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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
Mon Dec 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Enhanced conversion of Glycerol to Glycerol carbonate on modified Bio-Char from reed plant: Enhanced conversion of Glycerol to Glycerol carbonate on modified Bio-Char from reed plant
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The surplus glycerol produced from biodiesel production process as a by-product with high quantity can be considered as a good source to prepare glycerol carbonate (GC) whereas with each 1000 kg from biodiesel obtains 100 kg from glycerol. Glycerol converted to glycerol carbonate over bio-char as a catalyst prepared by slow pyrolysis process under various temperatures from 400 ᴼC to 800 ᴼC. The char prepared at 700 ᴼC considered as a best one between the others which was manufactured to activate the transesterification reaction. GC have large scale of uses such as liquid membrane in gas separation, surfactants ,detergents , blowing agent , in plastics industry, in  Pharmaceutical industry and electrolytes in lithium batteries.

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Publication Date
Mon Jan 28 2019
Journal Name
Soft Computing
Bio-inspired multi-objective algorithms for connected set K-covers problem in wireless sensor networks
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Publication Date
Tue Jun 03 2025
Journal Name
Journal Of Umm Al-qura University For Applied Sciences
Application of Benesi–Hildebrand and Tauc approaches of new synthesized Schiff bases interacted with two types of electron acceptors modules
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This study has three parts, the first one is the synthesis of a novel Schiff bases by the condensation of guanine or 9-[{2-hydroxyethoxy}methyl]-9H-guanine with variety aldehydes to yield four different bases as follows: (E)-2-((4-nitrobenzylidene)amino)-1,9-dihydro-6H-purin-6-one (S1), (E)-2-((4-methoxybenzylidene)amino)-1,9-dihydro-6H-purin-6-one (S2), (E)-2-((2-hydroxybenzylidene) amino)-9-((2-hydroxy ethoxy)methyl)-1,9-dihydro-6H-purin-6-one (S3), and (E)-2-(((9-((2-hydroxy ethoxy)methyl)-6-oxo-6,9-dihydro-1H-purin-2-yl)imino)methyl)benzoic acid (S4). Then, spectroscopic analyses such as Elemental Analysis, UV/VIS, Mass spectra, FTIR, 1H,13C-NMR were made to recognize these bases. In the second part, the ability of synthesized bases to

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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
BotDetectorFW: an optimized botnet detection framework based on five features-distance measures supported by comparisons of four machine learning classifiers using CICIDS2017 dataset
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<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation

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Publication Date
Wed Jun 04 2025
Journal Name
Engineering, Technology &amp; Applied Science Research
Evaluation of the Accuracy of Machine Learning Classifiers and Spectral Indices in Land Cover Classification
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Population growth and economic and industrial development coupled have significantly accelerated the rate of Land Use and Land Cover (LULC) changes, particularly in developing countries, so finding optimum ways to observe these change has become a pressing issue. Quantification evaluation of these changes is crucial to comprehend and oversee land management conversion, therefore, it is necessary to evaluate the accuracy of various algorithms for LULC classification to determine the most effective classifier for Earth observation applications. The performance of Maximum Likelihood (ML), Support Vector Machines (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN) was examined in this study, based on Sentinel 2A satellite images. T

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Publication Date
Mon Apr 07 2025
Journal Name
Al-nahrain Journal For Engineering Sciences
Navigating the Challenges and Opportunities of Tiny Deep Learning and Tiny Machine Learning in Lung Cancer Identification
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Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio

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Publication Date
Sun Dec 01 2024
Journal Name
Al-qadisiyah Journal For Agriculture Sciences
Effect of Holes Diameter and Speed of Die on the Performance of Machine and Feed Pellet Quality
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The aim of this study to evaluate the effects of die holes diameter and speed of die on the performance of machine and feed pellet quality. Machine productivity (Kg.h-1), consumed power (kW), pellet durability (%) and pellet bulk density (g.cm-3) was studied. The study factors consisted of three diameter of die holes (3, 4, and 5 mm), and three speeds die (280, 300, and 320 rpm). Results showed with increasing of die holes diameter from 3 to 4 and to 5 mm give a significant increase in machine productivity, while consumed power, pellet durability and pellet bulk density a significant decreased. By increasing the die speed, from 280 to 300 then to 320 rpm, the machine productivity increased significantly, while consumed power, pellet durabil

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Quick Response Manufacturing (QRM) and Impacts on the Scheduling Operations Applied Research in the general company for vegetable oil product/ Al-Farab factory
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He research specifies subjects which may contribute in improve productivity of the General Company for vegetable oil product/ Al-Farab factory and aims to release the relationship between system Quick Response Manufacturing (QRM) and scheduling operations.

The Implementation was in the general company for vegetable oil product (Al-Farab factory), Universe Factory It suffers from a failure to follow Scheduling in its operations And not taking into account the lead times And delays in product delivery dates, Here are drawing the attention of the administration in the factory to use Quick Response Manufacturing (QRM) to control the energy and inventory, machin

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Publication Date
Sat Jan 24 2026
Journal Name
Arab World English Journal
AI in Literary and Non-Literary Discourse: A Systematic Review of Human and Machine Authorship, and Style and Perception
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Artificial intelligence has quickly invaded the realms of both creative and information-based writing, raising new questions about human originality, authorship and style. Despite its ability to produce writings that are coherent and stylistically varied, there are still concerns over the uniqueness and cultural neutrality of AI programs such as ChatGPT. This review covers significant recent advancements with artificial intelligence applications in both the literary and non-literary fields. It analyzes 35 recent studies contrasting authorship and creativity, or stylistic considerations and impressions, between human and AI texts. These studies range from poetic and fictional writing through essay, news article and academic publicati

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Publication Date
Thu Jan 20 2022
Journal Name
Webology
Hybrid Intrusion Detection System based on DNA Encoding, Teiresias Algorithm and Clustering Method
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Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

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