The Experts below are selected from a list of 564081 Experts worldwide ranked by ideXlab platform
George J. M. Aitken - One of the best experts on this subject based on the ideXlab platform.
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Temporal Analysis of stellar wave-front-tilt data
Journal of the Optical Society of America A, 1997Co-Authors: Donald R. Mcgaughey, George J. M. AitkenAbstract:Two-dimensional fractional Brownian motion (FBM) is a good model for stellar wave fronts distorted by Kolmogorov turbulence. However, the time series generated by the movement of such a wave front past an observation point does not explain the reported predictability of measured wave-front slopes. Rescaled-range Analysis, a technique for detecting dependence among samples in a series, and a correlation-dimension algorithm that tests for the presence of deterministic chaos were applied to series of real, measured, stellar wavefront slopes. These tests suggest that the source of correlation and predictability is the low-pass spatial filtering of the FBM wave front by the lenslets of an adaptive-optics wave-front sensor and that the process is not chaotic. A simple modeling procedure is described for generating time series of measured wave-front slopes with the correct Temporal characteristics.
Neng-hsin Shih - One of the best experts on this subject based on the ideXlab platform.
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Reconstructing ADS data hiding in windows NTFS: A Temporal Analysis
Digital Investigation, 2018Co-Authors: Yuan-pei Chen, Neng-hsin ShihAbstract:Abstract The Windows NTFS file system supports for alternate data streams (ADS) to provide compatibility with files in the Macintosh file system. ADS can be used for hidden channels of storing and exchanging information on machines without altering their original functionality or contents. Executables in ADS can be executed from the command line. It is common for attackers to hide malware in cover media (files or folders) by ADS creation, modification or overwriting. The Temporal information is significant when the computer is on. The attributes of $SI and $FN in the Master File Table (MFT) hold the following four forensically interesting EMAC-time stamps. Timestamp dynamics refers to any influence that adds, changes, obscures, contaminates, or obliterates timestamps, regardless of intent. Getting precise information about the file metadata in the MFT is important to the assessment of the scenario of the offense. The study of file metadata and ADS manipulation assists in establishing timestamp patterns and correlating activities from timestamp evidence. Some experimental processes were conducted to identify EMAC-time stamps in $SI and $FN, collect experimental observations in MFT, examine hidden channels, analyze timeline scenario, and present artifacts and non-artifacts to reconstruct the incident. This study explores the Temporal Analysis facing the law enforcement community and discusses the application of Forensic Toolkit (FTK) software to copy with the increasingly ADS feature in digital forensic investigations. This study also establishes some timestamp rules on ADS manipulation, enhances the performance of investigations, and helps investigators reconstruct an incident. It is beneficial for investigators to evaluate an accident if an attacker has manipulated ADS to conceal his offense.
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Reconstructing ADS data hiding in windows NTFS: A Temporal Analysis
Digital Investigation, 2018Co-Authors: Da-yu Kao, Yuan-pei Chen, Neng-hsin ShihAbstract:Abstract The Windows NTFS file system supports for alternate data streams (ADS) to provide compatibility with files in the Macintosh file system. ADS can be used for hidden channels of storing and exchanging information on machines without altering their original functionality or contents. Executables in ADS can be executed from the command line. It is common for attackers to hide malware in cover media (files or folders) by ADS creation, modification or overwriting. The Temporal information is significant when the computer is on. The attributes of $SI and $FN in the Master File Table (MFT) hold the following four forensically interesting EMAC-time stamps. Timestamp dynamics refers to any influence that adds, changes, obscures, contaminates, or obliterates timestamps, regardless of intent. Getting precise information about the file metadata in the MFT is important to the assessment of the scenario of the offense. The study of file metadata and ADS manipulation assists in establishing timestamp patterns and correlating activities from timestamp evidence. Some experimental processes were conducted to identify EMAC-time stamps in $SI and $FN, collect experimental observations in MFT, examine hidden channels, analyze timeline scenario, and present artifacts and non-artifacts to reconstruct the incident. This study explores the Temporal Analysis facing the law enforcement community and discusses the application of Forensic Toolkit (FTK) software to copy with the increasingly ADS feature in digital forensic investigations. This study also establishes some timestamp rules on ADS manipulation, enhances the performance of investigations, and helps investigators reconstruct an incident. It is beneficial for investigators to evaluate an accident if an attacker has manipulated ADS to conceal his offense.
Ata Riadh - One of the best experts on this subject based on the ideXlab platform.
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A multi-Temporal Analysis of AMSR-E data for flood and discharge monitoring during the 2008 flood in Iowa
Hydrological Processes, 2011Co-Authors: Marouane Temini, Teodosio Lacava, Lakhandar Tarendra, Valerio Tramutoli, Hosni Ghedira, Ata RiadhAbstract:The objective of this work is to demonstrate the potential of using passive microwave data to monitor flood and discharge conditions and to infer watershed hydraulic and hydrologic parameters. The case study is the major flood in Iowa in summer 2008. A new Polarisation Ratio Variation Index (PRVI) was developed based on a multi-Temporal Analysis of 37 GHz satellite imagery from the Advanced Microwave Scanning Radiometer (AMSR-E) to calculate and detect anomalies in soil moisture and/or inundated areas. The Robust Satellite Technique (RST) which is a change detection approach based on the Analysis of historical satellite records was adopted. A rating curve has been developed to assess the relationship between PRVI values and discharge observations downstream. A time-lag term has been introduced and adjusted to account for the changing delay between PRVI and streamflow. Moreover, the Kalman filter has been used to update the rating curve parameters in near real time. The Temporal variability of the b exponent in the rating curve formula shows that it converges toward a constant value. A consistent 21-day time lag, very close to an estimate of the time of concentration, was obtained. The agreement between observed discharge downstream and estimated discharge with and without parameters adjustment was 65 and 95%, respectively. This demonstrates the interesting role that passive microwave can play in monitoring flooding and wetness conditions and estimating key hydrologic parameters.
Vijay Vittal - One of the best experts on this subject based on the ideXlab platform.
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a spatio Temporal Analysis approach for short term forecast of wind farm generation
IEEE Transactions on Power Systems, 2014Co-Authors: Lei Yang, Junshan Zhang, Vijay VittalAbstract:In this paper, short-term forecast of wind farm generation is investigated by applying spatio-Temporal Analysis to extensive measurement data collected from a large wind farm where multiple classes of wind turbines are installed. Specifically, using the data of the wind turbines' power outputs recorded across two consecutive years, graph-learning based spatio-Temporal Analysis is carried out to characterize the statistical distribution and quantify the level crossing rate of the wind farm's aggregate power output. Built on these characterizations, finite-state Markov chains are constructed for each epoch of three hours and for each individual month, which accounts for the diurnal non-stationarity and the seasonality of wind farm generation. Short-term distributional forecasts and a point forecast are then derived by using the Markov chains and ramp trend information. The distributional forecast can be utilized to study stochastic unit commitment and economic dispatch problems via a Markovian approach. The developed Markov-chain-based distributional forecasts are compared with existing approaches based on high-order autoregressive models and Markov chains by uniform quantization, and the devised point forecasts are compared with persistence forecasts and high-order autoregressive model-based point forecasts. Numerical test results demonstrate the improved performance of the Markov chains developed by spatio-Temporal Analysis over existing approaches.
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ICNC - Spatio-Temporal Analysis for smart grids with wind generation integration
2013 International Conference on Computing Networking and Communications (ICNC), 2013Co-Authors: Miao He, Lei Yang, Junshan Zhang, Vijay VittalAbstract:In this paper, we propose a spatio-Temporal Analysis approach for short-term forecasting of wind farm generation. Specifically, using extensive measurement data from an actual wind farm, the probability distribution and the level crossing rate (LCR) of wind farm generation are characterized by using tools from graphical learning and time-series Analysis. Based on these spatial and Temporal characterizations, finite state Markov chain models for wind farm generation are developed. Point-forecast of wind farm generation is derived using the Markov chains and integrated into power system economic dispatch. Numerical study on economic dispatch using the IEEE 30-bus test system demonstrates the significant improvement compared with conventional wind-speed-based forecasting methods.
Filiaci, Mattia Emidio - One of the best experts on this subject based on the ideXlab platform.
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Spatial Localization and Temporal Analysis of Optical Property Fluctuations by Multiplexed Near -Infrared Photon Density Waves in Turbid Media: In Vitro and in Vivo Studies
1Co-Authors: Filiaci, Mattia EmidioAbstract:103 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2001.Recently much attention has been given to the study of the processes in the human brain that lead to the changing of the optical parameters that characterize the tissue, measured by our frequency-domain instrumentation. These processes have been divided into two main categories with different time-scales. The slower one is mostly due to the fluctuations in the absorption coefficient caused by oxy- and deoxy-hemoglobin changes in the tissue. The Temporal Analysis of the signal resulting from this process is studied in detail, and I also introduce a time-series data Analysis technique that has not been applied to this field before but was introduced in another area very recently. The faster time-scale process has been attributed to the electrochemical excitation of the individual neurons in the brain that have been observed to cause a change in the scattering coefficient of the tissue. This is the other primary parameter that is measured by our frequency domain instrument. However, before this work it has not been clear how to go about to better localize these smaller fluctuations. I present a novel idea for improving spatial localization of macroscopic optical parameter fluctuations, and study the characteristics of this optical probe design using analytical solutions to the diffusion equation and Monte Carlo simulations that more appropriately represent the volume of excitation of the cortex neurons.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD
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Spatial localization and Temporal Analysis of optical property fluctuations by multiplexed near-infrared photon density waves in turbid media: In vitro and in vivo studies
1Co-Authors: Filiaci, Mattia EmidioAbstract:In recent years the application of near infrared non-invasive methods for medical diagnostics and clinical studies has grown rapidly. The ease of use, low cost and portability of these methods is a clear advantage over other techniques such as MRI. The limitations in detection of optical property inhomogeneities in tissues, such as tumors or hematomas, is due to the diffusive, highly scattering nature of near infrared light propagation. I have studied and developed methods to improve the spatial localization of these inhomogeneities in biological tissues, especially for the application of functional studies of the human brain in vivo. Recently much attention has been given to the study of the processes in the human brain that lead to the changing of the optical parameters that characterize the tissue, measured by our frequency-domain instrumentation. These processes have been divided into two main categories with different time-scales. The slower one is mostly due to the fluctuations in the absorption coefficient caused by oxy- and deoxy-hemoglobin changes in the tissue. The Temporal Analysis of the signal resulting from this process is studied in detail, and I also introduce a time-series data Analysis technique that has not been applied to this field before but was introduced in another area very recently. The faster time-scale process has been attributed to the electrochemical excitation of the individual neurons in the brain that have been observed to cause a change in the scattering coefficient of the tissue. This is the other primary parameter that is measured by our frequency domain instrument. However, before this work it has not been clear how to go about to better localize these smaller fluctuations. I present a novel idea for improving spatial localization of macroscopic optical parameter fluctuations, and study the characteristics of this optical probe design using analytical solutions to the diffusion equation and Monte Carlo simulations that more appropriately represent the volume of excitation of the cortex neurons.U of I OnlyThesi
