Design and implementation of a smart dual axis sun tracker based on astronomical equations

This paper presents a new design algorithm for stand-alone solar tracking system based on ATMEL Microcontroller. The proposed idea of the design is based on astronomical equations to determine the position of the sun in the sky at any time of the day to calculate the tilt angle and polar angle for the two axis tracking purposes. The system is capable of tracking the sun properly at any position on the earth because of the general nature of the algorithm used in the design. At the same time the system reliability, cost effectiveness, precision and flexibility are taken into consideration

Desıgn of a control and data acquısıtıon system for a multı-mode solar trackıng farm

This paper presents a combination network design for a solar tracking farm consisting of n-solar tracking systems. Serial communication protocol has been adopted for this network with developed strategy to make the farm expandable for possible future extension. The master control unit is responsible for managing all the trackers of the sun location in multi-tracking mode, diagnosis all the trackers for any faults and give complete information about the produced power by each of the solar tracking system. This network protocols is designed to deal with the error control, congestion control and flow control for data transmission in the network

Code of Conduct of Final Year Projects in Engineering Disciplines

The importance of the management and implementation of graduation projects lies in the fact that this activity constitutes one of the main pillars of the undergraduate academic curricula in most scientific or literary disciplines. In engineering studies, for example, the weight of the graduation project within the curriculum is estimated at 25% for the year of graduation and about 8% of the total weight of the first university degree in most universities in the developed countries. In this context, this paper suggests specific steps for conducting this work and the allocation of responsibilities in the management of this scientific activity. The paper also suggests a number of recommendations, to be included within the curricula of undergraduate engineering disciplines in the public and private engineering colleges

Resilient Back Propagation Algorithm for Breast Biopsy Classification Based on Artificial Neural Networks

Non

Neural Network Based Classification of Myocardial Infarction: A Comparative Study of Wavelet and Fourier Transforms

Non

Reliability Assessment of the Iraqi National Communication Network

The design of communication networks continues to progress rapidly in more suitable forms to meet the challenges of the present era. This paper presents a tentative study of the design of a reliable Iraqi National Communication Network (INCN). The INCN connects all major cities in Iraq with Baghdad as the central node. The followed subjected procedure is a general method which can be applied to all similar problems concerning any Wide Area Network design.  An optimal backbone is first designed by Prim’s algorithm which has distances between cities as input data. The INCN is subjected to reliability improvement by adding links to the initial backbone. An improved algorithm based on tie-sets method is developed for network reliability computation. Three chosen scenarios (Net1, Net2, and Net3) for the INCN are presented and underwent reliability estimation. Evaluation results show a successive improvement of the network reliability to yield to an optimal solution recognized as being Net3. The adopted topology for the INCN is based on two clusters having Baghdad as the common head cluster. Clustering will simplify the reliability evaluation by decreasing the number of tie-sets, and hence the computation complexity.

A Deep Learning-Based Tool for Face Mask Detection and Body Temperature Measurement

Due to the COVID-19 pandemic outbreak, wearing a mask and ensuring normal body temperature in overcrowded areas such as workplaces have become obligatory. In this paper, a deep learning-based tool for automatic mask detection and temperature measurement at the entrance of workplaces was developed to save costs of manual supervision and reduce human contact for safety concerns. Using Python, image/video processing techniques related to face and object detection are used to process image input from a webcam. A deep learning algorithm called MobileNetV2 was used to build the face mask detector model. Moreover, a non-contact thermal sensor, the MLX90614, along with Arduino, was employed to measure body temperature. The mask detection and temperature measurements are displayed correctly on a Graphical User Interface (GUI). Besides, an additional function related to the Internet of Things (IoT) was implemented, which sends high-temperature alerts to smartphones. It has been verified that the model can achieve an accuracy of about 98%. The developed system experiences a limitation when other objects are used to cover the mouth and nose in that they may still be classified as masks. However, compared to the mask detection systems available commercially, it can provide correct detection results when using the hand to pretend to be wearing a mask