Ahmed Hussein AliAl-Iraqia University · Computer Science
Ahmed Hussein Ali
Doctor of Philosophy
Big Data
About
62
Publications
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759
Citations
Introduction
Ahmed Ali currently works at the Department of Computer Science, Iraqia University. Ahmed does research in Big data, Distributed Computing, Data Mining and Artificial Neural Network. Their current project is 'How to connect Radoop (rapidMiner) to Hadoop'.
Publications
Publications (62)
Large language models (LLMs) have become prominent tools in various domains, such as natural language processing, machine translation, and the development of creative text. Nevertheless, in order to fully exploit the capabilities of Language Models, it is imperative to establish efficient communication channels between humans and machines. The disc...
Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.
The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualization.
to develop state-of-the-art Big
Data platform in research,
education and industrial
applications, and open it to the
Hong Kong society and the world
at large
The creation of chatbots, such as Generative Pre-trained Transformer (GPT), is a result of recent developments in natural language processing (NLP). Even though Chat GPT has demonstrated enormous promise in a number of areas, including scientific research, this impact is still developing. This paper attempts to investigate the possibilities, threat...
In order to speed up convolutional neural networks (CNNs), this study gives a complete overview of the use of FPGA-based pipelining for hardware acceleration of CNNs. These days, most people use convolutional neural networks (CNNs) to perform computer vision tasks like picture categorization and object recognition. The processing and memory demands...
Transfer Learning[1] is a machine learning technique that involves utilizing knowledge learned from one task to improve performance on another related task. This approach has been widely adopted in various fields such as computer vision, natural language processing, and speech recognition. The goal of this paper is to provide an overview of transfe...
![Fig. 1. How ChatGPT is trained [Downloaded from Google].](profile/Mohammad-Aljanabi/publication/367654480/figure/fig1/AS:11431281116311649@1675234370810/How-ChatGPT-is-trained-Downloaded-from-Google_Q320.jpg)
ChatGPT Cybersecurity Medical data Digitization Intro to ChatGPT ChatGPT is a large language model developed by OpenAI. It is trained on a dataset of conversational text and can be used to generate human-like responses to prompts in a variety of languages and formats. It can be used for tasks such as chatbots, language translation, and text complet...
Large-scale datasets are becoming more common, yet they can be challenging to understand and interpret. When dealing with big datasets, principal component analysis (PCA) is used to minimize the dimensionality of the data while maintaining interpretability and avoiding information loss. It accomplishes this by producing new uncorrelated variables t...
The use of network-connected gadgets is rising quickly in the internet age, which is escalating the number of cyberattacks. The detection of distributed denial of service (DDoS) attacks is a tedious task that has necessitated the development of a number of models for its identification recently. Nonetheless, because of major fluctuations in subscri...
ChatGPT-3 is a powerful language model developed by OpenAI that has the potential to revolutionize the way weinteract with technology. This model has been trained on a massive amount of data, allowing it to understand andgenerate human-like text with remarkable accuracy. One of the most exciting possibilities of ChatGPT-3 is its potentialto improve...
![The general challenges that universities face worldwide and in Iraq [7, 8].](profile/Mohammad-Aljanabi/publication/367964819/figure/tbl2/AS:11431281117104863@1675373723517/The-general-challenges-that-universities-face-worldwide-and-in-Iraq-7-8_Q320.jpg)
This research paper aims to investigate the current state of process efficiency in Iraqi universities and propose a management information system (MIS) to improve it. A literature review was conducted to identify the challenges faced by universities in Iraq, as well as the solutions proposed in the literature. The findings showed that the main chal...
4th International Conference on Engineering and Science Applications
(ICESA 2022)
تحت شعار "نستنهض كل الطاقات العلمية في اعادة بناء عراقنا الحبيب"، تقيم كلية السلام الجامعة، مؤتمرها العلمي الدولي الرابع (ICESA 2022) بالتعاون مع مؤسسة IEEE.
يهدف المؤتمر الى تعزيز البحث العلمي والنهوض بالتقنيات الحالية وكذلك إيجاد حلول مبتكرة للتحديات الناشئة واستخد...
The issue of waste treatment is one of the topics that have a direct impact on the
environment and human life. In previous studies the mathematical model of waste
treatment has proven its importance for large-scale waste treatment plant (WTP). Little
experience has been gained in mathematical modeling of waste treatment plant. In this
study an opti...
Computer science research is a rapidly evolving field that is shaping the future of technology. From artificial intelligence and machine learning to image processing and cybersecurity, researchers are constantly pushing the boundaries of what is possible. In this editorial, we will explore some of the current trends in computer science research and...
Advancements in information technology is contributing to the excessive rate of big data generation recently. Big data refers to datasets that are huge in volume and consumes much time and space to process and transmit using the available resources. Big data also covers data with unstructured and structured formats. Many agencies are currently subs...
Recent advancements in the internet, social media, and internet of things (IoT) devices have significantly increased the amount of data generated in a variety of formats. The data must be converted into formats that is easily handled by the data analysis techniques. It is mathematically and physically expensive to apply machine learning algorithms...
Intrusion detection is mainly achieved by using optimization algorithms. The need for optimization algorithms for intrusion detection is necessitated by the increasing number of features in audit data, as well as the performance failure of the human-based smart intrusion detection system (IDS) in terms of their prolonged training time and classific...
Intrusion detection is mainly achieved by using optimization algorithms. The need for optimization algorithms for intrusion detection is necessitated by the increasing number of features in audit data, as well as the performance failure of the human-based smart intrusion detection system (IDS) in terms of their prolonged training time and classific...
The proliferation of online platforms recently has led to unprecedented increase in data generation; this has given rise to the concept of big data which characterizes data in terms of volume, velocity, variety, and veracity. One of the common multivariate statistical data analysis tools is linear discriminant analysis (LDA) which relies on the con...
The term "big data" is becoming increasingly common these days. The amount of data generated is directly proportional to the amount of time spent on social media each day. The majority of users consider Twitter to be one of the most popular social networking platforms. The rise of social media has sparked an incredible amount of curiosity among tho...
A non-linear applied math knowledge modelling tool, Artificial Neural Networks (ANN) are predominantly used to model complicated interactions between inputs and outputs or to look for patterns within the data. Using VHDL coding, we developed a generic hardware-based ANN. This classifier has been trained to recognize letters on a 4x4 binary grid tha...
Intrusion detection systems (IDSs) are one of the promising tools for protecting data and networks; many classification algorithms, such as neural network (NN), Naive Bayes (NB), decision tree (DT), and support vector machine (SVM) have been used for IDS in the last decades. However, these classifiers is not working well if they applied alone witho...
the scale of data streaming in social networks, such as Twitter, is increasing exponentially. Twitter is one of the most important and suitable big data sources for machine learning research in terms of analysis, prediction, extract knowledge, and opinions. People use Twitter platform daily to express their opinion which is a fundamental fact that...
Owing to the exponential expansion in the data size, fast and efficient systems of analysis are extremely needed. The traditional algorithms of machine learning face the challenge of learning bottlenecks such as; human participation, time, and the accuracy of prediction. But, the efficient and fast methods of dynamic learning offer considerable adv...
p> The most dangerous type of cancer suffered by women above 35 years of age is breast cancer. Breast Cancer datasets are normally characterized by missing data, high dimensionality, non-normal distribution, class imbalance, noisy, and inconsistency. Classification is a machine learning (ML) process which has a significant role in the prediction of...
![Fig. 4. The overall architecture of the RapidMiner-Hadoop integration [27].](profile/Ahmed-Ali-94/publication/340274885/figure/fig3/AS:874761156571143@1585570720601/The-overall-architecture-of-the-RapidMiner-Hadoop-integration-27_Q320.jpg)
Data mining is known as the process of detection concerning patterns from essential amounts of data. As a process of knowledge discovery. Classification is a data analysis that extracts a model which describes an important data classes. One of the outstanding classifications methods in data mining is support vector machine classification (SVM). It...
The support vector machine (SVM) is a classifier with different applications due to its perfect experimental performance compared to other machine learning algorithms. It has been used mostly in pattern recognition, fault diagnosis, and text categorization. The performance of SVM is extremely dependent on the sufficient setting of its parameters su...
The huge number of irrelevant and redundant data used in building intrusion detection systems (IDS) is one of the common issues in network intrusion detection systems. This paper proposed the use of Fuzzy Generalized Hebbian Algorithm as a novel data reduction method to overcome this problem of data redundancy in IDS. Two methods for dimensionality...
Demand for resources is known beforehand
An interesting problem when provisioning virtual infrastructures is how to deal with situations where the demand for resources is known beforehand
for example, when an experiment depending on some complex piece of equipment is going to run from 2 pm to 4 pm, and computational resources must be available at e...
systems that provide the virtual machine provisioning and migration services
1- Amazon EC2
2-Eucalyptus
3-OpenNebula
technologies for open source cloud tools, which play an invaluable role in infrastructure as a service and in building private, public, and hybrid cloud architecture
IaaS provider characteristic
on-demand provisioning of computational resources
Virtualization technologies to lease resources
Provide public and simple remote interfaces to manage resources
use a pay-as-you-go cost model
“infinite capacity” or “unlimited elasticity”
Cloud computing is an emerging research infrastructure that builds on the achievements of different research areas, such as service-oriented architecture (SOA), grid computing, and virtualization technology.
The provisioning for systems and applications on a large number of physical machines is traditionally a time consuming process with low assura...
The alignment of a cloud computing model with an organization’s business objectives (profit, return on investment, reduction of operations costs) and processes
The algorithm of the Evolving Clustering Method (ECM) is an unsupervised clustering technique that provides a fast online and dynamic estimation of clusters. The number of clusters generated by the ECM is determined by the threshold Dthr value. The bottleneck of the ECM is how to determine the optimal value of Dthr for best clustering processes and...
Cloud computing is a new computing paradigm that offers a huge amount of compute and storage resources to the masses. Individuals (e.g., scientists) and enterprises (e.g., startup companies) can have access to these resources by paying a small amount of money just for what is really needed.
1. Mohammed, M. A., Hasan, R. A., Ahmed, M. A., Tapus, N., Shanan, M. A., Khaleel, M. K., & Ali, A. H. (2018, June). A
Focal load balancer based algorithm for task assignment in cloud environment. In 2018 10th International Conference
on Electronics, Computers and Artificial Intelligence (ECAI) (pp. 1-4). IEEE .
2. Ahmed, M. A., Hasan, R. A., Ali,...
A new trend rising in IT environs is the Mobile cloud computing with colossal prerequisites of infrastructure along with resources. In cloud computing environment, load balancing a vital aspect. Cloud load balancing way toward disseminating workloads across numerous computing resources. Proficient load balancing plan guarantees effective resource u...
The big data concept has elicited studies on how to accurately and efficiently extract valuable information from such huge dataset. The major problem during big data mining is data dimensionality due to a large number of dimensions in such datasets. This major consequence of high data dimensionality is that it affects the accuracy of machine learni...
In recent years, working on text classification and analysis of Arabic texts using machine learning has seen some progress, but most of this research has not focused on Arabic poetry. Because of some difficulties in the analysis of Arabic poetry, it was required the use of standard Arabic language on which "Al Arud", the science of studying poetry...
There is no doubt that we are entering the era of big data. The challenge is on how to store, search, and analyze the huge amount of data that is being generated per second. One of the main obstacles to the big data researchers is how to find the appropriate big data analysis platform. The basic aim of this work is to present a complete investigati...
A new trend rising in IT environs is the Mobile cloud computing with colossal prerequisites of infrastructure along with resources. In cloud computing environment, load balancing a vital aspect. Cloud load balancing way toward disseminating workloads across numerous computing resources. Proficient load balancing plan guarantees effective resource u...
The increment in industrial demand for electrical power come to search for alternative clean and cheap energy sources. One of these choices is the renewable energy sources. So, there are some energy sources now can connect to the main electrical distribution networks which may led to influence the stability and performance of the system. In this pa...
A new trend rising in IT environs is the Mobile cloud computing with colossal prerequisites of infrastructure along with resources. In cloud computing environment, load balancing a vital aspect. Cloud load balancing way toward disseminating workloads across numerous computing resources. Proficient load balancing plan guarantees effective resource u...
There is no doubt that big data has become an important source of information and knowledge, especially for large profitability companies such as Facebook and Amazon. But, dealing with this kind of data comes with great difficulties; thus, several techniques have been used to analyze them. Many techniques handle big data and give decisions based on...
There is no doubt that big data has become an important source of information and knowledge, especially for large profitability companies such as Facebook and Amazon. But, dealing with this kind of data comes with great difficulties; thus, several techniques have been used to analyze them. Many techniques handle big data and give decisions based on...
Data mining classification plays an important role in the prediction of outcomes. One of the outstanding classifications methods in data mining is Naive Bayes Classification (NBC). It is capable of envisaging results and mostly effective than other classification methods. Many Naive Bayes classification method provide low performance in classificat...
Background and Objective: The algorithm of the Evolving Clustering Method (ECM) is an unsupervised clustering technique that provides a fast online and dynamic estimation of clusters. ECM is dynamically estimating the number of clusters in a given set of data points; it is also deployed for finding the existing centers in a given input data space....
Background and Objective: The algorithm of the Evolving Clustering Method (ECM) is an unsupervised clustering technique that provides a fast online and dynamic estimation of clusters. ECM is dynamically estimating the number of clusters in a given set of data points; it is also deployed for finding the existing centers in a given input data space....
Questions
Questions (23)
Dear Researchers and postgraduate students
MESOPOTAMIAN JOURNAL OF BIG DATA (MJBD) issued by Mesopotamian Academic Press, welcomes the original research articles, short papers, long papers, review papers for the publication in the next issue the journal doesn’t requires any publication fee or article processing charge and all papers are published for free
Journal info.
1 -Publication fee: free
2- Frequency: 1 issues per year
3- Subject: computer science, Big data, Parallel Processing, Parallel Computing and any related fields
4- ISSN: 2958-6453
5- Published by: Mesopotamian Academic Press.
6- Contact: email: ahmed.h.ali@mesopotamian.press
Managing Editor: Dr. Ahmed Ali
The journal indexed in
1- Croosref
2- DOAJ
3- Google scholar
4- Research gate
Publish your paper for free
_________________________
Dear Researchers and postgraduate students
MESOPOTAMIAN JOURNAL OF BIG DATA (MJBD) issued by Mesopotamian Academic Press, welcomes the original research articles, short papers, long papers, review papers for the publication in the next issue the journal doesn’t requires any publication fee or article processing charge and all papers are published for free
Journal info.
1 -Publication fee: free
2- Frequency: 1 issues per year
3- Subject: computer science, Big data, Parallel Processing, Parallel Computing and any related fields
4- ISSN: 2958-6453
5- Published by: Mesopotamian Academic Press.
6- Contact: email: ahmed.h.ali@mesopotamian.press
Managing Editor: Dr. Ahmed Ali
The journal indexed in
1- Croosref
2- DOAJ
3- Google scholar
4- Research gate
Dear Scholars, Researchers, and Academics,
We are pleased to announce a Call for Papers for the upcoming Special Issue to be hosted by the Mesopotamian Academic Press. This prestigious event is dedicated to fostering intellectual exchange and advancing scholarship in the field of Computer Science.
The Mesopotamian Academic Press takes pride in its commitment to nurturing the academic community by providing a platform for thought-provoking discussions and interdisciplinary collaborations. We invite contributions from scholars, researchers, and academics working in various disciplines, such as Big Data, Cybersecurity, Information Technology , and beyond, to submit their original research papers and engage in lively discussions that delve into the multifaceted dimensions.
Sincerely,
Mesopotamian Academic Press
https://mesopotamian.press/journals/index.php/index/index
Register as a Reviewer
Mesopotamian Journal of Big Data(MJBD) welcomes academicians to join us as a member of review board. Being a reviewer is a matter of prestige and personnel achievement.
Mesopotamian Journal of Big Data
Online ISSN: 2958-6453
Frequency1 issue per year
DOI prefix 10.58496
Managing Editor
Assoc. Prof.O.S. Albahri (Osamah Shihab Albahrey)
Universiti Pendidikan Sultan Idris (UPSI) |upsi · Department of Computing, Malaysia
Email: osamahsh89@gmail.com
Assoc. Prof.Ahmed hussein ali, Full time editor at Mesopotamian Journal of Big Data
