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

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

In this paper, image compression technique is presented based on the Zonal transform method. The DCT, Walsh, and Hadamard transform techniques are also implements. These different transforms are applied on SAR images using Different block size. The effects of implementing these different transforms are investigated. The main shortcoming associated with this radar imagery system is the presence of the speckle noise, which affected the compression results.

Some problems want to be solved in image compression to make the process workable and more efficient. Much work had been done in the field of lossy image compression based on wavelet and Discrete Cosine Transform (DCT). In this paper, an efficient image compression scheme is proposed, based on a common encoding transform scheme; It consists of the following steps: 1) bi-orthogonal (tab 9/7) wavelet transform to split the image data into sub-bands, 2) DCT to de-correlate the data, 3) the combined transform stage's output is subjected to scalar quantization before being mapped to positive, 4) and LZW encoding to produce the compressed data. The peak signal-to-noise (PSNR), compression ratio (CR), and compression gain (CG) measures were used t

This research aims to reveal the quality standards available in press images published in the news sites, the Iraqi News Agency and Al-Mada Press for the period from: 1/9/2019, to: 30/9/2019. The research is a descriptive research, in which the researcher relied on the survey methodology to achieve its objectives. The research reached a number of results, most notably the weak role of photojournalists in the websites and the adoption of those the Internet as a source for obtaining press images published with news and reports through its pages, as well as the neglect of the standard Description/Comment below the press images, which plays an important function in explaining and interpreting them for users.

The segmentation of aerial images using different clustering techniques offers valuable insights into interpreting and analyzing such images. By partitioning the images into meaningful regions, clustering techniques help identify and differentiate various objects and areas of interest, facilitating various applications, including urban planning, environmental monitoring, and disaster management. This paper aims to segment color aerial images to provide a means of organizing and understanding the visual information contained within the image for various applications and research purposes. It is also important to look into and compare the basic workings of three popular clustering algorithms: K-Medoids, Fuzzy C-Mean (FCM), and Gaussia

Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images