The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

The multicast technology implements a very high-efficiency point-to-multipoint data transmission over IP networks (IPv4 and IPv6). Multicast reduces network load, eliminates traffic redundancy, and saves network bandwidth. Therefore, multicast used widely in LAN/WAN applications such as online games, video conferencing and IPTV. The multicast technology implements varied protocols such as DVMRP(Distance Vector Multicast Routing Protocol), MOSPF(Multicast Open Shortest Path First), or PIM-DM (Protocol Independent Multicast- Dense Mode) which considered source tree type, while PIM-SM (Protocol Independent Multicast- Sparse Mode) and CBT (Core Based Tree) uses shared tree. Current paper focuses on the performance evaluation of the two multi

      Several studies have shown that certain microbes, mainly bacteria may have the ability to digest plastic wastes. The goal of this study was to see how well Bacillus subtilis, Staphylococcus lentus, Aeromonas hydrophila, Sphingomonas paucimobilis and Kocuria paedia degrade three kinds of oil-based plastics: low-density polyethylene (LDPE), polystyrene (PS) and polyvinylchloride (PVC) polymer sheets. The experiment was conducted for 30 days under laboratory conditions with occasional shaking at 180 rpm and 32°C. Biodegradation was measured in terms of weight loss.. Accordingto IR Spectroscopy, the C-H stretch band at 2920cm-1 improved as a result of bacterial degradation of polyethyl

D-mannose sugar was used to prepare [benzoic acid 6-formyl-2, 2-dimethyl-tetrahydrofuro [3, 4-d][1, 3] dioxol-4-yl ester](compound A). The condensation reaction of folic acid with (compound A) resulted in the formation of new ligand [L]. These compounds were characterized by elemental analysis CHN, atomic absorption AA,(FT-IR),(UV-Vis), TLC, ES mass (for electrospray), molar conductance, and melting point. The new tetradentate ligand [L], reacted with two moles of some selected metal ions and two moles of (2-aminophenol),(metal: ligand: 2-aminophenol) at reflux in water medium to give a series of new complexes of the general formula K2 [M2 (L)(HA) 2] where M= Co (II), Ni (II), Cu (II) and Cd (II). These complexes were characterized by eleme

Dermatophytes are a group of morphologically and physiologically related molds some of which cause well defined infections: dermatophytoses (tineas or ringworm). The present study aims at identification of dermatophytes species and varieties from patients in Wasit province-Iraq using molecular approach based PCR fingerprint.
The short oligonucleotide (GACA)4 is a microsatellite primer was used in this study for identification of dermatophyte isolates. The results identified different species and varieties among dermatophytes. The numbers of resulting PCR bands ranged from 1 to 4 (size range, 600bp to 1600bp) for each species. The resulting patterns were distinct for Trichophyton and Microsporum species and varieties.
Trichophyton s

    Semantic segmentation is effective in numerous object classification tasks such as autonomous vehicles and scene understanding. With the advent in the deep learning domain, lots of efforts are seen in applying deep learning algorithms for semantic segmentation. Most of the algorithms gain the required accuracy while compromising on their storage and computational requirements. The work showcases the implementation of Convolutional Neural Network (CNN) using Discrete Cosine Transform (DCT), where DCT exhibit exceptional energy compaction properties. The proposed Adaptive Weight Wiener Filter (AWWF) rearranges the DCT coefficients by truncating the high frequency coefficients. AWWF-DCT model reinstate the convolutional l

Improving students’ use of argumentation is front and center in the increasing emphasis on scientific practice in K-12 Science and STEM programs. We explore the construct validity of scenario-based assessments of claim-evidence-reasoning (CER) and the structure of the CER construct with respect to a learning progression framework. We also seek to understand how middle school students progress. Establishing the purpose of an argument is a competency that a majority of middle school students meet, whereas quantitative reasoning is the most difficult, and the Rasch model indicates that the competencies form a unidimensional hierarchy of skills. We also find no evidence of differential item functioning between different scenarios, suggesting

A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un