Hot-wire cutting is one of the important, non-traditional thermomechanical way to cut polymer, usually expanded foam and extruded foam, in low volume manufacturing. The study and analysis of Hot-Wire cutting parameters play an important role to enhance the quality and accuracy of the process and products. The effects on the surface have been investigated by using experimental tests designed according to the Taguchi orthogonal array (OA). In this study, four parameters with five levels for each parameter have been used: [temperature of wire (A) (100, 120, 130, 150, 160) °C], [diameter of wire (B) (0.3,0.4,0.5,0.7,0.8) mm], [velocity of cutting (C) (200, 300,400,500,600) mm/min], [and density of foam (D) (0.01,0.027,0.029,0.032,0.037) g/cm3]. Statistical software (MINITAB17) used to find the optimum conditions, which they are in Material Removal: 100 ˚C, 0.5 mm, 300mm/min, 0.032 g/cm3.
Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed
... Show MoreObjective: To evaluate the functional outcome of percutaneous cross two K wires fixation for Gartland types II and III fractures of humerus. Methodology: This prospective study included80 patients with supracondylar humeral fracture, who underwent closed reduction and fixation by two crossed Kirschner wires. We included children with age < 15 years with closed fractures with Gartland types II and III, while the patient with vascular injury, open, irreducible fractures were excluded. The patients were following up for 6 months and assessed functionally by Flynn’s criteria. Results: The mean age of patients was 8.1 years. Trauma while child playing was the main mechanism of injury in 43 (59.8%) children and 46 (57.5%) fractures were of the
... Show MoreThe oxidative degradation of Orange G dye by nanosized CeO2 catalyst has been performed in this study. The catalyst was prepared by precipitation method. Various characterization techniques were carried out to study the physical and chemical properties of the synthesized catalyst. The XRD result confirms well the formation of CeO2 cubic phase. The FTIR result showed the effect of calcination temperature for CeO2 was clearly observed due to reduction in band intensity compared to uncalcined Ce nitrate sample. Meanwhile, the diffused reflection spectra recorded reflection spectra at 414 nm with an energy gap of 3.2 ev. The decolorization of Orange G dye by oxidation process were carried out unde
... Show MoreThe present study aimed to examine the effect of endosulfan insecticide on some molecular and biochemical parameters in white mice. Thirty mice were separated randomly into three groups for treatment with endosulfan. One group (G1) served as the control, while the other two groups received intraperitoneal injections of endosulfan G2 (3 mg/kg) and G3 (17 mg/kg) twice a week for 21 and 45 days, respectively. A biochemical study by measuring liver function parameters, including (alanine aminotransferase (ALT) and aspartate aminotransferase (AST)) and kidney function parameters, including (Blood Urea and Creatinine) and malondialdehyde (MDA), catalase activity (CAT). This study also tested DNA damage by comet assay (normal%, low%, med
... Show MoreThe photonconductor detectors CdSe:Cu was fabricated as a thin film of (1 μm) in thickness using vacuum evaporation technique. doping with copper was made using vacuum annealing at 350oC under argon atmosphere . The spectral responsivity and spectral detectivity of the detector were determined as a function of incident wavelength on the sample. A remarkable improvement in performance was absorbed for the specimen, which doping with (1-5 wt%) Cu.
The spectral response increases with increasing of wavelength for incident radiation to maximum value, after that , it reduced sharply . There is a shifting for peak responsivity indirect of higher wavelength. The detectivity was increased with doping but its decreased as the concentration in
Experimental investigations had been done in this research to demonstrate the effect of carbon fiber and Ceramic fillers contents on the tribological behaviour of (15% volume fraction) carbon-epoxy composite system under varying volume fraction, load, time and sliding distance. The wear resistance were investigated according to ASTM G99-05standard using pin on disc machine to present the composite tribological behaviour. The influence of three ceramic fillers, granite, perlite and calcium carbonate (CaCO3), on the wear of the carbon fabric reinforced epoxy composites under dry sliding conditions has been investigated. The effect of variants in volume fraction, applied load, time and sliding distance on the wear behaviour of po
... Show MoreOne of the most important problems in the statistical inference is estimating parameters and Reliability parameter and also interval estimation , and testing hypothesis . estimating two parameters of exponential distribution and also reliability parameter in a stress-strength model.
This parameter deals with estimating the scale parameter and the Location parameter µ , of two exponential distribution ,using moments estimator and maximum likelihood estimator , also we estimate the parameter R=pr(x>y), where x,y are two- parameter independent exponential random variables .
Statistical properties of this distribution and its properti
... Show MoreTo expedite the learning process, a group of algorithms known as parallel machine learning algorithmscan be executed simultaneously on several computers or processors. As data grows in both size andcomplexity, and as businesses seek efficient ways to mine that data for insights, algorithms like thesewill become increasingly crucial. Data parallelism, model parallelism, and hybrid techniques are justsome of the methods described in this article for speeding up machine learning algorithms. We alsocover the benefits and threats associated with parallel machine learning, such as data splitting,communication, and scalability. We compare how well various methods perform on a variety ofmachine learning tasks and datasets, and we talk abo
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