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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
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches
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Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Proposed Security Models for Node-level and Network-level Aspects of Wireless Sensor Networks Using Machine Learning Techniques
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     As a result of the pandemic crisis and the shift to digitization, cyber-attacks are at an all-time high in the modern day despite good technological advancement. The use of wireless sensor networks (WSNs) is an indicator of technical advancement in most industries. For the safe transfer of data, security objectives such as confidentiality, integrity, and availability must be maintained. The security features of WSN are split into node level and network level. For the node level, a proactive strategy using deep learning /machine learning techniques is suggested. The primary benefit of this proactive approach is that it foresees the cyber-attack before it is launched, allowing for damage mitigation. A cryptography algorithm is put

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Publication Date
Mon Jan 01 2024
Journal Name
2nd International Conference For Engineering Sciences And Information Technology (esit 2022): Esit2022 Conference Proceedings
Numerical solution to inverse coefficient problem for hyperbolic equation under overspecified condition of general integral type
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
A comparison among Different Methods for Estimating Regression Parameters with Autocorrelation Problem under Exponentially Distributed Error
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Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
A Linear Programming Method Based Optimal Power Flow Problem for Iraqi Extra High Voltage Grid (EHV)
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The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost, loss etc. while maintaining an acceptable system performance in terms of limits on generators real and reactive powers, line flow limits etc. The OPF solution includes an objective function. A common objective function concerns the active power generation cost. A Linear programming method is proposed to solve the OPF problem. The Linear Programming (LP) approach transforms the nonlinear optimization problem into an iterative algorithm that in each iteration solves a linear optimization problem resulting from linearization both the objective function and constrains. A computer program, written in MATLAB environme

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Publication Date
Tue Oct 02 2018
Journal Name
Iraqi Journal Of Physics
The efficiency calibration for local manufacturing gamma scanning systems of radioactive waste drums
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The Local manufacturing scanning gamma system designed in Tuwaitha site for nondestructive assay method of radioactive waste drums, where it consist of two main parts with their belongings for controlling the of detector and drum movements up-down and rotation respectively. The volume of the used drum is 220 L with 85 cm height. The drum filled with Portland cement. Six cylindrical holes were made within cement drum and distributed in radial arrangement.The152Eu source inserted in these holes individually, to measure the average angular count rate of gamma radiation. The full energy efficiency value for geometry of drum and detector is computed for thirteen photo peaks. The average efficiency represented by the curve of these peaks indic

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Publication Date
Mon Dec 28 2020
Journal Name
Journal Of Physical Education
The Effect of Self Scheduling Strategy Using Competitive Style in Learning Short and Long Passes in Handball for 2nd Grade Secondary School Students
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The research aimed at designing teaching sessions using the self-scheduling strategy with a competitive style in learning handball as well as identifying differences between pre and post tests in both groups in learning short and long passes in handball. The researchers used the experimental method on 2nd-grade secondary school students. The researchers concluded using the self-scheduling strategy due to its positive effect on learning short and long handball passes in handball. Finally, the researchers recommended applying strategies and styles in teaching different school levels as well as making similar studies using teaching strategies and styles for learning handball skills in students.

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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 01 2022
Journal Name
Proceedings Of International Conference On Computing And Communication Networks
Automatic Health Speech Prediction System Using Support Vector Machine
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Publication Date
Mon Jan 27 2020
Journal Name
Iraqi Journal Of Science
Sentiment Analysis in Social Media using Machine Learning Techniques
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Over the last period, social media achieved a widespread use worldwide where the statistics indicate that more than three billion people are on social media, leading to large quantities of data online. To analyze these large quantities of data, a special classification method known as sentiment analysis, is used. This paper presents a new sentiment analysis system based on machine learning techniques, which aims to create a process to extract the polarity from social media texts. By using machine learning techniques, sentiment analysis achieved a great success around the world. This paper investigates this topic and proposes a sentiment analysis system built on Bayesian Rough Decision Tree (BRDT) algorithm. The experimental results show

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