Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.

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Naturally occurring radioactive materials (NORM) contaminated sites at Al-Rumaila Iraqi oil fields have been characterized as a part of soil remediation project. Activity of radium isotopes in contaminated soil have been determined using gamma spectrometer High Purity Germanium detector (HPGe) and found to be very high for Al-Markezia, Al-Qurainat degassing stations and storage area at Khadhir Almay region. The activity concentration of samples ranges from 6474.11±563.8 Bq/kg to 1232.5±60.9 Bq/kg with mean value of 3853.3 Bq/kg for ²²⁶Ra, 843.59±8.39 Bq/kg to 302.2±9.2 Bq/kg  with mean value of 572.9 Bq/kg for ²³²Th and 294.31±18.56 Bq/kg to 156.64±18.1 Bq/kg with mean value of 225.5 for ⁴⁰K. S

This research aims to solve a problem in the field of accounting and financial knowledge in the world today, that is, the problem of creative accounting. Especially after the global financial crisis and the collapse of many large companies in the world, people find that they use creative accounting methods to distinguish them from reality, showing the results of their activities and their financial status. This research discusses the concept of creative accounting, the most important methods used in financial statements and its relationship with external auditing, and procedures to limit accounting creativity. This study uses descriptive analysis methods after confirming its theoretical aspects in practice. Using the statistical

The undetected error probability is an important measure to assess the communication reliability provided by any error coding scheme. Two error coding schemes namely, Joint crosstalk avoidance and Triple Error Correction (JTEC) and JTEC with Simultaneous Quadruple Error Detection (JTEC-SQED), provide both crosstalk reduction and multi-bit error correction/detection features. The available undetected error probability model yields an upper bound value which does not give accurate estimation on the reliability provided. This paper presents an improved mathematical model to estimate the undetected error probability of these two joint coding schemes. According to the decoding algorithm the errors are classified into patterns and their decoding

        In this paper, estimation of system reliability of the multi-components in stress-strength model R_(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through  Monte Carlo simulation technique were made depend on mean squared error (MSE)  criteria

Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a

In this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce

Paper Type: Review article.

another suggestion based on artificial neural networks.

Abstract Candida albicans is a commensal fungal pathogen that grows in yeast and hyphal forms in the human gut. C. albicans causes mucosal and cutaneous diseases that can result in significant mortality following systematic infections and it also exhibits drug resistance. Zebrafish have been an excellent model to investigate C. albicans infections because of their transparency and the availability of many transgenic lines. However, there is a limitation in using zebrafish as a model because the fish embryos cannot survive at 37°C therefore it is not suitable for studying Candida infections at physiological relevant human body temperature. In this thesis, the normal embryonic development of Arabian killifish (A. dispar) is investigated, rev

It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna