Related papers: Advances in the RXTE Proportional Counter Array Ca…
We study the accuracy of forecasts in the diffusion index forecast model with possibly weak loadings. The default option to construct forecasts is to estimate the factors through principal component analysis (PCA) on the available predictor…
Approximate computing has in recent times found significant applications towards lowering power, area, and time requirements for arithmetic operations. Several works done in recent years have furthered approximate computing along these…
A large area Resistive Plate Chamber (RPC) with a total active surface of 160x10 cm2 was built and tested. The surface was segmented in two 5 cm wide strips readout on both ends with custom, very high frequency, front end electronics. A…
This work studies estimation of sparse principal components in high dimensions. Specifically, we consider a class of estimators based on kernel PCA, generalizing the covariance thresholding algorithm proposed by Krauthgamer et al. (2015).…
Large Area X-ray Propositional Counter (LAXPC) instrument on AstroSat is aimed at providing high time resolution X-ray observations in 3 to 80 keV energy band with moderate energy resolution. To achieve large collecting area, a cluster of…
Probe-level models have led to improved performance in microarray studies but the various sources of probe-level contamination are still poorly understood. Data-driven analysis of probe performance can be used to quantify the uncertainty in…
This paper delivers improved theoretical guarantees for the convex programming approach in low-rank matrix estimation, in the presence of (1) random noise, (2) gross sparse outliers, and (3) missing data. This problem, often dubbed as…
Remote sensing observations, products and simulations are fundamental sources of information to monitor our planet and its climate variability. Uncovering the main modes of spatial and temporal variability in Earth data is essential to…
(Abridged) The CASA software suite, can now reduce very long baseline interferometry (VLBI) data with the recent addition of a fringe fitter. Here, we present the Radboud PIpeline for the Calibration of high Angular Resolution Data…
The time resolution of Multigap Resistive Plate Counters (MRPCs) to $511$ keV gamma rays has been investigated using a $^{22}$Na source and four detectors. The MRPCs time resolution has been derived from the Time-of-Flight information,…
Planetary rovers can use onboard data analysis to adapt their measurement plan on the fly, improving the science value of data collected between commands from Earth. This paper describes the implementation of an adaptive sampling algorithm…
In our previous work, a reduced order model (ROM) for a stochastic system was made, where noisy data was projected onto principal component analysis (PCA)-derived basis vectors to obtain an accurate reconstruction of the noise-free data.…
The new transient X-ray pulsar XTE J0111.2-7317 was observed with Advanced Satellite for Cosmology and Astrophysics (ASCA) on 1998 November 18, a few days after its discovery with the Proportional Counter Array onboard the Rossi X-ray…
We report on the RXTE/PCA observation of the X-ray burster 1E1724-3045 located in the globular cluster Terzan 2. The persistent X-ray emission shows a high level of noise variability, the so-called High Frequency Noise (HFN) with a…
Respiratory motion complicates accurate irradiation of thoraco-abdominal tumors during radiotherapy, as treatment-system latency entails target-location uncertainties. This work addresses frame forecasting in chest and liver cine MRI to…
Recent advancements in Retrieval-Augmented Generation have significantly enhanced code completion at the repository level. Various RAG-based code completion systems are proposed based on different design choices. For instance, gaining more…
In medical image segmentation, limited external validity remains a critical obstacle when models are deployed across unseen datasets, an issue particularly pronounced in the ultrasound image domain. Existing solutions-such as domain…
We present a new straightforward principal component analysis (PCA) method based on the diagonalization of the weighted variance-covariance matrix through two spectral decomposition methods: power iteration and Rayleigh quotient iteration.…
We report results of RXTE observations of PSR B1951+32 using the PCA instrument for 19k seconds during 1996 March 24th. We applied the contemporaneous radio ephemeris and various statistical tests to search for evidence of pulsation. These…
Sparse principal component analysis (PCA) aims at mapping large dimensional data to a linear subspace of lower dimension. By imposing loading vectors to be sparse, it performs the double duty of dimension reduction and variable selection.…