GAS: Generating Fast and Accurate Surrogate Models for Autonomous Vehicle Systems

Modern autonomous vehicle systems use complex perception and control components. These components can rapidly change during development of such systems, requiring constant re-testing. Unfortunately, high-fidelity simulations of these complex systems for evaluating vehicle safety are costly. The complexity also hinders the creation of less computationally intensive surrogate models. We present GAS, the first approach for creating surrogate models of complete (perception, control, and dynamics) autonomous vehicle systems containing complex perception and/or control components. GAS's two-stage approach first replaces complex perception components with a perception model. Then, GAS constructs a polynomial surrogate model of the complete vehicle system using Generalized Polynomial Chaos (GPC). We demonstrate the use of these surrogate models in two applications. First, we estimate the probability that the vehicle will enter an unsafe state over time. Second, we perform global sensitivity analysis of the vehicle system with respect to its state in a previous time step. GAS's approach also allows for reuse of the perception model when vehicle control and dynamics characteristics are altered during vehicle development, saving significant time. We consider five scenarios concerning crop management vehicles that must not crash into adjacent crops, self driving cars that must stay within their lane, and unmanned aircraft that must avoid collision. Each of the systems in these scenarios contain a complex perception or control component. Using GAS, we generate surrogate models for these systems, and evaluate the generated models in the applications described above. GAS's surrogate models provide an average speedup of $3.7\times$ for safe state probability estimation (minimum $2.1\times$) and $1.4\times$ for sensitivity analysis (minimum $1.3\times$), while still maintaining high accuracy

FastFlip: Compositional Error Injection Analysis

Instruction-level error injection analyses aim to find instructions where errors often lead to unacceptable outcomes like Silent Data Corruptions (SDCs). These analyses require significant time, which is especially problematic if developers wish to regularly analyze software that evolves over time. We present FastFlip, a combination of empirical error injection and symbolic SDC propagation analyses that enables fast, compositional error injection analysis of evolving programs. FastFlip calculates how SDCs propagate across program sections and correctly accounts for unexpected side effects that can occur due to errors. Using FastFlip, we analyze five benchmarks, plus two modified versions of each benchmark. FastFlip speeds up the analysis of incrementally modified programs by $3.2\times$ (geomean). FastFlip selects a set of instructions to protect against SDCs that minimizes the runtime cost of protection while protecting against a developer-specified target fraction of all SDC-causing errors

Machine Vision Using Cellphone Camera: A Comparison of deep networks for classifying three challenging denominations of Indian Coins

Indian currency coins come in a variety of denominations. Off all the varieties Rs.1, RS.2, and Rs.5 have similar diameters. Majority of the coin styles in market circulation for denominations of Rs.1 and Rs.2 coins are nearly the same except for numerals on its reverse side. If a coin is resting on its obverse side, the correct denomination is not distinguishable by humans. Therefore, it was hypothesized that a digital image of a coin resting on its either size could be classified into its correct denomination by training a deep neural network model. The digital images were generated by using cheap cell phone cameras. To find the most suitable deep neural network architecture, four were selected based on the preliminary analysis carried out for comparison. The results confirm that two of the four deep neural network models can classify the correct denomination from either side of a coin with an accuracy of 97%.Comment: 6 Pages, 4 Figures, 6 Tables, Conference pape

Removal of phosphate from River water using a new baffle plates electrochemical reactor

During the last 50 years, the human activities have significantly altered the natural cycle of phosphate in this planet, causing phosphate to accumulate in the freshwater ecosystems of some countries to at least 75% greater than preindustrial levels, which indicates an urgent need to develop efficient phosphate treatment methods. Therefore, the current study investigates the removal of phosphate from river water using a new electrochemical cell (PBPR). This new cell utilises perforated baffle plates as a water mixer rather than magnetic stirrers that require power to work. This study investigates the influence of key operational parameters such as initial pH (ipH), current density (Ј), inter-electrode distance (ID), detention time (t) and initial phosphate concentration (IC) on the removal efficiency, and influence of the electrocoagulation process on the morphology of the surface of electrodes. Overall, the results showed that the new reactor was efficient enough to reduce the concentration of phosphate to the permissible limits. Additionally, SEM images showed that the Al anode became rough and nonuniform due to the production of aluminium hydroxides. The main advantages of the electrocoagulation technique are: 1- The EC method does not produce secondary pollutants as it does not required chemical additives, while other traditional treatment methods required either chemical or biological additives [[1], [2], [3], [4]]. 2- It has a large treatment capacity and a relatively short treatment time in comparison with other treatment methods, such as the biological methods [1,[5], [6], [7]]. 3- The EC method produces less sludge than traditional treatment traditional chemical and biological treatment methods [8,9]. EC technology, like any other treatment method, has some drawbacks that could limit its performance. For instance, it still has a clear deficiency in the variety of reactor design, and the electrodes should be periodically replaced as they dissolve into the solution due to the oxidation process [2,10]

Implementation of a Cache Miss Calculator in LLVM/Polly

We propose an LLVM pass to mathematically measure cache misses for Static Control Parts (SCoPs) of programs. Our implementation builds on top of the Polly infrastructure and has support for features such as LRU associativity, unknown array base addresses, and (some) approximation. We describe our preliminary results and limitations by using this pass on a selection of SCoPs. Finally we list directions for expanding and improving this work

Contrast-Induced Nephropathy: Myth or Reality? Single center experience in patients undergoing planned percutaneous coronary intervention

The definition of Contrast-induced nephropathy (CIN) is the impairment of renal function and is measured either as increase in serum creatinine (SCr) by 25% from baseline or 0.5 mg/dL increase in absolute value, within 48-72 hours of intravenous contrast administration.The objectives were to establish the incidence of CIN and to define the clinical and periprocedural risk factors leading to CIN in patients receiving contrast media.Methods: In a retrospective, observational, descriptive study, patients who were admitted to the hospital for therapeutic Percutaneous Coronary Inervention (PCI) between June 2020 to December 2020, the serum creatinine and glomerular filtration rate (GFR) prior to angiography and 72 hours post procedure were measured. Results: 202 patients were included in the study, of which 4.45 % developed CIN.Discussion: In our study,the incidence was found to be lower than the literature review. The present study investigated renal function in the chronic phase in patients with ischemic heart disease undergoing planned PCI. The progression of renal dysfunction in patients who develop CIN is thought to result from glomerular overfiltration in the residual nephrons and the release of neurohormones that reduce renal blood flow

Management of Ectodermal Dysplasia in A 7 Year Old Child

Background: Ectodermal dysplasia is a hereditary group of disorders which are manifested as X-linked recessive trait and has a full expression in males, whereas females show little or no signs of the disorder. This disorder leads to disturbances in the ectoderm of the developing embryo. It has many evident general and oral features which makes its rehabilitation of utmost importance. Correction of the presenting clinical oral disorders may help improve the quality of life for the patient. A multidisciplinary approach has to be adopted for such cases and it becomes a challenge in pediatric patients. In this report, etiology, clinical presentation, diagnosis and treatment plan of a 7-year-old male patient suffering from ectodermal dysplasia has been discussed