Scalable software architecture for on-line multi-camera video processing

In this paper we present a scalable software architecture for on-line multi-camera video processing, that guarantees a good trade off between computational power, scalability and flexibility. The software system is modular and its main blocks are the Processing Units (PUs), and the Central Unit. The Central Unit works as a supervisor of the running PUs and each PU manages the acquisition phase and the processing phase. Furthermore, an approach to easily parallelize the desired processing application has been presented. In this paper, as case study, we apply the proposed software architecture to a multi-camera system in order to efficiently manage multiple 2D object detection modules in a real-time scenario. System performance has been evaluated under different load conditions such as number of cameras and image sizes. The results show that the software architecture scales well with the number of camera and can easily works with different image formats respecting the real time constraints. Moreover, the parallelization approach can be used in order to speed up the processing tasks with a low level of overhea

1SXPS: A deep Swift X-ray Telescope point source catalog with light curves and spectra

We present the 1SXPS (Swift-XRT Point Source) catalog of 151,524 X-ray point-sources detected by the Swift-XRT in 8 years of operation. The catalog covers 1905 square degrees distributed approximately uniformly on the sky. We analyze the data in two ways. First we consider all observations individually, for which we have a typical sensitivity of ~3e-13 erg/cm2/s (0.3--10 keV). Then we co-add all data covering the same location on the sky: these images have a typical sensitivity of ~9e-14 erg/cm2/s (0.3--10 keV). Our sky coverage is nearly 2.5 times that of 3XMM-DR4, although the catalog is a factor of ~1.5 less sensitive. The median position error is 5.5" (90% confidence), including systematics. Our source detection method improves on that used in previous XRT catalogs and we report >68,000 new X-ray sources. The goals and observing strategy of the Swift satellite allow us to probe source variability on multiple timescales, and we find ~30,000 variable objects in our catalog. For every source we give positions, fluxes, time series (in four energy bands and two hardness ratios), estimates of the spectral properties, spectra and spectral fits for the brightest sources, and variability probabilities in multiple energy bands and timescales.Comment: 27 pages, 19 figures; accepted for publication in ApJS. The accompanying website, http://www.swift.ac.uk/1SXPS is live; the Vizier entry should be available shortl

RFID Localisation For Internet Of Things Smart Homes: A Survey

The Internet of Things (IoT) enables numerous business opportunities in fields as diverse as e-health, smart cities, smart homes, among many others. The IoT incorporates multiple long-range, short-range, and personal area wireless networks and technologies into the designs of IoT applications. Localisation in indoor positioning systems plays an important role in the IoT. Location Based IoT applications range from tracking objects and people in real-time, assets management, agriculture, assisted monitoring technologies for healthcare, and smart homes, to name a few. Radio Frequency based systems for indoor positioning such as Radio Frequency Identification (RFID) is a key enabler technology for the IoT due to its costeffective, high readability rates, automatic identification and, importantly, its energy efficiency characteristic. This paper reviews the state-of-the-art RFID technologies in IoT Smart Homes applications. It presents several comparable studies of RFID based projects in smart homes and discusses the applications, techniques, algorithms, and challenges of adopting RFID technologies in IoT smart home systems.Comment: 18 pages, 2 figures, 3 table

A highly magnified candidate for a young galaxy seen when the Universe was 500 Myrs old

The early Universe at redshift z\sim6-11 marks the reionization of the intergalactic medium, following the formation of the first generation of stars. However, those young galaxies at a cosmic age of \lesssim 500 million years (Myr, at z \gtrsim 10) remain largely unexplored as they are at or beyond the sensitivity limits of current large telescopes. Gravitational lensing by galaxy clusters enables the detection of high-redshift galaxies that are fainter than what otherwise could be found in the deepest images of the sky. We report the discovery of an object found in the multi-band observations of the cluster MACS1149+22 that has a high probability of being a gravitationally magnified object from the early universe. The object is firmly detected (12 sigma) in the two reddest bands of HST/WFC3, and not detected below 1.2 {\mu}m, matching the characteristics of z\sim9 objects. We derive a robust photometric redshift of z = 9.6 \pm 0.2, corresponding to a cosmic age of 490 \pm 15Myr (i.e., 3.6% of the age of the Universe). The large number of bands used to derive the redshift estimate make it one of the most accurate estimates ever obtained for such a distant object. The significant magnification by cluster lensing (a factor of \sim15) allows us to analyze the object's ultra-violet and optical luminosity in its rest-frame, thus enabling us to constrain on its stellar mass, star-formation rate and age. If the galaxy is indeed at such a large redshift, then its age is less than 200 Myr (at the 95% confidence level), implying a formation redshift of zf \lesssim 14. The object is the first z>9 candidate that is bright enough for detailed spectroscopic studies with JWST, demonstrating the unique potential of galaxy cluster fields for finding highly magnified, intrinsically faint galaxies at the highest redshifts.Comment: Submitted to the Nature Journal. 39 Pages, 13 figure

Simultaneous exoplanet detection and instrument aberration retrieval in multispectral coronagraphic imaging

High-contrast imaging for the detection and characterization of exoplanets relies on the instrument's capability to block out the light of the host star. Some current post-processing methods for calibrating out the residual speckles use information redundancy offered by multispectral imaging but do not use any prior information on the origin of these speckles. We investigate whether additional information on the system and image formation process can be used to more finely exploit the multispectral information. We developed an inversion method in a Bayesian framework that is based on an analytical imaging model to estimate both the speckles and the object map. The model links the instrumental aberrations to the speckle pattern in the image focal plane, distinguishing between aberrations upstream and downstream of the coronagraph. We propose and validate several numerical techniques to handle the difficult minimization problems of phase retrieval and achieve a contrast of 10^6 at 0.2 arcsec from simulated images, in the presence of photon noise. This opens up the the possibility of tests on real data where the ultimate performance may override the current techniques if the instrument has good and stable coronagraphic imaging quality. This paves the way for new astrophysical exploitations or even new designs for future instruments

Mobile forensic triage for damaged phones using M_Triage

Mobile forensics triage is a useful technique in a digital forensics investigation for recovering lost or purposely deleted and hidden files from digital storage. It is particularly useful, especially when solving a very sensitive crime, for example, kidnapping, in a timely manner. However, the existing mobile forensics triage tools do not consider performing a triage examination on damaged mobile phones. This research addressed the issues of performing triage examination on damaged Android mobile phones and reduction of false positive result generated by the current mobile forensics triage tools. Furthermore, the research addressed the issues of ignoring possible evidence residing in a bad block memory location. In this research a new forensics triage tool called M_Triage was introduced by extending Decode’s framework to handle data retrieval challenges on damaged Android mobile phones. The tool was designed to obtain evidence quickly and accurately (i.e. valid address book, call logs, SMS, images, and, videos, etc.) on Android damaged mobile phones. The tool was developed using C#, while back end engines was done using C programming and tested using five data sets. Based on the computational time processing comparison with Dec0de, Lifter, XRY and Xaver, the result showed that there was 75% improvement over Dec0de, 36% over Lifter, 28% over XRY and finally 71% over Xaver. Again, based on the experiment done on five data sets, M_Triage was capable of carving valid address book, call logs, SMS, images and videos as compared to Dec0de, Lifter, XRY and Xaver. With the average improvement of 90% over DEC0DE, 30% over Lifter, 40% over XRY and lastly 61% over Xaver. This shows that M_Triage is a better tool to be used because it saves time, carve more relevant files and less false positive result are achieved with the tool