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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 space. In this research, A mathematical model of the scheduling problem was developed based on the above objectives. Here, we proposed a tailored tune-up of SA and BA, both of which have been specifically developed and implemented to solve the proposed model for integrated scheduling and delivery, geared for the bifunctional nature of the problem. Quantitative results indicate that the Bee Algorithm (BA) achieves a more diverse Pareto front, with an average improvement of approximately 12–18 % in solution diversity compared to Simulated Annealing (SA). In contrast, SA converges faster, reducing computational time by about 30–40 % for large problem instances (n ≥ 80). Overall, BA provides better trade-offs between objectives, while SA offers superior computational efficiency. The results showed that both algorithms can generate solutions that are balanced and time-efficient.

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Publication Date
Wed Jan 01 2014
Journal Name
Journal Of Thi – Qar Science
Enhanced of the Two photon Absorption in Nanostructure Wide Band gap Semiconductor CdS using femtosecond Laser
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We observed strong nonlinear absorption in the CdS nanoparticles of dimension in the range 50-100 nm when irradiant with femtosecond pulsed laser at 800 nm and 120 GW/cm 2 irradiance intensity. The repetition rate and average power were 250 kHz and

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Publication Date
Sat Feb 08 2014
Journal Name
Reaction Kinetics, Mechanisms And Catalysis
Kinetic and mathematical approaches to the corrosion of mild steel in nitric acid
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Publication Date
Wed Mar 08 2023
Journal Name
Sensors
A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

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Publication Date
Fri Jun 30 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Enhanced Prosthesis Control Through Improved Shoulder Girdle Motion Recognition Using Time-Dependent Power Spectrum Descriptors and Long Short-Term Memory
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Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class

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Publication Date
Mon Apr 20 2026
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Preparation and Annealing Effects on the Structural and Optical Properties of ZnTe Thin Film
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ZnTe possesses the proper optoelectronic properties as a candidate for device development. The structure and optical properties of ZnTe semiconductor thin films of 500 nm were studied using thermal evaporation technique. The influence of annealing temperatures on ZnTe thin films in the range ( R.T - 473 K). XRD and surface morphological analyses are used to examine the films. The ZnTe films are comparatively polycrystalline and cubic in phase, according to the XRD analysis. with a lattice constant of 0.61 nm upon an (111) orientation. The intensities of all the peaks rapidly increase though they show the same tendencies; it shows the crystallinity of the films becomes higher crystal size diameters (from 8.41 to 12.18nm) both increas

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Publication Date
Mon Jan 20 2025
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Assessing Landsat Processing Levels and Support Vector Machine Classification
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The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Laboratory Preparation of Simulated Sludge for Anaerobic Digestion Experimentation
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Health and environmental factors as well as operational difficulties are major challenges facing the development of an anaerobic digestion process. Some of these problems relate to the use of sludge collected from primary and secondary clarifier units in wastewater treatment plants for laboratory purposes.

The present study addresses the preparation of sludge for laboratory purposes by using a mixture that consists of the digested sludge, which is less pathogenic, compared to the collected sludge from the primary or secondary clarifier, and food wastes. The sludge has been tested experimentally for 19 and 32 days under mesophilic conditions. The results show a steady methane production rate from the anaerobic dig

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Publication Date
Tue Dec 01 2009
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
HUNTING BEHAVIOR OF THE ORIENTAL HORNET, VESPA ORIENTALIS L., AND DEFENSE BEHAVIOR OF THE HONEY BEE, Apis mellifera L., IN IRAQ
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When the guard honey bees, Apis mellifera L., form a clump at the hive entrance or on the flight board, the oriental hornet, Vespa orientails L., either creeps toward the clump or hovers over it in order to take a bee. Once the hornet creeps, only few bees facing the hornet become alert, rock their heads and antennae, open their wings, and take a posture of defense. The rest of the clump stays listless without any signal of concern. However, the clump stays dense and the defending bees do not detach themselves neither from the rest of the clump nor from each other. For this reason, it is very difficult for the hornet to grab a bee unless the latter makes a “mistake” by detaching herself from other adjacent bees. If the hornet grabs s

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Publication Date
Wed May 09 2018
Journal Name
International Journal Of Advanced Computer Science And Applications
New Techniques to Enhance Data Deduplication using Content based-TTTD Chunking Algorithm
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Publication Date
Wed Jan 15 2003
Journal Name
كلية الترا ث الجامعة
Estimating an Exponentiated Expanded Power Function Distribution Using an Artificial Intelligence Algorithm
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The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.