This study investigated the feasibility of anaerobic co-digestion of giant reed (GR) inoculated with waste manure as a co-substrate for biogas production. The performance of co-digestion was evaluated in 4 anaerobic digesters operated in batch mode at different conditions. The effects of alkali pretreatment with NaOH (4% w/v) solution, inoculum type, and thermal condition were studied. The results demonstrated that the alkali-pretreatment of GR enhanced the biogas generation by about 15% at mesophilic conditions. Thermophilic conditions enhanced the biogas recovery from both alkali-free and alkali pretreated GR by 15% and 127%, respectively. The kinetic study of the co-digestion process of GR for biogas recovery suggeste

Algae are photosynthetic microorganisms that play important role in aquatic ecosystems as they are the primary producers in aquatic food webs. Several groups of algae are capable of producing toxins that impact aquatic ecosystems, especially managed systems. Cyanobacteria are the most important algae in freshwaters, and many species produce cyanotoxins including hepatotoxins and neurotoxins. The potent cyano-neurotoxins β-N-methylamino-L-alanine (BMAA), 2, 4-diaminobutyric acid dihydrochloride (DABA), and anatoxin-a are especially critical with regards to public and animal health problems.

Image compression is one of the data compression types applied to digital images in order to reduce their high cost for storage and/or transmission. Image compression algorithms may take the benefit of visual sensitivity and statistical properties of image data to deliver superior results in comparison with generic data compression schemes, which are used for other digital data. In the first approach, the input image is divided into blocks, each of which is 16 x 16, 32 x 32, or 64 x 64 pixels. The blocks are converted first into a string; then, encoded by using a lossless and dictionary-based algorithm known as arithmetic coding. The more occurrence of the pixels values is codded in few bits compare with pixel values of less occurre

The necessities of steganography methods for hiding secret message into images have been ascend. Thereby, this study is to generate a practical steganography procedure to hide text into image. This operation allows the user to provide the system with both text and cover image, and to find a resulting image that comprises the hidden text inside. The suggested technique is to hide a text inside the header formats of a digital image. Least Significant Bit (LSB) method to hide the message or text, in order to keep the features and characteristics of the original image are used. A new method is applied via using the whole image (header formats) to hide the image. From the experimental results, suggested technique that gives a higher embe

In this study 737 stool specimens were collected from people attending some primary health care centres and hospitals in North of Baghdad, during the period from beginning of April 2009 till the end of March 2010. Different factors were examined to be related with the prevalence of Cryptosporidiosis which were (number of family member, travelling history, source of drinking water and domestic animal present). Significant relations (p≤0.05) were observed between infection rate and the following factor: -Number of family member: The high percentage of Cryptosporidium spp positive cases were seen in families composed of (15-19) and (more than 20) individual which were 28.32% and 16.37% respectively when compared with other family clusters -T

The usage of remote sensing techniques in managing and monitoring the environmental areas is increasing due to the improvement of the sensors used in the observation satellites around the earth. Resolution merge process is used to combine high resolution one band image with another one that have low resolution multi bands image to produce one image that is high in both spatial and spectral resolution. In this work different merging methods were tested to evaluate their enhancement capabilities to extract different environmental areas; Principle component analysis (PCA), Brovey, modified (Intensity, Hue ,Saturation) method and High Pass Filter methods were tested and subjected to visual and statistical comparison for evaluation. Both visu

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m