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A Decision Modeling Approach for Data Acquisition Systems of the Vehicle Industry Based on Interval-Valued Linear Diophantine Fuzzy Set
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Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide membership and nonmembership degrees freely, simulate real-world ambiguity efficiently, utilize a narrow fuzzy number space, and deal with interval data. Thus, this study used a more efficient fuzzy environment interval-valued linear Diophantine fuzzy set (IVLDF) with FWZIC II for criterion weighting and IVLDF with FDOSM for DAS modeling to address the issues and support industrial community characteristics in the design and implementation of advanced driver assistance systems in vehicles. The proposed methodology comprises two consecutive phases. The first phase involves adapting a decision matrix that intersects DAS alternatives and criteria. The second phase (development phase) proposes a decision modeling approach based on formulation of IVLD-FWZIC II and IVLD-FDOSM II to model DASs. A total of 14 DASs were modeled on the basis of 15 DAS criteria, including seven subcriteria for “comprehensive complexity assessment” and eight subcriteria for “design and implementation,” which had a remarkable effect on the DAS design when implemented by industrial communities. Systematic ranking, sensitivity analysis, and modeling checklists were conducted to demonstrate that the modeling results were subject to systematic ranking, as indicated by the high correlations across all described scenarios of changing criterion weight values, supporting the most important research points, and proposing a value-adding process in modeling the most desirable DAS.

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Publication Date
Mon Oct 01 2018
Journal Name
Ieee Transactions On Network Science And Engineering
A Resource Allocation Mechanism for Cloud Radio Access Network Based on Cell Differentiation and Integration Concept
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Publication Date
Thu Dec 24 2020
Journal Name
Psychology And Education
A Proposed Programme Based On Sensory Integration Theory For Remediating Some Development Learning Disabilities Among Children
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The current research aims to prepare a proposed Programmebased sensory integration theory for remediating some developmental learning disabilities among children, researchers prepared a Programme based on sensory integration through reviewing studies related to the research topic that can be practicedby some active teaching strategies (cooperative learning, peer learning, Role-playing, and educational stories). The Finalformat consists of(39) training sessions.

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Generalizations of Fuzzy k-ideals in a KU-algebra with Semigroup
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Abstract<p>We present the notion of bipolar fuzzy k-ideals with thresholds (<italic>θ, λ</italic>) of a KU-algebra with semigroup and give some basic properties of this ideal. Also, we study some relations about a bipolar fuzzy k-ideal with thresholds (<italic>θ, λ</italic>) and a k-ideal of a KU-semigroup.</p>
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

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Publication Date
Tue Oct 11 2022
Journal Name
College Of Islamic Sciences
Modeling strategy in the subject of recitation provisions for students of Islamic sciences colleges
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on the subject of the provisions of recitation among students of the Islamic Sciences Colleges).

The researchers adopted the experimental method and chose an experimental design for the two equivalent groups by post-test. The research sample consisted of (60) male and female students from (second stage) - Department of Qur’an Sciences and Islamic Education - University of Diyala, and the two researchers were rewarded between the two groups of research in the following variables: (Chronological age calculated in months, degrees of recitation rulings subject in the previous year, the two researchers studied the same research groups, and lasted for an entire semester, the researchers prepared the observation card to measure the ru

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Publication Date
Mon Nov 01 2021
Journal Name
International Journal Of Hydrogen Energy
Experimental study on combustion stability and performance of hydrogen-enriched compressed natural gas of a free-piston linear generator
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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Applying some hybrid models for modeling bivariate time series assuming different distributions for random error with a practical application
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Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
A general solution of some linear partial differential equations via two integral transforms
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In this paper, a new analytical method is introduced to find the general solution of linear partial differential equations. In this method, each Laplace transform (LT) and Sumudu transform (ST) is used independently along with canonical coordinates. The strength of this method is that it is easy to implement and does not require initial conditions.

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