the student of the structure of the city and its constituent elements will clearly sense the invisible relationships that underlie the different forms of urban activity, which in turn are defined by the generality of the urban patterns in that city, which will vary clearly according to the location in the city. These relations will be embodied in their true form in the interactions between the different uses of the earth, and the change that will result from their regularity in the form of entities in independent groups, which may share with each other a component of it.
Therefore, the process of controlling the functional interactions between the uses of the urban land and the awareness of t

Over the last period, social media achieved a widespread use worldwide where the statistics indicate that more than three billion people are on social media, leading to large quantities of data online. To analyze these large quantities of data, a special classification method known as sentiment analysis, is used. This paper presents a new sentiment analysis system based on machine learning techniques, which aims to create a process to extract the polarity from social media texts. By using machine learning techniques, sentiment analysis achieved a great success around the world. This paper investigates this topic and proposes a sentiment analysis system built on Bayesian Rough Decision Tree (BRDT) algorithm. The experimental results show

Emerge application was used in Hampsson-Russell programs and that uses a combination of multiple 3D or 2D seismic attributes to predict some reservoir parameter of interest. In this research used the seismic inversion technique was performed on post-stack three dimensions (3D) seismic data in Nasriya oilfield with five wells  and then used this results in  Emerge analysis (training and application) were used to estimate reservoir properties (effective porosity) with multiattribute analysis derive relations  between them at well locations. The horizon time slice of reservoir units of (Yb1, Yb3 and Yc) of Yamama Formation was made for property (effective porosity) to confirm match results and enhancement trends within these

Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.

This research presents a method of using MATLAB in analyzing a nonhomogeneous soil (Gibson-type) by
estimating the displacements and stresses under the strip footing during applied incremental loading
sequences. This paper presents a two-dimensional finite element method. In this method, the soil is divided into a number of triangle elements. A model soil (Gibson-type) with linearly increasing modulus of elasticity with depth is presented. The influences of modulus of elasticity, incremental loading, width of footing, and depth of footing are considered in this paper. The results are compared with authors' conclusions of previous studies.

     Recently, the Internet of Things has emerged as an encouraging technology that is scaling up new heights towards the modernization of real word physical objects into smarter devices in several domains. Internet of Things (IoT) based solutions in agriculture drives farming into a smart way through the proliferation of smart devices to enhanced production with minimal human involvement. This paper presents a comprehensive study of the role of IoT in prominent applications of farming, wireless communication protocols, and the role of sensors in precision farming. In this research article, the existing frameworks in IoT-based agriculture systems with relevant technologies are presented. Furthermore, the comparative analysis of the a