New Schiff-base ligands bearing tetrazole moiety and their polymeric metal complexes with Co(II), Ni(II) and Cd(II) ions are reported. Ligands were prepared in a multiple-step reaction. The reaction of sodium 2,6- diformylphenolate and cyclohexane-1,3-dione with 5-amino-2-fluorobenzonitrile resulted in the isolation of two precursors sodium 2,6-bis((E)-(3-cyano-4-fluorophenylimino)methyl)-4-methylphenolate 1 and 5,5'- (1E,1'E)-cyclohexane-1,3-diylidenebis- (azan-1-yl-1-ylidene)bis(2-fluorobenzonitrile) 2, respectively. The reaction of precursors with azide gave the required ligands; sodium 2,6-bis((E)-(4-fluoro-3-(1H-tetrazol-5- yl)phenylimino)methyl)-4-methylphenolate (NaL) and (N,N'E,N,N'E)-N,N'-(cyclohexane-1,3-diylidene)bis(4- fluoro-3-

    Terrestrial laser scanners (TLSs) are 3D imaging systems that provide the most powerful 3D representation and practical solutions for various applications. Hence this is due to effective range measurements, 3D point cloud reliability, and rapid acquisition performance. Stonex X300 TOF scanner delivered better certainty in far-range than in close-range measurements due to the high noise level inherent within the data delivered from Time of Flight (TOF) scanning sensors. However, if these errors are manipulated properly using a valid calibration model, more accurate products can be obtained even from very close-range measurements. Therefore, to fill this gap, this research presents a user-oriented target-based calibration routine to

A preliminary test single stage Shrinkage (PTSSS) techniques is used for estimation the scale parameter q of an exponential distribution when a prior knowledge about q is a available in the form of initial estimate q₀ of q. It is proposed to estimate q by a testimator  that is based upon the result of a test of the hypothesis H₀ :q = q₀ against the hypothesis H_A

     Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing

      In this paper, we are mainly concerned with estimating cascade reliability model (2+1) based on inverted exponential distribution and comparing among the estimation methods that are used . The maximum likelihood estimator and uniformly minimum variance unbiased estimators are used to get  of the strengths  and the stress ;k=1,2,3 respectively then, by using the unbiased estimators, we propose Preliminary test single stage shrinkage (PTSSS) estimator when a prior knowledge is available for the scale parameter as initial value due past experiences . The Mean Squared Error [MSE] for the proposed estimator is derived to compare among the methods. Numerical results about conduct of the considered

يهدف هذا البحث إلى تحليل محتوى كتابي الحاسوب للمرحلة الإعدادية في جمهورية العراق وفقاً للتفكير المنطقي، واتبعت الباحثة منهج البحث الوصفي التحليلي، وتم توظيف أداة تحليل المحتوى، التي صُمِّمت وفقاً للعمليات العقلية المتضمنة في التفكير المنطقي بحسب العالم بياجيه ( Piaget )، واعتماد وحدة الفكرة (الصريحة) في عملية التحليل. تبين من نتائج هذا البحث أنَّ نسبة تضمين مهارات التفكير المنطقي في محتوى كتابي الحاسوب للمرحل

     The diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca