This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF

Objective: To evaluate the functional outcomes after extended curettage and reconstruction using a combination of bone graft and bone cement (sandwich). Methodology: In this prospective case series 16 skeletally mature patients with primary giant cell tumor around the knee were included. Patients with previous surgically treated, malignant transformation, degenerative knee changes and those presenting with pathological fracture were excluded. The tumor was excised with bone graft filling space beneath the articular cartilage and a block of gel foam was placed over the cortical surface of picked bone graft. Remaining cavity was filled with polymethylmethacrylate cement (sandwich) with or without internal fixation. The func tional evaluation

Zinc sulfide (ZnS) thin films were deposited on glass substrates using pulsed laser deposition technique. The laser used is the Q-switched Nd: YAG laser with 1064nm wavelength and 1Hz pulse repetition rate and varying laser energy 700mJ-1000mJ with 25 pulse. The substrate temperature was kept constant at 100°C. The structural, morphological and optical properties of ZnS thin films were characterized with X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscope (AFM) and UV-VIS spectrophotometer.

For the first time Iron tungstate semiconductor oxides films (FeWO4) was successfully synthesized simply by advanced controlled chemical spray pyrolysis technique, via employed double nozzle instead of single nozzle using tungstic acid and iron nitrate solutions at three different compositions and spray separately at same time on heated silicone (n-type) substrate at 600 °C, followed by annealing treatment for one hour at 500 °C. The crystal structure, microstructure and morphology properties of prepared films were studied by X-ray diffraction analysis (XRD), electron Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM) respectively. According to characterization techniques, a material of well-crystallized monoclinic ph

Abstract

Although the rapid development in reverse engineering techniques, 3D laser scanners can be considered the modern technology used to digitize the 3D objects, but some troubles may be associate this process due to the environmental noises and limitation of the used scanners. So, in the present paper a data pre-processing algorithm has been proposed to obtain the necessary geometric features and mathematical representation of scanned object from its point cloud which obtained using 3D laser scanner (Matter and Form) through isolating the noised points. The proposed algorithm based on continuous calculations of chord angle between each adjacent pair of points in point cloud. A MATLAB program has been built t

In this paper, we present new algorithm for the solution of the nonlinear high order multi-point boundary value problem with suitable multi boundary conditions. The algorithm is based on the semi-analytic technique and the solutions are calculated in the form of a rapid convergent series. It is observed that the method gives more realistic series solution that converges very rapidly in physical problems. Illustrative examples are provided to demonstrate the efficiency and simplicity of the proposed method in solving this type of multi- point boundary value problems.

Reservoir rock typing integrates geological, petrophysical, seismic, and reservoir data to identify zones with similar storage and flow capacities. Therefore, three different methods to determine the type of reservoir rocks in the Mushrif Formation of the Amara oil field. The first method represents cluster analysis, a statistical method that classifies data points based on effective porosity, clay volume, and sonic transient time from well logs or core samples. The second method is the electrical rock type, which classifies reservoir rocks based on electrical resistivity. The permeability of rock types varies due to differences in pore geometry, mineral composition, and fluid saturation. Resistivity data are usually obtained from w