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Linguistic Fuzzy Trust Model over Oscillating Wireless Sensor Networks
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Simulation  of  the  Linguistic  Fuzzy Trust  Model  (LFTM)  over  oscillating  Wireless  Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Networks (BTRM-WSN) in terms of the accuracy and the average path length suggested by each model is presented. Both models give quite good and accurate outcomes over oscillating WSNs. Also it must be mentioned that the evaluation environment used here is Trust and Reputation Model Simulator for WSN.

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Publication Date
Mon Oct 05 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
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Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

Publication Date
Thu Mar 24 2022
Journal Name
Arab World English Journal
Collocation Networks of Selected Words in Academic Writing: A Corpus-Based Study
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This study aims at shedding light on the linguistic significance of collocation networks in the academic writing context. Following Firth’s principle “You shall know a word by the company it keeps.” The study intends to examine three selected nodes (i.e. research, study, and paper) shared collocations in an academic context. This is achieved by using the corpus linguistic tool; GraphColl in #LancsBox software version 5 which was announced in June 2020 in analyzing selected nodes. The study focuses on academic writing of two corpora which were designed and collected especially to serve the purpose of the study. The corpora consist of a collection of abstracts extracted from two different academic journals that publish for writ

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
Using fuzzy logic for estimating monthly pan evaporation from meteorological data in Emara/ South of Iraq
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Evaporation is one of the major components of the hydrological cycle in the nature, thus its accurate estimation is so important in the planning and management of the irrigation practices and to assess water availability and requirements. The aim of this study is to investigate the ability of fuzzy inference system for estimating monthly pan evaporation form meteorological data. The study has been carried out depending on 261 monthly measurements of each of temperature (T), relative humidity (RH), and wind speed (W) which have been available in Emara meteorological station, southern Iraq. Three different fuzzy models comprising various combinations of monthly climatic variables (temperature, wind speed, and relative humidity) were developed

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Publication Date
Sun Dec 03 2023
Journal Name
2023 Ieee International Conference On Energy Technologies For Future Grids (etfg)
Optimal Hybrid Type-2 Fuzzy-PID Controller for Blade Pitch Angle in Horizontal-axis Wind Turbines
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In the modern world, wind turbine (WT) has become the largest source of renewable energy. The horizontal-axis wind turbine (HAWT) has higher efficiency than the vertical-axis wind turbine (VAWT). The blade pitch angle (BPA) of WT is controlled to increase output power generation over the rated wind speed. This paper proposes an accurate controller for BPA in a 500-kw HAWT. Three types of controllers have been applied and compared to find the best controller: PID controller (PIDC), fuzzy logic type-2 controller (T2FLC), and hybrid type-2 fuzzy-PID controller (T2FPIDC). This paper has been used Mamdani and Sugeno fuzzy inference systems (FIS) to find the best inference system for WT controllers. Furthermore, genetic algorithm (GA) and particl

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Using Adaptive Neuro Fuzzy Inference System to Predict Rate of Penetration from Dynamic Elastic Properties
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Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

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Publication Date
Mon Sep 01 2025
Journal Name
International Journal Of Renewable Energy Research
A Comparative Study of Optimal Fuzzy Logic Controllers for Blade Pitch Angle in Horizontal-axis Wind Turbines
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The blade pitch angle (BPA) in wind turbine (WT) is controlled to maximize output power generation above the rated wind speed (WS). In this paper, four types of controllers are suggested and compared for BPA controller in WT: PID controller (PIDC), type-1 fuzzy logic controller (T1-FLC), type-2 fuzzy logic controller (T2-FLC), and hybrid fuzzy-PID controller (FPIDC). The Mamdani and Sugeno fuzzy inference systems (FIS) have been compared to find the best inference system used in FLC. Genetic algorithm (GA) and Particle swarm optimization algorithm (PSO) are used to find the optimal tuning of the PID parameter. The results of500-kw horizontal-axis wind turbine show that PIDC based on PSO can reduced 2.81% in summation error of power

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Publication Date
Fri Sep 30 2022
Journal Name
College Of Islamic Sciences
The Effectiveness of Combining the Meanings of Grammatical Tools in Understanding the Arabic Sentence A study of Some Linguistic Evidences
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abstract

The grammatical tools (the letters of meanings) are of great importance in understanding the meanings of the Arabic sentences,

This research is a simple attempt to show how our venerable scholars employed the meanings of these tools when they interpreted the linguistic evidence, that is, the grammatical structure largely depends on the tool in forming the meaning within the sentences and employing the meanings of these grammatical tools in explaining the linguistic evidence by clarifying their significance in the contexts of their use and effectiveness. Synthesis of the meanings of grammatical tools is an important tool in understanding the linguistic structure in order to reveal its meaning.

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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of The College Of Languages (jcl)
The Role of Gender and Culture in Dealing with the Arab Woman's Issues Embodied in Caricatures: A Cognitive Linguistic Analysis
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Gender and culture are among the factors that influence the process of understanding and interpreting different types of communication, especially images. The current study, which is a part of a master’s thesis, aims at investigating the role of gender and culture in interpreting and understanding the caricatures that deal with women’s issues in Arab societies. To this end, the researchers adopted Barthes’ (1957) concepts of denotation and connotation in his theory of mythologies in addition to Langacker’s (1987) theory of (Domains). The research concludes that the female subjects have better cognitive abilities in investing the signs within the selected caricatures. The other factor the study reached to is that the respondents

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Publication Date
Mon Mar 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Adsorptive Desulfurization of Iraqi Heavy Naphtha Using Different Metals over Nano Y Zeolite on Carbon Nanotube
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The present research was conducted to reduce the sulfur content of Iraqi heavy naphtha by adsorption using different metals oxides over Y-Zeolite. The Y-Zeolite was synthesized by a sol-gel technique. The average size of zeolite was 92.39 nm, surface area 558 m2/g, and pore volume 0.231 cm3/g. The metals of nickel, zinc, and copper were dispersed by an impregnation method to prepare Ni/HY, Zn/HY, Cu/HY, and Ni + Zn /HY catalysts for desulfurization. The adsorptive desulfurization was carried out in a batch mode at different operating conditions such as mixing time (10,15,30,60, and 600 min) and catalyst dosage (0.2,0.4,0.6,0.8,1, and 1.2 g). The most of the sulfur compounds were removed at 10 min for all catalyst ty

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