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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
Sun Jan 01 2023
Journal Name
Journal Of Molecular Liquids
Theoretical modeling study on preparation of nanosized drugs using supercritical-based processing: Determination of solubility of Chlorothiazide in supercritical carbon dioxide
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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Optimization Algorithms Based on Path Planning and Neural Controller for Mobile Robot
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

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Publication Date
Tue Jan 03 2023
Journal Name
College Of Islamic Sciences
Ruling on selling big data (Authentical Fiqh Study): Ruling on selling big data (Authentical Fiqh Study)
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Abstract:

Research Topic: Ruling on the sale of big data

Its objectives: a statement of what it is, importance, source and governance.

The methodology of the curriculum is inductive, comparative and critical

One of the most important results: it is not permissible to attack it and it is a valuable money, and it is permissible to sell big data as long as it does not contain data to users who are not satisfied with selling it

 Recommendation: Follow-up of studies dealing with the provisions of the issue

Subject Terms

Judgment, Sale, Data, Mega, Sayings, Jurists

 

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Publication Date
Thu Jul 01 2021
Journal Name
Journal Of Engineering
Proposed Security Framework for Mobile Data Management System
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Portable devices such as smartphones, tablet PCs, and PDAs are a useful combination of hardware and software turned toward the mobile workers. While they present the ability to review documents, communicate via electronic mail,  appointments management, meetings, etc. They usually lack a variety of essential security features. To address the security concerns of sensitive data, many individuals and organizations, knowing the associated threats mitigate them through improving authentication of users, encryption of content, protection from malware, firewalls,  intrusion prevention, etc. However, no standards have been developed yet to determine whether such mobile data management systems adequately provide the fu

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Publication Date
Sat Sep 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Role of Tourism Industry in the Developing of Economie to Iraq for (1990- 2009)
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The Developing economies of countries have witnessed essential changes to words the development of tourism industry in the 21st century . in addition to adopting same of policies and strategies to grow up with the tourism sector to make it one of the important economic sector to compete the tourist cal  developments in the wear .

As for the tourism sector in Iraq ,it's still afresh one , has many of elements which can be in vested ,needs a wide strategies of tourist cal in statutes and variety completive services and change of success for the locale and forgin investor ,the essential aim after this research is to prompt the national economic through the tourism industry and making concisen

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Publication Date
Tue Nov 06 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Factors Affecting Birth Space Interval of Women Who Are Attending Primary Health Care Centers
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Objective: The aim of this study is to determine the factors affecting birth space interval in a sample of women.
Methodology: A cross-sectional study conducted in primary health centers in Al-Tahade and Al- Shak Omar in
Baghdad city. Data were collected by direct interview using questionnaire especially prepared for the study.
Sample size was (415) women in age group (20-40) years who were chosen randomly.
Results: Analysis of data shows highest rate of women (31.8%) had a birth space interval of (8-12) months
followed by (26.7%) had a birth space interval of (19-24) months, (20.2%) had a birth space interval of (>24)
months and (16.1%) had a birth space interval of (13-18) months respectively, while lower rate of w

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
An approximate solution for solving linear system of integral equation with application on "Stiff" problems
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An approximate solution of the liner system of ntegral cquations fot both fredholm(SFIEs)and Volterra(SIES)types has been derived using taylor series expansion.The solusion is essentailly

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Publication Date
Tue Sep 09 2014
Journal Name
Iosr Journal Of Mathematics (iosr-jm)
An Efficient Shrinkage Estimator for the Parameters of Simple Linear Regression Model
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