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The development of algorithms and models to be used for prediction of the reliability and health monitoring of components and sensors is of great importance in aerospace, automotive and power generation industry. For this purpose metamodels have been developed that are based on physical simulations and that are able to quantify the impact of uncertainties on system behavior. These surrogate metamodels...
Suppliers developing semiconductor technologies for consumer electronics have been operating in a high-volume manner for decades. It is often believed that there is a link between high volume, high yield, and high reliability. A potentially concerning misconception is that low volume manufacturing facilities then cannot achieve high reliability. However, many ‘high reliability’ markets, such as military,...
All engineering disciplines are founded and rely on models, although they may differ on purposes and usages of modeling. Interdisciplinary domains such as Cyber Physical Systems (CPSs) seek approaches that incorporate different modeling needs and usages. Specifically, the Simulink modeling platform greatly appeals to CPS engineers due to its seamless support for simulation and code generation. In...
We present SimCoTest, a tool to generate small test suites with high fault revealing ability for Simulink/Stateflow controllers. SimCoTest uses meta-heuristic search to (1) maximize the likelihood of presence of specific failure patterns in output signals (failure-based test generation), and to (2) maximize diversity of output signal shapes (output diversity test generation). SimCoTest has been evaluated...
We propose a Low-Dimensional Deep Feature based Face Alignment (LDFFA) method to address the problem of face alignment “in-the-wild”. Recently, Deep Bottleneck Features (DBF) has been proposed as an effective channel to represent input with compact, low-dimensional descriptors. The locations of fiducial landmarks of human faces could be effectively represented using low dimensional features due to...
In this paper we propose a method to improve the detection of shadowed flaws in ultrasonic non-destructive testing (NDT). The B-scans are expressed in the context of Sparse Signal Recovery (SSR), where the shadowing effect is incorporated during the reconstruction: Whenever a new defect is found, its shadow on all other dictionary atoms is determined and the dictionary is updated accordingly. We develop...
Accurate pedestrian detection with high speed is always of great interests especially for practical application. Detectors usually follow the feature selection paradigm, and need to first construct rich and diverse features. In particular, current state-of-the-arts generate more channels of feature by convolving the basic feature channels with filter banks, which significantly improves accuracy. In...
This paper presents a new approach of Extreme Learning Machine (ELM) ensembles that use majority voting with the q-Gaussian Activation function Circular Extreme Learning Machine (QCELM) to make the final decision for classification problems. For each QCELM is work on the CELM using q-Gaussian activation functions based on Tsallis distribution that varies the different parameter q values (called the...
This paper proposes a practical implementation for the generation of real-time K-Distributed correlated sea-clutter in firmware. The method uses a dual cumulative distribution function (CDF) based look-up method to transpose a complex uniformly distributed random variable (RV) to the required RV. The clutter is correlated by means of a filter process before translation, and it is shown that this technique...
With the development of intelligent technology, Smart Home began to integrate into people's family life, and intelligent technology can provide more ideas for the establishment of a healthy home ecology. In order to better solve the security risks of family ecological environment, maintain the health of families, we analyzes the application and development of wisdom life philosophy, family ecological...
A fuzzy string matching approach is proposed to solve the pattern recognition problems in this paper. The edit cost is presented as a fuzzy number. The string matching problem with fuzzy edit cost was then equivalent to a shortest path problem with fuzzy weights. By ranking the fuzzy numbers, the object is classified as the reference object that has the minimum fuzzy distance. Some testing objects...
Image contains repetitive patterns always cause the point ambiguity, which makes the local descriptors less discriminative. The descriptor which is combined scale-invariant feature transform (SIFT) with the global context (GC) is used to solve the problem widely. But this descriptor is invalid when the variation of viewpoint is large. In this paper, an affine invariant matching method for image contains...
Recent works of non-rigid registration have shown promising applications on tasks of deformable manipulation. Those approaches use thin plate spline-robust point matching (TPS-RPM) algorithm to regress a transformation function, which could generate a corresponding manipulation trajectory given a new pose/shape of the object. However, this method regards the object as a bunch of discrete and independent...
This work introduces a novel artificial intelligence approach to household object recognition. The approach used in this work is feature-based and it works toward recognition under a broad range of circumstances. The necessary image processing techniques are applied to recognize the objects. These techniques include removal of shadow that is segmenting the object from its shadow, extraction of shape...
Plant species identification is a digitally challenging object for a better classification such as in taxonomy resources problem. Feature selection as a preprocessing technique in data mining help to identify the prominent attributes of herbal leave with higher dimensioned data set. For this purpose, Relief Feature Selection algorithm was utilized for the improvement of Fuzzy K-Nearest Neighbor (Fuzzy...
Drop testing is very important in many industries. In industries, the items face severe environmental conditions during their working life. These environmental conditions can be due to high temperature, high pressure, vibration, transportation effect and it can be shock effects. Drop testing is used for shock effects. First of all, theoretical modeling was done for the drop table to check that either...
The shaping by hydroforming process involves several complex phenomena and presents several types of nonlinearities (geometric, material,…). The development of a hydroforming operation requires a lot of testing to determine with precision the optimum loads of trips and get a room without defects. Advances in digital tools have enabled manufacturers to simulate and optimize their production facilities...
Hydrokinetic turbines, also known as marine current turbines, have the potential to be a major component of the world's renewable energy portfolio. Improving the efficiency of turbines is critical to making this technology more widespread and cost-effective. This work focused on raising power output for a given turbine blade design and flow speed through the addition of a straight-diffusing shroud...
Text detection is a difficult task due to the significant diversity of the texts appearing in natural scene images. In this paper, we propose a novel text descriptor, SPP-net, extracted by equipping the Convolutional Neural Network (CNN) with spatial pyramid pooling. We first compute the feature maps from the original text lines without any cropping or warping, and then generate the fixed-size representations...
Behaviour-Driven Development (BDD) is an "outside-in" approach to software development built upon semi-formal mediums for specifying the behaviour of a system as it would be observed externally. Through the representation of a system as a collection of user stories and scenarios using BDD's notation, practitioners automate acceptance tests using examples of desired behaviour for the envisioned...
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