doi:10.24996/ijs.2021.62.5.28

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Publication Date

Mon May 31 2021

Journal Name

Iraqi Journal Of Science

Volume

62

Issue Number

5

DOI

10.24996/ijs.2021.62.5.28

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Multi-criteria Decision Making on the Best Drug for Rheumatoid Arthritis

Choquet integral

λ – Sugeno measure

Multi-criteria decision making

Rheumatoid arthritis disease

Mojeba

Jabbar

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The theory of Multi-Criteria Decision Making (MCDM) was introduced in the second half of the twentieth century and aids the decision maker to resolve problems when interacting criteria are involved and need to be evaluated. In this paper, we apply MCDM on the problem of the best drug for rheumatoid arthritis disease. Then, we solve the MCDM problem via -Sugeno measure and the Choquet integral to provide realistic values in the process of selecting the most appropriate drug. The approach confirms the proper interpretation of multi-criteria decision making in the drug ranking for rheumatoid arthritis.

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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

Mon Jun 05 2023

Journal Name

Journal Of Engineering

Image Compression Using 3-D Two-Level Technique

Image compression

3-D two level wavelet transform

3-D two level multi-wavelet transform

3-D two level hybrid technique

Image data properties

Zainab Ibraheem

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In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent r

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Publication Date

Wed Feb 12 2025

Journal Name

Journal Of Engineering

Image Compression Using 3-D Two-Level Techniques

Image compression

3-D two level wavelet transform

3-D two level multi-wavelet transform

3-D two level hybrid technique

Image data properties.

Zainab

...Show More Authors

In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-

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Publication Date

Sat Oct 01 2016

Journal Name

Journal Of Theoretical And Applied Information Technology

Factors affecting global virtual teams’ performance in software projects

Today the trend is to perform software development work via distributed geographical area among team

individual or even as an organization. However

due to the global market and international presence of many companies

there is a need to implement a global virtual teams. The global virtual team members are gradually engaged in globalized business environments across space

time and organizational boundaries via information and communication technologies. A global virtual team relies on communication

collaboration

and information exchange are the most important criteria in global virtual teams’ operations. The purpose of this paper is to answer two research questions. The first research question is to identify the factors affecting global virtual teams’ performance. A systematic literature review was conducted to answer the first research question. The second research question is on what the rank of the factor affecting the global virtual teams’ performance according to their level of effect on global virtual teams’ performance. Online survey was conducted within 103 developers and IT managers from eight IT companies to answer the second research question. The Statistical Package for Social Science (SPSS 22) was used to analyze the collected data. In this study

we investigated factors that affect global virtual teams’ performance

factors considered include cultural differences

language problems

time-zone differences

team size

technical problems

lack of trust

lack of sufficient training

and ICT problems. Also the findings indicated that lack of sufficient training is the highest level of effect on global virtual teams’ performance. On the other hand

Ali Yahya Gheni

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