Sequence covering array (SCA) generation is an active research area in recent years. Unlike the sequence-less covering arrays (CA), the order of sequence varies in the test case generation process. This paper reviews the state-of-the-art of the SCA strategies, earlier works reported that finding a minimal size of a test suite is considered as an NP-Hard problem. In addition, most of the existing strategies for SCA generation have a high order of complexity due to the generation of all combinatorial interactions by adopting one-test-at-a-time fashion. Reducing the complexity by adopting one-parameter- at-a-time for SCA generation is a challenging process. In addition, this reduction facilitates the supporting for a higher strength of coverage. Motivated by such challenge, this paper proposes a novel SCA strategy called Dynamic Event Order (DEO), in which the test case generation is done using one-parameter-at-a-time fashion. The details of the DEO are presented with a step-by-step example to demonstrate the behavior and show the correctness of the proposed strategy. In addition, this paper makes a comparison with existing computational strategies. The practical results demonstrate that the proposed DEO strategy outperforms the existing strategies in term of minimal test size in most cases. Moreover, the significance of the DEO increases as the number of sequences increases and/ or the strength of coverage increases. Furthermore, the proposed DEO strategy succeeds to generate SCAs up to t=7. Finally, the DEO strategy succeeds to find new upper bounds for SCA. In fact, the proposed strategy can act as a research vehicle for variants future implementation.
Journal of Theoretical and Applied Information Technology is a peer-reviewed electronic research papers & review papers journal with aim of promoting and publishing original high quality research dealing with theoretical and scientific aspects in all disciplines of IT (Informaiton Technology
Evaporation is one of the major components of the hydrological cycle in the nature, thus its accurate estimation is so important in the planning and management of the irrigation practices and to assess water availability and requirements. The aim of this study is to investigate the ability of fuzzy inference system for estimating monthly pan evaporation form meteorological data. The study has been carried out depending on 261 monthly measurements of each of temperature (T), relative humidity (RH), and wind speed (W) which have been available in Emara meteorological station, southern Iraq. Three different fuzzy models comprising various combinations of monthly climatic variables (temperature, wind speed, and relative humidity) were developed
... Show MoreShear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr
... Show MoreThis paper compare the accurecy of HF propagation prediction programs for HF circuits links between Iraq and different points world wide during August 2018 when solar cycle 24 (start 2009 end 2020) is at minimun activity and also find out the best communication mode used. The prediction programs like Voice of America Coverage Analysis Program (VOACAP) and ITU Recommendation RS 533 (REC533 ) had been used to generat HF circuit link parameters like Maximum Usable Frequency ( MUF) and Frequency of Transsmision (FOT) .Depending on the predicted parameters (data) , real radio contacts had been done using a radio transceiver from Icom model IC 7100 with 100W RF
... Show MoreIn this study, a three-dimensional finite element analysis using ANSYS 12.1 program had been employed to simulate simply supported reinforced concrete (RC) T-beams with multiple web circular openings subjected to an impact loading. Three design parameters were considered, including size, location and number of the web openings. Twelve models of simply supported RC T-beams were subjected to one point of transient (impact) loading at mid span. Beams were simulated and analysis results were obtained in terms of mid span deflection-time histories and compared with the results of the solid reference one. The maximum mid span deflection is an important index for evaluating damage levels of the RC beams subjected to impact loading. Three experi
... Show MoreThis study is the first investigation in Iraq dealing with genotyping of
Information hiding strategies have recently gained popularity in a variety of fields. Digital audio, video, and images are increasingly being labelled with distinct but undetectable marks that may contain a hidden copyright notice or serial number, or even directly help to prevent unauthorized duplication. This approach is extended to medical images by hiding secret information in them using the structure of a different file format. The hidden information may be related to the patient. In this paper, a method for hiding secret information in DICOM images is proposed based on Discrete Wavelet Transform (DWT). Firstly. segmented all slices of a 3D-image into a specific block size and collecting the host image depend on a generated key
... Show MoreIn this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation) structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of these procedures and compare them using generated data.
In this paper, integrated quantum neural network (QNN), which is a class of feedforward
neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that
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