Robot and insect navigation by polarized skylight

A study of a large number of published experiments on the behaviour of insects navigating by skylight has led to the design of a system for navigation in lightly clouded skies, suitable for a robot or drone. The design is based on the measurement of the directions in the sky at which the polarization angle, i.e. the angle χ between the polarized E-vector and the meridian, equals ±π/4 or ±(π/4 + π/3) or ±(π/4 - π/3). For any one of these three options, at any given elevation, there are usually 4 such directions and these directions can give the azimuth of the sun accurately in a few short steps, as an insect can do. A simulation shows that this compass is accurate as well as simple and well suited for an insect or robot. A major advantage of this design is that it is close to being invariant to variable cloud cover. Also if at least two of these 12 directions are observed the solar azimuth can still be found by a robot, and possibly by an insect.

Histogram of oriented gradients front end processing: An FPGA based processor approach

The Field Programmable Gate Array (FPGA) implementation of the commonly used Histogram of Oriented Gradients (HOG) algorithm is explored. The HOG algorithm is employed to extract features for object detection. A key focus has been to explore the use of a new FPGA-based processor which has been targeted at image processing. The paper gives details of the mapping and scheduling factors that influence the performance and the stages that were undertaken to allow the algorithm to be deployed on FPGA hardware, whilst taking into account the specific IPPro architecture features. We show that multi-core IPPro performance can exceed that of against state-of-the-art FPGA designs by up to 3.2 times with reduced design and implementation effort and increased flexibility all on a low cost, Zynq programmable system.

Accelerating integer-based fully homomorphic encryption using Comba multiplication

Fully Homomorphic Encryption (FHE) is a recently developed cryptographic technique which allows computations on encrypted data. There are many interesting applications for this encryption method, especially within cloud computing. However, the computational complexity is such that it is not yet practical for real-time applications. This work proposes optimised hardware architectures of the encryption step of an integer-based FHE scheme with the aim of improving its practicality. A low-area design and a high-speed parallel design are proposed and implemented on a Xilinx Virtex-7 FPGA, targeting the available DSP slices, which offer high-speed multiplication and accumulation. Both use the Comba multiplication scheduling method to manage the large multiplications required with uneven sized multiplicands and to minimise the number of read and write operations to RAM. Results show that speed up factors of 3.6 and 10.4 can be achieved for the encryption step with medium-sized security parameters for the low-area and parallel designs respectively, compared to the benchmark software implementation on an Intel Core2 Duo E8400 platform running at 3 GHz.

New FMO Type to Flag ROI in H264/AVC

This paper presents a new type of Flexible Macroblock Ordering (FMO) type for the H.264 Advanced Video Coding (AVC) standard, which can more efficiently flag the position and shape of regions of interest (ROIs) in each frame. In H.264/AVC, 7 types of FMO have been defined, all of which are designed for error resilience. Most previous work related to ROI processing has adopted Type-2 (foreground & background), or Type-6 (explicit), to flag the position and shape of the ROI. However, only rectangular shapes are allowed in Type-2 and for non-rectangular shapes, the non-ROI macroblocks may be wrongly flagged as being within the ROI, which could seriously affect subsequent processing of the ROI. In Type-6, each macroblock in a frame uses fixed-length bits to indicate to its slice group. In general, each ROI is assigned to one slice group identity. Although this FMO type can more accurately flag the position and shape of the ROI, it incurs a significant bitrate overhead. The proposed new FMO type uses the smallest rectangle that covers the ROI to indicate its position and a spiral binary mask is employed within the rectangle to indicate the shape of the ROI. This technique can accurately flag the ROI and provide significantly savings in the bitrate overhead. Compared with Type-6, an 80% to 90% reduction in the bitrate overhead can be obtained while achieving the same accuracy.

Empirical evaluation of multi-device profiling side-channel attacks

Side-channel analysis of cryptographic systems can allow for the recovery of secret information by an adversary even where the underlying algorithms have been shown to be provably secure. This is achieved by exploiting the unintentional leakages inherent in the underlying implementation of the algorithm in software or hardware. Within this field of research, a class of attacks known as profiling attacks, or more specifically as used here template attacks, have been shown to be extremely efficient at extracting secret keys. Template attacks assume a strong adversarial model, in that an attacker has an identical device with which to profile the power consumption of various operations. This can then be used to efficiently attack the target device. Inherent in this assumption is that the power consumption across the devices under test is somewhat similar. This central tenet of the attack is largely unexplored in the literature with the research community generally performing the profiling stage on the same device as being attacked. This is beneficial for evaluation or penetration testing as it is essentially the best case scenario for an attacker where the model built during the profiling stage matches exactly that of the target device, however it is not necessarily a reflection on how the attack will work in reality. In this work, a large scale evaluation of this assumption is performed, comparing the key recovery performance across 20 identical smart-cards when performing a profiling attack.

Robust bimodal person identification using face and speech with limited training data and corruption of both modalities

This paper presents a novel method of audio-visual fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there is a limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new representation and a modified cosine similarity are introduced for combining and comparing bimodal features with limited training data as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal data set created from the SPIDRE and AR databases with variable noise corruption of speech and occlusion in the face images. The new method has demonstrated improved recognition accuracy.

Photoionization cross sections for O-like S IX: a Breit-Pauli R-matrix calculation

In this paper we present photoionization cross sections for the lowest five states of O-like S IX (1s(2)2s(2)2p(4) P-3(0,1,2), D-1(2), S-1(0)). The relativistic Breit-Pauli R-matrix codes were utilized including all terms of the 2s(2)2p(3), 2s2p(4), 2p(5), 2s(2)2p(2)3s, 3p, 3d and 2s2p(3)3s, 3p, 3d configurations in the expansion of the collision wavefunction for S X. It was also found that to achieve convergence of the low-lying energy separations of the target levels, an additional 21 configuration functions needed to be included in the configuration interaction expansion, incorporating two-electron excitations from the 2s and 2p shells to the 3s, 3p and 3d shells. The present work thus constitutes the most sophisticated photoionization evaluation for ground and metastable levels of the S IX ion. Direct comparisons have been made with the only available data found on the OPEN-ADAS database between level resolved contributions of the spectrum. This comparison for the background cross section exhibits excellent agreement at all photon energies for each partial photoionization cross section contribution investigated. Finally, the autoionizing bound states arising from numerous open channels have also been investigated and identified using the QB approach, a procedure for analyzing resonances in atomic and molecular collision theory which exploits the analytic properties of R-matrix theory. Major Rydberg resonance series are also presented and tabulated for the dominant linewidths considered.

Epidemiology of Dysglycemia in Pregnant Oklahoma American Indian Women

CONTEXT: Minority communities are disproportionately affected by diabetes, and minority women are at an increased risk for glucose intolerance (dysglycemia) during pregnancy.

OBJECTIVES: In pregnant American Indian women, the objectives of the study were to use current criteria to estimate the prevalence of first-trimester (Tr1) dysglycemia and second-trimester (Tr2) incidence of gestational diabetes mellitus (GDM) and to explore new candidate measures and identify associated clinical factors.

DESIGN: This was a prospective cohort study. In Tr1 we performed a 75-g, 2-hour oral glucose tolerance test (OGTT) and glycated hemoglobin (HbA1c) to determine the following: fasting insulin; homeostasis model assessment of insulin resistance; serum 1,5-anhydroglucitol; noninvasive skin autofluorescence (SCOUT). We defined dysglycemia by American Diabetes Association and Endocrine Society criteria and as HbA1c of 5.7% or greater. In Tr2 in an available subset, we performed a repeat OGTT and SCOUT.

PARTICIPANTS: Pregnant American Indian women (n = 244 at Tr1; n = 114 at Tr2) participated in the study.

OUTCOMES: The prevalence of dysglycemia at Tr1 and incidence of GDM at Tr2 were measured.

RESULTS: At Tr1, one woman had overt diabetes; 36 (15%) had impaired glucose tolerance (American Diabetes Association criteria and/or abnormal HbA1c) and 59 (24%) had GDM-Tr1 (Endocrine Society criteria). Overall, 74 (30%) had some form of dysglycemia. Associated factors were body mass index, hypertension, waist/hip circumferences, SCOUT score, fasting insulin, and homeostasis model assessment of insulin resistance. At Tr2, 114 of the Tr1 cohort underwent a repeat OGTT and SCOUT, and 26 (23%) had GDM. GDM-Tr2 was associated with increased SCOUT scores (P = .029) and Tr1 body mass index, waist/hip circumferences, diastolic blood pressure, fasting insulin, and triglyceride levels. Overall, dysglycemia at Tr1 and/or Tr2 affected 38% of the women.

CONCLUSIONS: Dysglycemia at some point during pregnancy was common among American Indian women. It was associated with features of insulin resistance and may confer long-term health risks for mother and child.

Binaural Reproduction of Finite Difference Simulations Using Spherical Array Processing

Due to its efficiency and simplicity, the finite-difference time-domain method is becoming a popular choice for solving wideband, transient problems in various fields of acoustics. So far, the issue of extracting a binaural response from finite difference simulations has only been discussed in the context of embedding a listener geometry in the grid. In this paper, we propose and study a method for binaural response rendering based on a spatial decomposition of the sound field. The finite difference grid is locally sampled using a volumetric array of receivers, from which a plane wave density function is computed and integrated with free-field head related transfer functions, in the spherical harmonics domain. The volumetric array is studied in terms of numerical robustness and spatial aliasing. Analytic formulas that predict the performance of the array are developed, facilitating spatial resolution analysis and numerical binaural response analysis for a number of finite difference schemes. Particular emphasis is placed on the effects of numerical dispersion on array processing and on the resulting binaural responses. Our method is compared to a binaural simulation based on the image method. Results indicate good spatial and temporal agreement between the two methods.

Statistical data correction for unreliable memories

In this paper, we introduce a statistical data-correction framework that aims at improving the DSP system performance in presence of unreliable memories. The proposed signal processing framework implements best-effort error mitigation for signals that are corrupted by defects in unreliable storage arrays using a statistical correction function extracted from the signal statistics, a data-corruption model, and an application-specific cost function. An application example to communication systems demonstrates the efficacy of the proposed approach.

On the performance of LDPC and turbo decoder architectures with unreliable memories

In this paper, we investigate the impact of faulty memory bit-cells on the performance of LDPC and Turbo channel decoders based on realistic memory failure models. Our study investigates the inherent error resilience of such codes to potential memory faults affecting the decoding process. We develop two mitigation mechanisms that reduce the impact of memory faults rather than correcting every single error. We show how protection of only few bit-cells is sufficient to deal with high defect rates. In addition, we show how the use of repair-iterations specifically helps mitigating the impact of faults that occur inside the decoder itself.

An effective key generation system using improved channel reciprocity

In physical layer security systems there is a clear need to exploit the radio link characteristics to automatically generate an encryption key between two end points. The success of the key generation depends on the channel reciprocity, which is impacted by the non-simultaneous measurements and the white nature of the noise. In this paper, an OFDM subcarriers' channel responses based key generation system with enhanced channel reciprocity is proposed. By theoretically modelling the OFDM subcarriers' channel responses, the channel reciprocity is modelled and analyzed. A low pass filter is accordingly designed to improve the channel reciprocity by suppressing the noise. This feature is essential in low SNR environments in order to reduce the risk of the failure of the information reconciliation phase during key generation. The simulation results show that the low pass filter improves the channel reciprocity, decreases the key disagreement, and effectively increases the success of the key generation.

Foreword

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

A hybrid mixed cost-function TEQ initialization algorithm for ADSL modems

In this paper, we present a hybrid mixed cost-function adaptive initialization algorithm for the time domain equalizer in a discrete multitone (DMT)-based asymmetric digital subscriber loop. Using our approach, a higher convergence rate than that of the commonly used least-mean square algorithm is obtained, whilst attaining bit rates close to the optimum maximum shortening SNR and the upper bound SNR. Moreover, our proposed method outperforms the minimum mean-squared error design for a range of TEQ filter lengths.