In-situ measurements of ultraviolet (UV) and solar irradiance is very sparse in Nigeria because of cost; it is  estimated using meteorological parameters. In this work, a low-cost UV and pyranometer device, using locally sourced materials, was developed. The instrument consists of a UV sensor (ML8511), a photodiode (BPW34) housed in a carefully sealed vacuumed glass bulb, the UV and solar irradiance sensor amplifiers, a 16-bit analog-to-digital converter (ADS1115), Arduino mega 2560, liquid crystal display (LCD) and microSD card for data logging. The designed amplifier has an offset voltage of 0.8676 mV. The sensitivity of the irradiance device is 86.819 Wm^-2/mV with a correcting factor of 27.77 Wm^-2 and a

The dimensions of bubbles were measured in a stirrer tank electrochemical reactor, where the analysis of the bubble size distribution has a substantial impact on the flow dynamics. The high-speed camera and image processing methods were used to obtain a reliable photo. The influence of varied air flow rates (0.3; 0.5; 1 l/min) on BSD was thoroughly investigated. Two types of distributors (cubic and circular) were examined, and the impact of various airflow rates on BSD was investigated in detail. The results showed that the bubbles for the two distributors were between 0.5 and 4.5 mm. For both distributors at each airflow, the Sauter mean diameter for the bubbles was calculated. According to the results, as the flow rate raised, the bubb

Cooperation spectrum sensing in cognitive radio networks has an analogy to a distributed decision in wireless sensor networks, where each sensor make local decision and those decision result are reported to a fusion center to give the final decision according to some fusion rules. In this paper the performance of cooperative spectrum sensing examines using new optimization strategy to find optimal weight and threshold curves that enables each secondary user senses the spectrum environment independently according to a floating threshold with respect to his local environment. Our proposed approach depends on proving the convexity of the famous optimization problem in cooperative spectrum sensing that stated maximizing the probability of detec

This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

     Biosensor is defined as a device that transforms the interactions between bioreceptors and analytes into a logical signal proportional to the reactants' concentration. Biosensors have different applications that aim primarily to detect diseases, medicines, food safety, the proportion of toxins in water, and other applications that ensure the safety and health of the organism. The main challenge of biosensors is represented in the difficulty of obtaining sensors with accuracy, specific sensitivity, and repeatability for each use of the patient so that they give reliable results. The rapid diversification in biosensors is due to the accuracy of the techniques and materials used in the manufacturing process and the interrelationshi

In the present work, classification of radioactive wastes based on Annual Intake (AI) values is studied. Where the characterization of radionuclides was done by hand held GeLi detector with an overall efficiency better than 42%. It was noted the most predominant contaminant are Cs-137, Co-60 and Pa-234.The radioactive waste in disposal silo has been divided into five categories according to the harmful effect of radionuclides.For the purpose of storageradioactive wastein a safe manner, it wassuggesteda new method by shielding radioactive waste in each category with concrete;where the thickness of shielding is the time required to reduce the annual dose to 10%.