Clustering is an unsupervised learning method that classified data according to similarity probabilities. DBScan as a high-quality algorithm has been introduced for clustering spatial data due to its ability to remove noise (outlier) and constructing arbitrarily shapes. However, it has a problem in determining a suitable value of Eps parameter. This paper proposes a new clustering method, termed as DBScanBAT, that it optimizes DBScan algorithm by BAT algorithm. The proposed method automatically sets the DBScan parameters (Eps) and finds the optimal value for it. The results of the proposed DBScanBAT automatically generates near original number of clusters better than DBScanPSO and original DBScan. Furthermore, the proposed method

The principal concern of this study is Disjunct and Conjunct adverbials in the
English language. The study sets out to explore and clarify the types, nature and
structure of disjuncts and conjuncts. It also aims at testing student's performance to
evaluate the use and usage of the disjuncts and conjuncts in their written performance.
Two tests, accordingly, were given to some fifty students of at the Dept. of English, at
the college of languages (third and fourth stages) in the University of Sulaimani. The
hypothesis that the study was based on are those students use disjuncts and conjuncts
hardly enough in their writings and when doing so, they generally tend to stick only to
the most commonly used and familiar o

In line with the advancement of hardware technology and increasing consumer demands for new functionalities and innovations, software applications grew tremendously in term of size over the last decade. This sudden increase in size has a profound impact as far as testing is concerned. Here, more and more unwanted interactions among software systems components, hardware, and operating system are to be expected, rendering increased possibility of faults. To address this issue, many useful interaction-based testing techniques (termed t-way strategies) have been developed in the literature. As an effort to promote awareness and encourage its usage, this chapter surveys the current state-of-the-art and reviews the state-of-practices in t

In line with the advancement of hardware technology and increasing consumer demands for new functionalities and innovations, software applications grew tremendously in term of size over the last decade. This sudden increase in size has a profound impact as far as testing is concerned. Here, more and more unwanted interactions among software systems components, hardware, and operating system are to be expected, rendering increased possibility of faults. To address this issue, many useful interaction-based testing techniques (termed t-way strategies) have been developed in the literature. As an effort to promote awareness and encourage its usage, this chapter surveys the current state-of-the-art and reviews the state-of-practices in t

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust EA wit

      Restoration is the main process in many applications. Restoring an original image from a damaged image is the foundation of the restoring operation, either blind or non-blind. One of the main challenges in the restoration process is to estimate the degradation parameters. The degradation parameters include Blurring Function (Point Spread Function, PSF) and Noise Function. The most common causes of image degradation are errors in transmission channels, defects in the optical system, inhomogeneous medium, relative motion between object and camera, etc. In our research, a novel algorithm was adopted based on Circular Hough Transform used to estimate the width (radius, sigma) of the Point Spread Function. This algorithm is based o

Al-Dalmaj marsh and the near surrounding area is a very promising area for energy resources, tourism, agricultural and industrial activities. Over the past century, the Al-Dalmaje marsh and near surroundings area endrous from a number of changes. The current study highlights the spatial and temporal changes detection in land cover for Al-Dalmaj marsh and near surroundings area using different analyses methods the supervised maximum likelihood classification method, the Normalized  Difference Vegetation Index (NDVI), Geographic Information Systems(GIS),  and Remote Sensing (RS). Techniques spectral indices were used in this study to determine the change of wetlands and drylands area and of other land classes, th

Biological image edge detection preserving the important structural properties in an image. Detecting accurate edges are very important for analyzing the basic properties associated with a biological image. Gradient operator plays very important role in edge detection. In this paper the images had been using are color biological images taken from microbiology laboratory at the biological department college of science Al-MustansiriyhUniversity and the effect of gradient operation have applied on around 10 different biological color images but view only two. In our proposed approach comparative of various gradient of biological image include (gradient of image, gradient of image using first order derivative edge detection (Soble,Prewitt,Ro