In this study, brain, and gait dynamic information were combined and used for diagnosis and monitoring of Parkinson's disease (the most important Neurodegenerative Disorder). Analysis of the information correspond...
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In this study, brain, and gait dynamic information were combined and used for diagnosis and monitoring of Parkinson's disease (the most important Neurodegenerative Disorder). Analysis of the information corresponding to a prescribed movement involving tremor, and the related changes in brain connectivity is novel and original. Analytically, developing a space-time nonlinear adaptive system which fuses brain and gait information algorithmically is proposed here for the first time. The overall dynamic system will be constrained by the clinical impressions of the patient symptoms embedded in a knowledge-based system. The entire complex constrained problem were solved to enable a powerful model for recognition and monitoring of Parkinson's disease and establishing appropriate rules for its clinical following up.
In recent years, we are seeing an important increase in network interface transmission rates. This poses a challenge to come up with better methods of mitigating latency at all levels in a computer system. In this pap...
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In recent years, we are seeing an important increase in network interface transmission rates. This poses a challenge to come up with better methods of mitigating latency at all levels in a computer system. In this paper, we propose an approach that works well in systems where scatter-gather transfers are fast compared to memory accesses. We note that, in a Transport level flow, a large part of the Network and Data Link layer headers do not vary. As a result, we assert that it is favorable to store the parts of the header that do not vary, instead of copying them from the socket data structure to the packet buffer for each packet transmission. The network interface then uses scatter-gather to assemble the network packet without explicitly copying data in memory. This approach was partially implemented, but we propose extending it from the Data Link to the superior Network level, hoping that it will aid in lessening the load on legacy hardware at high packet transmission rates.
Texture classification, texture synthesis, or similar tasks are an active topic in computer vision and pattern recognition. This paper aims to present two spatial pyramid representations for texture classification. Mo...
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Texture classification, texture synthesis, or similar tasks are an active topic in computer vision and pattern recognition. This paper aims to present two spatial pyramid representations for texture classification. Most techniques designed for texture classification are based on machine learning. Images are usually represented as feature vectors, which are then used to train a classifier. In the spatial pyramid representation, images are divided into increasingly fine sub-regions (bins) and features are extracted from each bin. This representation is able to capture details about the fractal structure of the texture images. Two experiments are conducted on popular texture classification data sets, namely Brodatz and UIUCTex. In the experiments, several kernel representations and kernel classifiers are combined and evaluated. It seems that the spatial pyramid in combination with intersection kernel and Kernel Discriminant Analysis gives the best results. The proposed pyramid representations can improve the accuracy by as much as 5% over the standard feature representation, showing that the pyramid structure is indeed useful for texture classification.
In this paper we study state-space realizations of Linear and Time-Invariant (LTI) systems. Motivated by biochemical reaction networks, Gonçalves and Warnick have recently introduced the notion of a Dynamical Str...
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Cloud computing becomes more and more popular providing the means to organize and deliver almost any kind of data and software services. Since it is inherently scalable to support rapid economic growth and productivit...
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ISBN:
(纸本)9781479907342
Cloud computing becomes more and more popular providing the means to organize and deliver almost any kind of data and software services. Since it is inherently scalable to support rapid economic growth and productivity, its distributed data storage layer needs to be capable to address these requirements. A distributed file system contains a large number of cluster nodes and a large number of clients interacting with it. In this article, we propose two acceleration mechanisms based on multi-core network SoC to maximize each cluster node performance. First, the requests to the cluster node are balanced evenly on the platform cores, and second the requests are classified to decrease latency of sensitive operations and improve the overall cluster responsiveness and availability. For implementation, tests and measurements we have used a novel open source distributed file system: Ceph. Among many advantages over the competitors of Ceph we mention preservation of POSIX API, completely decoupled data and metadata and usage of object storage devices instead of block devices.
Passive Infrared Sensors (PIR) are inexpensive devices widely used as motion detectors. Standard sensor provides just trigger signal on movement detection. This paper aims to extend standard usage of the sensor from m...
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ISBN:
(纸本)9781479902255
Passive Infrared Sensors (PIR) are inexpensive devices widely used as motion detectors. Standard sensor provides just trigger signal on movement detection. This paper aims to extend standard usage of the sensor from motion detection to motion recognition and activity classification. In applications where motion detection based on video surveillance is not possible due regulations or high costs smart PIR sensor could be the only solution. This publication starts the topic of PIR based motion classification with analyses of hardware requirements and hardware selection for the smart sensor.
Modern sensing technologies create new possibilities to control mobile robots without any dedicated manipulators. In this article authors present a novel method that enables driving of the Mindstorms NXT artificial ar...
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Modern sensing technologies create new possibilities to control mobile robots without any dedicated manipulators. In this article authors present a novel method that enables driving of the Mindstorms NXT artificial arm with Microsoft Kinect, using gesture recognition. To imitate movement of an artificial robotic arm, an algorithm of the human-computer interaction is employed using skeleton tracking and gesture control in 3D space.
This paper deals with human action classification by utilizing spatio-temporal (ST) co-occurrences between labels of video-words that are stored within ST correlo-grams. Mutual information based clustering method is e...
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Results of scientific research works considering selection of measuring transducer applied for registration of acoustic emission signals generated by on load tap changers are presented in the paper. During the couplin...
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Results of scientific research works considering selection of measuring transducer applied for registration of acoustic emission signals generated by on load tap changers are presented in the paper. During the coupling process acoustic emission signals are generated by: the mechanical setup of tap changer, contacts operation, and other phenomena. For most on load tap changers types, the working medium is insulation oil in which the acoustic wave being formed propagates to the steal tank. There exists a possibility to register acoustic emission signals with a piezoelectric transducer attached to the outer tank surface or with a hydrophone immersed in the oil. Acoustic emission signal obtained in such manner contains information which describes operation of the power tap changer and the selector. A comparative analysis of acoustic emission signals generated by on load tap changers working under laboratory conditions, with applied measuring transducers with different transmittances, is presented in the paper. The comparative analysis was performed in order to determine their suitability for on load tap changers technical condition diagnosis. Based on the results achieved, one transducer which allows the registration of acoustic events generated during on load tap changers operation was selected.
A new adaptive comb filtering algorithm, capable of tracking the fundamental frequency and amplitudes of different frequency components of a nonstationary harmonic signal embedded in white measurement noise, is propos...
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A new adaptive comb filtering algorithm, capable of tracking the fundamental frequency and amplitudes of different frequency components of a nonstationary harmonic signal embedded in white measurement noise, is proposed. Frequency tracking characteristics of the new scheme are studied analytically, proving (under Gaussian assumptions and optimal tuning) its statistical efficiency for quasi-linear frequency changes. Laboratory tests show that the proposed algorithm can be successfully used for active control of MRI noise.
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