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jih-1817
Local Search Algorithms for Multi-criteria Single Machine Scheduling Problem
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   Real life scheduling problems require the decision maker to consider a number of criteria before arriving at any decision. In this paper, we consider the multi-criteria scheduling problem of n jobs on single machine to minimize a function of five criteria denoted by total completion times (∑), total tardiness (∑), total earliness (∑), maximum tardiness () and maximum earliness (). The single machine total tardiness problem and total earliness problem are already NP-hard, so the considered problem is strongly NP-hard.

We apply two local search algorithms (LSAs) descent method (DM) and simulated annealing method (SM) for the 1// (∑∑∑) problem (SP) to find near optimal solutions. The local search methods are used to speed up the process of finding a good enough solution, where an exhaustive search is impractical for the exact solution. The two heuristic (DM and SM) were compared with the branch and bound (BAB) algorithm in order to evaluate effectiveness of the solution methods.

            Some experimental results are presented to show the applicability of the (BAB) algorithm and (LSAs). With a reasonable time, (LSAs) may solve the problem (SP) up to 5000 jobs.

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Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning
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Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Networks And Systems
Using Machine Learning to Control Congestion in SDN: A Review
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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Mechanical Engineering
Process Parameters Optimization in Single Point Incremental Forming Of Al1050
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This work aims to optimize surface roughness, wall angle deviation, and average wall thickness as output responses of ALuminium-1050 alloy cone formed by the single point incremental sheet metal forming process. The experiments are accomplished based on the use of a mixed level Taguchi experimental design with an L18 orthogonal array. Six levels of step depth, three levels of tool diameter, feed rate, and tool rotational speed have been considered as input process parameters. The analyses of variance (ANOVA) have been used to investigate the significance of parameters and the effect of their levels for minimum surface roughness, minimum wall angle deviation, and maximum average wall thickness. The results indicate that step depth and tool r

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Gamipog: A deterministic genetic multi-parameter-order strategy for the generation of variabLE STRENGTH COVERING ARRAYS
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Publication Date
Wed Nov 17 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Pearson coefficient matrix for studying the correlation of community detection scores in multi-objective evolutionary algorithm
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Publication Date
Thu Nov 01 2018
Journal Name
International Journal Of Biomathematics
A non-conventional hybrid numerical approach with multi-dimensional random sampling for cocaine abuse in Spain
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This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

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Publication Date
Sun Jan 03 2016
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Coronary Artery Spasm; Frequency and Angiographic Findings in the Iraqi center for heart diseases (Single Centre experience)
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Background: Coronary artery spasm occurs spontaneously leading to the syndrome of variant angina. It occurs in about 15 % of patients undergoing coronary angiography.
Objectives: This study sought to estimate the rate of coronary artery spasm that occurs during coronary angiography and percutaneous coronary intervention with their risk factors in patients admitted to the Iraqi center for heart disease.
Methods: This is a cross sectional observational study, We prospectively collected the data of patients over six months period (from August 2014 till February 2015 ) who developed coronary artery spasm during cardiac catheterization (diagnostic and therapeutic).
Results: Out of 1274 patients, 106 patients developed coronary artery

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Publication Date
Thu Feb 21 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Reality of Environmental Pollution and The Use of Environmental Taxes to Limit It: Analytical Search for Diesel Generators in Governorate of Baghdad
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The research depth and dimensions of the problem of environmental pollution resulting from the combustion of fuel used in electric power generators, especially in the summer and you are the national electric power supplied by almost non-existent state where this problem is a local phenomenon that has serious dimensions to human health, as well as the possibility of using a the tax system tools of b (environmental taxes) to reduce these pollutants, so the search is aimed at the types of gases emitted from burning fuel electric generators operating in the province of Baghdad and then measure the amount of environmental pollution as well as compared to the amount of some of these gases, which is more risk to humans with permitted by the Wor

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Developing the Complexity and Security of the Twofish Algorithm Through a New Key Scheduling Design
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     The Twofish cipher is a very powerful algorithm with a fairly complex structure that permeates most data parsing and switching and can be easily implemented. The keys of the Twofish algorithm are of variable length (128, 192, or 256 bits), and the key schedule is generated once and repeated in encrypting all message blocks, whatever their number, and this reduces the confidentiality of encryption. This article discusses the process of generating cipher keys for each block. This concept is new and unknown in all common block cipher algorithms. It is based on the permanent generation of sub keys for all blocks and the key generation process, each according to its work. The Geffe's Generator is used to generate subkeys to make eac

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