Solar cells thin films were prepared using polyvinyl alcohol (PVA) as a thin film, with extract of natural pigment from local flower. A concentration of 0.1g/ml of polyvinyl alcohol solution in water was prepared for four samples, with various concentrations of plant pigment (0, 15, 25 and 50) % added to each of the four solutions separately for preparing (PVA with low concentrated dye , PVA with medium concentrated dye and PVA with high concentrated dye ) thin films respectively . Ultraviolet absorption regions were obtained by computerized UV-Visible (CECIL 2700). Optical properties including (absorbance, reflectance, absorption coefficient, energy gap and dielectric constant) via UV- Vis were tested, too. Fourier transform infrared (FTIR) spectrophotometer was employed to test the samples. Thermal analysis of thin films, including melting point (Tm), onset degree, endset degree, and crystallinity% were tested by differential scanning calorimeter (DSC). Three dimensional morphologies of thin films were inspected by atomic force microscopy (ATM). Contact angle also was tested as an index to hydrophilicity. Results proved that the ultraviolet and FTIR absorption increase after adding the natural pigment to PVA thin film, as well as it increases with increasing concentration of natural pigment. DSC analysis revealed an increase of PVA melting point when adding 15% concentration and it decreases with a 50% concentration of pigment. AFM results show an increase in surface roughness, hence the surface bearing index of PVA thin films is inversely proportional to pigment concentration. Contact angle decreases from 46.5° for pure PVA thin film to 44. 8°, 42. 6° and 35.2° after adding (15, 25, and 50)% concentration of natural dye respectively. Optical properties were enhanced by adding the natural dye, hence energy gap decreased from 3 eV for pure PVA to 2.3 eV for the PVA with a high concentrate dye. Dielectric constant increased with increasing concentration of dye, which leads to high polarization of solar cell.
This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB
... Show MoreIn present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.
Identifying the total number of fruits on trees has long been of interest in agricultural crop estimation work. Yield prediction of fruits in practical environment is one of the hard and significant tasks to obtain better results in crop management system to achieve more productivity with regard to moderate cost. Utilized color vision in machine vision system to identify citrus fruits, and estimated yield information of the citrus grove in-real time. Fruit recognition algorithms based on color features to estimate the number of fruit. In the current research work, some low complexity and efficient image analysis approach was proposed to count yield fruits image in the natural scene. Semi automatic segmentation and yield calculation of fruit
... Show MoreAt the end of 2019, a new form of Coronavirus (later dubbed COVID-19) emerged in China and quickly spread to other regions of the globe. Despite the virus’s unique and unknown characteristics, it is a widely distributed infectious illness. Finding the geographical distribution of the virus transmission is therefore critical for epidemiologists and governments in order to respond to the illness epidemic rapidly and effectively. Understanding the dynamics of COVID-19’s spatial distribution can help to understand the pandemic’s scope and effects, as well as decision-making, planning, and community action aimed at preventing transmission. The main focus of this study is to investigate the geographic patterns of COVID-19 disseminat
... Show MoreBackground: Hashimoto's thyroiditis has been found to coexist with differentiated thyroid cancer in surgical specimens, but an association between the two conditions has been discounted by the medical literature. So, we performed this research to determine any potential relationship between Hashimoto's thyroiditis and the risk of developing differentiated thyroid cancer in clinical status. we assessed the related clinical factors linking these conditions, especially serum thyroid-stimulating hormone concentration, family history of thyroid disease, gender& young age group. Aim of study: to determine that hashimoto’s thyroiditis increases risk for differentiated thyroid carcinoma. Patients and method: This study is a Cross-sectiona
... Show MoreIn this paper, a literature survey was introduced to study of enhancing the hazy images , because most of the images captured in outdoor images have low contrast, color distortion, and limited visual because the weather conditions such as haze and that leads to decrease the quality of images capture. This study is of great importance in many applications such as surveillance, detection, remote sensing, aerial image, recognition, radar, etc. The published researches on haze removal are divided into several divisions, some of which depend on enhancement the image, some of which depend on the physical model of deformation, and some of them depend on the number of images used and are divided into single-image and multiple images dehazing model
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