Journal of Artificial Intelligence and Big Data

Journal profile

Journal of Artificial Intelligence and Big Data is an international and interdisciplinary scholarly open access journal on artificial intelligence. It publishes original research articles, reviews, communications, that offer substantial new insight into any field of study that involves artificial intelligence (AI) and big data,  including machine and deep learning, knowledge reasoning and discovery, automated planning and scheduling, natural language processing and recognition, computer vision, robotics, big data, and artificial general intelligence.

Latest Articles

Open Access April 15, 2024 Endnote/Zotero/Mendeley (RIS) BibTeX

Predictive Failure Analytics in Critical Automotive Applications: Enhancing Reliability and Safety through Advanced AI Techniques

Journal of Artificial Intelligence and Big Data 2024, 4(1), 48-60. DOI: 10.31586/jaibd.2024.917
Abstract
Failure prediction can be achieved through prognostics, which provides timely warnings before failure. Failure prediction is crucial in an effective prognostic system, allowing preventive maintenance actions to avoid downtime. The prognostics problem involves estimating the remaining useful life (RUL) of a system or component at any given time. The RUL
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Failure prediction can be achieved through prognostics, which provides timely warnings before failure. Failure prediction is crucial in an effective prognostic system, allowing preventive maintenance actions to avoid downtime. The prognostics problem involves estimating the remaining useful life (RUL) of a system or component at any given time. The RUL is defined as the time from the current time to the time of failure. The goal is to make accurate predictions close to the failure time to provide early warnings. J S Grewal and J. Grewal provide a comprehensive definition of RUL in their paper "The Kalman Filter approach to RUL estimation." A process is a quadruple (XU f P), where X is the state space, U is the control space, P is the set of possible paths, and f represents the transition between states. The process involves applying control values to change the system's state over time.Full article
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Open Access April 11, 2024 Endnote/Zotero/Mendeley (RIS) BibTeX

5V’s of Big Data Shifted to Suite the Context of Software Code: Big Code for Big Software Projects

Journal of Artificial Intelligence and Big Data 2024, 4(1), 36-47. DOI: 10.31586/jaibd.2024.911
Abstract
Data is the collection of facts and observations in terms of events, it is continuously growing, getting denser and more varied by the minute across different disciplines or fields. Hence, Big Data emerged and is evolving rapidly, the various types of data being processed are huge, but no one has
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Data is the collection of facts and observations in terms of events, it is continuously growing, getting denser and more varied by the minute across different disciplines or fields. Hence, Big Data emerged and is evolving rapidly, the various types of data being processed are huge, but no one has ever thought of where this data resides, we therefore noticed this data resides in software’s and the codebases of the software’s are increasingly growing that is the size of the modules, functionalities, the size of the classes etc. Since data is growing so rapidly it also mean the codebases of software’s or code are also growing as well. Therefore, this paper seeks to discuss the 5V’s of big data in the context of software code and how to optimize or manage the big code. When we talk of "Big Code for Big Software's," we are referring to the specific challenges and considerations involved in developing, managing, and maintaining of code in large-scale software systems.Full article
Article
Open Access February 19, 2024 Endnote/Zotero/Mendeley (RIS) BibTeX

The use of contemporary Enterprise Resource Planning (ERP) technologies for digital transformation

Journal of Artificial Intelligence and Big Data 2024, 4(1), 31-35. DOI: 10.31586/jaibd.2024.881
Abstract
Our lives are becoming more and more digital, and this has an impact on how we work, study, communicate, and interact. Businesses are currently digitally altering their information systems, procedures, culture, and strategy. Existing businesses and economies are severely disrupted by the digital revolution. The Internet of Things, microservices, and
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Our lives are becoming more and more digital, and this has an impact on how we work, study, communicate, and interact. Businesses are currently digitally altering their information systems, procedures, culture, and strategy. Existing businesses and economies are severely disrupted by the digital revolution. The Internet of Things, microservices, and mobile services are examples of IT systems with numerous, dispersed, and very small structures that are made possible by digitization. Utilizing the possibilities of cloud computing, mobile systems, big data and analytics, services computing, Internet of Things, collaborative networks, and decision support, numerous new business prospects have emerged throughout the years. The logical basis for robust and self-optimizing run-time environments for intelligent business services and adaptable distributed information systems with service-oriented enterprise architectures comes from biological metaphors of living, dynamic ecosystems. This has a significant effect on how digital services and products are designed from a value- and service-oriented perspective. The evolution of enterprise architectures and the shift from a closed-world modeling environment to a more flexible open-world composition establish the dynamic framework for highly distributed and adaptive systems, which are crucial for enabling the digital transformation. This study examines how enterprise architecture has changed over time, taking into account newly established, value-based relationships between digital business models, digital strategies, and enhanced enterprise architecture.Full article
Review Article
Open Access February 18, 2024 Endnote/Zotero/Mendeley (RIS) BibTeX

An Appraisal of Challenges in Developing Information Literacy Skills in the Colleges of Education of Ghana

Journal of Artificial Intelligence and Big Data 2024, 4(1), 19-30. DOI: 10.31586/jaibd.2024.878
Abstract
The purpose of this study was to examine the challenges faced by students of Colleges of Education (CoEs) in developing their Information Literacy skills. The study adopted the post-positivism paradigm. Descriptive survey research design used in this study Survey. The population for this study comprised all Level 200 students at
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The purpose of this study was to examine the challenges faced by students of Colleges of Education (CoEs) in developing their Information Literacy skills. The study adopted the post-positivism paradigm. Descriptive survey research design used in this study Survey. The population for this study comprised all Level 200 students at Wiawso CoE, Enchi CoE, and Bia Lamplighter CoE in the Western North Region. Purposive, stratified, and convenience sampling techniques were used to select colleges of education and level 200 students. The three (3) colleges of education were stratified and purposively selected while 256 level 200 students were stratified and conveniently sampled. The study employed questionnaires to collect data from the sampled students. Questionnaires (open and closed-ended questions) focused on the challenges faced by the students in developing their Information Literacy (IL) skills. The quantitative data was captured, analysed, and presented in descriptive statistics such as percentages, and frequency tables, to determine the objective of the study. It is recommended that to improve digital literacy and academic pursuits, the college management should improve access to desktop computers and the Internet in the library and computer centre. It is also recommended that Management and librarians of the Colleges of Education ensure that students have access to these devices at the library and can use them to develop their IL skills and help them manage their references more effectively.Full article
Article
Open Access February 17, 2024 Endnote/Zotero/Mendeley (RIS) BibTeX

Universal Evaluation of SAP S/4 Hana ERP Cloud System

Journal of Artificial Intelligence and Big Data 2024, 4(1), 14-18. DOI: 10.31586/jaibd.2024.882
Abstract
Regardless of their traditional ERP Systems, it is essential for every business to acquire a universal advantage in the contemporary international market. When everything is considered, end users in these kinds of businesses have to deal with poorly designed interfaces and unusable technologies. Despite the claims of significant benefits from
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Regardless of their traditional ERP Systems, it is essential for every business to acquire a universal advantage in the contemporary international market. When everything is considered, end users in these kinds of businesses have to deal with poorly designed interfaces and unusable technologies. Despite the claims of significant benefits from using S4 Hana cloud ERP software, the possibility of achieving maximum productivity is not fully utilized. One of the causes of this reality is the underfunding of ergonomic measures and the newest technologies. Through the design of S4 Hana cloud ERP software applications, we will demonstrate how important and highly recommended ergonomic research is in order to minimize the financial and human costs that enterprises are currently facing.Full article
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Review Article
Open Access February 15, 2024 Endnote/Zotero/Mendeley (RIS) BibTeX

Stock Closing Price and Trend Prediction with LSTM-RNN

Journal of Artificial Intelligence and Big Data 2024, 4(1), 1-13. DOI: 10.31586/jaibd.2024.877
Abstract
The stock market is very volatile and hard to predict accurately due to the uncertainties affecting stock prices. However, investors and stock traders can only benefit from such models by making informed decisions about buying, holding, or investing in stocks. Also, financial institutions can use such models to manage risk
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The stock market is very volatile and hard to predict accurately due to the uncertainties affecting stock prices. However, investors and stock traders can only benefit from such models by making informed decisions about buying, holding, or investing in stocks. Also, financial institutions can use such models to manage risk and optimize their customers' investment portfolios. In this paper, we use the Long Short-Term Memory (LSTM-RNN) Recurrent Neural Networks (RNN) to predict the daily closing price of the Amazon Inc. stock (ticker symbol: AMZN). We study the influence of various hyperparameters in the model to see what factors the predictive power of the model. The root mean squared error (RMSE) on the training was 2.51 with a mean absolute percentage error (MAPE) of 1.84%.Full article
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Open Access February 23, 2023 Endnote/Zotero/Mendeley (RIS) BibTeX

Substituting Intelligence

Journal of Artificial Intelligence and Big Data 2023, 3(1), 1-3. DOI: 10.31586/jaibd.2023.623
Abstract
The development of ChatGPT is a topical subject of reflection. This short paper focuses on the (possible) use of ChatGPT in academia and some of its (possible) ramifications for users’ cognitive abilities and, dramatically put, their existence.
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The development of ChatGPT is a topical subject of reflection. This short paper focuses on the (possible) use of ChatGPT in academia and some of its (possible) ramifications for users’ cognitive abilities and, dramatically put, their existence.Full article
Communication
Open Access July 10, 2022 Endnote/Zotero/Mendeley (RIS) BibTeX

Digital Therapeutics in Oncology: A Better Outlook for Cancer Patients in the Future

Journal of Artificial Intelligence and Big Data 2022, 2(1), 1-8. DOI: 10.31586/jaibd.2022.347
Abstract
Digital therapeutics (DTx) is an evidence-based treatment that makes use of high-quality software. As many healthcare systems confront increasing expectations for quality results, the need for digital medications is steadily growing in the clinical arena. To ensure that patients are supported during chemotherapy and that needless hospital visits are avoided,
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Digital therapeutics (DTx) is an evidence-based treatment that makes use of high-quality software. As many healthcare systems confront increasing expectations for quality results, the need for digital medications is steadily growing in the clinical arena. To ensure that patients are supported during chemotherapy and that needless hospital visits are avoided, digital therapeutics must be integrated into the cancer care pathway. Oncology patients are usually immunocompromised die to their disease and treatment, rendering them more susceptible to infection than the general population. As a result, visiting to a hospital might endanger their health. In addition, when cancer patients and survivors return home after treatment, digital health interventions provide them with the tools they need to manage their illness and its side effects in the privacy of their own homes. Considering the increasing prevalence of cancer patients and the solution that digital therapeutics has to offer in oncology, its future looks promising. This review article aims to summarize the existing companies in this domain, while evaluating the prospects as well.Full article
Review Article
Open Access December 27, 2021 Endnote/Zotero/Mendeley (RIS) BibTeX

A Comparative Study for Recommended Triage Accuracy of AI Based Triage System MayaMD with Indian HCPs

Journal of Artificial Intelligence and Big Data 2021, 1(1), 48-55. DOI: 10.31586/jaibd.2021.198
Abstract
Artificial intelligence (AI) based triage and diagnostic systems are increasingly being used in healthcare. Although these online tools can improve patient care, their reliability and accuracy remain variable. We hypothesized that an artificial intelligence (AI) powered triage and diagnostic system (MayaMD) would compare favorably with human doctors with respect to
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Artificial intelligence (AI) based triage and diagnostic systems are increasingly being used in healthcare. Although these online tools can improve patient care, their reliability and accuracy remain variable. We hypothesized that an artificial intelligence (AI) powered triage and diagnostic system (MayaMD) would compare favorably with human doctors with respect to triage and diagnostic accuracy. We performed a prospective validation study of the accuracy and safety of an AI powered triage and diagnostic system. Identical cases were evaluated by an AI system and individual Indian healthcare practitioners (HCPs) to draw comparison for accuracy and safety. The same cases were validated with the help of consensus received from an expert panel of 3 doctors. These cases in the form of clinical vignettes were provided by an expert medical team. Overall, the study showed that the MayaMD AI based platform for virtual triage was able to recommend the most appropriate triage ensuring patient safety. In fact, the accuracy of triage recommendation by MayaMD was significantly better than that provided by individual HCPs (74% vs. 91.67%, p=0.04) with consensus being used as standard.Full article
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Open Access October 19, 2021 Endnote/Zotero/Mendeley (RIS) BibTeX

A Ligthweight Wayfinding Assistance System for IoT Applications

Journal of Artificial Intelligence and Big Data 2021, 1(1), 39-47. DOI: 10.31586/jaibd.2021.147
Abstract
In this paper, we propose to design an indoor sign detection system for industry 4.0. In order to implement the proposed system, we proposed a lightweight deep learning-based architecture based on MobileNet which can be run on embedded devices used to detect and recognize indoor landmarks signs in order to
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In this paper, we propose to design an indoor sign detection system for industry 4.0. In order to implement the proposed system, we proposed a lightweight deep learning-based architecture based on MobileNet which can be run on embedded devices used to detect and recognize indoor landmarks signs in order to assist blind and sighted during indoor navigation. We apply various operations in order to minimize the network size as well as computation complexity. Internet of things (IoT) presents a connection between internet and the surroundings objects. IoT is characterized to connect physical objects with their numerical identities and enables them to connect with each other. This technique creates a kind of bridge between the physical world and the virtual world. The paper provides a comprehensive overview of a new method for a set of landmark indoor sign objects based on deep convolutional neural network (DCNN) for internet of things applications.Full article
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ISSN: 2771-2389
DOI prefix: 10.31586/jaibd
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