The objective of this study is to determine the efficacy of class V Er:YAG laser (2940 nm) cavity preparation and conventional bur cavity preparation regarding Intrapulpal temperature rise during cavity preparation in extracted human premolar teeth. Twenty non carious premolar teeth extracted for orthodontic purposes were used and class V cavity preparation was applied both buccal and lingual sides for each tooth .Samples were equally grouped into two major groups according to cavity depth (1mm and 2mm). Each major group was further subdivided into two subgroupsof ten teeth for each (twenty cavities for each subgroup). TwinlightEr:YAG laser (2940 nm) with 500mJ pulse energy, P.R.R of 10 Hz and 63.69 J/cm2 energy density was used. The analysis of the data collected revealed that there was highly significant difference between subgroups of each group, i.e., (Er:YAG laser and conventional bur cavity preparation). Also there was a highly significant difference between both group1 and group 2 subgroups (with 1mm and 2mm cavity depth). Best results were obtained from subgroup A which represents class V cavities prepared using Er:YAG laser with energy density of 63.69 J/cm2 .Er:YAG laser cavity preparation with energy density of 63.69 J/cm2 was less temperature rise than conventional bur cavity preparation taking into account the invitro temperature rise of class V cavity preparation.
The study presents the test results of Completely Decomposed Granite (CDG) soil tested under drained triaxial compression, direct shear and simple shear tests. Special attention was focused on the modification of the upper halve of conventional Direct Shear Test (DST) to behave as free
head in movement along with vertical strain control during shear stage by using Geotechnical Digital System (GDS). The results show that Free Direct Shear Test (FDST) has clear effect on the measured shear stress and vertical strain during the test. It has been found that shear strength
parameters measured from FDST were closer to those measured from simple shear and drained triaxial compression test. This study also provides an independent check on
The subject of this research involves studying adsorption to remove hexavalent chromium Cr(VI) from aqueous solutions. Adsorption process on bentonite clay as adsorbent was used in the Cr(VI) concentration range (10-100) ppm at different temperatures (298, 303, 308 and 313)K, for different periods of time. The adsorption isotherms were obtained by obeying Langmuir and Freundlich adsorption isotherm with R2 (0.9921-0.9060) and (0.994-0.9998), respectively. The thermodynamic parameters were calculated by using the adsorption process at four different temperatures the values of ?H, ?G and ?S was [(+6.582 ? +6.547) kJ.mol-1, (-284.560 ? -343.070) kJ.mol-1 and (+0.977 ? +1.117) kJ.K-1.mol-1] respectively. This data indicates the spontaneous sorp
... Show MoreIn this paper, simulation studies and applications of the New Weibull-Inverse Lomax (NWIL) distribution were presented. In the simulation studies, different sample sizes ranging from 30, 50, 100, 200, 300, to 500 were considered. Also, 1,000 replications were considered for the experiment. NWIL is a fat tail distribution. Higher moments are not easily derived except with some approximations. However, the estimates have higher precisions with low variances. Finally, the usefulness of the NWIL distribution was illustrated by fitting two data sets
Speech is the essential way to interact between humans or between human and machine. However, it is always contaminated with different types of environment noise. Therefore, speech enhancement algorithms (SEA) have appeared as a significant approach in speech processing filed to suppress background noise and return back the original speech signal. In this paper, a new efficient two-stage SEA with low distortion is proposed based on minimum mean square error sense. The estimation of clean signal is performed by taking the advantages of Laplacian speech and noise modeling based on orthogonal transform (Discrete Krawtchouk-Tchebichef transform) coefficients distribution. The Discrete Kra
R. Vasuki [1] proved fixed point theorems for expansive mappings in Menger spaces. R. Gujetiya and et al [2] presented an extension of the main result of Vasuki, for four expansive mappings in Menger space. In this article, an important lemma is given to prove that the iteration sequence is Cauchy under suitable condition in Menger probabilistic G-metric space (shortly, MPGM-space). And then, used to obtain three common fixed point theorems for expansive type mappings.
During the two last decades ago, audio compression becomes the topic of many types of research due to the importance of this field which reflecting on the storage capacity and the transmission requirement. The rapid development of the computer industry increases the demand for audio data with high quality and accordingly, there is great importance for the development of audio compression technologies, lossy and lossless are the two categories of compression. This paper aims to review the techniques of the lossy audio compression methods, summarize the importance and the uses of each method.
In this paper we introduce a new type of functions called the generalized regular
continuous functions .These functions are weaker than regular continuous functions and
stronger than regular generalized continuous functions. Also, we study some
characterizations and basic properties of generalized regular continuous functions .Moreover
we study another types of generalized regular continuous functions and study the relation
among them
The huge amount of documents in the internet led to the rapid need of text classification (TC). TC is used to organize these text documents. In this research paper, a new model is based on Extreme Machine learning (EML) is used. The proposed model consists of many phases including: preprocessing, feature extraction, Multiple Linear Regression (MLR) and ELM. The basic idea of the proposed model is built upon the calculation of feature weights by using MLR. These feature weights with the extracted features introduced as an input to the ELM that produced weighted Extreme Learning Machine (WELM). The results showed a great competence of the proposed WELM compared to the ELM.