1,600 research outputs found
Ingress of threshold voltage-triggered hardware trojan in the modern FPGA fabricâdetection methodology and mitigation
The ageing phenomenon of negative bias temperature instability (NBTI) continues to challenge the dynamic thermal management of modern FPGAs. Increased transistor density leads to thermal accumulation and propagates higher and non-uniform temperature variations across the FPGA. This aggravates the impact of NBTI on key PMOS transistor parameters such as threshold voltage and drain current. Where it ages the transistors, with a successive reduction in FPGA lifetime and reliability, it also challenges its security. The ingress of threshold voltage-triggered hardware Trojan, a stealthy and malicious electronic circuit, in the modern FPGA, is one such potential threat that could exploit NBTI and severely affect its performance. The development of an effective and efficient countermeasure against it is, therefore, highly critical. Accordingly, we present a comprehensive FPGA security scheme, comprising novel elements of hardware Trojan infection, detection, and mitigation, to protect FPGA applications against the hardware Trojan. Built around the threat model of a naval warshipâs integrated self-protection system (ISPS), we propose a threshold voltage-triggered hardware Trojan that operates in a threshold voltage region of 0.45V to 0.998V, consuming ultra-low power (10.5nW), and remaining stealthy with an area overhead as low as 1.5% for a 28 nm technology node. The hardware Trojan detection sub-scheme provides a unique lightweight threshold voltage-aware sensor with a detection sensitivity of 0.251mV/nA. With fixed and dynamic ring oscillator-based sensor segments, the precise measurement of frequency and delay variations in response to shifts in the threshold voltage of a PMOS transistor is also proposed. Finally, the FPGA security scheme is reinforced with an online transistor dynamic scaling (OTDS) to mitigate the impact of hardware Trojan through run-time tolerant circuitry capable of identifying critical gates with worst-case drain current degradation
Cross-Layer Approaches for an Aging-Aware Design of Nanoscale Microprocessors
Thanks to aggressive scaling of transistor dimensions, computers have revolutionized our life. However, the increasing unreliability of devices fabricated in nanoscale technologies emerged as a major threat for the future success of computers. In particular, accelerated transistor aging is of great importance, as it reduces the lifetime of digital systems. This thesis addresses this challenge by proposing new methods to model, analyze and mitigate aging at microarchitecture-level and above
Low-Cost Throttle-By-Wire-System Architecture For Two-Wheeler Vehicles
This paper investigates the performance of a low-cost Throttle-by-Wire-System
(TbWS) for two-wheeler applications. Its consisting of an AMR throttle position
sensor and a position controlled stepper motor driven throttle valve actuator.
The decentralized throttle position sensor is operating contactless and
acquires redundant data. Throttle valve actuation is realized through a
position controlled stepper motor, sensing its position feedback by Hall
effect. Using a PI-controller the stepper motors position is precisely set.
Sensor and actuator units are transceiving data by a CAN bus. Furthermore,
failsafe functions, plausibility checks, calibration algorithms and energy
saving modes have been implemented. Both modules have been evaluated within a
Hardware-in-the-Loop test environment in terms of reliability and
measurement/positioning performance before the TbWS was integrated in a Peugeot
Kisbee 50 4T (Euro 5/injected). Finally, the sensor unit comes with a
measurement deviation of less then 0.16% whereas the actuator unit can approach
throttle valve positions with a deviation of less then 0.37%. The actuators
settling time does not exceed 0.13s while stable, step-loss free and noiseless
operation
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Multi-functional anodes boost the transient power and durability of proton exchange membrane fuel cells.
Proton exchange membrane fuel cells have been regarded as the most promising candidate for fuel cell vehicles and tools. Their broader adaption, however, has been impeded by cost and lifetime. By integrating a thin layer of tungsten oxide within the anode, which serves as a rapid-response hydrogen reservoir, oxygen scavenger, sensor for power demand, and regulator for hydrogen-disassociation reaction, we herein report proton exchange membrane fuel cells with significantly enhanced power performance for transient operation and low humidified conditions, as well as improved durability against adverse operating conditions. Meanwhile, the enhanced power performance minimizes the use of auxiliary energy-storage systems and reduces costs. Scale fabrication of such devices can be readily achieved based on the current fabrication techniques with negligible extra expense. This work provides proton exchange membrane fuel cells with enhanced power performance, improved durability, prolonged lifetime, and reduced cost for automotive and other applications
Robust elbow angle prediction with aging soft sensors via output-level domain adaptation
Wearable devices equipped with soft sensors provide a promising solution for body movement monitoring. Specifically, body movements like elbow flexion can be captured by monitoring the stretched soft sensorsâ resistance changes. However, in addition to stretching, the resistance of a soft sensor is also influenced by its aging, which makes the resistance a less stable indicator of the elbow angle. In this paper, we leverage the recent progress in Deep Learning and address the aforementioned issue by formulating the aging-invariant prediction of elbow angles as a domain adaption problem. Specifically, we define the soft sensor data (i.e., resistance values) collected at different aging levels as different domains and adapt a regression neural network among them to learn domain-invariant features. However, unlike the popular pairwise domain adaptation problem that only involves one source and one target domain, ours is more challenging as it has âinfiniteâ target domains due to the non-stop aging. To address this challenge, we novelly propose an output-level domain adaptation approach which builds on the fact that the elbow angles are in a fixed range regardless of aging. Experimental results show that our method enables robust and accurate prediction of elbow angles with aging soft sensors, which significantly outperforms supervised learning ones that fail to generalize to aged sensor data
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The Effects of Neurosteroids, such as Pregnenolone Sulfate and its receptor, TrpM3 in the Retina.
Pregnenolone sulfate (PregS) is the precursor to all steroid hormones and is produced in neurons in an activity dependent manner. Studies have shown that PregS production is upregulated during certain critical periods of development, such as in the first year of life in humans, during adolescence, and during pregnancy. Conversely, PregS is decreased during aging, as well as in several neurodevelopmental and neurodegenerative conditions. There are several known targets of PregS, such as a positive allosteric modulator NMDA receptors, sigma1 receptor, and as a negative allosteric modulator of GABA-A receptors. Recently a transient receptor potential channel, TrpM3 has been shown to be activated by PregS. TrpM3 is a heat sensitive (between 33-40oC), non-selective cation channel that is outwardly rectifying. PregS has been shown to increase the frequency of post-synaptic currents in the hippocampus and developing cerebellum, induce calcium transients in a subset of retinal ganglion cells, and enhance memory formation in rodents. Furthermore, PregS mediated TrpM3 activation induces calcium dependent transcription of early immediate genes, suggesting that activation of this channel may produce lasting effects on cells and systems in which it is activated. Because PregS is abundant during critical periods of development, we hypothesized that it may play a significant role during development. Furthermore, the role of PregS or its receptor TrpM3, has not previously been well characterized in the retina. To address this question, in this dissertation, we examine the role of the neurosteroid PregS and its receptor, TrpM3, on retinal waves, which are characteristic of specific stages of synaptic development and connectivity. Briefly, we show that PregS induces a TrpM3 dependent prolonged calcium transient, which is absent in the TrpM3-/- animals and increases the correlation of cell participation in waves. We also show that TrpM3 increases the frequency of post-synaptic currents, indicating a mechanism of action presynaptic to retinal ganglion cells, but that TrpM3 is expressed primarily in RGCs and MĂŒller glia. Taken together, our results indicate that both PregS and TrpM3 are important in modulating spontaneous synaptic activity during development
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