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Multi-objective of wind-driven optimization as feature selection and clustering to enhance text clustering
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Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as the multi-objective first time as unsupervised Feature Selection (WDOFS) and the second time as a Clustering algorithm (WDOC). For example, the WDOC outperformed Harmony Search and Particle Swarm in terms of F-measurement by 93.3%; in contrast, text clustering's performance improves 0.9% because of using suggested clustering on the proposed feature selection. With WDOFS more than 50 percent of features have been removed from the other examination of features. The best result got the multi-objectives with F-measurement 98.3%.

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Publication Date
Tue Apr 01 2025
Journal Name
Mesopotamian Journal Of Cybersecurity
The Impact of Feature Importance on Spoofing Attack Detection in IoT Environment
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The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

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Publication Date
Tue Nov 01 2016
Journal Name
Indian Journal Of Pathology And Microbiology
Panniculitis is a common unrecognized histopathological feature of cutaneous leishmaniasis
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KE Sharquie, AF Hameed, AA Noaimi, Indian Journal of Pathology and Microbiology, 2016 - Cited by 12

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Engineering
Optimization of Dye Removal Using Waste Natural Material and Polymer Particles
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In this paper waste natural material (date seed) and polymer particles(UF) were used for investigation of  removal dye of the potassium permanganate. Also study effect some variables such as pH, dye concentration and adsorbent concentration on dye removal. 15 experimental runs were done using  the itemized conditions designed established on the Box-Wilson design employed to optimize dye removal. The optimum conditions for the dye removal were found: (pH) 12, (dye con.) 2.38 ppm, (adsorbant con.) 0.0816 gm for date seed with 95.22% removal and for UF (pH) 12, (dye con.) 18 ppm, (adsorbant con.) 0.2235 gm with 91.43%. The value of R-square was 85.47%  for Date seed  and (88.77%) for UF.

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Publication Date
Fri May 15 2015
Journal Name
Euphrates Journal Of Agricultural Science
Performance Evaluation of field and genetic for genotype selection from Tomato Lycopersicon esculeuntum Mill.
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The study was conducted at the fields of the Department of Horticulture and Landscape Gardening,College of Agriculture, University of Baghdad during the growing seasons of 2013- 2014 .forPerformance of Evaluation Vegetative growth and yield traits and estimate some important geneticparameter on seven selected breed of tomato which (S1-S7 ) Pure line. the results found significantdifferences between breeds in all study trails except clusters flowering number .S1 significantly plantlength which reached 227.3 .Also S1,S2 and S4 were significantly increased the number fruit for plant,Fruit weight Increased in S3 ,S6 and plant yield. Increased in S1, S4 ,S5. Genetic variation valueswere low in Floral clusters , TSS and fruit firmest and medium i

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
state selection of ammonia molecular beam using tapered ring focuser
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I've made extensive studies on the distribution of the electric field stable heterogeneous within intensive that contain metal rings with slope diagonal positive to a site halfway to be in its maximum value, followed by decline negative and equally to the other end of the concentrated distributed by electric stable thanking sequentially and have focused empirical studies in the pastthe molecules that you focused Pantqaúha during passage

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Publication Date
Fri Oct 19 2018
Journal Name
Journal Of Economics And Administrative Sciences
Big Data Approch to Enhance Organizational Ambidexterity An Exploratory Study of a Sample of Managers at ASIA Cell For Mobile Telecommunication Company in Iraq
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               The research aimed at measuring the compatibility of Big date with the organizational Ambidexterity dimensions of the Asia cell  Mobile telecommunications company in Iraq in order to determine the possibility of adoption of Big data Triple as a approach to achieve organizational Ambidexterity.

The study adopted the descriptive analytical approach to collect and analyze the data collected by the questionnaire tool developed on the Likert scale After  a comprehensive review of the literature related to the two basic study dimensions, the data has been subjected to many statistical treatments in accordance with res

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Mon May 27 2019
Journal Name
Al-khwarizmi Engineering Journal
Investigation the Optimization of Machining Parameters to Surface Roughness in Free Form Surface of Composite Material
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The aim of this research is to investigation the optimization of the machining parameters (spindle speed, feed rate, depth of cut, diameter of cutter and number of flutes of cutter) of surface roughness for free-form surface of composite material (Aluminum 6061 reinforced boron carbide) by using HSS uncoated flat end mill cutters which are rare use of the free-form surface. Side milling (profile) is the method used in this study by CNC vertical milling machine. The purpose of using ANFIS to obtain the better prediction of surface roughness values and decreased of the error prediction value and get optimum machining parameters by using Taguchi method for the best surface roughness at spindle speed 4500 r.p.m, 920mm/rev feed rate, 0.6mm de

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Publication Date
Sat Apr 01 2023
Journal Name
Heliyon
Application of solar photo-electro-Fenton technology to petroleum refinery wastewater degradation: Optimization of operational parameters
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Publication Date
Tue May 01 2012
Journal Name
Journal Of Engineering
Study on wind loads coefficients and flow field characteristics around the parabolic trough with stiffeners
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wind load coefficient