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Annealing effect on characterization of nano crystalline SnSe thin films prepared by thermal evaporation
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Tin Selenide (SnSe) Nano crystalline thin films of thickness 400±20 nm were deposited on glass substrate by thermal evaporation technique at R.T under a vacuum of ∼ 2 × 10− 5 mbar to study the effect of annealing temperatures (as-deposited, 100, 150 and 200) °C on its structural, surface morphology and optical properties. The films structure was characterized using X-ray diffraction (XRD) which showed that all the films have polycrystalline in nature and orthorhombic structure, with the preferred orientation along the (111) plane. These films was synthesized of very fine crystallites size of (14.8-24.5) nm, the effect of annealing temperatures on the cell parameters, crystallite size and dislocation density were observed. Surface morphology of SnSe films as-prepared and annealed are investigated using atomic force microscopy (AFM) analysis, the grain size of these films vary in the rang from (60.12 to 94.70)nm with increasing annealing temperatures. The results obtained from XRD and AFM indicated that these films were Nano crystalline. The optical constants like absorption coefficient, loss factor, quality factor and optical conductivity of these films has been evaluated. The optical properties revealed that SnSe films have optical energy band gap values increase from (1.5-2.2) eV upon annealing temperatures and high value of absorption coefficient hich implies choosing them in solar cell application.

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Secure Smart Contract Based on Blockchain to Prevent the Non-Repudiation Phenomenon
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Blockchain is an innovative technology that has gained interest in all sectors in the era of digital transformation where it manages transactions and saves them in a database. With the increasing financial transactions and the rapidly developed society with growing businesses many people looking for the dream of a better financially independent life, stray from large corporations and organizations to form startups and small businesses. Recently, the increasing demand for employees or institutes to prepare and manage contracts, papers, and the verifications process, in addition to human mistakes led to the emergence of a smart contract. The smart contract has been developed to save time and provide more confidence while dealing, as well a

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

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Publication Date
Wed May 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On Comparison between Radial Basis Function and Wavelet Basis Functions Neural Networks
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      In this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space. The trained networks are then used in an conjugate gradient algorithm to estimate the output. These neural networks are then applied to solve differential equation. Results of applying these algorithms to several examples are presented

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Publication Date
Fri Mar 31 2023
Journal Name
Wasit Journal Of Computer And Mathematics Science
Security In Wireless Sensor Networks Based On Lightweight Algorithms : An Effective Survey
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At the level of both individuals and companies, Wireless Sensor Networks (WSNs) get a wide range of applications and uses. Sensors are used in a wide range of industries, including agriculture, transportation, health, and many more. Many technologies, such as wireless communication protocols, the Internet of Things, cloud computing, mobile computing, and other emerging technologies, are connected to the usage of sensors. In many circumstances, this contact necessitates the transmission of crucial data, necessitating the need to protect that data from potential threats. However, as the WSN components often have constrained computation and power capabilities, protecting the communication in WSNs comes at a significant performance pena

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Publication Date
Sun Sep 16 2018
Journal Name
British Journal Of Educational Technology
Group tagging: Using video tagging to facilitate reflection on small group activities
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Collaborative learning in class‐based teaching presents a challenge for a tutor to ensure every group and individual student has the best learning experience. We present Group Tagging, a web application that supports reflection on collaborative, group‐based classroom activities. Group Tagging provides students with an opportunity to record important moments within the class‐based group work and enables reflection on and promotion of professional skills such as communication, collaboration and critical thinking. After class, students use the tagged clips to create short videos showcasing their group work activities, which can later be reviewed by the teacher. We report on a deployment of Group Tagging in an undergraduate Computing Scie

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Publication Date
Fri Jan 01 2010
Journal Name
Iraqi Journal Of Biotechnology
BIOCHEMICAL STUDY ON SUPEROXIDE DISMUTASE ENZYME IN PATIENTS WITH DIFFERENT BRAIN TUMORS
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The aim of the current study is to in evaluate the role of SOD activity in the previously reported oxidative stress in our laboratory(1), in the patients with different brain tumors. SOD activity was assayed according to riboflavin/NBT method and its specific activity was calculated in patients with benign and malignant brain tumors and control. Moreover the specific activity was compared in these samples according to gender and the occurrence of disease.Non significant elevation (P > 0.05) in SOD specific activity was observed in tissue of malignant tumors in comparison to that of in benign brain tumors. While a highly significant decrease (P < 0.001) of the specific activity was found in sera of malignant patients group in comparison to t

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Publication Date
Tue Mar 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Formation Evaluation for Nasiriyah Oil Field Based on The Non-Conventional Techniques
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The unconventional techniques called “the quick look techniques”, have been developed to present well log data calculations, so that they may be scanned easily to identify the zones that warrant a more detailed analysis, these techniques have been generated by service companies at the well site which are among the useful, they provide the elements of information needed for making decisions quickly when time is of essence. The techniques used in this paper are:

  • Apparent resistivity Rwa
  • Rxo /Rt

   The above two methods had been used to evaluate Nasiriyah oil field formations (well-NS-3) to discover the hydrocarbon bearing formations. A compu

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Publication Date
Fri Mar 04 2022
Journal Name
Journal Of Water Resources And Geosciences
A Review Study on Gypseous Soils Stabilized with Different Additives in Iraq
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Publication Date
Mon Feb 01 2016
Journal Name
Ieee Transactions On Circuits And Systems Ii: Express Briefs
Adaptive Multibit Crosstalk-Aware Error Control Coding Scheme for On-Chip Communication
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The presence of different noise sources and continuous increase in crosstalk in the deep submicrometer technology raised concerns for on-chip communication reliability, leading to the incorporation of crosstalk avoidance techniques in error control coding schemes. This brief proposes joint crosstalk avoidance with adaptive error control scheme to reduce the power consumption by providing appropriate communication resiliency based on runtime noise level. By switching between shielding and duplication as the crosstalk avoidance technique and between hybrid automatic repeat request and forward error correction as the error control policies, three modes of error resiliencies are provided. The results show that, in reduced mode, the scheme achie

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Publication Date
Fri Jun 01 2007
Journal Name
Journal Of Al-nahrain University Science
ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
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The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

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