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ELEMENTS OF MARKETING MIX AND THEIR ROLE IN CONSUMER PERCEPTION OF BRAND IMAGE: A SURVEY OF SAMPLE OPINIONS FROM CONSUMERS OF ENIEM BRAND IN THE ALGERIAN MARKET.: ELEMENTS OF MARKETING MIX AND THEIR ROLE IN CONSUMER PERCEPTION OF BRAND IMAGE: A SURVEY OF SAMPLE OPINIONS FROM CONSUMERS OF ENIEM BRAND IN THE ALGERIAN MARKET.
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The current research aimed to analyze the importance, correlation and the effect of independent variables represented by marketing variables on the dependent variable represented by local brand, through taking ENIEM as a model for this study, which represents a sensitive sector for the Algerian consumer. The results of the study evinced that the Algerian consumer has a positive image toward the brand ENIEM given marketing variables which has acquired considerable importance to this consumer. Also, the results of this study showed a statistically significant correlation between marketing variables and good perception toward the brand ENIEM, at the same time, the existence of a statistically significant effect for each of these variables on the perception of this brand. The study is concluded to make recommendations and propose a model for marketing factors contribute to improving local brand image and the application requirements of this model.

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Fri Apr 30 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
SMS Spam Detection Based on Fuzzy Rules and Binary Particle Swarm Optimization
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Publication Date
Sun Oct 03 2021
Journal Name
Journal Of Interdisciplinary Mathematics
Fibrewise <i>ω</i>-compact and locally <i>ω</i>-compact spaces
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The goal of this article is to construct fibrewise w-compact (resp. locally w-compact) spaces. Some related results and properties of these concepts will be investigated. Furthermore, we investigate various relationships between these concepts and three classes of fibrewise w-separation axioms.

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Publication Date
Wed Mar 01 2023
Journal Name
Results In Engineering
Low-cost autonomous car level 2: Design and implementation for conventional vehicles
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Publication Date
Wed Jan 01 2014
Journal Name
Pharmacology &amp;amp; Pharmacy
Gift Acceptance and Its Effect on Prescribing Behavior among Iraqi Specialist Physicians
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Publication Date
Tue Feb 24 2026
Journal Name
Baghdad Science Journal
EEG Lossless Signal Compression Based on Magnitude Classification and Run Length Encoding
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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Crack Growth Behavior through Wall Pipes under Impact Load and Hygrothremal Environment
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This research concerns study the crack growth in the wall of pipes made of low carbon steel under the impact load and using the effect of hygrothermal (rate of moisture 50% and 50℃ temperature). The environmental conditions were controlled using high accuracy digital control with sensors. The pipe have a crack already. The test was performed and on two type of specimens, one have length of 100cm and other have length 50cm. The results were, when the humidity was applied to the pipe, the crack would enhance to growth (i.e. the number of cycles needed to growth the crack will reduce). In addition, when the temperature was increase the number of cycles needed to growth the crack are reduced because the effect of heat on the mechanical pro

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Publication Date
Sun Mar 01 2026
Journal Name
Journal Of Engineering
Bi-objective Machine Scheduling Using Enhanced Simulated Annealing and Bee Algorithm Approaches
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Many industrial systems involve multiple criteria and objectives, and they are very complex problems in computational science, such as task scheduling. We propose bi-criteria and bi-objective scheduling problems, which are solved by two nature-inspired evolutionary algorithms, such as Simulated Annealing (SA) and Bee Algorithm (BA). This problem is characterized by scheduling a batch of tasks on multiple machines, and it is fundamental because the solution should focus on the simultaneous optimization of two conflicting objectives: the makespan minimization and the total tardiness minimization. This problem is NP-Hard, and therefore, two evolutionary methods were used to search for solutions intelligently in this huge, very complex

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Publication Date
Sun May 14 2023
Journal Name
Agrosystems, Geosciences &amp; Environment
Cover crop and biofuel crop effects on hydraulic properties for claypan soils
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Perennial biofuel and cover crops systems are important for enhancing soil health and can provide numerous soil, agricultural, and environmental benefits. The study objective was to investigate the effects of cover crops and biofuel crops on soil hydraulic properties relative to traditional management for claypan soils. The study site included selected management practices: cover crop (CC) and no cover crop (NC) with corn/soybean rotation, switchgrass (SW), and miscanthus (MI). The CC mixture consisted of cereal rye, hairy vetch, and Austrian winter pea. The research site was located at Bradford Research Center in Missouri, USA, and was implemented on a Mexico silt loam. Intact soil cores (76‐mm diam. by 76‐mm long) were taken from the

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Publication Date
Wed Aug 05 2026
Journal Name
Technology In Agronomy
Modeling wheat harvest index using stacking ensemble learning and seeder operational parameters
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