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Review on Hybrid Swarm Algorithms for Feature Selection
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    Feature selection represents one of the critical processes in machine learning (ML). The fundamental aim of the problem of feature selection is to maintain performance accuracy while reducing the dimension of feature selection. Different approaches were created for classifying the datasets. In a range of optimization problems, swarming techniques produced better outcomes. At the same time, hybrid algorithms have gotten a lot of attention recently when it comes to solving optimization problems. As a result, this study provides a thorough assessment of the literature on feature selection problems using hybrid swarm algorithms that have been developed over time (2018-2021). Lastly, when compared with current feature selection procedures, the majority of hybrid algorithms enhance classification accuracy.

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Publication Date
Tue Jun 14 2022
Journal Name
International Journal Of Health Sciences
Knee osteoarthritis
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Osteoarthritis (OA) is recognized as a main public health difficult. It is one of the major reasons of reduced function that diminishes quality of life worldwide. Osteoarthritis is a very common disorder affecting the joint cartilage. As there is no cure for osteoarthritis, treatments currently focus on management of symptoms. Pain relief, improved joint function, and joint stability are the main goals of therapy. The muscle weakness and muscle atrophy contribute to the disease process. So, rehabilitation and physiotherapy were often prescribed with the intention to alleviate pain and increase mobility. Medical therapy provides modest benefits in pain reduction and functional improvement; however, non-steroidal anti-inflammatory dru

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Climatic Water Balance and Groundwater Recharge in Abu-Jir Village, Al-Anbar Governorate, Western Iraq
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     The study area is located in Al-Anbar Governorate, western Iraq. The climatic data were collected from Al-Ramadi Meteorological Station for the period 1990 to  2020 and used to assess the climatic condition of the study area. The total annual rainfall, relative humidity, monthly average temperature, evaporation, wind speed and sunshine duration are 108 mm, 52.7 %, 22.6˚C, 2814.3 mm, 2.2 m/s and 8.8 h/day, respectively. The climate of the study area is described as an arid to sub arid and relatively hot in summer and cold with low rain in winter. During the data used, the highest potential evapotranspiration was 217.1 mm in July, while the lowest value was 10.7 mm in January, with a total amount of 1170.07 mm. The highest and l

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Self-Localization of Guide Robots Through Image Classification
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The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Tadpole Domination in Graphs
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A new type of the connected domination parameters called tadpole domination number of a graph is introduced. Tadpole domination number for some standard graphs is determined, and some bounds for this number are obtained. Additionally, a new graph, finite, simple, undirected and connected, is introduced named weaver graph. Tadpole domination is calculated for this graph with other families of graphs.

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

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Publication Date
Thu Dec 15 2022
Journal Name
Al-adab Journal
Metaphors and comparisons as a means of rethinking the phenomena of the surrounding world
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The article characterizes metaphors and comparisons as a means of rethinking the phenomena of the surrounding world; two directions are named within which metaphors and comparisons are studied: 1) the linguo-classification direction combines several classifications of metaphors and comparisons, which are basically focused on comparing two denotations through the meanings of word forms that are part of the trope; 2) the theoretical and conceptual direction is associated with the concept of conceptual displacement and is the basis of the theoretical and methodological study of metaphor and comparison, i.e. the modern theory of metaphor is being formed; The main attention is focused on the comparative concept of Aristotle, which postul

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Publication Date
Sat Dec 01 2018
Journal Name
Al-nahrain Journal Of Science
Image Classification Using Bag of Visual Words (BoVW)
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In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Hn-Domination in Graphs
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The aim of this article is to introduce a new definition of domination number in graphs called hn-domination number denoted by . This paper presents some properties which show the concepts of connected and independent hn-domination. Furthermore, some bounds of these parameters are determined, specifically, the impact on hn-domination parameter is studied thoroughly in this paper when a graph is modified by deleting or adding a vertex or deleting an edge.

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Calculating Groundwater Recharge Using Water Balance in Mandaly City, Diyala Governorate, Eastern Iraq
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      Water balance approaches are strategies for resolving key theoretical and practical hydrological issues. The major goals of this study are to examine climatic elements and conditions to calculate groundwater recharge using the water balance approach. The study area is located in Mandaly city, Diyala Governorate, eastern Iraq. The metrological data was gathered between 1994 and 2020 to evaluate the study area's climate. The annual rainfall rate has been 248.61 mm, with a relative humidity of 43.89%, a temperature of 24.41 oC, a wind speed of 1.99 m/sec, sunshine of 8.32 hours per day, and evaporation of (268.09 mm). The total amount of corrected evapotranspiration was 1010.09 mm, with a peak value of 225.29 mm in Jul

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Publication Date
Tue Oct 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Performance Enhancement of Face Recognition under High-Density Noise Using PCA and De-Noising Technique
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       There are many techniques for face recognition which compare the desired face image with a set of faces images stored in a database. Most of these techniques fail if faces images are exposed to high-density noise. Therefore, it is necessary to find a robust method to recognize the corrupted face image with a high density noise. In this work, face recognition algorithm was suggested by using the combination of de-noising filter and PCA. Many studies have shown that PCA has ability to solve the problem of noisy images and dimensionality reduction. However, in cases where faces images are exposed to high noise, the work of PCA in removing noise is useless, therefore adding a strong filter will help to im

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