The integer simulation and development finite impulse response (FIR) filters taking into account the possibilities of their realization on digital integer platforms are considered. The problem statement and solution of multifunctional synthesis of digital FIR filters such a problem on the basis of the numerical methods of integer nonlinear mathematical programming are given. As an several examples, the problem solution of synthesis FIR-filters with short coefficient word length  has been given. The analysis of their characteristics is resulted. The paper discusses issues of modeling and synthesis of digital FIR filters with provision for the possibilities of their implementation on digital platforms with integer computation arithme

      Faces of the individual in his life many stressful events, which includes expertise undesirable, and events may involve a lot of sources of tension and the risk factors and threats in all areas of life, and this would make the stressful events play a role in the genesis of many diseases physical.            

The high blood pressure is one of the most Actual manifestations of mental stress in the present scale physical disorders which may frequently in men relative to women, which may be caused by spasms in the blood vessels.      

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

Background: Recently, Poly propylene fibers with and without plasma treatment have been used to reinforce heat cure denture base acrylic but, so far some of properties like tensile strength , wettability and wear resistance not evaluated yet, the aim of the study is to clarify the influence of incorporation of treated and untreated fibers on these properties. Materials and methods: Twenty one specimens were fabricated for every tested property(tensile strength, wear resistance and wettability) that classified into three groups(control, untreated poly propylene fibers reinforced specimens and Oxygen plasma treated group)and for each test sevens amples were used(n=7). Tensile strength was tested using Instron universal testing machine, wear

 Abstract

In order to determine what type of photovoltaic solar module could best be used in a thermoelectric photovoltaic power generation. Changing in powers due to higher temperatures (25^oC, 35^oC, and 45^oC) have been done for three types of solar modules: monocrystalline , polycrystalline, and copper indium gallium (di) selenide (CIGS). The Prova 200 solar panel analyzer is used for the professional testing of three solar modules at different ambient temperatures; 25^oC, 35^oC, and 45^oC and solar radiation range 100-1000 W/m². Copper indium gallium (di) selenide module   has the lowest power drop (with the average percent

Background: The PMMA polymer denture base materials are low mechanical properties, adaptation of the denture base to underlying tissue is important for retention and stability of denture. The aim of the study was toevaluate the effect of mixtureZrO2-Al2O3 nanoparticles on impact strength, transverse strength, hardness, roughness, denture base adaptation of heat cured acrylic resin denture base material. Materials and methods: One hundred (100) specimens were prepared, the specimens were divided into five groups (20 specimens to each) according to the test type, each group was subdivided in to two subgroups (control and experimental) each subgroup consist of 10 specimens, the experimental group included mixture of 2% (ZrO2-Al2O3ratio2:1) b

Background: Polymethyl methacrylate (PMMA) is the most commonly used material in denture fabrication. The material is far from ideal in fulfilling the mechanical requirements. Midline fracture; poor thermal conductivity and water sorption, are common problem in this material. The purpose of this study was to evaluate the effect of addition of surface treated Aluminum oxide nano fillers on some properties of heat cured (PMMA). Materials and methods: In addition to controlled group of heat cured PMMA the silanized (Al2O3) nanoparticles was added to PMMA powder by weight in three different percentages 1wt%, 2wt% and 3wt%, mixed by probe ultra-sonication machine. 200 specimens were constructed and divided into 5 groups according to the test (e

Background: Heat-cured poly (methyl methacrylate) the principal material for the fabrication of denture base have a relatively poor mechanical properties. The aim of this study was to investigate the effect of glass flakes used as reinforcement on the surface hardness and surface roughness of the heat-processed acrylic resin material. Material and method: Glass flakes (product code: GF002) pretreated with silane coupling agent were added to Triplex® denture base powder using different concentrations. A total of 100 specimens of similar dimensions (65 x 10 x 2.5) mm were prepared, subdivided into 2 main groups of 50 specimens for each of the study tests. Ten specimens for the control group and 40 specimens for each of the experimental gro

Background: Polymethylmethacrylate (PMMA) has relatively unsatisfactory mechanical properties such as low flexural strength and impact strength also dimensional instability. Material and method: Zirconium silicate nanoparticles were coated with a layer of trimethoxysilylpropylmethacrylate (TMSPM) before sonication in monomer (MMA) with the percentages 1% and 1.5% by weight then mixed with powder using conventional procedure, (150) samples were prepared and divided into three groups, each group consisted of (50) samples, the first group prepared from PMMA without addition (control), another group with the addition of 1% wt Zrsio4 nanoparticles (experimental) and the third one with 1.5% wt Zrsio4 nanoparticles (experimental). Each group