Mesopotamian Journal of Computer Science

Purpose: The purpose of this abstract is to outline the role and capabilities of ChatGPT, a language model developed by OpenAI for computer programming. Methodology: ChatGPT is a large language model that has been trained on a diverse range of texts and can perform a variety of programming-related tasks. These tasks include code completion and correction, code snippet prediction and suggestion, automatic syntax error fixing, code optimization and refactoring suggestions, missing code generation, document generation, chatbot development, text-to-code generation, and answering technical queries. Results: ChatGPT can provide users with explanations, examples, and guidance to help them understand complex concepts and technologies, find relevant resources, and diagnose and resolve technical problems. Its use can improve overall satisfaction with support services and help organizations build a reputation for expertise and reliability. Conclusions: In conclusion, ChatGPT is a powerful and versatile tool for computer programming that can support developers and users in a wide range of tasks. Its ability to provide explanations, examples, and guidance makes it a valuable resource for technical support, while its ability to perform programming-related tasks can improve efficiency and accurac

Artificial intelligence (AI) images, like those produced by DALL-E, have seen explosive growth in the
past several years and have the potential to disrupt numerous markets. While the technology offers
exciting opportunities for creativity and innovation, it also raises important ethical considerations that
must be addressed. These ethical implications include issues related to bias and discrimination, privacy,
job displacement, and unintended consequences. To mitigate these challenges, a multi-disciplinary
approach is needed, including the development of effective regulations and governance frameworks, the
creation of unbiased algorithms, responsible data management practices, and educational and training
programs. Additionally, encouraging ethical discussions and debates is crucial in ensuring the
responsible use of AI-generated images. While AI-generated images offer many benefits, it is important
to consider the ethical implications and work towards responsible AI practices to ensure their benefits
are realized by society as a whol

Chatgpt
NLP
Conversational interfaces
Openai

Brain tumors are among the most dangerous diseases that lead to mortality after a period of time from
injury. Therefore, physicians and healthcare professionals are advised to make an early diagnosis of
brain tumors and follow their instructions. Magnetic resonance imaging (MRI) is operated to provide
sufficient and practical data in detecting brain tumors. Applications based on artificial intelligence
contribute a very large role in disease detection, provide incredible accuracy and assist in creating the
right decisions. In particular, deep learning models, which are a significant part of artificial intelligence,
have the ability to diagnose and process medical image datasets. In this concern, one of the deep learning
techniques (MobileNetV1model) is utilized to detect brain disease from 1265 images gathered from the
Kaggle platform. The behavior of this model is studied through four main metrics. This article deduced
that this model has a significant effect in diagnosing these images from the most important metric,
which is accuracy, as it gained an accuracy result of more than 97%, which is an excellent effect

Accurate, timely, and safe administration of data from IoT devices is made possible by intelligent
computing. As the number of IoT devices proliferates, more and more data will be collected, adding
depth and breadth to the existing range of IoT services. Technology that incorporates entire systems on
a single integrated circuit has improved to the point where more and more consumer electronics can
support full-fledged operating systems. It is impractical to use a single computing model for the entire
planet since doing so would cause severe network congestion and security holes. In order to solve this
problem, we present a framework that utilizes both blockchain technology and edge computing to
provide a lightweight data aggregation and secure data investigation solution for Internet of Things (IoT)
applications without compromising data security or protection. We use a lightweight data aggregation
process at the hub level to keep traffic flowing smoothly and quickly. In order to protect the safety of
sensitive data and ensure the precision of IoT AI models, we also offer a multi-level fuzzy hashing
process. Preliminary testing demonstrates the viability of the method presented here

The effects of climate change, such as droughts, storms, and extreme weather, are increasingly being felt around the world. Greenhouse gases are the primary contributors to climate change, with carbon dioxide (CO2) being the most significant. In fact, CO2 accounts for a significant percentage of all greenhouse gas emissions. As a result, reducing CO2 emissions has become a critical priority for mitigating the impacts of climate change and preserving our planet for future generations. Based on simulation and data mining technologies that use historical data, CO2 is expected to continue to rise. Around the world, 80% of CO2 emissions come from burning fossil fuels, mostly in the automotive or manufacturing industries. Governments have created policies to control CO2 emissions by focusing them on either consumers or manufacturers, in both developed and developing nations. Within the scope of this project, an investigation of vehicle emissions will be carried out using various attributes included within the vehicle dataset, as well as the use of many data mining techniques via the utilization of an orange application. The practical program is an example of organization, and the example will be about cars, exploring data, and figuring out how much gas will be needed. CO2 is taken away from cars, and we will use the CARS.csv file, which has data for a group of car types. It has a table with 36 records that shows the model, weight, and amount of carbon dioxide based on the car's size and weight.

Wireless networks are confronted with enormous challenge because of the limited availability of radio
spectrum, which has culminated in spectrum congestion and ineffective utilization of the spectrum's
resources. This has led to a great deal of innovation in both communication and mobile devices that
enable the delivery of high-quality multimedia content from various sources. However, despite these
advances, there is still a need to find new ways to utilize existing frequency bands. Recent years have
witnessed an awful research on cognitive radio (CR) based networks development. This review paper
provides a comprehensive overview of CR technology, its capabilities, and its various applications in
wireless communications. It not only provides an understanding of CR technology, its capabilities, and
its potential applications; but also serves as a useful resource for researchers, practitioners and students
interested in wireless communications and cognitive radio technology.

The end-of-term ratings are one of the most crucial components of improving educational institutions'
ability to assess teachers' performance. The paper-based evaluation system for teachers at Cebu
Technological University's Tuburan Campus is time-consuming and laborious. During the flexible
learning, the school uses Google Forms to create surveys to rate the teachers which also has shortcomings
since Google Forms has limited functions. To solve these issues, the proponents created a web-based
evaluation system that makes it simple for students to rate their professors and generates evaluation
reports at ease. Additionally, the system gives the system administrator the ability to control colleges,
users, and evaluations. It will save time and manpower because the results are created automatically. The
system was developed using HTML, CSS, Bootstrap, PHP, and MySQL while adhering to the Agile
Model of the Software Development Life Cycle. The proponents allowed the SAST Coordinator and
students to test the system and evaluate each module during the usability testing. Throughout unit testing,
integration testing, and system/alpha testing, the system was successful and performed as planned.
Enhancements to the system's features is highly recommended in order to augment the system’s
functionality including further study on the system's technology acceptanc

In recent years, education has become especially related to the applications provided by artificial
intelligence technology through a digital environment that includes a set of tools that assist in processing
and storing information. Artificial intelligence techniques contribute to the development of students'
skills by providing them with advanced scientific content and building their mental capabilities faster.
Moreover, these techniques support analysing student data and suggest suitable educational materials
and activities for them. Artificial intelligence is a noteworthy tool for the growth of distance education,
especially after the development of expert systems that have become a human advisor in many domains,
as this leads to the development of education systems that adjust the level of difficulty of materials based
on the student’s performance in the electronic classroom, which ensures that the student continues in
education and is not frustrated. This article will review the influential role of artificial intelligence
applications in growing distance learning, improving the quality of education, and making it an adaptable
and practical environment for student

Any company's most valuable asset, its workforce, is its employees. As a result, the company's primary
goal should be to develop an excellent strategy for supporting and investing in its employees and staff
by providing the best training and development. Employee Promotion denotes the advancement of an
employee's rank. It raises the salary, position, duties, and benefits. It is a part of the job that propels
employees to the highest commitment and loyalty to their organizations. Employee morale and loyalty
are two critical components of any successful business. Employee promotion is the key to improving
employee performance and engagement. It is a complex process that may require effort and time from
the human resource department. However, artificial intelligence is a recent science that has proven
effective in many sectors, including healthcare and finance. Thus, this study used artificial intelligence
techniques to automate employee promo. A new promotion approach based on machine learning
techniques was proposed. Three machine learning techniques were applied: Logistic regression, support
vector machine, and random forest. The result shows the efficacy of these techniques on the employee
promotion problem.

Neural networks, also known as artificial neural networks (ANNs) or artificially generated neural
networks (SNNs) are a subset of machine learning that provide the foundation of deep learning
techniques. Their name and form are inspired by the human brain, and they replicate the way real neurons
communicate with one another. Artificial neural networks (ANNs) are massively parallel systems
comprised of a huge number of interconnected basic processors. This paper discuss about the artificial
neural network and its basic types. This article explains the ANN and its basic outlines the fundamental
neuron and the artificial computer model. It describes network structures and learning methods, as well
as some of the most popular ANNs

Orthogonal Frequency Division Multiplexing (OFDM) is well recognized as a very efficient
multicarrier technology. OFDM has witnessed a significant increase in its utilization within
contemporary wideband digital communication systems. The technology possesses several notable
benefits, including its capacity to effectively manage challenging channel circumstances, optimize
spectrum utilization, mitigate inter symbol interference (ISI), and support high data transmission rates.
Hence, it has been employed in several forthcoming wired and wireless communication systems, such
as 4G LTE mobile communications. This work primarily concentrates on the performance assessment
and investigation of the OFDM system in the presence of Rayleigh fading channels. By analyzing the
outcomes of simulations, we may gain insights into various impacts and signal-to-noise ratios (SNRs).
In order to determine their respective signal delivery capabilities, channels are compared and ranked.
The evaluation of system performance involves assessing the quality of received signals, including
factors like as signal quality, bit-error rates (BERs), and peak signal-to-noise ratios (PSNRs)

Significant scholarly interest has been focused on the use of AI in English as a Foreign Language (EFL)
instruction because it presents novel opportunities for improving language learning contexts and
pedagogical approaches. This study provides an in-depth investigation into how AI is revolutionizing
English as a foreign language (EFL) instruction, with special focus on the ways in which this technology
can help students acquire a language in a fun, engaging, and one-on-one setting. This research examines
the ethical and sociological implications of the broad integration of AI technology into language learning
environments, highlighting major trends and identifying critical gaps through a thorough literature
assessment and bibliometric analysis. In order to advance the conversation and promote responsible AI
integration in EFL classrooms, the findings stress the importance of addressing long-term efficacy and
sustainability concerns, offering extensive pedagogical training for educators, and developing
interdisciplinary collaborations. This study aids the expanding body of knowledge by clarifying the
complex role that AI plays in EFL classrooms, providing direction for future studies, and paving the way
for the creation of solid frameworks for the responsible application of AI in educational settings.