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jeasiq-1816
The impact of social audit in social performance an applied study of the views of a sample of managers and staff of Algerian business organizations
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            This research aims at clarifying the concept of social auditing, which is one of the most important reasons for its emergence is social responsibility accounting and its role in measuring the social performance of enterprises. The study also aimed to know how social auditing has an impact and its role in improving the social performance of business organizations, and the research refers to testing the hypotheses of an impact of social auditing on social performance through a commitment to social responsibility. The research sample consisted of 200 individuals from 20 Algerian business organizations and represented individuals who were researched in managers and employees of these organizations, and to achieve research objectives the survey was a tool for collecting information and relying on the partial micro squares method using the PLSPM package in the programming of the R. The results of the field study showed that there is interest on the part of Algerian organizations in social scrutiny by improving its social performance, despite its lack of practice, it is necessary to take care of the subject of social scrutiny by scientific and professional organizations in Algeria by teaching it at the universities and relevant institutes and encouraging research on the subject.

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Publication Date
Thu Sep 23 2021
Journal Name
Egyptian Journal Of Chemistry
Some 3,4,5-Trisubstituted-1,2,4-triazole Synthesis, Antimicrobial Activity, and Molecular Docking Studies
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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
Thu Feb 16 2017
Journal Name
Signal, Image And Video Processing
Enhancing Prony’s method by nuclear norm penalization and extension to missing data
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Publication Date
Sun Sep 01 2013
Journal Name
2013 Ieee International Conference On Circuits And Systems (iccas)
Improved undetected error probability model for JTEC and JTEC-SQED coding schemes
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The undetected error probability is an important measure to assess the communication reliability provided by any error coding scheme. Two error coding schemes namely, Joint crosstalk avoidance and Triple Error Correction (JTEC) and JTEC with Simultaneous Quadruple Error Detection (JTEC-SQED), provide both crosstalk reduction and multi-bit error correction/detection features. The available undetected error probability model yields an upper bound value which does not give accurate estimation on the reliability provided. This paper presents an improved mathematical model to estimate the undetected error probability of these two joint coding schemes. According to the decoding algorithm the errors are classified into patterns and their decoding

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Publication Date
Mon Apr 20 2026
Journal Name
Baghdad Science Journal
Approximate Solution and Simulation for Fractional Burger Equation with Two Initial Conditions
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This paper considers the nonlinear homogeneous fractional Burger's equation as a type of nonlinear fractional partial differential equations (FPDE). Our goal in this paper is to show that an initial value problem (IVP) can be modified with a second initial condition when (α ∈ ( 1,2 ]) as the velocity of the movement, and the obtained solution agrees with the nature of the wave with space and time for the problem. The Caputo fractional derivative is used in all the fractional derivatives. Also, the algorithm of the Laplace transform decomposition method (LTDM) for fractional PDEs is presented. The approximate solution converges to the exact solution in Theorem 1. Also, a numerical simulation is made to confirm the theoretical resu

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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
Mon Apr 19 2021
Journal Name
Iraqi Journal Of Agricultural Sciences
TETRACYCLINE ANTIBIOTIC REMOVAL FROM AQUEOUS SOLUTION USING CLADOPHORA AND SPIRULINA ALGAE BIOMASS
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Cladophora and Spirulina algae biomass have been used for the removal of Tetracycline (TC) antibiotic from aqueous solution. Different operation conditions were varied in batch process, such as initial antibiotic concentration, different biomass dosage and type, contact time, agitation speed, and initial pH. The result showed that the maximum removal efficiencies by using 1.25 g/100 ml Cladophora and 0.5 g/100 ml Spirulina algae biomass were 95% and 94% respectively. At the optimum experimental condition of temperature 25°C, initial TC concentration 50 mg/l, contact time 2.5hr, agitation speed 200 rpm and pH 6.5. The characterization of Cladophora and Spirulina biomass by Fourier transform infrared (FTIR) indicates that the presenc

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Publication Date
Fri Jul 01 2016
Journal Name
Composite Structures
Bond behaviour between CFRP laminates and steel members under different loading rates
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Carbon fibre reinforced polymers are widely used to strengthen steel structural elements. These structural elements are normally subjected to static, dynamic and fatigue loadings during their life-time. A number of studies have focused on the characteristics of CFRP sheets bonded to steel members under static, dynamic and fatigue loadings. However, there is a gap in understanding the bonding behaviour between CFRP laminates and steel members under impact loading. This paper shows the effect of different load rates from quasi-static to 300 × 103 mm/min on this bond. Two types of CFRP laminate, CFK 150/2000 and CFK 200/2000, were used to strengthen steel joints using Araldite 420 epoxy. The results show a significant bond strength enhancemen

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Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Molecular Structure
Asymmetric 1,3,4-thiadiazole derivatives: Synthesis, characterization and studying their liquid crystalline properties
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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Human Face Recognition Based on Local Ternary Pattern and Singular Value Decomposition
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There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

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