Obstacle avoidance is one of the major tasks needed to be carefully focused by the autonomous system designers. In this digital era, most industries are moving towards autonomous systems. Obstacle avoidance is considered as a primary concern for any autonomous system. In this paper, a prototype of an autonomous vehicle is presented, which is capable of obstacle avoidance using an ultrasonic sensor for its movement and avoidance. An Arduino microcontroller is used to achieve the desired operation. In order to achieve the desired task of the proposed system, a proper methodology is followed which combines appropriate selection of hardware components as well as logic design of actions for obstacle avoidance. The proposed system can

In this work, Co-Y-oxide Nano Structure is successfully synthesized via hydrothermal method. The XRD analysis, SEM analysis, optical, electrical and photo sensing properties have been investigated for Co3O4 and Co-Y-oxide thin films. The X-ray diffraction (XRD) analysis reveals that all films are polycrystalline in nature, having cubic structure. The SEM images of thin films clearly indicates that Co3O4 possesses nanosphere like structure and flower like for Co-Y-oxide. The optical properties show that the optical energy gap follows allowed direct electronic transition calculated using Tauc equation and it increases for Co-Y-oxide. The photo sensing properties of thin films are investigated as a function of time at different wavelengths to

An immunological technique was investigated for the detection of human semen in forensic analysis.This technique included a preparation of anti-human seminal plasma antibodies, by immunizing rabbits with treated human semen. The human semen was treated with an acid to prevent cross reactivity with other human body fluids. The antibody produced was tested against different animal,s seminal fluid samples (dog, goat ,sheep, cow) and human body fluids( saliva, blood , vaginal fluid, ear wax and human semen). It was found that using this developed technique was only selectively responsed with human semen . The prepered kit was evaluated and tested in Forensic laboratory- Ministry of Health. Finally, results were obtained in a c

This research presents a statistical study of radiation generated from communication towers in the Nineveh Plain region Baghdeda. The intensity of radiation energy was measured at 10 meters away from the communication tower in different locations, using a (1PC XH-901 Dosimeter/ Personal Dose Alarm / Radiation Detector, dosage rate: 0.01 μSv/h to 150μSv/h) to measure the amount of radiation at various times. Energy densities were measured and compared with standard limits provided by other authorities, such as the International Committee for Radiation Protection. Results were analyzed using SPSS version 26 to implement the data. The results show that the means of the radiation levels measured at all the zones do not statistically differ

The present study is an attempt to throw light on the nature of the US policy regarding the Middle East region as portrayed by AI-Sabah, Al-Mashriq and Tariq Al-Shaab papers over a period of three months from 1st of July to 30th of September 2013.

In writing this study, a number of goals have been set by the researcher. These goals may include but in no way limited to the nature of the US image as carried by the above three papers, the nature of the topics tackled by them and the nature of the Arab countries which received more and extensive coverage than others.

A qualitative research approach is proposed for the study. This approach has allowed the researcher to arrive at definite answers for the possible questions rais

This work aimed to investigate the prevalence of pathogenic fungi and evaluate the antifungal activity of Trichoderma orientale FMR12486 crude extract against pathogenic fungi isolated from patients attending the National Center for Thoracic and Respiratory Diseases (having a history of tuberculosis) and consultant of Dermatology of Baghdad hospital, Iraq. A total of 80 clinical specimens were collected: 20 skin scrapings specimens and 60 sputum specimens. The results of direct examination by KOH 10% and culture showed that 11 (55%) cases from 20 skin specimens were positive for fungal infections, while in the sputum specimens, 28 (47%) cases from 60 were positive. Candida albicans represented the most common fungal infection isolat

Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors. In this paper, tried to implement an automated segmentation methods of gray level CT images is used to provide information such as anatomical structure and identifying the Region of Interest (ROI) i.e. locate tumor, lesion and other in kidney.
A CT image has inhomogeneity, noise which affects the continuity and accuracy of the images segmentation. In

     Always MRI and CT Medical images are noisy so that preprocessing is necessary for enhance these images to assist clinicians and make accurate diagnosis. Firstly, in the proposed method uses two denoising filters (Median and Slantlet) are applied to images in parallel and the best enhanced image gained from both filters is voted by use PSNR and MSE as image quality measurements. Next, extraction of brain tumor from cleaned images is done by segmentation method based on k-mean.  The result shows that the proposed method is giving an optimal solution due to denoising method which is based on multiple filter types to obtain best clear images and that is leads to make the extraction of tumor more precision best.<

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s