Colonoscopy is a popular procedure which is used to detect an abnormality. Early diagnosis can help to heal many patients. The purpose of this paper is removing/reducing some artifacts to improve the visual quality of colonoscopy videos to provide better information for physicians. This work complements a series of work consisting of three previously published papers. In this paper, optic flow is used for motion compensation, where a number of consecutive images are registered to integrate some information to create a new image that has/reveals more information than the original one. Colon images were classified into informative and noninformative images by using a deep neural network. Then, two different strategies were use

Several remote sensor network (WSN) tasks require sensor information join. This in-processing Join is configured in parallel sensor hub to save battery power and limit the communication cost. Hence, a parallel join system is proposed for sensor networks. The proposed parallel join algorithm organizes in section-situated databases. A novel join method has been proposed for remote WSNs to limit the aggregate communication cost and enhance execution. This approach depends on two procedures; section-situated databases and parallel join algorithm utilized to store sensor information and speed up processing respectively. A segment arranged databases store information table in segmented shrewd. The Parallel-Joining WSN algorithm is effectively

Background: It was stated in scientific literatures that the entire craniofacial complex is influenced by the growth of the cranial base structures. Nevertheless, many times this is not the case, and this point is subject to great controversy so the aim of this study is to evaluate the possible differences in cranial base shape and flexure between different skeletal classes for both genders and to investigate any possible correlation between cranial base variables and other skeletal base variables. Materials and Methods: The sample include 75 lateral cephalometric radiographs of Iraqi adults aged between 18-25 years (39 males, 36 females), collected from patients and undergraduate students in the orthodontic department of College of Dentist

In this work, two cone-inverted cylindrical and cross-hybrid dielectric resonator antennas are stacked and excited by the coaxial probe method with an operating standard resonant frequency of 5.438 GHz. A drawback of these standard Dielectric Resonator Antennas (DRAs) is their narrow bandwidth. For good antenna performance, a stacked DR geometry and a thick dielectric substrate having a low dielectric constant are desired since this provides large bandwidth, better radiation power, reduces conductor loss and nonappearance of surface waves. Many approaches, such as changing the shape of the dielectric resonator, have been used to enhance bandwidth. Using DRA, having the lowest dielectric constant, increases the bandwidth and the electroma

     In this research, we propose to use two local search methods (LSM's); Particle Swarm Optimization (PSO) and the Bees Algorithm (BA) to solve Multi-Criteria Travelling Salesman Problem (MCTSP) to obtain the best efficient solutions. The generating process of the population of the proposed LSM's may be randomly obtained or by adding some initial solutions obtained from some efficient heuristic methods. The obtained solutions of the PSO and BA are compared with the solutions of the exact methods (complete enumeration and branch and bound methods) and some heuristic methods. The results proved the efficiency of PSO and BA methods for a large number of nodes ( ). The proposed LSM's give the best efficient solutions for the MCTSP for

The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled

The research aims to study and assess the effectiveness of preventive measures banking for the reduction of money laundering based on the checklist (Check list), which have been prepared based on the paragraphs of some of the principles and recommendations of international and Money Laundering Act No. 93 of 2004 and the instructions thereto, to examine and assess the application of these measures by Gulf Commercial Bank, which was chosen to perform the search.

I've been a statement the concept of money laundering in terms of the definition and characteristics, stages and effects of political, economic and social as well as the nature of banking supervision in terms of the definition and the most important

Stemming is a pre-processing step in Text mining applications as well as it is very important in most of the Information Retrieval systems. The goal of stemming is to reduce different grammatical forms of a word and sometimes derivationally related forms of a word to a common base (root or stem) form like reducing noun, adjective, verb, adverb etc. to its base form. The stem needs not to be identical to the morphological root of the word; it is usually sufficient that related words map to the same stem, even if this stem is not in itself a valid root. As in other languages; there is a need for an effective stemming algorithm for the indexing and retrieval of Arabic documents while the Arabic stemming algorithms are not widely available.

Clustering algorithms have recently gained attention in the related literature since
they can help current intrusion detection systems in several aspects. This paper
proposes genetic algorithm (GA) based clustering, serving to distinguish patterns
incoming from network traffic packets into normal and attack. Two GA based
clustering models for solving intrusion detection problem are introduced. The first
model coined as handles numeric features of the network packet, whereas
the second one coined as concerns all features of the network packet.
Moreover, a new mutation operator directed for binary and symbolic features is
proposed. The basic concept of proposed mutation operator depends on the most
frequent value