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We present a model-based testing approach for reactive systems where both test inputs and expected results are generated from ‘restricted’ Event-B specifications. We show that it is possible to automatically build the restricted Event-B specifications from the original ones base on a knowledge base of the system under tests. The restricted models are to reduce the state space of the original Event-B...
The hashtag recommendation problem addresses recommending (suggesting) one or more hashtags to explicitly tag a post made on a given social network platform, based upon the content and context of the post. In this work, we propose a novel methodology for hashtag recommendation for microblog posts, specifically Twitter. The methodology, EmTaggeR, is built upon a training-testing framework that builds...
Ramsey theory assures us that in any graph there is a clique or independent set of a certain size, roughly logarithmic in the graph size. But how difficult is it to find the clique or independent set? If the graph is given explicitly, then it is possible to do so while examining a linear number of edges. If the graph is given by a black-box, where to figure out whether a certain edge exists the box...
When using formal verification on critical software, an important question involves whether we have we specified enough properties for a given implementation model. To address this question, coverage metrics for property-based formal verification have been proposed. Existing metrics are usually based on mutation, where the implementation model is repeatedly modified and re-analyzed to determine whether...
Fault injection testing approaches assess the reliability of execution environments for critical software. They support the early testing of safety concepts that mitigate the impact of hardware failures on software behavior. The growing use of platform software for embedded systems raises the need to verify safety concepts that execute on top of operating systems and middleware platforms. Current...
A classical difficult isomorphism testing problem is to test isomorphism of p-groups of class 2 and exponent p in time polynomial in the group order. It is known that this problem can be reduced to solving the alternating matrix space isometry problem over a finite field in time polynomial in the underlying vector space size. We propose a venue of attack for the latter problem by viewing it as a linear...
The Computational Thinking (CT) conceptual framework is entering its second decade of research yet still lacks a cohesive definition by which the field can coalesce. The lack of clear definition makes assessment tool challenging to formulate, pedagogical efforts difficult to compare, and research difficult to synthesize. This paper looks to operationalize differing definitions of CT enhancing the...
Although Deep Convolutional Neural Networks (CNNs) have liberated their power in various computer vision tasks, the most important components of CNN, convolutional layers and fully connected layers, are still limited to linear transformations. In this paper, we propose a novel Factorized Bilinear (FB) layer to model the pairwise feature interactions by considering the quadratic terms in the transformations...
This paper describes the use of convolutional neural network(CNN) method to classify various image and photo of Indonesia ancient temple. The method itself implements Deep Learning technique designed for Computer Vision task. The idea behind CNN is image pre-processing through a stack of convolution layers to create many patterns that can be easily recognized. The result shows that the learning model...
This paper introduces a kind of simulation testing system scheme for train-borne controller and applies it to the simulation testing system of the controller. Besides, it elaborates the system structure, interface type and key module of the hardware realization. The simulation testing system for train-borne controller is completely built, and plays a vital role in the train-borne controller simulation...
We present CoSTest, a tool that supports the validation of Conceptual Schemas by using testing. The tool implements techniques for transforming instantiations from a Requirements Model into test case implementations by supporting a Model-driven architecture.
The Automated Systems of Technical Diagnostics (ASTD) of the dynamic distributed information systems (DIS) need the operational reconfiguration corresponding to changes of DIS. As a result, support of ASTD also requires the up-dating, advancing changes of DIS. In this work, development of the network model of testing is provided, allowing to reduce time of synthesis of tests for DIS. The Model is...
Model-Based Testing is a testing approach used for automated test generation, execution, and evaluation. It is based on a formal behavioral model of the tested system. This paper presents a new test generation method that utilizes an advanced variant of Petri nets for a description of the systems under test and Constraint programming for tests generation. The presented method aims for modeling and...
This paper presents hybrid L- and P-stable implicit numerical methods for solving differential equations of electronic circuits and systems. Hybrid methods are developed on the basis of two known subclasses of implicit Runge-Kutta methods commonly referred to as Rado IIA and Lobatto IIIA methods. Comparative analysis of the known methods and the proposed hybrid methods demonstrates a high accuracy...
The programmability of Software-Defined Networking (SDN) challenges the correctness and reliability of networks. There may be design flaws as well as implementation bugs in SDN applications. White-box testing methods with formal models rely on source codes, which limits the applicability of these methods. Black-box methods without behavior models cannot systematically cover an application's functions...
This paper discusses how to enhance the ability of text modeling in Arabic during chat sessions. Hanini and Jabari et al. modeled the text in chat sessions, but there is still a problem when using Arabic, because the Arabic language is very difficult to comprehend, has complex derivative and many ambiguities. This paper enhanced the previous study and added MADAMIRA tool to analyze the Arabic text...
Recurrent neural networks with various types of hidden units have been used to solve a diverse range of problems involving sequence data. Two of the most recent proposals, gated recurrent units (GRU) and minimal gated units (MGU), have shown comparable promising results on example public datasets. In this paper, we introduce three model variants of the minimal gated unit which further simplify that...
In this paper, we address the problem of fault detection (FD) of chemical processes using improved generalized likelihood ratio test. The improved GLRT is the method that combines the advantages of the exponentially weighted moving average (EWMA) filter with those of the GLRT method. The idea behind the developed EWMA-GLRT is to compute a new GLRT statistic that integrates current and previous data...
We presented a generalization of the delay-and-sum beamforming based on the Dirac-Delta functions but with nonlinear argument. For this end, a closed-form expression of the beampattern $\mathcal{B}(r)=\sum\nolimits_{k,q}w(k,q,r)x(k,q,r)$ with r = r(θ), was derived. This expression is computationally simulated through an algorithm that includes integer-order Bessel input functions and random noise...
Car Recognition is a part of Intelligent Transportation System. This research proposes the manufacture of ITS-based system to identify car model from Its frontal image using Binary Robust Invariant Scalable method. The BRISK method is used to detect image keypoint, and it uses Hamming Distance for keypoint matching. As for matching error, this research depends on RANSAC. BRISK method excellence lies...
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