To achieve fast charging at the current mainstream voltage levels of 800 V or 1000 V, a cascaded voltage source converter with higher voltage output capability has been proposed. However, current cascaded voltage sour...
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The work is devoted to the study issues of increasing the operational efficiency of information systems based on the utilization of various procedures for distributed software control of the flow of applications for p...
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ISBN:
(纸本)9781538664742
The work is devoted to the study issues of increasing the operational efficiency of information systems based on the utilization of various procedures for distributed software control of the flow of applications for providing information to consumers. One of the main tasks of information system control is to control parameters that characterize the functioning of the information system based on the formation of the distribution plan of applications for the provision of information services. The formed plan determines the predetermined priority for the selection of outgoing information directions for the application transfer from the node-receiver of information services to all other nodes. Various variants of requests streams distribution in the information system are based on global and local adaptation procedures.
Effective failure detection and diagnosis are crucial for ensuring that product requirements are met throughout the entire life cycle of mechatronic systems. An agile scenario analysis can help evaluate potential misb...
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Imagery data acquired by recently launched space borne SAR systems demonstrate a very good spatial resolution (e.g. one meter with TerraSAR-X). The designs of such complex systems make it compulsory to do SAR end-to-e...
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The segmentation algorithm described here, has the facility of locating contiguous bodies which are brighter (alternatively darker) than the immediate surrounding areas. The algorithm is based on the reconstruction al...
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The paper presents Echo State Network (ESN) as classifier to diagnose the abnormalities in mammogram images. Abnormalities in mammograms can be of different types. An efficient system which can handle these abnormalit...
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The paper presents Echo State Network (ESN) as classifier to diagnose the abnormalities in mammogram images. Abnormalities in mammograms can be of different types. An efficient system which can handle these abnormalities and draw correct diagnosis is vital. We experimented with wavelet and Local Energy based Shape Histogram (LESH) features combined with Echo State Network classifier. The suggested system produces high classification accuracy of 98% as well as high sensitivity and specificity rates. We compared the performance of ESN with Support Vector Machine (SVM) and other classifiers and results generated indicate that ESN can compete with benchmark classifier and in some cases beat them. The high rate of Sensitivity and Specificity also signifies the power of ESN classifier to detect positive and negative case correctly.
In this research, two types of mental disorders were studied: Major Depression Disorder (Depression) and Bipolar disorder (BP). We train the data on both binary/multi-class classification models through machine learni...
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ISBN:
(数字)9781728196381
ISBN:
(纸本)9781728196398
In this research, two types of mental disorders were studied: Major Depression Disorder (Depression) and Bipolar disorder (BP). We train the data on both binary/multi-class classification models through machine learning approaches and fuzzy clustering using statistical analysis as a probabilistic reference for the potential users to identify whether or not they potentially have certain types of mental disorders. In order to achieve our goal, we first gather the ICD-10 MDD 58 Depression and Control samples (GSE41826) and 72 BP and Control subjects (GSE129428). All groups, for both case and control groups, are collected by Infinium Methylation EPIC Bead Chip, where each sample consists of around 440,000 target CpGs over 23 chromosomes. we applied statistical procedures and identified differentially methylated loci (DMLs) that have the most impact on diagnosis through DNA methylation. Furthermore, we use Principal Component Analysis (PCA) to project the selected 6000 CpGs into 50 Principal Components (PCs). Based on the top three PCs, we then build and test several binary/multi classification models. These advances can provide insights for the development of new methods that can diagnose multiple mental diseases at one time. we construct a Phonogram, denoting the overlapping CpG islands that the two diseases have in common from the predicting features for the diagnosis of diseases. Also, disease ontology analysis was conducted on our data to build up these relationships through web-based DO Analysis tools, Visualization, and Integrated Discovery (DAVID). With the accuracy rates returned from the above models, we can prove the meaningfulness of our models in practical use and relate these features of the models with other diseases that have already been proven to have relationships with certain types of genes referenced by CpG islands.
Controlling current in critical conduction mode (CRM) to achieve zero voltage switching (ZVS) of switches is an effective way to improve the efficiency and power density of inverters without additional hardware costs....
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Comparing and contrasting two things is one of the most basic ideas in science. While existing tools allow such comparisons for pairs (e.g. texts, trees, graphs, histograms), there are currently no such tools for time...
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ISBN:
(纸本)9781450370240
Comparing and contrasting two things is one of the most basic ideas in science. While existing tools allow such comparisons for pairs (e.g. texts, trees, graphs, histograms), there are currently no such tools for time series data. This is somewhat surprising, given the ubiquity of time series data in modern life. One could imagine a tool for comparing and contrasting two time series by reporting various summary statistics. However, scientists, engineers, and physicians typically communicate such findings in natural language. In this work we present Natura, a domain agnostic natural language framework for comparing and contrasting two time series, that aims to duplicate this human skill. Through case study, we demonstrate the effectiveness and utility of our framework.
It is usually difficult to resolve the fine details of turbulent flows, especially when targeting real-time applications. We present a novel, scalable turbulence method that uses a realistic energy model and an effici...
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