Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Mohammad Tubishat"'
Autor:
Maen T. Alrashdan, Mutaz Abdel Wahed, Emran Aljarrah, Mohammad Tubishat, Malek Alzaqebah, Nader Aljawarneh
Publikováno v:
International Journal of Data and Network Science, Vol 8, Iss 4, Pp 2539-2546 (2024)
A large-scale cloud data center must have a low failure incidence rate and great service dependability and availability. However, due to several issues, such as hardware and software malfunctions that regularly cause task and job failure, large-scale
Externí odkaz:
https://doaj.org/article/51f51e102ea0415e9594adb7176528d9
Autor:
Sharif Naser Makhadmeh, Mohammed Azmi Al-Betar, Feras Al-Obeidat, Osama Ahmad Alomari, Ammar Kamal Abasi, Mohammad Tubishat, Zenab Elgamal, Waleed Alomoush
Publikováno v:
Sustainable Operations and Computers, Vol 5, Iss , Pp 88-101 (2024)
This paper presents the energy planning problem (EPP) as an optimization problem to find the optimal schedules to minimize energy consumption costs and demand and enhance users’ comfort levels. The grey wolf optimizer (GWO), One of the most powerfu
Externí odkaz:
https://doaj.org/article/61566f2eb3a34a4f9667cc3eba59cf9e
Publikováno v:
Intelligent Systems with Applications, Vol 22, Iss , Pp 200362- (2024)
This research explores the user perceptions of the Metaverse Marketplace, analyzing a substantial dataset of over 860,000 Twitter posts through sentiment analysis and topic modeling techniques. The study aims to uncover the driving factors behind use
Externí odkaz:
https://doaj.org/article/ffb9f35bed99406c90faf10b0f9bf5ec
Publikováno v:
Heliyon, Vol 10, Iss 10, Pp e31413- (2024)
This review explores the Metaverse, focusing on user perceptions and emphasizing the critical aspects of usability, social influence, and interoperability within this emerging digital ecosystem. By integrating various academic perspectives, this anal
Externí odkaz:
https://doaj.org/article/861320ba32f248dea52ca01583e2d345
Autor:
Osama Ahmad Alomari, Ashraf Elnagar, Imad Afyouni, Ismail Shahin, Ali Bou Nassif, Ibrahim Abaker Hashem, Mohammad Tubishat
Publikováno v:
IEEE Access, Vol 10, Pp 121816-121830 (2022)
The rapid growth of electronic documents has resulted from the expansion and development of internet technologies. Text-documents classification is a key task in natural language processing that converts unstructured data into structured form and the
Externí odkaz:
https://doaj.org/article/09af1c0b11134b3a97018a12bc0b07ae
Autor:
Zenab Elgamal, Aznul Qalid Md Sabri, Mohammad Tubishat, Dina Tbaishat, Sharif Naser Makhadmeh, Osama Ahmad Alomari
Publikováno v:
IEEE Access, Vol 10, Pp 51428-51446 (2022)
The increased volume of medical datasets has produced high dimensional features, negatively affecting machine learning (ML) classifiers. In ML, the feature selection process is fundamental for selecting the most relevant features and reducing redunda
Externí odkaz:
https://doaj.org/article/4a219f7cfb8244f799af5a3a5a00aec0
An Improved Dandelion Optimizer Algorithm for Spam Detection: Next-Generation Email Filtering System
Publikováno v:
Computers, Vol 12, Iss 10, p 196 (2023)
Spam emails have become a pervasive issue in recent years, as internet users receive increasing amounts of unwanted or fake emails. To combat this issue, automatic spam detection methods have been proposed, which aim to classify emails into spam and
Externí odkaz:
https://doaj.org/article/0e23decd32624cb4959ab1d99c3977d2
Publikováno v:
IEEE Access, Vol 8, Pp 121127-121145 (2020)
The rapid increase in data volume and features dimensionality have a negative influence on machine learning and many other fields, such as decreasing classification accuracy and increasing computational cost. Feature selection technique has a critica
Externí odkaz:
https://doaj.org/article/bbf553bd3d08490e8b1e936d2b6ae5d9
Autor:
Ahmad Amin, Toqir A. Rana, Natash Ali Mian, Muhammad Waseem Iqbal, Abbas Khalid, Tahir Alyas, Mohammad Tubishat
Publikováno v:
IEEE Access, Vol 8, Pp 212675-212686 (2020)
In Natural Language Processing (NLP), topic modeling is the technique to extract abstract information from documents with huge amount of text. This abstract information leads towards the identification of the topics in the document. One way to retrie
Externí odkaz:
https://doaj.org/article/6724720762db4d408608da11933ff3a0
Autor:
Mohammad Tubishat, Mohammed Alswaitti, Seyedali Mirjalili, Mohammed Ali Al-Garadi, Ma'en Tayseer Alrashdan, Toqir A. Rana
Publikováno v:
IEEE Access, Vol 8, Pp 194303-194314 (2020)
Feature selection represents an essential pre-processing step for a wide range of Machine Learning approaches. Datasets typically contain irrelevant features that may negatively affect the classifier performance. A feature selector can reduce the num
Externí odkaz:
https://doaj.org/article/8425d50d899c44fb8b8fdfd129efeb61