Multiple Scattering and Attenuation Phenomena in Diffraction Imaging

The problem of cross sectional (tomographic) imaging bf objects with diffracting sources is addressed. Specifically the area of investigation is the effect of multiple scattering and attenuation phenomena in diffraction imaging. The validity of either the Born or the Rytov approximations is the basic assumption behind all the inverse scattering techniques in diffraction tomography. To test these techniques When these assumptions are not satisfied, we have developed a computational procedure for the calculation of the “ true” scattered fields from a multi-component object. Using this procedure, the performance of two available diffraction reconstruction techniques is examined in the presence of multiple scattering effects. The simulation results show the superiority of the Synthetic Aperture technique. We have also studied the role of attenuation in the reconstruction techniques. To calculate the scattered fields from an object in the presence of attenuation, new computer simulation programs are developed. These codes are used in a simulation study of the effect of the attenuation parameter on the object reconstuctions. [reconstruction

Lack of association between two ACE gene polymorphisms (rs4291 and Alu I/D) and late onset Alzheimer’s disease

Alzheimer’s disease (AD) is a prevalent disorder and the most common cause of dementia in elderly populations. Genetic and environmental factors together play a role in developing late onset Alzheimer's disease (LOAD). According to the recent published papers, ACE is one of the candidate susceptibility genes for LOAD. In this study, allele and genotype frequencies for rs4291 and rs1799752 polymorphisms of ACE gene, for 100 Iranian patients, affected with AD and 100 healthy controls were compared using Chi-square test. No statistically significant differences were found in genotype and allele frequencies of rs4291 and rs1799752 polymorphisms between our LOAD patients and controls. The pair-wise haplotype analysis of rs4291 -240 A/T and rs1799752 Alu I/D polymorphisms were also performed, but no significant associations were identified.Key words: ACE, Alzheimer’s disease, Iranian, association, polymorphism

FireNN: Neural Networks Reliability Evaluation on Hybrid Platforms

The growth of neural networks complexity has led to adopt of hardware-accelerators to cope with the computational power required by the new architectures. The possibility to adapt the network for different platforms enhanced the interests of safety-critical applications. The reliability evaluation of neural networks are still premature and requires platforms to measure the safety standards required by mission-critical applications. For this reason, the interest in studying the reliability of neural networks is growing. We propose a new approach for evaluating the resiliency of neural networks by using hybrid platforms. The approach relies on the reconfigurable hardware for emulating the target hardware platform and performing the fault injection process. The main advantage of the proposed approach is to involve the on-hardware execution of the neural network in the reliability analysis without any intrusiveness into the network algorithm and addressing specific fault models. The implementation of FireNN, the platform based on the proposed approach, is described in the paper. Experimental analyses are performed using fault injection on AlexNet. The analyses are carried out using the FireNN platform and the results are compared with the outcome of traditional software-level evaluations. Results are discussed considering the insight into the hardware level achieved using FireNN

On the evaluation of SEU effects on AXI interconnect within AP-SoCs

G-Programmable System-on-Chips offering the union of a processor system with a programmable hardware gave rise to applications that choose hardware acceleration to offload and parallelize computationally demanding tasks. Due to flexibility and performance they provide at low cost, these devices are also appealing for several applications in avionics, aerospace and automotive sectors, where reliability is the main concern. In particular, the interconnection architecture, and especially the AXI Interconnection for FPGA-accelerated applications, plays a critical role in these systems. This paper presents a reliability analysis of the AXI Interconnect IP Core implemented on Zynq-7000 AP-SoC against SEUs in the configuration memory of the programmable logic. The analysis has been conducted performing a fault injection campaign on the specific section of the configuration memory implementing the IP Core under test, which has been implemented within a benchmark design. The results are analyzed and classified, highlighting the criticality of the AXI Interconnect IP Core as a point of failure, especially for SEU-hardened hardware accelerator relying on mitigation techniques based on fine-grained and coarse-grained replication

On the Analysis of Radiation-induced Failures in the AXI Interconnect Module

Due to the increasing demand for high performance in embedded systems, devices such as SRAM-based programmable devices are becoming an appealing solution to reach high performance with limited costs. However, SRAM-based programmable devices are subjected to various sources of radiation-induced faults that affect their reliability, such as ionizing radiation and particles, even at sea-level. In this paper, we evaluate the reliability of the interconnection module, implemented on the programmable hardware, against radiation-induced faults in the configuration layer. To do so, we performed a fault injection campaign in order to emulate the radiation-induced effects impacting the configuration memory of AP-SoC Zynq 7000, specifically targeting the configuration memory section programming the interconnection module implemented on the programmable logic. This interconnection module is a crucial element for a wide range of applications and mitigation techniques such as hardware-accelerated designs, Dynamic Partial Reconfiguration, or Triple Modular Redundancy; especially if they are adopted to achieve high performance, high bandwidth and high reliability. The fault injection results have been analyzed and classified accordingly with the effect observed on the processor-system side in terms of availability and fault model affecting data computed by cores implemented on the programmable logic side

Analysis and Mitigation of Soft-Errors on High Performance Embedded GPUs

Multiprocessor system-on-chip such as embedded GPUs are becoming very popular in safety-critical applications, such as autonomous and semi-autonomous vehicles. However, these devices can suffer from the effects of soft-errors, such as those produced by radiation effects. These effects are able to generate unpredictable misbehaviors. Fault tolerance oriented to multi-threaded software introduces severe performance degradations due to the redundancy, voting and correction threads operations. In this paper, we propose a new fault injection environment for NVIDIA GPGPU devices and a fault tolerance approach based on error detection and correction threads executed during data transfer operations on embedded GPUs. The fault injection environment is capable of automatically injecting faults into the instructions at SASS level by instrumenting the CUDA binary executable file. The mitigation approach is based on concurrent error detection threads running simultaneously with the memory stream device to host data transfer operations. With several benchmark applications, we evaluate the impact of softerrors classifying Silent Data Corruption, Detection, Unrecoverable Error and Hang. Finally, the proposed mitigation approach has been validated by soft-error fault injection campaigns on an NVIDIA Pascal Architecture GPU controlled by Quad-Core A57 ARM processor (JETSON TX2) demonstrating an advantage of more than 37% with respect to state of the art solution

Preliminary Results of Relationship between Preoperative Walking Ability and Magnetic Resonance Imaging Morphology in Patients with Lumbar Canal Stenosis: Comparison between Trefoil and Triangle Types of Spinal Stenosis

Study DesignCross-sectional.PurposeTo examine the relationship between magnetic resonance imaging (MRI) morphology stenosis grades and preoperative walking ability in patients with lumbar canal stenosis (LCS).Overview of LiteratureNo previous study has analyzed the correlation between MRI morphology stenosis grades and walking ability in patients with LCS.MethodsThis prospective study included 98 consecutive patients with LCS who were candidates for surgery. Using features identified in T2-weighted axial magnetic, stenosis type was determined at the maximal stenosis level, and only trefoil and triangle stenosis grade types were considered because of sufficient sample size. Intraobserver and interobserver reliability were assessed by calculating weighted kappa coefficients. Symptom severity was evaluated via the Japanese Orthopedic Association Back Pain Evaluation Questionnaire (JOABPEQ). Walking ability was assessed using the Self-Paced Walking Test (SPWT) and JOABPEQ subscales. Demographic characteristics, SPWT scores, and JOABPEQ scores were compared between patients with trefoil and triangle stenosis types.ResultsThe mean patient age was 58.1 (standard deviation, 8.4) years. The kappa values of the MRI morphology stenosis grade types showed a perfect agreement between the stenosis grade types. The trefoil group (n=53) and triangle group (n=45) showed similar preoperative JOABPEQ subscale scores (e.g., low back pain, lumbar function, and mental health) and were not significantly different in age, BMI, duration of symptoms, or lumbar stenosis levels (all p>0.05); however, trefoil stenosis grade type was associated with a decreased walking ability according to the SPWT and JOABPEQ subscale scores.ConclusionsThese findings suggest preoperative walking ability is more profoundly affected in patients with trefoil type stenosis than in those with triangle type stenosis