This paper presents effective mathematical description models, methods, algorithms, software and intelligent geoinformation technologies for processing, storage, analysis, recognition, 3D modeling and visualization of...
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ISBN:
(纸本)9781538675311
This paper presents effective mathematical description models, methods, algorithms, software and intelligent geoinformation technologies for processing, storage, analysis, recognition, 3D modeling and visualization of large volumes of Earth remote sensing data and other heterogeneous thematic information of spatially distributed data, including hyperspectral data used in geoinformation systems.
Data partition and replication mechanisms directly determine query execution patterns in parallel database systems. which have a great impact on system performance. Recently, there have been some workload-aware data s...
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Heterogeneous distributedsystems.(HDS) provides service to users executed on a set of geographically heterogeneous distributed resources with dynamic nature. In HDS, load balancing approaches has a vital role in task...
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This paper introduces a weighted consensus control for multi-drone system for power line inspection in a dynamic networked computing environment. The system achieves global load balancing by transferring data with nei...
ISBN:
(数字)9781728116754
ISBN:
(纸本)9781728116761
This paper introduces a weighted consensus control for multi-drone system for power line inspection in a dynamic networked computing environment. The system achieves global load balancing by transferring data with neighbor drones. Algorithms are introduced and their robustness properties against system dynamics are established. Examples and case studies demonstrate the feasibility in power line fault detection applications using multi-drone systems.
Geographically distributed data centers (GDCs) serving as infrastructures for cloud services, are growing in both number and scale. They usually consume enormous amount of electric power, which lead to high operationa...
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ISBN:
(纸本)9781538663509
Geographically distributed data centers (GDCs) serving as infrastructures for cloud services, are growing in both number and scale. They usually consume enormous amount of electric power, which lead to high operational costs and this has been recognized as a main challenge in cloud computing. Energy cost can be reduced by directing the requests to the favor of data center with lower electricity price by incorporating spatially and temporally price diversity, especially in the multi-region electricity markets. If the electricity prices of data centers are predicted in advance, the cloud provider can reduce energy cost. An efficient electricity price prediction is needed for minimizing electricity bill of GDCs. This paper proposes electricity price prediction for GDCs in multi-region electricity markets. Experiment is conducted on real-life electricity price data sets with machine learning algorithms. By comparatively assessing the prediction accuracy of the models, the most accurate one is selected. Experiment results show that the prediction model can provide promising accuracy.
The proceedings contain 140 papers. The topics discussed include: implementation of green IT In education industries;multi-facet analysis of technology-enhanced learning;batik pattern identification using GLCM and art...
ISBN:
(纸本)9781538669204
The proceedings contain 140 papers. The topics discussed include: implementation of green IT In education industries;multi-facet analysis of technology-enhanced learning;batik pattern identification using GLCM and artificial neural network backpropagation;SPOT: a low cost intelligent parking system for urban malls;application development based on mobile learning framework on rice and vegetable agriculture;a collaborative process scheme in strategic information systems.planning;android-based text recognition on receipt bill for tax sampling system;automatic time-based learning type analysis towards dynamic personalization;the physical and engineering requirements of scalable, decentralized, distributed, large-scale MIMO;design of orchid monitoring system based on IoT;and influence of blended learning on learning result of algorithm and programming.
The distributed estimator will need lower communication bandwidth and computational resources. Consequently, the distributed estimator using wireless sensor networks increases in the reliability, robustness and surviv...
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ISBN:
(纸本)9781538649855
The distributed estimator will need lower communication bandwidth and computational resources. Consequently, the distributed estimator using wireless sensor networks increases in the reliability, robustness and survivability of the system since subsystem do not need to transmit their unprocessed observations to the central station. In order to estimates the system states, we first expand nonlinear cyber physical systems.such as power system model using Tailor series then it uses extended Kalman Filter (EKF) to estimate the local system states. The coordinator estimator is linearly combined with the information received from local estimators with learning rate parameter.
The proceedings contain 96 papers. The topics discussed include: bike security with theft prevention;audio hiding in an image using steganographic methods;automated api testing;extended kalman filter based distributed...
ISBN:
(纸本)9781538649855
The proceedings contain 96 papers. The topics discussed include: bike security with theft prevention;audio hiding in an image using steganographic methods;automated api testing;extended kalman filter based distributed state estimation algorithm for cyber physical systems.review on application of machine learning algorithm for data science;a review of data mining & machine learning approaches for identifying risk factor contributing to likelihood of cardiovascular diseases;offloading with QOS in the mobile cloud computing environment;application of IoT in monitoring patient's health ward relevant parameters;hybrid solar and wind powered electric vehicle using sepic converter;design of MEMS sensor for the detection of diabetes;and hard and soft decision decoding using Viterbi algorithm.
There has been a growing interest in using smart grids due to their capability in delivering automated and distributed energy level to the consumption units. However, in order to guarantee the safe and reliable delive...
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The presence of bugs in a software release has become inevitable. The loss incurred by a company due to the presence of bugs in a software release is phenomenal. Modern methods of testing and debugging have shifted fo...
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