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

           A  new  Schiff base  ligand  [2,3,8,9–tetra -phenyl-1,4,5,7,10,12-hexa azo-5,12- dihydro -6,11- dione 1,3,7,10-dudec-tetra-ene]  [H2L]  and  its  complexes In general formula [M(H2L)]Cl2 (where : M= CoII, NiII, and PdII) were prepared. This ligand was prepared in two steps,in the first step a solution of  benzil in methanol was reacted  under  reflux   with    semicarbazidhydrochlorid  to give an (intermediate compound)[benzyl bis–(Semicarbazone)] which was  reacted  in the  second   step with  benzil giving  the  mentioned  ligand. The

In this paper, the continuous classical boundary optimal control problem (CCBOCP) for triple linear partial differential equations of parabolic type (TLPDEPAR) with initial and boundary conditions (ICs & BCs) is studied. The Galerkin method (GM) is used to prove the existence and uniqueness theorem of the state vector solution (SVS) for given continuous classical boundary control vector (CCBCV). The proof of the existence theorem of a continuous classical boundary optimal control vector (CCBOCV) associated with the TLPDEPAR is proved. The derivation of the Fréchet derivative (FrD) for the cost function (CoF) is obtained. At the end, the theorem of the necessary conditions for optimality (NCsThOP) of this problem is stated and prov

Osteoporosis (OP)is one of the most important metabolic disorder also affected by interaction of genetic and environmental factors by almost 70% and 30% respectively. Genetic components are identified to strongly effect bone mineral density, bone building and turnover, so they play an important role in determining risk of OP and fragility fractures. This study consists of patient and control group; Group A: (70) postmenopausal women with OP and osteopenia, Group B: (20) control group.  five milliliters of blood sample were divided into three tubes; one tube (1ml) contain gel for obtain serum to measure glucose level, the others tubes containing ethylene-diamine-tetra-acetic acid (EDTA), in 2 tube 2ml stored in deep freeze at (–40

     Diabetes mellitus (DM) is the most common endocrine disorder and one of the highly progressive diseases which is indicated by high blood sugar (hyperglycemia). The present study aims to study the effects of treatment with zinc and vitamin C on glycemic profile [fasting blood sugar (FBS), glycated haemoglobin (HbA_1C), and insulin hormone level] in type 2 diabetic patients. The study included 56 diabetic patients [30 without foot ulcers (15 without zinc and vitamin C supplements, 15 with zinc and vitamin C supplements) and 26 with foot ulcers (15 without zinc and vitamin C supplements, 11 with zinc and vitamin C supplements)]. Also, 15 healthy persons were used as a control group. The patients were enrol

Type 2 Diabetes Mellitus (T2DM) is the furthermost common form of DM which is identified by hyperglycemia, insulin resistance, and relative insulin deficiency. This study aims to detect the role of interleukin-17 (IL-17) in patients with T2DM compared with the healthy control and to investigate the relationship between IL-17 and insulin resistance. The study involved 50 Iraqi T2DM patients, randomly selected with an age range of 33-71 years .For the purpose of comparison, 30 Iraqi healthy persons with an age range of 33-71 years were also included. Patients and control groups were characterized in terms of gender, age, body mass index (BMI), homeostatic model assessment-insulin resistance(HOMA-IR),fasting serum glucose (FSG) and lipid pr

Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD