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A survey on bio-signal analysis for human-robot interaction
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<span lang="EN-US">The use of bio-signals analysis in human-robot interaction is rapidly increasing. There is an urgent demand for it in various applications, including health care, rehabilitation, research, technology, and manufacturing. Despite several state-of-the-art bio-signals analyses in human-robot interaction (HRI) research, it is unclear which one is the best. In this paper, the following topics will be discussed: robotic systems should be given priority in the rehabilitation and aid of amputees and disabled people; second, domains of feature extraction approaches now in use, which are divided into three main sections (time, frequency, and time-frequency). The various domains will be discussed, then a discussion of each domain's benefits and drawbacks, and finally, a recommendation for a new strategy for robotic systems.</span>

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Publication Date
Fri Jun 30 2023
Journal Name
International Journal Of Intelligent Engineering And Systems
DeepFake Detection Improvement for Images Based on a Proposed Method for Local Binary Pattern of the Multiple-Channel Color Space
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DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio

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Publication Date
Tue Oct 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Efficiency of Human Resources Information System and Its Impact on The Level Effectiveness of Employees Performance Appraisal System / Practical Research on Ministry of Higher Education and Scientific Research
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Abstract

The research aims to determine the role of the efficiency of Human Resources Information System in the effectiveness of Employees Performance Appraisal System in the Ministry of Higher Education and Scientific Research / Center for the ministry, it was touching the researchers need the ministry to devise methods that employ outputs Human Resources Information System in the organization surveyed for the development of methods and levels of process evaluate the performance of its employees, in order to identify the extent of the role played by human resources information system in the process of assessing the performance of employees, we raised the question of the President as follows:

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
the role of Green Human Resources Management Practices in strengthening the Strategic Positioning An Analytical Research on Leaders opinion in the Nongovernmental Hospitals in Erbil
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This research is seeks to state the role of Green Human Resources Management Practices and their dimensions (Green Employment and Selection, Green Performance Assessment, Green Training & Development and Green Compensation and Stimulation Systems) in strengthening the Strategic Positioning in the Nongovernmental Hospitals in Erbil city, and aims to analyze the relationship between Green Human Resources Management Practices and Strategic Positioning and to show the impact of Green Human Resources Management Practices in determining the Strategic Position.

            It is depended on a questionnaire as key tools for achieving data, as designed on

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Publication Date
Thu Jan 15 2009
Journal Name
Basrah Journal For Date Palm Research 8 (1), 64-71‏
Survey study of ten rare cultivars of Date Palm Phoenix dactylifera L. in Basrah city‏
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Publication Date
Sun Dec 01 2013
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
THE FAUNISTIC SURVEY OF LADY BEETLES (COLEOPTERA, COCCINELLIDAE) IN THE MEHRIZ REGION(YAZD PROVINCE), IRAN
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  In this study the faunistic of lady beetles (Coleoptera, Coccinellidae) was studied in Mehriz region (Yazd province) during 2009-2010. The total number of specimens of coccinellid beetles were collected from 6 different localities having altitudes from 1420-2420 m. Altogether 11 species from 8 genera, 3 tribes and 3 subfamilies were collected and identified. External characters plus characteristics male and female genitalia were used in order to diagnose species. Seven species were recorded for the first time from Yazd province (marked*). Many species were predacious, preying on various species of aphids, mites and coccids. Some species were also sent to Dr. Helmut Fursch in Germany for identification or confirmation. T

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Publication Date
Thu Mar 22 2018
Journal Name
Journal Of Biodiversity And Environmental Sciences
Survey and taxonomical study of ants that collected from indoor in different regions of Iraq
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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi Journal Of Physics
A nonlinear edge –preserving smoothing filter for edge detection on color and gray satellite images
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A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

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Publication Date
Thu Sep 01 2022
Journal Name
Brazilian Journal Of Chemical Engineering
A computational study on the potential application of Ca12O12 cluster for sensing of fungicide molecule
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Density functional theory calculations are employed to investigate the impact of edifenphos molecule on the reactivity and electronic sensitivity of pure calcium oxide (CaO) nanocluster. The strong adsorption of edifenphos molecule on CaO nanocluster occurs by the sulfur head of the adsorbate, and the amount of the energy of this adsorption is around − 84.40 kcal/mol. The adsorption of edifenphos molecules results in a decrease in the values of Eg of CaO from 4.67 to 3.56 eV, as well as an increase in the electrical conductance. Moreover, the work function of CaO nanocluster is significantly affected, which changes the current of the field emission electron. Eventually, the recovery time is calculated around 99 ms at ambient temperature f

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Publication Date
Sat Feb 25 2017
Journal Name
International Journal On Advanced Science, Engineering And Information Technology
A Novel DNA Sequence Approach for Network Intrusion Detection System Based on Cryptography Encoding Method
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A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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