A Review of Bayesian Methods in Electronic Design Automation

The utilization of Bayesian methods has been widely acknowledged as a viable solution for tackling various challenges in electronic integrated circuit (IC) design under stochastic process variation, including circuit performance modeling, yield/failure rate estimation, and circuit optimization. As the post-Moore era brings about new technologies (such as silicon photonics and quantum circuits), many of the associated issues there are similar to those encountered in electronic IC design and can be addressed using Bayesian methods. Motivated by this observation, we present a comprehensive review of Bayesian methods in electronic design automation (EDA). By doing so, we hope to equip researchers and designers with the ability to apply Bayesian methods in solving stochastic problems in electronic circuits and beyond.Comment: 24 pages, a draft version. We welcome comments and feedback, which can be sent to [email protected]

Prognostics and health management of light emitting diodes

Prognostics is an engineering process of diagnosing, predicting the remaining useful life and estimating the reliability of systems and products. Prognostics and Health Management (PHM) has emerged in the last decade as one of the most efficient approaches in failure prevention, reliability estimation and remaining useful life predictions of various engineering systems and products. Light Emitting Diodes (LEDs) are optoelectronic micro-devices that are now replacing traditional incandescent and fluorescent lighting, as they have many advantages including higher reliability, greater energy efficiency, long life time and faster switching speed. Even though LEDs have high reliability and long life time, manufacturers and lighting systems designers still need to assess the reliability of LED lighting systems and the failures in the LED. This research provides both experimental and theoretical results that demonstrate the use of prognostics and health monitoring techniques for high power LEDs subjected to harsh operating conditions. Data driven, model driven and fusion prognostics approaches are developed to monitor and identify LED failures, based on the requirement for the light output power. The approaches adopted in this work are validated and can be used to assess the life of an LED lighting system after their deployment based on the power of the light output emitted. The data driven techniques are only based on monitoring selected operational and performance indicators using sensors whereas the model driven technique is based on sensor data as well as on a developed empirical model. Fusion approach is also developed using the data driven and the model driven approaches to the LED. Real-time implementation of developed approaches are also investigated and discussed

Workshop on Fuzzy Control Systems and Space Station Applications

The Workshop on Fuzzy Control Systems and Space Station Applications was held on 14-15 Nov. 1990. The workshop was co-sponsored by McDonnell Douglas Space Systems Company and NASA Ames Research Center. Proceedings of the workshop are presented

VLSI Design

This book provides some recent advances in design nanometer VLSI chips. The selected topics try to present some open problems and challenges with important topics ranging from design tools, new post-silicon devices, GPU-based parallel computing, emerging 3D integration, and antenna design. The book consists of two parts, with chapters such as: VLSI design for multi-sensor smart systems on a chip, Three-dimensional integrated circuits design for thousand-core processors, Parallel symbolic analysis of large analog circuits on GPU platforms, Algorithms for CAD tools VLSI design, A multilevel memetic algorithm for large SAT-encoded problems, etc

Sensors Fault Diagnosis Trends and Applications

Fault diagnosis has always been a concern for industry. In general, diagnosis in complex systems requires the acquisition of information from sensors and the processing and extracting of required features for the classification or identification of faults. Therefore, fault diagnosis of sensors is clearly important as faulty information from a sensor may lead to misleading conclusions about the whole system. As engineering systems grow in size and complexity, it becomes more and more important to diagnose faulty behavior before it can lead to total failure. In the light of above issues, this book is dedicated to trends and applications in modern-sensor fault diagnosis

NASA Tech Briefs, June 1989

Topics include: New Product Ideas; NASA TU Services; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery; Fabrication Technology; Mathematics and Information Sciences; Life Sciences

Bio-Inspired Multi-Spectral Image Sensor and Augmented Reality Display for Near-Infrared Fluorescence Image-Guided Surgery

Background: Cancer remains a major public health problem worldwide and poses a huge economic burden. Near-infrared (NIR) fluorescence image-guided surgery (IGS) utilizes molecular markers and imaging instruments to identify and locate tumors during surgical resection. Unfortunately, current state-of-the-art NIR fluorescence imaging systems are bulky, costly, and lack both fluorescence sensitivity under surgical illumination and co-registration accuracy between multimodal images. Additionally, the monitor-based display units are disruptive to the surgical workflow and are suboptimal at indicating the 3-dimensional position of labeled tumors. These major obstacles have prevented the wide acceptance of NIR fluorescence imaging as the standard of care for cancer surgery. The goal of this dissertation is to enhance cancer treatment by developing novel image sensors and presenting the information using holographic augmented reality (AR) display to the physician in intraoperative settings. Method: By mimicking the visual system of the Morpho butterfly, several single-chip, color-NIR fluorescence image sensors and systems were developed with CMOS technologies and pixelated interference filters. Using a holographic AR goggle platform, an NIR fluorescence IGS display system was developed. Optoelectronic evaluation was performed on the prototypes to evaluate the performance of each component, and small animal models and large animal models were used to verify the overall effectiveness of the integrated systems at cancer detection. Result: The single-chip bio-inspired multispectral logarithmic image sensor I developed has better main performance indicators than the state-of-the-art NIR fluorescence imaging instruments. The image sensors achieve up to 140 dB dynamic range. The sensitivity under surgical illumination achieves 6108 V/(mW/cm2), which is up to 25 times higher. The signal-to-noise ratio is up to 56 dB, which is 11 dB greater. These enable high sensitivity fluorescence imaging under surgical illumination. The pixelated interference filters enable temperature-independent co-registration accuracy between multimodal images. Pre-clinical trials with small animal model demonstrate that the sensor can achieve up to 95% sensitivity and 94% specificity with tumor-targeted NIR molecular probes. The holographic AR goggle provides the physician with a non-disruptive 3-dimensional display in the clinical setup. This is the first display system that co-registers a virtual image with human eyes and allows video rate image transmission. The imaging system is tested in the veterinary science operating room on canine patients with naturally occurring cancers. In addition, a time domain pulse-width-modulation address-event-representation multispectral image sensor and a handheld multispectral camera prototype are developed. Conclusion: The major problems of current state-of-the-art NIR fluorescence imaging systems are successfully solved. Due to enhanced performance and user experience, the bio-inspired sensors and augmented reality display system will give medical care providers much needed technology to enable more accurate value-based healthcare

Para-images: Cultural ideas and technical apparatuses beyond the pictorial surfaces

Our world is hinged on images. The mass obsession with selfies and spectacles, the surveillance technology and Deepfake videos enabled by computer vision, the Event Horizon Telescope that produced the first image of a black hole, the simulations which climate change research relies on. Reality is being ever more entangled with image, yet images are increasingly detached from the physical world and escape human comprehension. It is obvious that the traditional understanding of images as a representation of the world, while valid, will no longer suffice to account for the intertwined relationship images has with our world. Contemplating the ever-complex relationship between images and reality, the thesis proposes a new approach to understanding images in contemporary visual culture: para-images. The thesis employs Vilém Flusser’s notion of counter vision to examine cultural ideas and technical apparatuses operating beyond the pictorial surfaces of seven images of water splashes. In the process, the thesis identifies agential realism and twenty-first-century media as two useful frameworks in formulating the triangular relationship among humans, images and the world. Attempting to answer the question ‘What is left of an image if the pictorial surface is scratched away?’, the thesis uncovers the often neglected ideological and technical infrastructures that make images possible in the first place. Situating images and machines at the same level of humans as entities with their own agencies, the image theory this thesis establishes concerns the entanglement of humans, machines, apparatuses, images and the world. In short, an image is the world, the world is an image

Following the light:Novel event reconstruction techniques for neutrino oscillation analyses in KM3NeT/ORCA

Neutrinos are tiny, subatomic particles which currently present some outstanding questions in the field of particle physics. Though neutrino oscillations are now an understood phenomenon, efforts are still underway to measure the neutrino oscillation parameters even more precisely. Furthermore, the ordering of the three neutrino mass states relative to one another - the neutrino mass ordering - is still unknown. The KM3NeT/ORCA detector is currently being built in the Mediterranean Sea to address such questions. This infrastructure surrounds huge volumes of seawater with photodetectors, bypassing the tiny interaction cross section of these particles, and detecting the Cherenkov radiation of products of neutrino interactions in the water. In this thesis, the software used to simulate atmospheric muons in the detector using parametric formulae is tuned to KM3NeT/ORCA data, resulting in an improved simulation of the atmospheric muons, which form the main background for neutrino analyses. A novel neutrino event reconstruction algorithm is developed and explored in this thesis, aiming to reconstruct neutrino events with both a track-like and particle shower-like component. The estimate of the reconstructed neutrino energy is improved upon with this technique, as well as directly reconstructing the fractional energy transfer to the hadronic shower component of the interaction. This reconstruction technique also shows the potential for identifying different neutrino interaction channels. The improved energy estimate and the potential to identify the interaction channel pave the way for future analyses, leading to an improved measurement of the neutrino oscillation parameters and determination of the yet-unknown neutrino mass ordering

SCEE 2008 book of abstracts : the 7th International Conference on Scientific Computing in Electrical Engineering (SCEE 2008), September 28 – October 3, 2008, Helsinki University of Technology, Espoo, Finland

This report contains abstracts of presentations given at the SCEE 2008 conference.reviewe