Search results for " Detection"
showing 10 items of 1676 documents
An analytical model of a new packet marking algorithm for TCP flows
2005
In Differentiated Services networks, packets may receive a different treatment according to their Differentiateo Services Code Point (DSCP) label. As a consequence, packet marking schemes can also be devised to differentiate packets belonging to a same TCP flow, with the goal of improving the performance experienced. This paper presents an analytical model for an adaptive packet marking scheme proposed in our previous work. The model combines three specific sub-models aimed at describing (i) the TCP sources aggregate, (ii) the marker, and (iii) the network status. Preliminary simulation results show quite accurate predictions for throughput and average queue occupancy. Besides, the research…
Robust fault detection design for unknown inputs Takagi-Sugeno models with parametric uncertainties and time-varying delays
2014
This paper deals with the design of robust fault detection system for Takagi-Sugeno (T-S) modes with parametric uncertainties and time-varying delay. An Unknown Input Observer (UIO) is designed such that the unknown inputs are thoroughly decoupled from residual signals while they show the maximum possible sensitivity to the faults and the minimum possible sensitivity to the external disturbances. Since the system under consideration is subjected to parametric uncertainties, the H ∞ model matching approach is used to design an optimal observer. Design procedure is given in terms of Linear Matrix Inequalities (LMIs). Finally, a numerical example is presented to show the effectiveness of the p…
Combined use of liquid chromatography triple quadrupole mass spectrometry and liquid chromatography quadrupole time-of-flight mass spectrometry in sy…
2012
As a suitable way for routine screening of pesticides and control of other organic contaminants in water, the combination of liquid chromatography triple quadrupole tandem mass spectrometry (LC-QqQ-MS/MS) and liquid chromatography-hybrid quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) has been applied to the analysis of 63 surface and waste water samples after conventional solid-phase extraction (SPE). The extracts were screened for 43 pesticides or degradation products by LC-QqQ-MS/MS achieving limits of detection (LOD) ranged from 0.04 to 2 ng L(-1). Of the 43 selected pesticides, 33 were detected in water samples. The ESI-QTOF MS instrument was run using two simultaneous acquisi…
Multi-feature Counting of Dense Crowd Image Based on Multi-column Convolutional Neural Network
2020
The crowd counting task is an important research problem. Now more and more people are concerned about safety issues. When the population density reaches a very high peak, the population density counts, the alarm is sent out, and the crowds are diverted. The trampling of the Shanghai New Year’s stampede will not happen again. The final density map is produced by two steps: at first, extract feature maps from multiple layers, and then adjust their output so that they are all the same size, all these resized layers are combined into the final density map. We also used texture features and target edge detection to reduce the loss of density map detail to better integrate with our convolutional…
Methods of Condition Monitoring and Fault Detection for Electrical Machines
2021
Nowadays, electrical machines and drive systems are playing an essential role in different applications. Eventually, various failures occur in long-term continuous operation. Due to the increased influence of such devices on industry, industrial branches, as well as ordinary human life, condition monitoring and timely fault diagnostics have gained a reasonable importance. In this review article, there are studied different diagnostic techniques that can be used for algorithms’ training and realization of predictive maintenance. Benefits and drawbacks of intelligent diagnostic techniques are highlighted. The most widespread faults of electrical machines are discussed as well as techniques fo…
PIECEWISE ANOMALY DETECTION USING MINIMAL LEARNING MACHINE FOR HYPERSPECTRAL IMAGES
2021
Abstract. Hyperspectral imaging, with its applications, offers promising tools for remote sensing and Earth observation. Recent development has increased the quality of the sensors. At the same time, the prices of the sensors are lowering. Anomaly detection is one of the popular remote sensing applications, which benefits from real-time solutions. A real-time solution has its limitations, for example, due to a large amount of hyperspectral data, platform’s (drones or a cube satellite) constraints on payload and processing capability. Other examples are the limitations of available energy and the complexity of the machine learning models. When anomalies are detected in real-time from the hyp…
Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer
2013
Journal article TERT-locus SNPs and leukocyte telomere measures are reportedly associated with risks of multiple cancers. Using the Illumina custom genotyping array iCOGs, we analyzed ~480 SNPs at the TERT locus in breast (n = 103,991), ovarian (n = 39,774) and BRCA1 mutation carrier (n = 11,705) cancer cases and controls. Leukocyte telomere measurements were also available for 53,724 participants. Most associations cluster into three independent peaks. The minor allele at the peak 1 SNP rs2736108 associates with longer telomeres (P = 5.8 × 10!-7), lower risks for estrogen receptor (ER)-negative (P = 1.0 × 10!-8) and BRCA1 mutation carrier (P = 1.1 × 10!-5) breast cancers and altered promot…
Comprehensive Modeling and Experimental Testing of Fault Detection and Management of a Nonredundant Fault-Tolerant VSI
2015
This paper presents an investigation and a comprehensive analysis on fault operations in a conventional three-phase voltage source inverter. After an introductory section dealing with power converter reliability and fault analysis issues in power electronics, a generalized switching function accounting for both healthy and faulty conditions and an easy and feasible method to embed fault diagnosis and reconfiguration within the control algorithm are introduced. The proposed system has simple and compact implementation. Experimental results operating both at open- and closed-loop current control, obtained using a test bench realized using a dSPACE system and the fault-tolerant inverter protot…
Event generation and statistical sampling for physics with deep generative models and a density information buffer
2021
Simulating nature and in particular processes in particle physics require expensive computations and sometimes would take much longer than scientists can afford. Here, we explore ways to a solution for this problem by investigating recent advances in generative modeling and present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physical events, but to also ensure that these events occur with the correct frequencies. We investigate the feasibility of learning the event generation and the frequency of occurrence with several generative machine learning models to produce events l…
Antidoping Science
2018
The ineffectiveness of antidoping programs in elite sport, largely due to human and political factors, is leading to a new resolve and greater transparency of antidoping authorities and those stakeholders interested in drug-free sport. The perception by the public, athletes, and the World Anti-Doping Agency (WADA) of antidoping science and current drug testing programs in elite sport varies widely from "ineffective" to "robust and reliable." Here, we discuss why a careful and considered reevaluation of the underlying premise of antidoping science is needed to bring this unique application of predictive/diagnostic science more in line with other areas of medicine. We show how the validity of…