Bioethanol produced from lignocellulose feedstock is a renewable substitute to declining fossil fuels. Pretreatment using ultrasound assisted alkaline was investigated to enhance the enzyme digestibility of waste paper. The pretreatment was conducted over a wide range of conditions including waste paper concentrations of 1-5%, reaction time of 10-30 min and temperatures of 30-70°C. The optimum conditions were 4 % substrate loading with 25 min treatment time at 60°C where maximum reducing sugar obtained was 1.89 g/L. Hydrolysis process was conducted with a crude cellulolytic enzymes produced by Cellulomonas uda (PTCC 1259).The maximum amount of sugar released and hydrolysis efficiency were 20.92 g/L and 78.4 %, respectively. Sugars

Hyperpigmentation is the increase in the natural color of the skin. The purpose of this study is to evaluate the efficacy and safety of Q-Switched Nd:YAG (1064 & 532 nm) Laser in treatment of skin hyper pigmentation. This study was done in the research clinic of Institute of laser for postgraduate Studies/University of Baghdad from October 2008 to the end of January 2009. After clinical assessment of skin hyperpigmentation color, twenty six patients were divided according to their lesions. Eight Patients with freckles, seven patients with melasma, four patients with tattoo. Cases with tattoo, were subdivided into amateur tattoos two, professional tattoos one, and one traumatic tattoo. Four Patients with post inflammatory hyperpigment

In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected  from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.

       Remote sensing is a source of up-to-date information. The present study relied on various approaches for gathering information, including descriptive, quantitative and quantitative analytical processes. Particularly,  we conducted the analysis of the satellite data ETM + of the satellite Landsat7 and the digital models of Digital Elevation Model of SRTM using ArcGIS9.2. The model depends on primary mathematical equations and  constitutes an essential base for GIS applications that rely on data, computer, and software, performing the processes of data entry, analysis and processing. This paper deals with the geomorphological characteristics of a selected study area in Kirkuk province. The cha

Detection and classification of animals is a major challenge that is facing the researchers. There are five classes of vertebrate animals, namely the Mammals, Amphibians, Reptiles, Birds, and Fish, and each type includes many thousands of different animals. In this paper, we propose a new model based on the training of deep convolutional neural networks (CNN) to detect and classify two classes of vertebrate animals (Mammals and Reptiles). Deep CNNs are the state of the art in image recognition and are known for their high learning capacity, accuracy, and robustness to typical object recognition challenges. The dataset of this system contains 6000 images, including 4800 images for training. The proposed algorithm was tested by using 1200