Among the available chaotic modulation schemes, differential chaos shift keying (DSCK) offers the perfect noise performance. The power consumption of DCSK is high since it sends chaotic signal in both of 1 and 0 transmission, so it does not represent the optimal choice for some applications like indoor wireless sensing where power consumption is a critical issue. In this paper a novel noncoherent chaotic communication scheme called differential chaos on-off keying (DCOOK) is proposed as a solution of this problem. With the proposed scheme, the DCOOK signal have a structure similar to chaos on-off keying (COOK) scheme with improved performance in noisy and multipath channels by introducing the concept of differential coherency used in DCS

Hydrocarbon displacement at the pore scale is mainly controlled by the wetness properties of the porous media. Consequently, several techniques including nanofluid flooding were implemented to manipulate the wetting behavior of the pore space in oil reservoirs. This study thus focuses on monitoring the displacement of oil from artificial glass porous media, as a representative for sandstone reservoirs, before and after nanofluid flooding. Experiments were conducted at various temperatures (25 – 50° C), nanoparticles concentrations (0.001 – 0.05 wt% SiO2 NPs), salinity (0.1 – 2 wt% NaCl), and flooding time. Images were taken via a high-resolution microscopic camera and analyzed to investigate the displacement of the oil at dif

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima

A descriptive study, which was using an assessment approach, was conducted for the
determination of the impact of rheumatoid arthritis and osteoarthritis patient’s functional disability
upon their life style. The study was carried out at the Rheumatology and outpatients clinics of ALKarama
Teaching Hospital, Baghdad Teaching Hospital AL-Kindey Teaching Hospital and Specialized
surgeries Teaching Hospital for the period of October 15th 2003 through May 13th 2004 in Baghdad
City. A purposive (non-probability) sample of (245) arthritis patients which was comprised (111)
rheumatoid arthritis patients and (134) osteoarthritis patients, was selected out of the early stated
settings. The questionnaire was comprised of

  Empirical research in the disciplines of art and design has started to escalate and gather consideration within the academic community over the past few decades. However, still, graphic design tends to be a topic extremely under-researched by scholarly persons. Profound research in the field of graphic design extends far beyond the works produced by the designer himself (Khoury, 2009, p.844). In order to develop a clear insight, one needs to delve deep into the subcategories that the diverse field of graphic design is comprised of, including illustration, typography, interaction design, branding and even the impact of notable, eminent institutes from around the world that have taken the budding artists for quite a long time (Walke

Orthogonal polynomials and their moments serve as pivotal elements across various fields. Discrete Krawtchouk polynomials (DKraPs) are considered a versatile family of orthogonal polynomials and are widely used in different fields such as probability theory, signal processing, digital communications, and image processing. Various recurrence algorithms have been proposed so far to address the challenge of numerical instability for large values of orders and signal sizes. The computation of DKraP coefficients was typically computed using sequential algorithms, which are computationally extensive for large order values and polynomial sizes. To this end, this paper introduces a computationally efficient solution that utilizes the parall

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

Leishmaniasis is one of the important parasitic diseases, affecting mainly low social class people indeveloping countries, and is more prevalent and endemic in the tropical and subtropical regions of old worldand new world. Despite ofbroad distribution in Iraq,little known about the geneticcharacteristics of thecausative agents. So this study was aimed to evaluate the genetic varietyoftwo IraqiLeishmaniatropicaisolatesbased on heat shock protein gene sequence 70 (HSP70) in comparison with universal isolates recordedsequences data. After amplification and sequencing of HSP70 gene,the obtainedresults were alignment alongwith homologous Leishmania sequences retrieved from NCBI by using BLAST. The analysis results showedpresence of particular g