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Publication Date

Mon Apr 30 2018

Journal Name

Journal Of Theoretical And Applied Information Technology

Volume

96

Issue Number

8

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An efficient artificial fish swarm algorithm with harmony search for scheduling in flexible job-shop problem

Artificial Fish Swarm Algorithm

Harmony Search

Makespan

Flexible Job-Shop SchedulingProblem

Faeq I.F.

MEHDI G. DUAIMI

AHMED T. SADIQ AL-OBAIDI

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Flexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best solution. When it is the better one, it replaces with the artificial fish swarm solution from which this solution was improvised. Meanwhile the best improvised solutions are carried over to the Harmony Memory. The objective is to minimize a total completion time (makespan) and to make the proposed approach as a portion of the expert and the intelligent scheduling system for remanufacturing decision support. Harmony search algorithm has demonstrated to be efficient, simple and strong optimization algorithm. The ability of exploration in any optimization algorithm is one of the key points. The obtained optimization results show that the proposed algorithm provides better exploitation ability and enjoys fast convergence to the optimum solution. As well, comparisons with the original artificial fish swarm algorithm demonstrate improved efficiency.

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Publication Date

Tue Jun 01 2021

Journal Name

Iop Conference Series: Earth And Environmental Science

Performance Evaluation of Al-Karkh Water Treatment Plant Using Model-driven and Data-Driven Models

Operational performance evaluation

water treatment plant

multiple linear regression

multivariate multiple regression

artificial neural network model

model-driven and data-driven modeling types.

Basim Hussein

Awatif Soaded

Basim H.

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Abstract<p>There is a great operational risk to control the day-to-day management in water treatment plants, so water companies are looking for solutions to predict how the treatment processes may be improved due to the increased pressure to remain competitive. This study focused on the mathematical modeling of water treatment processes with the primary motivation to provide tools that can be used to predict the performance of the treatment to enable better control of uncertainty and risk. This research included choosing the most important variables affecting quality standards using the correlation test. According to this test, it was found that the important parameters of raw water: Total Hardn</p> ... Show More

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Publication Date

Tue Aug 10 2021

Journal Name

Design Engineering

Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri

Image compression

Convolutional Autoencoder (CAE)

k-mean algorithm

PSNR

Compression Rate (CR)

MSE

Clustering

CLIC

Kodak

deep learning

lossy

Mohammed

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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

Publication Date

Thu Nov 29 2018

Journal Name

Iraqi Journal Of Science

Improving Extractive Multi-Document Text Summarization Through Multi-Objective Optimization

Multi-objective optimization

multi-objective multi-document text summarization problem

MOO

multi-objective evolutionary algorithm

non-dominated solution

EP

Nasreen J.

Hilal H.

Bara’a

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Multi-document summarization is an optimization problem demanding optimization of more than one objective function simultaneously. The proposed work regards balancing of the two significant objectives: content coverage and diversity when generating summaries from a collection of text documents.

Any automatic text summarization system has the challenge of producing high quality summary. Despite the existing efforts on designing and evaluating the performance of many text summarization techniques, their formulations lack the introduction of any model that can give an explicit representation of – coverage and diversity – the two contradictory semantics of any summary. In this work, the design of

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Publication Date

Sat Jan 01 2022

Journal Name

Turkish Journal Of Physiotherapy And Rehabilitation

classification coco dataset using machine learning algorithms

learning Machine

classification

MCOCO dataset

K Nearest Neighbor's

Stochastic Gradient Descent learning (SGD)

Logistic Regression Algorithm(LR)

and Multi-Layer Perceptron (MLP).

Rasool

Bushra

Raaid

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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

Publication Date

Wed Jun 01 2022

Journal Name

Journal Of Engineering

The Design and Simulation of a Novel Optical Adder Depending on Optical Tri-state Gates

The Basic Arithmetic Unit(BAU)

Optic Gates with Three States

Binary Signed Digit Number (BSD) system

Addition process

Algorithm of Three-step Addition.

Qabeela

Issa Ahmed

Alaa A

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Essential approaches involving photons are among the most common uses of parallel optical computation due to their recent invention, ease of production, and low cost. As a result, most researchers have concentrated their efforts on it. The Basic Arithmetic Unit BAU is built using a three-step approach that uses optical gates with three states to configure the circuitry for addition, subtraction, and multiplication. This is a new optical computing method based on the usage of a radix of (2): a binary number with a signed-digit (BSD) system that includes the numbers -1, 0, and 1. Light with horizontal polarization (LHP) (↔), light with no intensity (LNI) (⥀), and light with vertical polarization (LVP) (↨) is represen

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Publication Date

Sat Sep 01 2018

Journal Name

Polyhedron

Novel dichloro (bis {2-[1-(4-methylphenyl)-1H-1, 2, 3-triazol-4-yl-κN3] pyridine-κN}) metal (II) coordination compounds of seven transition metals (Mn, Fe, Co, Ni, Cu, Zn and Cd)

The 1

3-dipolar cycloaddition “click” reaction between an azide and an alkyne to give a 1

2

3-triazole was reported by Huisgen in 1961 [1]. In 2002 the Copper(I)-catalyzed Azide-Alkyne Cycloaddition (CuAAC) to prepare a 1

2

3-triazole was reported [2]

[3]. The existence of relatively basic nitrogen atoms in the 1

2

3-triazole rings

and the possibility of introducing additional donor groups in the substituents (Fig. 1)

made the CuAAC “click” reaction an attractive method to prepare differently substituted 1

2

3-triazoles. These compounds have been used as ligands to coordinate to various metal ions that display a range of applications such as in electrochemical and photochemical studies

in supramolecular chemistry

magnetism

metal-ion sensing and catalysis [4]. The reasons for the success of the “click” reaction

is that it is easy to carry out and is widely applicable. It is not affected by a variety of functional groups

and can be carried out with a variety of Cu(I) catalysts and solvents

including aqueous conditions. The Cu(I) catalysts overcome the high activation energy barrier of the non-catalyzed Huisgen reaction by changing the mechanism of the reaction. A large variety of copper catalysts can be used for the CuAAC reaction

on condition that the maximum concentration of Cu(I) species is generated during the reaction. The pre-catalyst can be a Cu(II) salt (usually CuSO4) together with a reducing agent (often sodium ascorbate) or a Cu(I) compound in the presence of a base or amine ligand and a reducing agent to prevent oxidation to Cu(II). Some strong oxidising cupric salts or complexes such as Cu(OAc)2 also work. The solvent is very flexible from organic to aqueous

with the most commonly used combination water + an alcohol (t-BuOH

MeOH or EtOH). The key role of the solvent or solvent mixture is to solubilize the substrates and Cu(I) catalyst in order to ensure rapid reactions. Such aqueous conditions are very useful for biochemical conjugations

as well as for organic syntheses. We recently reported on the synthesis of a series of differently substituted 1

2

3-triazole chromophores

the substituted 2-(1-phenyl-1H-1

2

3-triazol-4-yl)pyridine ligands [5]

see Fig. 2 middle

with substituents R = H (L1)

CH3 (L2)

OCH3 (L3)

COOH

F

Cl

CN

CF3

O(CH2)3CH3 and N(CH3)2. These versatile ligands were found to coordinate to various first row transition metals

such as manganese

cobalt and nickel [6]. Here we extend the series to include more first row transition metal(II) coordination compounds

iron

copper and zinc

as well as a second row transition metal(II) coordination compound

cadmium

containing the 2-(1-(4-methyl-phenyl)-1H-1

2

3-triazol-1-yl)pyridine chromophore (Fig. 2 right with R = CH3). This series of seven novel coordination compounds is the first series of pyridyl-triazole based transition metal coordination compounds where seven different transition metals are coordinated to the same 1

2

3-triazole chromophore

namely 2-(1-(4-methyl-phenyl)-1H-1

2

3-triazol-1-yl)pyridine.

Kinaan M

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