In this paper the incipient fault detection problem in induction machine stator-winding is considered. The problem is solved using a new technique of change point detection in time series, based on a three-step formul...
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Photonic crystal cavities with tunable surface area via multiple-hole defects were investigated for increased resonance wavelength shifts upon exposure to variable-index analytes. Sensitivity was improved by 10% compa...
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Most biomedical and biological systems have nonlinear dynamics [25, 27], which bring difficulties in modelling and identification. These systems are usually represented as a series of blocks, and each block stands for...
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A novel real-time patient-specific algorithm to predict epileptic seizures is proposed. The method is based on the analysis of the positive zero-crossing intervals in the scalp electroencephalogram (EEG), describing t...
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A novel real-time patient-specific algorithm to predict epileptic seizures is proposed. The method is based on the analysis of the positive zero-crossing intervals in the scalp electroencephalogram (EEG), describing the brain dynamics. In a moving-window analysis, the histogram of these intervals in each EEG epoch is computed, and the distribution of the histogram value in specific bins, selected using interictal and preictal references, is estimated based on the values obtained from the current epoch and the epochs of the last 5 min. The resulting distribution for each selected bin is then compared to two reference distributions (interictal and preictal), and a seizure prediction index is developed. Comparing this index with a patient-specific threshold for all EEG channels, a seizure prediction alarm is finally generated. The algorithm was tested on ~15.5 hours of multichannel scalp EEG recordings from three patients with temporal lobe epilepsy, including 14 seizures. 86% of seizures were predicted with an average prediction time of 20.8 min and a false prediction rate of 0.12/hr.
Using asymmetrical non-adiabatic tapers we excite 3 modes in an etched-core-fiber-Bragg-grating sensor and show that the refractive index, temperature and strain can be measured simultaneously in bio-chemical sensing ...
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Using asymmetrical non-adiabatic tapers we excite 3 modes in an etched-core-fiber-Bragg-grating sensor and show that the refractive index, temperature and strain can be measured simultaneously in bio-chemical sensing experiments.
This paper introduces a new cantilever type multi-source energy harvester generating electric power from both ambient heat and vibration. Harvesting energy from vibration was realized by electromagnetic conversion, wh...
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This paper introduces a new cantilever type multi-source energy harvester generating electric power from both ambient heat and vibration. Harvesting energy from vibration was realized by electromagnetic conversion, whereas the energy generation from heat was supplied by making use of Seebeck effect of Cr–Al thermocouples implemented on the microcantilevers. The measured average Seebeck coefficient is 12 μV/K per thermocouple. A total voltage of 3.3 mV was generated from the thermoelectric part and 13.4 mV from the electromagnetic part of the device. Measured total power from the fabricated chip is 1.91 nW (1.12 nW from vibration, 0.79 nW from thermoelectric).
An automated diagnosis procedure based on a statistical machine learning methodology using electroencephalograph (EEG) data is proposed for diagnosis of psychiatric illness. First, a large collection of candidate feat...
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An automated diagnosis procedure based on a statistical machine learning methodology using electroencephalograph (EEG) data is proposed for diagnosis of psychiatric illness. First, a large collection of candidate features, mostly consisting of various statistical quantities, are calculated from the subject's EEG. This large set of candidate features is then reduced into a much smaller set of most relevant features using a feature selection procedure. The selected features are then used to evaluate the class likelihoods, through the use of a mixture of factor analysis (MFA) statistical model. In a training set of 207 subjects, including 64 subjects with major depressive disorder (MDD), 40 subjects with chronic schizophrenia, 12 subjects with bipolar depression and 91 normal or healthy subjects, the average correct diagnosis rate attained using the proposed method is over 85%, as determined by various cross-validation experiments. The promise is that, with further development, the proposed methodology could serve as a valuable adjunctive tool for the medical practitioner.
Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains....
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Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains. Previous researches in semantic web related applications have deployed various semantic similarity measures. Despite the usefulness of the measurements in those applications, measuring semantic similarity between two terms remains a challenge task. The proposed method exploits page counts returned by the Web Search Engine. We define various similarity scores for two given terms P and Q, using the page counts for querying P, Q and P AND Q. Moreover, we propose a novel approach to compute semantic similarity using lexico-syntactic patterns with page counts. These different similarity scores are integrated adapting support vector machines, to leverage the robustness of semantic similarity measures. Experimental results on two datasets achieve correlation coefficients of 0.798 on the dataset provided by A. Hliaoutakis, 0.705 on the dataset provide by T. Pedersen with physician scores and 0.496 on the dataset provided by T. Pedersen et al. with expert scores.
Core-shell CdSe-ZnS quantum dots have been one of the most actively researched nanomaterials in the past decade. In this paper we introduce thiophene thiol (TPT) as a capping ligand on the CdSe-ZnS heterostructure. Th...
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ISBN:
(纸本)9781424458547
Core-shell CdSe-ZnS quantum dots have been one of the most actively researched nanomaterials in the past decade. In this paper we introduce thiophene thiol (TPT) as a capping ligand on the CdSe-ZnS heterostructure. These conjugated ligands allow for improved carrier transport in comparison to their saturated, long chain hydrocarbon counterparts. By demonstrating a robust and inexpensive method to deposit close packed monolayers of these nanostructures, we hope to open the door for a new family of low cost inorganic devices employing them.
There exists a need for additional transmission capacity to connect distributed resources such as wind energy from remote locations to the power grid. The high cost of running transmission lines necessitates having a ...
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ISBN:
(纸本)9781424465460
There exists a need for additional transmission capacity to connect distributed resources such as wind energy from remote locations to the power grid. The high cost of running transmission lines necessitates having a way to minimize the length of transmission required to connect the distributed resources to load centers. In addition, the substations that connect to the transmission lines need to be fault tolerant by ensuring that the loss of any one transmission line does not result in the loss of power to any substation. In this paper, the relative cost of connecting a range of sources to a range of loads with and without fault tolerance is presented. Fault tolerance is achieved through a 2-path redundant graph approach. Studies show that the additional cost of ensuring fault tolerance for selected schemes ranges between 8% and 33%. This percentage value can support decision making in practice.
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