The problem of text recognition and its applicability as part of images captured in the wild has gained a significant attention from the computer vision community in recent years. In contrast to the recognition of printed documents, scene text recognition is a difficult problem. Contrary to recognition of printed documents, recognizing a scene text is a challenging problem. Many researches focus on the problem of recognizing text extracted from natural scene images. Significant attempts have been made to address this problem in recent past. However, many of these attempts work on utilizing availability of strong context, which naturally limits the dictionary. This paper presents a review of recent papers related to scene text

Medical image segmentation is a frequent processing step in image medical understanding and computer aided diagnosis. In this paper, development of range operator in image segmentation is proposed depending on dermatology infection. Three different block sizes have been utilized on the range operator and the developed ones to enhance the behavior of the segmentation process of medical images. To exploit the concept of range filtering, the extraction of the texture content of medical image is proposed. Experiment is conducted on different medical images and textures to prove the efficacy of our proposed filter was good results.

Breast cancer is the second deadliest disease infected women worldwide. For this
reason the early detection is one of the most essential stop to overcomeit dependingon
automatic devices like artificial intelligent. Medical applications of machine learning
algorithmsare mostly based on their ability to handle classification problems,
including classifications of illnesses or to estimate prognosis. Before machine
learningis applied for diagnosis, it must be trained first. The research methodology
which isdetermines differentofmachine learning algorithms,such as Random tree,
ID3, CART, SMO, C4.5 and Naive Bayesto finds the best training algorithm result.
The contribution of this research is test the data set with mis

 Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.

Image classification can be defined as one of the most important tasks in the area of machine learning. Recently, deep neural networks, especially deep convolution networks, have participated greatly in end-to-end learning which reduce need for human designed features in the image recognition like Convolution Neural Network. It is offers the computation models which are made up of several processing layers for learning data representations with several abstraction levels. In this work, a pre-trained deep CNN is utilized according to some parameters like filter size, no of convolution, pooling, fully connected and type of activation function which includes 300 images for training and predict 100 image gender using probability measures. Re

Remote sensing provide the best means to monitoring change in vegetation over a wide range of temporal scales over large areas. In this study, the vegetation index which has been applied known as the Stress Related Vegetation Index (STVI) on in the area around the Euphrates River and part of Al-Habbaniyah lake which located at western side of the river in Ramadi city, Al-Anbar province at Iraq to study the vegetation cover changes and detect the areas of changes, using two satellite sensors multispectral images such as TM and ALI, after geometric correction procedure to rectifying these images. The STVI-4 index result was the best than other vegetation indices (STVI-1 and STVI-3) to discriminate the vegetable cover distribution. The diff

     In this review paper, several research studies were surveyed to assist future researchers to identify available techniques in the field of infectious disease modeling across complex networks. Infectious disease modelling is becoming increasingly important because of the microbes and viruses that threaten people’s lives and societies in all respects. It has long been a focus of research in many domains, including mathematical biology, physics, computer science, engineering, economics, and the social sciences, to properly represent and analyze spreading processes. This survey first presents a brief overview of previous literature and some graphs and equations to clarify the modeling in complex networks, the detection of societie

     Water balance as a technique is considered one of the means that is relied upon in solving significant hydrological problems. The soil and water assessment tool (SWAT) model was used in this study to assess the water balance in the Wadi Al-Mohammadi basin located at the eastern edge of the Western Desert. Digital elevation model, soil data, Land use - Land cover, and climate data represent the most important requirements for the SWAT model's input as a database. The Wadi Al-Mohammadi basin delineation results show the overall drainage area was 2286.8 km² with seven sub-basins. The trend line of climate data indicates a clear increase in the total rainfall, relative humidity, temperature, and solar radiation from 1990-

The ascorbic acid content of juices of some fruits and pharmaceutical tablets of Vitamin C was determined by a homemade apparatus of DIE technique using a thermocouple as heat sensor. The method is simple, speed, low cost and the different types of turbid, colored samples can be analyzed without any problem. The results were of a valuable accuracy and precision, and the recovery of results was with acceptable values