Preprint: Using RF-DNA Fingerprints To Classify OFDM Transmitters Under Rayleigh Fading Conditions

The Internet of Things (IoT) is a collection of Internet connected devices capable of interacting with the physical world and computer systems. It is estimated that the IoT will consist of approximately fifty billion devices by the year 2020. In addition to the sheer numbers, the need for IoT security is exacerbated by the fact that many of the edge devices employ weak to no encryption of the communication link. It has been estimated that almost 70% of IoT devices use no form of encryption. Previous research has suggested the use of Specific Emitter Identification (SEI), a physical layer technique, as a means of augmenting bit-level security mechanism such as encryption. The work presented here integrates a Nelder-Mead based approach for estimating the Rayleigh fading channel coefficients prior to the SEI approach known as RF-DNA fingerprinting. The performance of this estimator is assessed for degrading signal-to-noise ratio and compared with least square and minimum mean squared error channel estimators. Additionally, this work presents classification results using RF-DNA fingerprints that were extracted from received signals that have undergone Rayleigh fading channel correction using Minimum Mean Squared Error (MMSE) equalization. This work also performs radio discrimination using RF-DNA fingerprints generated from the normalized magnitude-squared and phase response of Gabor coefficients as well as two classifiers. Discrimination of four 802.11a Wi-Fi radios achieves an average percent correct classification of 90% or better for signal-to-noise ratios of 18 and 21 dB or greater using a Rayleigh fading channel comprised of two and five paths, respectively.Comment: 13 pages, 14 total figures/images, Currently under review by the IEEE Transactions on Information Forensics and Securit

Science career aspiration and science capital in China and UK: a comparative study using PISA data

The concept of science capital has a growing influence in science education research for understanding young people’s science trajectories. Popularised in the UK, this paper aims to extend and evaluate the applicability of science capital in the context of China by drawing on PISA2015. More specifically, we make use of existing items in the PISA2015 survey as a proxy for operationalising the construct of science capital to explore the science career aspirations and attainments of 15-year-old Chinese and UK students (n=23,998). Our findings indicate that science capital has more explanatory power for understanding UK students’ science career aspirations than for Chinese students, where science attainment seems most important. We raise the potential challenge for Chinese students to convert their science capital into scientific self-efficacy and science career aspirations as we highlight the importance of recognising cultural and national differences in operationalising science capital

Measurement of the CMS Magnetic Field

The measurement of the magnetic field in the tracking volume inside the superconducting coil of the Compact Muon Solenoid (CMS) detector under construction at CERN is done with a fieldmapper designed and produced at Fermilab. The fieldmapper uses 10 3-D B-sensors (Hall probes) developed at NIKHEF and calibrated at CERN to precision 0.05% for a nominal 4 T field. The precise fieldmapper measurements are done in 33840 points inside a cylinder of 1.724 m radius and 7 m long at central fields of 2, 3, 3.5, 3.8, and 4 T. Three components of the magnetic flux density at the CMS coil maximum excitation and the remanent fields on the steel-air interface after discharge of the coil are measured in check-points with 95 3-D B-sensors located near the magnetic flux return yoke elements. Voltages induced in 22 flux-loops made of 405-turn installed on selected segments of the yoke are sampled online during the entire fast discharge (190 s time-constant) of the CMS coil and integrated offline to provide a measurement of the initial magnetic flux density in steel at the maximum field to an accuracy of a few percent. The results of the measurements made at 4 T are reported and compared with a three-dimensional model of the CMS magnet system calculated with TOSCA.Comment: 4 pages, 5 figures, 15 reference

Understanding Soft Errors in Uncore Components

The effects of soft errors in processor cores have been widely studied. However, little has been published about soft errors in uncore components, such as memory subsystem and I/O controllers, of a System-on-a-Chip (SoC). In this work, we study how soft errors in uncore components affect system-level behaviors. We have created a new mixed-mode simulation platform that combines simulators at two different levels of abstraction, and achieves 20,000x speedup over RTL-only simulation. Using this platform, we present the first study of the system-level impact of soft errors inside various uncore components of a large-scale, multi-core SoC using the industrial-grade, open-source OpenSPARC T2 SoC design. Our results show that soft errors in uncore components can significantly impact system-level reliability. We also demonstrate that uncore soft errors can create major challenges for traditional system-level checkpoint recovery techniques. To overcome such recovery challenges, we present a new replay recovery technique for uncore components belonging to the memory subsystem. For the L2 cache controller and the DRAM controller components of OpenSPARC T2, our new technique reduces the probability that an application run fails to produce correct results due to soft errors by more than 100x with 3.32% and 6.09% chip-level area and power impact, respectively.Comment: to be published in Proceedings of the 52nd Annual Design Automation Conferenc

Isotope harvesting at heavy ion fragmentation facilities

Introduction The National Superconducting Cyclotron Laboratory (NSCL) is a national nuclear physics facility in which heavy ion beams are fragmented to produce exotic nuclei. In this process of fragmentation many nuclei are created, however, only one isotope is selected for experimentation. The remaining isotopes that are created go unused. The future upgrade of the NSCL to the Facility for Rare Isotope Beams (FRIB) will increase the incident energy of these heavy ion beams and amplify the current by three orders of magnitude. An aqueous beam dump will be created to collect the unused isotopes created in the process of fragmentation. Several of these isotopes are of interest for many applications including nuclear security, medical imaging, and therapy and are not currently available or are only available in very limited supply. Harvesting these isotopes from the aqueous beam dump could provide a consistent supply of these im-portant isotopes as an ancillary service to the existing experimental program. Material and Methods A liquid water target system was designed and tested to serve as a mock beam dump for exper-iments at the NSCL1. A 25 pnA 130 MeV/u 76Ge beam was fragmented using a 493 mg/cm2 thick beryllium production target. After fragmentation the beam was separated using the A1900 frag-ment separator2 set up for maximum 67Cu pro-duction using a 240 mg/cm2 aluminum wedge and a 2% momentum acceptance. The secondary beam was collected for four hours in the liquid water target system before being transferred to a collection vessel. Four additional four hour collections were made before finally shipping the five collections to Washington University and Hope College for chemical separation. Four of the five samples were separated using a two part separation scheme. First they were passed through and 3M Empore iminodiacetic acid functionalized chelation disk in a 1.25M ammonium acetate solution at pH 5. The flow through was collected and analyzed using an HPGe detector. Then 10mL of 6M HCl acid was passed through the chelation disk to remove the 2+ transition metals. The 10mL of 6M HCl acid was collected after passing through the disk and added to an anion-exchange column with 2.5 g AG1-X8 resin. The eluate was collected and then an additional 10mL of 6M HCl was passed through the column to remove the nickel. The 67Cu was then collected by passing 10mL of 0.5M HCl and the eluate was collected in 1mL fractions each analyzed by HPGe for 67Cu concentration and purity. The two highest 67Cu fractions were heated to dryness and reconstituted in 50 μL 0.1M ammonium acetate pH 5.5. 2 μL of 7.9 mg/mL NOTA-Bz-Trastuzumab was added to 45 μL of 67Cu and 3 μL 0.1M ammonium acetate pH 5.5. This solution was placed in a shaking incubator at 37 °C for twenty minutes and then analyzed by radio-instant thin layer chromatography in order to determine the per-cent of 67Cu bound to the antibody. Results and Conclusion 67Cu was collected into the liquid water target system with an average efficiency of 85 ± 5 %. The secondary beam was 73 % pure with the impurities, half-lives greater than 1 minute, listed in TABLE 1. Separation of 67Cu from the impurities resulted in an average recovery of 88 ± 3 % for a total recovery of 67Cu from the beam and separation of 75 ± 4 %. No detectable radioactive impurities were found in the final samples when analyzed using an HPGe detector. TABLE 2 shows the amount of 67Cu collected from the beam and the amount recovered decay corrected to end of bombardment. Labeling NOTA-Bz-Trastuzumab with 67Cu resulted in > 95 % radiochemical yield. Collection of the 73 % pure 67Cu beam in water and the resulting separation proved successful. These results demonstrate that radioisotopes can be collected from fragmented heavy ion beams and isolated in usable quantities and purity for many radiochemical applications. Further experimentation with an unpurified beam to better simulate conditions in the beam dump at the Facility for Rare Isotope Beams will be performed in the near future

National geological screening : the Pennines and adjacent areas

This report is the published product of one of a series of studies covering England, Wales and Northern Ireland commissioned by Radioactive Waste Management (RWM) Ltd. The report provides geological information about the Pennines and adjacent areas region to underpin the process of national geological screening set out in the UK’s government White Paper Implementing geological disposal: a framework for the long-term management of higher activity radioactive waste (DECC, 2014). The report describes geological features relevant to the safety requirements of a geological disposal facility (GDF) for radioactive waste emplaced onshore and up to 20 km offshore at depths between 200 and 1000 m from surface. It is written for a technical audience but is intended to inform RWM in its discussions with communities interested in finding out about the potential for their area to host a GDF

UKGEOS: Glasgow Geothermal Energy Research Field Site (GGERFS): initial summary of the geological platform

The preferred second UKGEOS site is at Clyde Gateway, in the east end of Glasgow, Scotland. The focus of this, the Glasgow Geothermal Energy Research Field Site (GGERFS), is on characterising and monitoring the subsurface for minewater and hot sedimentary aquifer geothermal energy, and for cooling and heat storage. This report details BGS data and knowledge at late 2016, to define initial characterisation of the ‘geological platform’ relevant for the planning of a geothermal research facility and associated environmental baseline monitoring. The report covers knowledge of the bedrock and superficial deposits geology, abandoned coal mines, hydrogeology, geothermal datasets, geochemistry, remote sensed data, seismicity, stress fields, engineering geology and rock property datasets. BGS holds a great deal of legacy borehole, mining and geochemistry data and has updated existing bedrock and superficial deposits models of the area. However, deep borehole and seismic data are lacking to define the geology and structure of the area below a few hundred metres. Hydrogeological and temperature data are also lacking for the bedrock strata. Regional datasets and knowledge have (and can be further) used to reduce uncertainty and risk in these aspects of the geological characterisation

Radio Identity Verification-based IoT Security Using RF-DNA Fingerprints and SVM

It is estimated that the number of Internet of Things (IoT) devices will reach 75 billion in the next five years. Most of those currently and soon-to-be deployed devices lack sufficient security to protect themselves and their networks from attacks by malicious IoT devices masquerading as authorized devices in order to circumvent digital authentication approaches. This work presents a Physical (PHY) layer IoT authentication approach capable of addressing this critical security need through the use of feature-reduced, Radio Frequency-Distinct Native Attributes (RF-DNA) fingerprints and Support Vector Machines (SVM). This work successfully demonstrates (i) authorized Identity (ID) verification across three trials of six randomly chosen radios at signal-to-noise ratios greater than or equal to 6 dB and (ii) rejection of all rogue radio ID spoofing attacks at signal-to-noise ratios greater than or equal to 3 dB using RF-DNA fingerprints whose features are selected using the Relief-F algorithm