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A plan for transportation and distribution the products based on multi-objective travelling salesman problem in fuzzy environmental
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Transportation and distribution are the most important elements in the work system for any company, which are of great importance in the success of the chain work. Al-Rabee factory is one of the largest ice cream factories in Iraq and it is considered one of the most productive and diversified factories with products where its products cover most areas of the capital Baghdad, however, it lacks a distribution system based on scientific and mathematical methods to work in the transportation and distribution processes, moreover, these processes need a set of important data that cannot in any way be separated from the reality of fuzziness industrial environment in Iraq, which led to use the fuzzy sets theory to reduce the levels of uncertainty. The decision-maker has several goals that he aspires to accomplish for two stages, so, the decision-maker adopted in his work system on a multi-objective travelling salesman problem. A network of paths for transportation and distribution of the products has been designed based on a multi-objective travelling salesman problem, by building a mathematical model that finds the best paths for each stage, taking into account the goals required by the decision-maker. The results obtained from the use of (Lingo) software showed the importance of these methods in determining the optimal path for the processes of collecting and transporting milk from their collection centers to the Al-Rabee factory as a first stage, as well as transporting the final products and distributing them from the Al-Rabee factory to the shopping centers as a second stage.

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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Emotion Recognition System Based on Hybrid Techniques
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Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

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Publication Date
Thu Feb 28 2019
Journal Name
Multimedia Tools And Applications
Shot boundary detection based on orthogonal polynomial
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Publication Date
Thu Jul 01 2021
Journal Name
Energy
Experimental investigations of the performance of a flat-plate solar collector using carbon and metal oxides based nanofluids
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Publication Date
Fri Oct 01 2021
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
The Use of Logistic Regression Model in Estimating the Probability of Being Affected By Breast Cancer Based On the Levels of Interleukins and Cancer Marker CA15-3
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Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased o

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation
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Publication Date
Sun Mar 01 2020
Journal Name
Materials Research Express
Spray pyrolysis of graphene oxide based composite for optical and wettability applications
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Abstract<p>In this study, silica-graphene oxide nano–composites were prepared by sol-gel technique and deposited by spray pyrolysis method on glass substrate. The effect of changing the graphene/silica ratio on the optical properties and wetting of these nano–structures has been investigated. The structural and morphological properties of the thin films have been studied by x-ray diffraction spectroscopy (XRD), field emission scanning electron microscope (FESEM), energy dispersive x-ray spectroscopy (EDS) and atomic force microscope (AFM). XRD results show that silica structures present in the synthesized films exhibit amorphous character and there is a poor arrangement in graphene plates al</p> ... Show More
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Publication Date
Tue Jul 11 2023
Journal Name
Journal Of Educational And Psychological Researches
Functional Engagement and Its Relationship to Hope-Based Thinking for Kindergarten Teachers
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The research aims to identify the level of functional engagement and hope-based thinking of kindergarten teachers, identify if there is a significant difference in functional engagement and hope-based thinking in terms of specialization and years of service for kindergarten teachers, identify if there is a significant correlation between functional engagement and hope-based thinking of kindergarten teachers. The current research is determined by kindergarten teachers in the Second Rusafa Baghdad Education Directorate for the academic year (2022-2023). In order to achieve the objectives of the research, the researcher prepared a functional engagement scale, which consists of (45) items in three areas: Perceptual and functional engagement

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Publication Date
Sun Oct 04 2026
Journal Name
Journal Of Engineering
Design and Implementation of ICT-Based Recycle-Rewarding System for Green Environment
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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

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Publication Date
Wed Jul 30 2025
Journal Name
International Studies
A Paradigm Shift for the Middle East: How Trump Can Build on Israel’s Success and Keep Iran Off Balance
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