Background: Diabetic cheiroarthropathy is a term derived from the Greek word “cheiros” meaning “of the hand”, It is characterized by stiff hands with distinctively thick, tight, and waxy skin, especially on the dorsal aspects of the hands. It is part of long term complication of diabetes and many suggest it is associated with microvascular complication. The aim of the study was to determine the prevalence of diabetic cheiroarthropathy in Iraqi patients with diabetes, and to study its association with diabetic retinopathy and glycemic control. Material and Methods: A cross-sectional study in which 110 diabetic patients and 110 non-diabetic healthy people who accepted to take part in the study were randomly recruited. 45 of the diabetic patients have Type 1 diabetes mellitus, and the other 65 have Type II diabetes mellitus. All diabetic patients and non-diabetic controls were examined for the presence of cheiroarthropathy, It’s association with sex, age of onset and duration of diabetes was recorded, the diabetic patients were also examined by an ophthalmologist for the evidence of diabetic retinopathy. Results: The total prevalence of cheiroarthropathy in all studied diabetic patients was 55.5%, while the prevalence in the control group was 4.5%. The cheiroarthropathy was more sever in Type 1 diabetes compared with Type 1I diabetes. Longer disease duration in both types of diabetes was associated with increased incidence of cheiroarthropathy, Diabetic retinopathy was higher in frequency in patients with cheiroarthropathy than in those without. Conclusions: The prevalence of diabetic cheiroarthropathy is high and nearly equal in both types of diabetes, but more sever in type 1 diabetes mellitus, it was associated with the duration of diabetes in both types and with the presence of diabetic retinopathy for only type1 diabetes mellitus.
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show More
(5)
(4)
(11)
(10)
A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.
(9)
(5)
A series of laboratory model tests has been carried out to investigate the using of pomegranate sticks mat as reinforcement to increase the bearing capacity of footing on loose sand. The influence of depth and length of pomegranate sticks layer was examined. In the present research single layer of pomegranate sticks reinforcement was used to strengthen the loose sand stratum beneath the strip footing. The dimensions of the used foundation were 4*20 cm. The reinforcement layer has been embedded at depth 2, 4 and 8 cm under surcharge stresses . Reinforcing layer with length of 8 and 16 cm were used. The final model test results indicated that the inclusion of pomegranate sticks reinforcement is very effective in improvement the loading cap
... Show More
(17)
(7)
Two Prototypes of Transversely Excited at atmospheric pressure (TEA) Nitrogen laser systems (One Stage Blumlein Circuit and Two Stage Blumlein Circuit) were fabricated and operated. High voltage power supply with variable operating voltage (0-20 kv) and operating current (1-3A) was built and tested successfully. The gas flow rate of 15 L/ min and 10 L/ min for OSBC and TSBC was used. The performance of the fabricated systems was studied extensively reaching to the optimum operating conditions. The obtained laser output energy for the first system has linear relationship with the applied voltage. The maximum output energy was about (1.14 mJ) with (10.40) ns pulse duration and the half-wave divergence angle was about (0.1455 m rad). In the
... Show More
(2)
(2)
The necessary optimality conditions with Lagrange multipliers are studied and derived for a new class that includes the system of Caputo–Katugampola fractional derivatives to the optimal control problems with considering the end time free. The formula for the integral by parts has been proven for the left Caputo–Katugampola fractional derivative that contributes to the finding and deriving the necessary optimality conditions. Also, three special cases are obtained, including the study of the necessary optimality conditions when both the final time and the final state are fixed. According to convexity assumptions prove that necessary optimality conditions are sufficient optimality conditions.
... Show More
(11)
(2)
In this paper, variable gain nonlinear PD and PI fuzzy logic controllers are designed and the effect of the variable gain characteristic of these controllers is analyzed to show its contribution in enhancing the performance of the closed loop system over a conventional linear PID controller. Simulation results and time domain performance characteristics show how these fuzzy controllers outperform the conventional PID controller when used to control a nonlinear plant and a plant that has time delay.