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We propose EC3, a novel algorithm that merges classification and clustering together in order to support both binary and multi-class classification. EC3 is based on a principled combination of multiple classification and multiple clustering methods using a convex optimization function. We additionally propose iEC3, a variant of EC3 that handles imbalanced training data. We perform an extensive experimental...
The gravitational water vortex power plant (GWVPP) is a new type of low head turbine system in which a channel and basin structure is used to form a vortex, where the rotational energy from the water can be extracted through a runner. This study is focused on the optimization of the runner to improve the efficiency of the GWVPP. Computational fluid dynamics (CFD) analysis is carried out on three different...
Multi-objective optimization plays an important role when one has fitness functions that are somehow conflicting with each other. Also, parameter-dependent machine learning techniques can benefit from such optimization tools. In this paper, we propose a multi-objective-based strategy approach to build compact though representative training sets for Optimum-Path Forest (OPF) learning purposes. Although...
This paper gives a brief overview of the current state in the ant colony optimization (ACO) field of study. Furthermore, it introduces an alternative pheromone laying strategy for the ACO algorithm. In the paper, the newly introduced strategy is implemented, tested on a model problem and compared with the classical approach. A parameterized problem space generator has been introduced. The generator...
The systems and the software in the domain of industrial trucks are becoming increasingly complex due to the rapidly increasing demand for more functionality. This leads to an even faster rising effort for manual verification activities. Therefore, automated testing techniques need to be introduced into the verification process.In this work, a search-based test generation technique has been adapted...
In an iterative and incremental development environment software regression testing plays an important role; it helps to ensure the reliability in the building process of a software product. The optimization of a regression test depends on the size of the test suite to be executed. Regression testing helps to verify existing modifications (fixing bugs) or verify new features added to a software product...
Pairwise strategies have tested effectively a range of software and hardware systems. These testing strategies offer solutions that can substitute exhaustive testing. In simple terms, a pairwise testing strategy significantly minimizes large input parameter values (or configuration options) of a system into a smaller set based on pairwise interaction (or combination). Fuzzy Adaptive Teaching Learning-based...
Object-branch coverage (OBC) is often used as a measure of the thoroughness of tests suites, augmenting or substituting source-code based structural criteria such as branch coverage and modified condition/decision coverage (MC/DC). In addition, with the increasing use of third-party components for which source-code access may be unavailable, robust object-code coverage criteria are essential to assess...
Mutation testing is known as an effective method for evaluating test sets in terms of their error-revealing capability. When applying mutation testing, it is necessary to identify and filter out the equivalent mutants, i.e. mutants that despite their syntactical difference have the same semantic as the original program. Due to the undecidable nature of the problem of determining whether two programs...
Understanding the extent to which computational results can change across platforms, compilers, and compiler flags can go a long way toward supporting reproducible experiments. In this work, we offer the first automated testing aid called FLiT (Floating-point Litmus Tester) that can show how much these results can vary for any user-given collection of computational kernels. Our approach is to take...
A novel framework in image sparse representation based on ensemble learning is proposed in this paper. Due to the random extraction of training patches and the variation of single optimal processing result, the proposed scheme develops classical dictionary learning algorithms in compressed sensing with ensemble learning theory to improve the performance of sparse representation. The analysis of computational...
In order to solve the problem that the accuracy of flaws identification in ultrasonic testing is not high enough due to the error in sensor information acquisition and the noise interference in the detection environment, a method of flaws identification in ultrasonic testing based on evidential reasoning rule (ER rule) is studied. Firstly, ER rule is proposed to consider the reliability and weights...
Three dimensional (3D) integration based on through-Silicon-Via (TSV) is currently evolving as an area of great interest in modern semiconductor industry. 3D integration provides higher performance, bandwidth and lower power consumption. But due to scaling in technology features these chips are more complex. Hence, testing of these 3D integrated circuits (ICs) is a challenging task. Effective test...
In this position paper, we define the SISSY challenge and explore what it might mean for the usual expected integrations and for the more difficult unexpected integrations.
Semiconductor manufacture companies make an effort to reduce the test time for the test cost reduction until mass production starts. One of the effective test time reduction techniques is to improve the parallel test efficiency with the test program optimization by debugging on the automatic test equipment (ATE). However, given the time constraints of production schedules, the available time for the...
Controlling blood glucose is a way to avoid complications of diabetes. Blood glucose monitoring is a way to test the concentration of glucose in the blood. This study aims to determine the suitability of Artificial Raindrop Algorithm (ARA) and capacitance method in measuring the blood glucose. ARA is a new search algorithm that produces very promising results on the nonlinear function approximation...
Intrusion detection systems are used in computer networking and other applications to detect and respond to attempts to compromise computers, servers, firewalls and other network resources. As intrusion detection systems move beyond providing simple pattern recognition capabilities for known attack types, the ability to test these systems with conventional techniques (or use formal or other similar...
Regression testing is the testing activity performed after changes occurred on software. Its aim is to increase confidence that achieved software adjustments have no negative impact on the already functional parts of the software. Test case prioritization is one technique that could be applied in regression testing with the aim to find faults early, resulting in reduced cost and shorten time of testing...
For solving the problems of modern intelligence algorithms such as slow convergence and low precision, a new algorithm based on bionics principle has been proposed which is inspired by the foraging behavior of seven-spot ladybirds in the nature. By analyzing the bionic principle of Seven-spot ladybird Optimization(SLO), we simulate the region search pattern of predation of seven-spot ladybirds, combining...
FauM diagnosis is crucial to maintain safe and efficient operations of industrial processes. In this paper, a minimax probability machine (MPM) approach based on the framework of probabilistic representations is put forward for diagnosing process faults, without imposing any assumptions on data distributions. Moreover, a technique of pairwise discriminate analysis is incorporated to handle the classification...
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