names and, thus, the lexicons used in the APIs are important to ease the developers’ comprehension. In this paper, we study the lexicons and the linguistic (anti)patterns from 16 providers of REST Cloud computing APIs. We observe that, although the 16 REST APIs describe the same domain (Cloud computing), contrary to what one might expect, their lexicons do not share a large number of common terms and 90% of the terms (3,561/3,947) are just used by one provider. Thus, the APIs are lexically heterogeneous and there is not a consensus on which terms to use in Cloud computing. Further, we observe that the majority of the URIs, 54%, follow the Contextualised Resource Names pattern, which is considered a good practice in REST API design. However, a majority of the URIs, 62.82%, suffer from the Non-pertinent Documentation antipattern. Thus, we present three main contributions: (1) a tooled approach, called CloudLex, for extracting and analysing REST Cloud computing lexicons;(2) our analysis of the terms used in 16 REST APIs in 59,677 term occurrences;(3) our analysis of the linguistic (anti)patterns in more than 23,000 URIs of the 142 services of the 16 Cloud providers. We also show that CloudLex has an average precision of 84.82%, recall of 63.57%, and F1-measure of 71.03% on one complete API, Docker Engine, which confirms the accuracy of our semantic analyses for the detection of linguistic (anti)patterns. © Springer international Publishing AG, part of Springer Nature 2018.

关键词： Cloud computing

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Dynamically generating NOSQL data schemas using archetypes

Dynamically generating NOSQL data schemas using archetypes

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international conference on www/internet 2017 and applied computing 2017

作者： De Araújo, André Magno Costa Times, Valéria Cesário Da Silva, Marcus Urbano Center for Informatics Federal University of Pernambuco Av.Jornalista Anibal Fernandess/n-Cidade Universitaria Recife Brazil

ISBN: (纸本)9789898533692

The creation of databases for Electronic Health Records (EHR) has traditionally been done through relational database management systems (RDBMS). Using relational databases guarantees a referential integrity of the data, however, it hinders the extension and evolution of the data schemas due to the constant changes in the clinical concepts of the healthcare sector. This article presents a cloud service that dynamically creates NoSQL data schemas from a health informatics standard (i.e., openEHR archetype) that homogenizes data attributes, terminologies and EHR constraints. In order to achieve this, we designed a cloud architecture and specified a set of algorithms that demonstrate how NoSQL data schemas are generated in document and column family paradigms from reading archetypes. To validate the proposed service, we generate NoSQL data schemas from openEHR repository archetypes, and process a set of write-and-read data transactions on the generated data schemas. © 2017.

关键词： Cloud computing architecture

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Automatic improvement of terms used in focused crawling processes on web pages

Automatic improvement of terms used in focused crawling proc...

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international conference on www/internet 2017 and applied computing 2017

作者： Costa, Gilson Faria De Assis, Guilherme Tavares Souza, Marcos Vinicius Oliveira Department of Computing Universidade Federal de Ouro Preto Ouro Preto MG Brazil

ISBN: (纸本)9789898533692

The great popularity and, specially, the fast Web growth have led to the proposal and analysis of new techniques for helping users to locate effectively the needed information in a satisfactory time, without much difficulty. Traditional crawlers are not capable to identify relevant sub-spaces on Web related to a specific theme;however, focused crawlers are capable to solve, effectively and efficiently, the mentioned problem. Usually, a focused crawler process requires, as an input parameter, a well-defined set of terms that express the desired topic of interest;depending on such set of terms, the effectiveness of a crawling process may not be satisfactory. In order to automatically improve the set of terms necessary to perform focused crawling processes related to a genre-aware approach, we propose two strategies in this work. Our experiments generated results that improved precision and F1 measures by up to 88.9% and 32.1%, respectively, in crawling processes that considered not well-defined sets of terms as input parameter. © 2017.

关键词： Websites

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Modeling data cleaning techniques for big data

Modeling data cleaning techniques for big data

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international conference on www/internet 2017 and applied computing 2017

作者： Martinez-Mosquera, Diana Luján-Mora, Sergio Parra, Fidel Departamento de Ciencias de la Ingeniería Universidad Israel Quito Ecuador Department of Software and Computing Systems University of Alicante Alicante Spain

ISBN: (纸本)9789898533692

Big Data is currently a popular term, it focuses on high volumes of data processed into relevant information to assist in decision making. A few researches about data cleaning techniques have been adapted to Big Data and we consider that filtering irrelevant data is an important task aimed to reduce hardware and processing time requirements. Moreover, there are separate researches about data cleaning processes in Big Data, thus, our approach proposes to model techniques used for this intent. Since logs can be considered as Big Data we have modeled two different approaches, one to clean a firewall log in a vertical dimension and another to clean a web log in a horizontal dimension. An advantage of our proposal is the use of the Unified Modeling Language, an international Organization for Standardization standard widely accepted since 2005. Consequently, the data cleaning process is composed by logical units that can be replaced or modified by the designer. Thus, the examples demonstrate the integration possibility of several clustering techniques, for example, Levenshtein Distance, Longitudinal Distance, Transposition Invariant Distance, Word Position Invariant Distance, etc. © 2017.

关键词： Big data

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Using GPGPU Accelerated Interpolation Algorithms for Marine Bathymetry Processing with On-Premises and Cloud Based Computational Resources 12th

Using GPGPU Accelerated Interpolation Algorithms for Marine ...

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12th international conference on Parallel Processing and applied Mathematics (PPAM)

作者： Marcellino, Livia Montella, Raffaele Kosta, Sokol Galletti, Ardelio Di Luccio, Diana Santopietro, Vincenzo Ruggieri, Mario Lapegna, Marco D'Amore, Luisa Laccetti, Giuliano Univ Napoli Parthenope Dept Sci & Technol Naples Italy Univ Napoli Federico II Dept Math & Applicat Naples Italy Aalborg Univ CMI Copenhagen Denmark

ISBN: (纸本)9783319780542;9783319780535

Data crowdsourcing is one of most remarkable results of pervasive and internet connected low-power devices making diverse and different "things" as a world wide distributed system. This paper is focused on a vertical application of GPGPU virtualization software exploitation targeted on high performance geographical data interpolation. We present an innovative implementation of the Inverse Distance Weight (IDW) interpolation algorithm leveraging on CUDA GPGPUs. We perform tests in both physical and virtualized environments in order to demonstrate the potential scalability in production. We present an use case related to high resolution bathymetry interpolation in a crowdsource data context.

关键词： GPGPU Virtualization High performance computing Geographic data Interpolation

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Journal of Physics: conference Series

Journal of Physics: Conference Series

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2nd international conference on computing and applied Informatics 2017, ICCAI 2017

The proceedings contain 124 papers. The topics discussed include: improved line segmentation framework for Sundanese old manuscripts;automated color classification of urine dipstick image in urine examination;designing Indonesian teacher engagement index (ITEI) applications based on Android;performance test for prototype game for children with ADHD;usability testing of Indonesia tourism promotion website;Vi-da: vitiligo diagnostic assistance mobile application;the development of Indonesian traditional Bekel game in Android platform;diagnostics vehicle's condition using OBD-II and Raspberry Pi technology: study literature;Indonesia knowledge dissemination: a snapshot;usability evaluation of user interface of thesis title review system;implementation of Utaut model to understand the use of virtual classroom principle in higher education;supply chain management using FP-growth algorithm for medicine distribution;automated hydroponics nutrition plants systems using Arduino uno microcontroller based on android;application modeling IPv6 (internet protocol version 6) on E-ID card for identification number for effectiveness and efficiency of registration process identification of population;and Real-time detection with AdaBoost-SVM combination in various face orientation;and delay and cost performance analysis of the Diffie-Hellman key exchange protocol in opportunistic mobile networks.

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15th international conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2017

15th International Conference on Practical Applications of A...

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15th international conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2017

ISBN: (纸本)9783319615776

The proceedings contain 54 papers. The special focus in this conference is on Practical Applications of Agents and Multi-Agent Systems. The topics include: Understanding homophily and more-becomes-more through adaptive temporal-causal network models;towards a framework for agent-based simulation of user behaviour in e-commerce context;low cost architecture of autonomous subsystems for internet of things;long term reliability analysis of a microgrid on isolated mode using CPN formalism;photovoltaic inverter scheduler with the support of storage unit to minimize electricity bill;real-time emulation and simulation system of asynchronous motor consumption;economic evaluation of predictive dispatch model in MAS-based smart home;gravitational search algorithm applied for residential demand response using real-time pricing;learning frequent behaviors patterns in intelligent environments for attentiveness level;indoor children location system using BLE technology;learning to colorize infrared images;automatic construction of domain-specific sentiment lexicons for polarity classification;a hash based image matching algorithm for social networks;using twitter data to monitor political campaigns and predict election results;applying data mining for sentiment analysis in music;acceleration of dissimilarity-based classification algorithms using multi-core computation;a study on IoT technologies in smart cities;malware propagation software for wireless sensor networks;new perspectives in the study of advanced persistent threats;towards modelling organisational dynamics for large-scale multiagent systems;active ageing agents;rethinking posts through emotion awareness;big data in efficient smart grids management and multisensor indoor location system.

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