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 i...
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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 av...
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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.
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. Develope...
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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 da...
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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 diff...
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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 ...
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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...
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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.
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;designin...
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.
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 adaptiv...
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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