Photonic Crystal Fiber Fabry–Perot Interferometers (FPI) based on Surface Plasmon Resonance (SPR) was investigated in this paper in order to detect changes in photonic crystal fiber sensitivity with increasing temperature. FPI is composed of a PCF (ESM-12) solid core spliced with a single-mode fiber (SMF) on one side and a 40nm thick gold Nano film on the other. In order to obtain the SPR curve, the end of PCF can be spliced with the side of SMF before covering the gold film on the PCF. SPR results are included in the suggested sensor, based on the conclusions of the investigations. Resolution (R) is 0.0871, Signal-to-Noise Ratio (SNR) is 0.1867, a figure of merit (FOM) is 0.0069, and sensitivity (S) is 1.1481 . This sensor proposed is s

This study produces an image of theoretical and experimental case of high loading stumbling condition for hip prosthesis. Model had been studied namely Charnley. This model was modeled with finite element method by using ANSYS software, the effect of changing the design parameters (head diameter, neck length, neck ratio, stem length) on Charnley design, for stumbling case as impact load where the load reach to (8.7* body weight) for impact duration of 0.005sec.An experimental rig had been constructed to test the hip model, this rig consist of a wood box with a smooth sliding shaft where a load of 1 pound is dropped from three heights.
The strain produced by this impact is measured by using rosette strain gauge connected to Wheatstone

This study offers numerical simulation results using the ABAQUS/CAE version 2019 finite element computer application to examine the performance, and residual strength of eight recycle aggregate RC one-way slabs. Six strengthened by NSM CFRP plates were presented to study the impact of several parameters on their structural behavior. The experimental results of four selected slabs under monotonic load, plus one slab under repeated load, were validated numerically. Then the numerical analysis was extended to different parameters investigation, such as the impact of added CFRP length on ultimate load capacity and load-deflection response and the impact of concrete compressive strength value on the structural performance of

Natural honey is well known for its therapeutic value and has been used in traditional medicine of different cultures throughout the world. The aim of this study was to investigate the anti-inflammatory effect of Malaysian Gelam honey in inflammation-induced rats. Paw edema was induced by a subplantar injection of 1% carrageenan into the rat right hind paw. Rats were treated with the nonsteroidal anti-inflammatory drug (NSAID) Indomethacin (10 mg/kg, p.o.) or Gelam honey at different doses (1 or 2 g/kg, p.o.). The increase in footpad thickness was considered to be edema, which was measured using a dial caliper. Plasma and paw tissue were collected to analyze the production of inflammatory mediators, such as NO, PGE₂

Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a

The historical center's landscape suffers from neglect, despite their importance and broad capabilities in enhancing the cultural value of the historical center, as landscape includes many heterogeneous human and non-human components, material and immaterial, natural and manufactured, also different historical layers, ancient, modern and contemporary. Due to the difference in these components and layers, it has become difficult for the designer to deal with it. Therefore, the research was directed by following a methodology of actor-network theory as it deals with such a complex system and concerned with an advanced method to connect the various components of considering landscape as a ground that can include various elements and deal wi

Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a

The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (k_La), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited g

The quality of Global Navigation Satellite Systems (GNSS) networks are considerably influenced by the configuration of the observed baselines. Where, this study aims to find an optimal configuration for GNSS baselines in terms of the number and distribution  of baselines to improve the quality criteria of the GNSS networks. First order design problem (FOD) was applied in this research to optimize GNSS network baselines configuration, and based on sequential adjustment method to solve its objective functions.

FOD for optimum precision (FOD-p) was the proposed model which based on the design criteria of A-optimality and E-optimality. These design criteria were selected as objective functions of precision, whic