This study aimed at revealing the degree of availability of standards of word problems in mathematics books for the first three grades of the basic stage in Palestine. For this purpose, the researcher prepared an analysis tool and a list of criteria consisting of two areas: linguistic formulation and mathematical content. Every area had seven items. The results of the study showed that the third-grade mathematics book has the highest degree of availability of the standards with 85.75%, and then came the second-grade mathematics book with 83.12%. Finally, the first-grade mathematics book came with 80.13%. In the light of the previous results, the researcher recommended to develop the language of word problems, to take into account their i
... Show MoreBackground: The bond strength of the root canal sealers to dentin seems to be a very important property for maintaining the integrity and the seal of root canal filling. The aim of this study was to evaluate the shear bond strength of four different obturation systems using push-out test. Materials and methods: Forty straight palatal roots of the maxillary first molars teeth were used in this study, these roots were instrumented using crown down technique and ProTaper system, instrumentation were done with copious irrigation of 2.5% sodium hypochlorite and 17% buffered solution of EDTA was used as final irrigant followed by distilled water, roots were randomly divided into four groups according to the obturation system (ten teeth for each g
... Show MoreThe 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
... Show MoreThis work presents an innovative approach to enhancing the performance of concrete with reclaimed asphalt pavement (RAP) aggregates using titanium dioxide (TiO2) nanoparticles. Traditional limestone coarse aggregates were partially replaced with 30% and 50% RAP aggregates; a subset of mixtures containing RAP aggregates was treated with TiO2 nanoparticles. The rheological, mechanical, and long-term properties of concrete, along with changes in its chemical composition following the addition of RAP and TiO2, were evaluated. Results revealed that using 30% and 50% RAP in concrete mixtures reduced their compressive strength by 18% and 27%, respectively. However, using TiO2 in those mixtures enhanced their compressive strength by 8.7% an
... Show MoreDecision-making in Operations Research is the main point in various studies in our real-life applications. However, these different studies focus on this topic. One drawback some of their studies are restricted and have not addressed the nature of values in terms of imprecise data (ID). This paper thus deals with two contributions. First, decreasing the total costs by classifying subsets of costs. Second, improving the optimality solution by the Hungarian assignment approach. This newly proposed method is called fuzzy sub-Triangular form (FS-TF) under ID. The results obtained are exquisite as compared with previous methods including, robust ranking technique, arithmetic operations, magnitude ranking method and centroid ranking method. This
... Show MoreClinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b