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Study and Analysis of the Factors that Affect the Efficiency of Small and Medium Enterprises in the Kingdom of Saudi Arabia
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Encouraging micro-enterprises for comprehensive economic development are crucial to achieve the ambitious vision 2030 of the Kingdom of Saudi Arabia.

 Small and Medium enterprises are inputting around 15.5 per cent to GDP while 33 per cent contribution as a private sector to Saudi Arabia's gross domestic product (GDP). This study aims to identify the most important factors that affect the efficiency of small enterprises in Saudi Arabia. To accomplish this objective, the study was conducted for small projects via the comprehensive inventory method under the supervision of the Institute of Entrepreneurship. A total of 282 questionnaires were collected from entrepreneurs and the differentiation analysis was applied. The results of the data analysis revealed the existence of many administrative, marketing, financing and human as well as legislative factors affecting the efficiency of small and medium enterprises in Saudi Arabia. In the light of the results, a number of recommendations are suggested that could contribute to encouraging and enhancing the role of small and medium enterprises in achieving the ambitious vision 2030 of the Kingdom

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Publication Date
Wed May 11 2022
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Some Methods For A single Imputed A missing Observation In Estimating Nonparametric Regression Function
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In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

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Publication Date
Thu Dec 05 2019
Journal Name
Advances In Intelligent Systems And Computing
An Enhanced Evolutionary Algorithm for Detecting Complexes in Protein Interaction Networks with Heuristic Biological Operator
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Publication Date
Sun Jun 05 2022
Journal Name
Network
A Computationally Efficient Gradient Algorithm for Downlink Training Sequence Optimization in FDD Massive MIMO Systems
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Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve

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Publication Date
Wed Jan 01 2020
Journal Name
2nd International Conference On Materials Engineering & Science (iconmeas 2019)
A kinetic model for prodigiosin production by Serratia marcescens as a bio-colorant in bioreactor
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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
Sat Aug 25 2012
Journal Name
Wireless Personal Communications
Multi-Objective Evolutionary Algorithm Based on Decomposition for Energy Efficient Coverage in Wireless Sensor Networks
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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Global DNA Methylation Levels in Epstein-Barr-Virus-Positive Iraqi Patients with Acute Lymphoblastic Leukaemia
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       Acute lymphoblastic leukemia (ALL) is one of the commonest hematological malignancies affecting children and adults. Recent evidence suggests an involvement of Epstein-Barr virus (EBV) in ALL pathogenicity. Epigenetic aberration, especially altered DNA methylation marks, is a key event of cancer development. The present study aims to investigate how the ALL epimethylome reacts to viral infection through the assessment of the total 5-methylcytosine (5mC) levels in ALL patients, according to EBV infection. The 5mC global DNA methylation levels in 50 diagnosed ALL patients (age mean 26.23 yrs; age range 10-60 yrs) and 25 age-matched healthy controls were assessed using MethylFlash™ Methylated DNA Quantification Kit. Acute pri

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Publication Date
Fri Feb 24 2023
Journal Name
Membranes
Enhanced Antifouling in Flat-Sheet Polyphenylsulfone Membranes Incorporating Graphene Oxide–Tungsten Oxide for Ultrafiltration Applications
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In this study tungsten oxide and graphene oxide (GO-WO2.89) were successfully combined using the ultra-sonication method and embedded with polyphenylsulfone (PPSU) to prepare novel low-fouling membranes for ultrafiltration applications. The properties of the modified membranes and performance were investigated using Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), contact angle (CA), water permeation flux, and bovine serum albumin (BSA) rejection. It was found that the modified PPSU membrane fabricated from 0.1 wt.% of GO-WO2.89 possessed the best characteristics, with a 40.82° contact angle and 92.94% porosity. The permeation flux of the best membrane was the highest. The pure water permeation f

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Publication Date
Mon Jul 18 2022
Journal Name
Ieee Access
Moderately Multispike Return Neural Network for SDN Accurate Traffic Awareness in Effective 5G Network Slicing
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Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Sum Rate Maximization Versus MSE Minimization in FDD Massive MIMO Systems With Short Coherence Time
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