Single-molecule super-resolution imaging and tracking can measure molecular motions inside living cells on the scale of the molecules themselves. Diffusion in biological systems commonly exhibits multiple modes of mot...
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Single-molecule super-resolution imaging and tracking can measure molecular motions inside living cells on the scale of the molecules themselves. Diffusion in biological systems commonly exhibits multiple modes of motion, which can be effectively quantified by fitting the cumulative probability distribution of the squared step sizes in a two-step fitting process. Here we combine this two-step fit into a single least-squares minimization;this new method vastly reduces the total number of fitting parameters and increases the precision with which diffusion may be measured. We demonstrate this Global Fit approach on a simulated two-component system as well as on a mixture of diffusing 80 nm and 200 nm gold spheres to show improvements in fitting robustness and localization precision compared to the traditional Local Fit algorithm. (C) 2017 Elsevier B.V. All rights reserved.
In this paper we survey static analysis methods for identifying security vulnerabilities in software systems. We cover three areas that have been associated with sources of security vulnerabilities: access-control, in...
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In this paper we survey static analysis methods for identifying security vulnerabilities in software systems. We cover three areas that have been associated with sources of security vulnerabilities: access-control, information-flow, and application-programming-interface conformance. Because access control mechanisms fall into two major categories, stack-based access control and role-based access control, we discuss static analysis techniques for these two areas of access control separately. Similarly, security violations pertaining to information flow consist of integrity violations and confidentiality violations, and consequently, our discussion of static analysis techniques for information-flow vulnerabilities includes these two topics. For each type of security vulnerability we present our findings in two parts: in the first part we describe recent research results, and in the second part we illustrate implementation techniques by describing selected static analysis algorithms.
In this paper, we propose a risk analysis model to obtain the probability of default of microfinance clients in Peru. Our model uses trends of predictive analysis through variants of neural network algorithms;and data...
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ISBN:
(纸本)9781728147468
In this paper, we propose a risk analysis model to obtain the probability of default of microfinance clients in Peru. Our model uses trends of predictive analysis through variants of neural network algorithms;and data processing methodologies such as the Knowledge Discovery in Databases (KDD). The analysis method is used through Bayesian networks which allows the customer data evaluation and is related to our model data. This model is composed of 5 phases: 1. The input elements for the analysis;2. The process of evaluation and analysis;3. The regulatory standards;4. The technological architecture;5. The output elements. This model allows knowing the probability of compliance of a client with 84% prediction accuracy. The model validation was carried out in a microfinance institution in Lima, Peru, using cross-validation, evaluating the sensitivity and specificity of the results.
This paper describes an integrated approach for supporting packet network performance management and planning. As more and more packet networks — such as the public packet switched networks, common channel signalling...
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This paper describes an integrated approach for supporting packet network performance management and planning. As more and more packet networks — such as the public packet switched networks, common channel signalling networks and metropolitan area networks — are being deployed in the Regional Bell Operating Companies, new network operations systems are required for planning the evolution and engineering the service performance of these traffic-sensitive packet networks. This paper describes some of the synthesis and analysis algorithms that we have designed for supporting the traffic engineering of a public packet switched network. The synthesis algorithms include network element sizing, processor load balancing, network layer window size adjustment and traffic rerouting. The analysis algorithms include network element utilization and delay estimation as well as network end-to-end delay estimation.
We present the calibration and performance tests carried out with two detectors for intense proton pulses accelerated by lasers. Most of the procedures were realized with proton beams of 0.46-5.60 MeV from a tandem ac...
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Fetal magnetocardiography (fMCG) is a noninvasive technique suitable for the prenatal diagnosis of the fetal heart function. Reliable fetal cardiac signals can be reconstructed from multi-channel fMCG recordings by me...
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Fetal magnetocardiography (fMCG) is a noninvasive technique suitable for the prenatal diagnosis of the fetal heart function. Reliable fetal cardiac signals can be reconstructed from multi-channel fMCG recordings by means of independent component analysis (ICA). However, the identification of the separated components is usually accomplished by visual inspection. This paper discusses a novel automated system based on entropy estimators, namely approximate entropy (ApEn) and sample entropy (SampEn), for the classification of independent components (ICs). The system was validated on 40 fMCG datasets of normal fetuses with the gestational age ranging from 22 to 37 weeks. Both ApEn and SampEn were able to measure the stability and predictability of the physiological signals separated with ICA, and the entropy values of the three categories were significantly different at p < 0.01. The system performances were compared with those of a method based on the analysis of the time and frequency content of the components. The outcomes of this study showed a superior performance of the entropy-based system, in particular for early gestation, with an overall ICs detection rate of 98.75% and 97.92% for ApEn and SampEn respectively, as against a value of 94.50% obtained with the time-frequency-based system.
An erasable programmable read-only memory (EPROM) contour generator has been fabricated to produce contours for use in flow cytometry. Contours are analog waveforms representing the fluorescence or light-scatter inten...
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An erasable programmable read-only memory (EPROM) contour generator has been fabricated to produce contours for use in flow cytometry. Contours are analog waveforms representing the fluorescence or light-scatter intensity distribution along a cell or object. The generator has particular utility in the development and testing of slit-scan instrumentation and analysis algorithms. Contours are generated without the requirement of specimens or full operation of the flow instrumentation. The generator provides control of contour height, width, offset, and rate. The EPROM may be custom programmed to produced contours for specific test applications or for reproducing "real" contour events. The generator is useful in situations where constant repetitive contours of predetermined characteristics are required.
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