Photonic Crystal Fiber Interferometers (PCFIs) are widely used for sensing applications. This work presents the fabrication and study the characterization of a relative humidity sensor based on a polymer-infiltrated photonic crystal fiber that operates in a Mach- Zehnder Interferometer (MZI) reflection mode. The fabrication of the sensor only involves splicing and cleaving Photonic Crystal Fiber (PCF) with Single Mode Fiber (SMF). A stub of (LMA-10) PCF spliced to SMF (Corning-28). In the splice regions. The PCFI sensor operation based on the adsorption and desorption of water vapour at the silica-air interface within the PCF. The sensor shows a high sensitivity to RH variations from (27% RH - 95% RH), with a change in its reflected powe

A novel fractal design scheme has been introduced in this paper to generate microstrip bandpass filter designs with miniaturized sizes for wireless applications. The presented fractal scheme is based on Minkowski-like prefractal geometry. The space-filling property and self-similarity of this fractal geometry has found to produce reduced size symmetrical structures corresponding to the successive iteration levels. The resulting filter designs are with sizes suitable for use in modern wireless communication systems. The performance of each of the generated bandpass filter structures up to the 2^nd iteration has been analyzed using a method of moments (MoM) based software IE3D, which is widely adopted in microwave research and in

Photonic Crystal Fiber Interferometers (PCFIs) are widely used for sensing applications. This work presents the fabrication and the characterization of a relative humidity sensor based on a polymer-coated photonic crystal fiber that operates in a Mach- Zehnder Interferometer (MZI) transmission mode. The fabrication of the sensor involved splicing a short (1 cm) length of Photonic Crystal Fiber (PCF) between two single-mode fibers (SMF). It was then coated with a layer of agarose solution. Experimental results showed that a high humidity sensitivity of 29.37 pm/%RH was achieved within a measurement range of 27–95%RH. The sensor also showed good repeatability, small size, measurement accuracy and wide humidity range. The RH sensitivity o

     Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing

A Geographic Information System (GIS) is a computerized database management system for accumulating, storage, retrieval, analysis, and display spatial data. In general, GIS contains two broad categories of information, geo-referenced spatial data and attribute data. Geo-referenced spatial data define objects that have an orientation and relationship in two or three-dimensional space, while attribute data is qualitative data that can be counted for recording and analysis. The main aim of this research is to reveal the role of GIS technology in the enhancement of bridge maintenance management system components such as the output results, and make it more interpretable through dynamic colour coding and more sophisticated visualization

We are used Bayes estimators for unknown scale parameter  when shape Parameter  is known of Erlang distribution. Assuming different informative priors for unknown scale  parameter. We derived The posterior density with posterior mean and posterior variance using different informative priors for unknown scale parameter  which are the inverse exponential distribution, the inverse chi-square distribution, the inverse Gamma distribution, and the standard Levy distribution as prior. And we derived Bayes estimators based on the general entropy loss function (GELF) is used the Simulation method to obtain the results. we generated different cases for the parameters of the Erlang model, for different sample sizes. The estimates have been comp

Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very