The new trend in the process of data-intensive management indicates the importance of a distributed file system for both Internet large scale services and cloud computing environments. I/O latency and application buff...
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ISBN:
(纸本)9781479904051
The new trend in the process of data-intensive management indicates the importance of a distributed file system for both Internet large scale services and cloud computing environments. I/O latency and application buffering sizes are two of a number of issues that are essential to be analysed on different class of distributed file systems. In this paper, it is presented a research work comparing four different high performance distributed file systems. Those systems were employed to support a medical image server application in a private storage environment. Experimental results highlight the importance of an appropriate distributed file system to provide a differential level of performance considering application specific characteristics.
Multi-hole defect (MHD) photonic crystal cavities functionalized with in situ synthesized DNA bioreceptors are demonstrated for biosensing applications. By significantly increasing light interaction with target biomol...
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For an automatic chromosome classification, band resolution information is required in order to perform diagnosis on numerical and structural abnormalities. Metaphases with low band resolution are normal used for nume...
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For an automatic chromosome classification, band resolution information is required in order to perform diagnosis on numerical and structural abnormalities. Metaphases with low band resolution are normal used for numerical abnormality analysis while metaphases with high band resolution are used for structural abnormality analysis. In our work, we classify metaphases into low and high band resolution groups using chromosome shape. This band classification task can automatically perform without human intervention leading to faster the diagnosis process. The results showed that chromosome shape information is able to classify metaphases into low and high band resolution groups with the accuracy of 73.08% and 95.24%, respectively.
This work proposes a topology of compensator with the purpose of compensate harmonics and reactive loads or supply the load with balanced three-phase voltages, even when the grid voltage presents harmonics. The topolo...
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ISBN:
(纸本)9781479902712
This work proposes a topology of compensator with the purpose of compensate harmonics and reactive loads or supply the load with balanced three-phase voltages, even when the grid voltage presents harmonics. The topologies have two operation modes. Mode A: acting as shunt active power filter and mode B: acting as ac-dc-ac converter. The model of the system is derived and a suitable control strategy, including the PWM technique, is developed. Experimental results are presented, as well.
This paper presents an approach for speeding up the convergence of adaptive intelligent agents using reinforcement learning algorithms. Speeding up the learning of an intelligent agent is a complex task since the choi...
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ISBN:
(纸本)9789898565105
This paper presents an approach for speeding up the convergence of adaptive intelligent agents using reinforcement learning algorithms. Speeding up the learning of an intelligent agent is a complex task since the choice of inadequate updating techniques may cause delays in the learning process or even induce an unexpected acceleration that causes the agent to converge to a non-satisfactory policy. We have developed a technique for estimating policies which combines instance-based learning and reinforcement learning algorithms in Markovian environments. Experimental results in dynamic environments of different dimensions have shown that the proposed technique is able to speed up the convergence of the agents while achieving optimal action policies, avoiding problems of classical reinforcement learning approaches.
The amount of data generated in different knowledge areas has made it necessary the use of data mining tools capable of automatically analyzing and extracting knowledge from datasets. Clustering is one of the most imp...
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ISBN:
(纸本)9781479904532
The amount of data generated in different knowledge areas has made it necessary the use of data mining tools capable of automatically analyzing and extracting knowledge from datasets. Clustering is one of the most important tasks in data mining and can be defined as the process of partitioning objects into groups or clusters, such that objects in the same group are more similar to one another than to objects belonging to other groups. In this context, this paper aims to propose an adaptation of a bee-inspired optimization algorithm so that it is able to solve data clustering problems. The algorithm was run for different datasets and the results obtained showed high quality clusters and diversity of solutions, whilst a suitable number of clusters was automatically determined.
We created an online development environment, specifically for educational robotics applications, in which it is possible to register programming languages associated with different robotic platforms, so that the user...
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We created an online development environment, specifically for educational robotics applications, in which it is possible to register programming languages associated with different robotic platforms, so that the user program a robot using the registered language or the language R-Educ, developed for teaching programming. To validate the platform, we conducted a series of tests divided into six steps to verify that the complete cycle was satisfied - registering a language, program in R-Educ, compile to the registered language, compile to machine code and send the code for the robot.
In this paper we describe an extension to the MATLAB Phased Array Toolkit that adds a configurable clutter object to model clutter signals returned along a specified signal path. The clutter model is based on the Simk...
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We report on a nearly 8-fold increase in multi-hole defect photonic crystal biosensor response by incorporating insitu synthesis of DNA probes, as compared to the conventional functionalization method employing pre-sy...
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We report on a nearly 8-fold increase in multi-hole defect photonic crystal biosensor response by incorporating insitu synthesis of DNA probes, as compared to the conventional functionalization method employing pre-synthesized DNA probe immobilization.
In this paper we describe a novel clutter cancellation platform based on a two stage approach that combines a feedback guided predictive front-end hybrid clutter canceller with high performance back-end filtering and ...
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