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EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and Machine learning algorithm
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The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communicating with the outside world. This article examines the use of the SVM, k-NN, and decision tree algorithms to classify EEG signals. To minimize the complexity of the data, maximum overlap discrete wavelet transform (MODWT) is used to extract EEG features. The mean inside each window sample is calculated using the Sliding Window Technique. The vector machine (SVM), k-Nearest Neighbor, and optimize decision tree load the feature vectors.

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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Hexapod Robot Static Stability Enhancement using Genetic Algorithm
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Abstract

Hexapod robot is a flexible mechanical robot with six legs. It has the ability to walk over terrain. The hexapod robot look likes the insect so it has the same gaits. These gaits are tripod, wave and ripple gaits. Hexapod robot needs to stay statically stable at all the times during each gait in order not to fall with three or more legs continuously contacts with the ground. The safety static stability walking is called (the stability margin). In this paper, the forward and inverse kinematics are derived for each hexapod’s leg in order to simulate the hexapod robot model walking using MATLAB R2010a for all gaits and the geometry in order to derive the equations of the sub-constraint workspaces for each

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Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
An edge detection algorithm matching visual contour perception
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For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

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Publication Date
Thu Dec 01 2011
Journal Name
2011 Developments In E-systems Engineering
Enhanced Computation Time for Fast Block Matching Algorithm
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Publication Date
Fri Sep 03 2021
Journal Name
Entropy
Reliable Recurrence Algorithm for High-Order Krawtchouk Polynomials
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Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the

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Publication Date
Fri Apr 01 2022
Journal Name
Symmetry
Fast Overlapping Block Processing Algorithm for Feature Extraction
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In many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th

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Publication Date
Wed Jun 01 2022
Journal Name
Annals Of The Faculty Of Arts
Motivation and Second Language Acquisition: Motivational Orientations in Foreign Language Learning
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Numerous research studies have been conducted on why some learners acquire a second language more easily and quickly than others. Most of these studies have demonstrated that acquiring a second language does not depend only on learners’ cognitive ability or professional teaching strategies. The learning language process is more complicated than that. It is affected by crucial factors that are beyond the control of learners and teachers. These factors are known as sociolinguistic factors. These factors include culture, age, motivation, socio-economic status, and gender. This research paper mainly concentrates on the role of motivation in second language acquisition.

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
Brain Dominance Learning Styles for Secondary School Students Distinguished and Ordinary
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The current research aims at detecting Brain Dominance Learning Styles distinguished
and ordinary secondary school students (males and females).The researcher adopted Torrance
measure, known as ‘the style of your learning and thinking to measure Brain Dominance
Learning Styles’, the codified version of Joseph Qitami (1986); picture (a). The researcher
verified the standard properties of tool. The final application sample was 352 distinguished
and ordinary students; 176 distinguished male and female students and 176 ordinary male and
female students at the scientific fifth level of secondary school from schools in the province of
Baghdad, AL- KarKh Education Directorates in the First and Second . and who have been

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Publication Date
Mon Jan 28 2019
Journal Name
Journal Of The College Of Education For Women
Mindfulness and Its Relation to Self Regulated Learning Among University Students
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Mindfulness is considered a process to draw an image of the active event and to creat new social varieties which leaves the individuals open to modernity and to be sensitive towards the context. in contrast, when individuals act with less attention, they need to be more determined concerning the varieties and events of the past . and as a result , they become unaware of the characteristics that creat the individual condition .The problem of the current study is represented in asking about the nature of the possible relationship between mindfulness and self-regulated learning within specific demographic frame of an importantsocial category represented in university students where no previous researches nor theories have agreed on the natu

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Publication Date
Mon Mar 02 2020
Journal Name
Journal Of Applied Research In Higher Education
Proposal of a guide for talent evaluation and management based on a qualitative and three-staged approach
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Purpose

The key objective of the study is to understand the best processes that are currently used in managing talent in Australian higher education (AHE) and design a quantitative measurement of talent management processes (TMPs) for the higher education (HE) sector.

Design/methodology/approach

The three qualitative multi-method studies that are commonly used in empirical studies, namely, brainstorming, focus group discussions and semi-structured individual interviews were considered. Twenty-three individuals from six Australian universities parti

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Comparison some of methods wavelet estimation for non parametric regression function with missing response variable at random
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Abstract

 The problem of missing data represents a major obstacle before researchers in the process of data analysis in different fields since , this problem is a recurrent one in all fields of study including social , medical , astronomical and clinical experiments .

The presence of such a problem within the data to be studied may influence negatively on the analysis and it may lead to misleading conclusions , together with the fact that these conclusions that result from a great bias caused by that problem in spite of the efficiency of wavelet methods but they are also affected by the missing of data , in addition to the impact of the problem of miss of accuracy estimation

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