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

Recently, important efforts have been made in an attempt to search for the cheapest and ecofriendly alternatives adsorbents. In the present work, waste molasses from Iraqi date palm (Zahdi) had been used as a provenance to produce charcoal for the removal of methylene blue (MB) dye from water. The optimum prepared charcoal was obtained at 150 C, by increasing temperature to 175 C, the charcoal had almost converted to ash. The obtained charcoal have been inspected for properties using scanning electron microscope (SEM), atomic force microscope (AFM), porosity and surface area. Adsorption data were optimized to Langmuir and Freundlich and adsorption parameters have been evaluated. The thermodynamic parameters like a change

       Laboratory experiments were carried  out in Technical college AL- Mussiab / Babylon during 2005  to study bioactivity of different concentration from ( aqueous , alcohol and hexane) extracts of bee venom collected from different workers of bees against some bacterial types that cause European Foul – brood Melissococcus plutom , Bacillus alvei and B. letrosporus which had been isolated from infected arched with disease . Two diffusion methods (digging and paper discs) were followed for the extraction of the venom . Results showed that digging diffusion method was more efficient for  test of bacterial inhibition which led to increase the activity of bee venom extract with general a

Two hundred fifty mid-stream urine specimens were collected from Baqubah Teaching Hospital and Al-Batool Teaching Hospital from patients with urinary tract infections (UTI). Of these investigated urine specimens, 66 (26.4%) specimens showed positive growth culture of Gram-negative bacteria. From these, Escherichia coli was the most prevalent bacteria of the examined culture (41, 62.12%). Additionally, the cup assay was used to determine colicin producers while the most efficient colicin producers were estimated by the formation of larger inhibition zone. Approximately half of the investigated E. coli isolates (20, 49 %) was colicin producers. Colicins was extracted after induction by mitomycin-C showed a concentration o

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f

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

In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of how the

Photonic Crystal Fiber Interferometers (PCFIs) are greatly used
for sensing applications. This work presents the fabrication and
characterization of a relative humidity sensor based on Mach-
Zehnder Interferometer (MZI), which operates in reflection mode.
The humidity sensor operation based on the adsorption and
desorption of water vapour at the silica-air interface within the PCF.
The fabrication of this sensor is simple, it only includes splicing and
cleaving the PCF with SMF.PCF (LMA-10) with a certain length
spliced to SMF (Corning-28).
The spectrum of PCFI exhibits good sensitivity to humidity
variations. The PCFI response is observed for a range of humidity
values from (27% RH to 85% RH), the positi

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

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