Roles of Big Data and AI in Manufacturing DOI

Hussain Ebrahim Ahmed,

Muneer Al Mubarak

Studies in systems, decision and control, Год журнала: 2024, Номер unknown, С. 3 - 25

Опубликована: Янв. 1, 2024

Язык: Английский

Modeling Hybrid Feature-Based Phishing Websites Detection Using Machine Learning Techniques DOI Open Access

Sumitra Das Guptta,

Khandaker Tayef Shahriar,

Hamed Alqahtani

и другие.

Annals of Data Science, Год журнала: 2022, Номер 11(1), С. 217 - 242

Опубликована: Март 21, 2022

Язык: Английский

Процитировано

49

The Evolving Role of Artificial Intelligence in the Future of Distance Learning: Exploring the Next Frontier DOI Creative Commons
Maad M. Mijwil, Guma Ali, Emre Sadıkoğlu

и другие.

Mesopotamian Journal of Computer Science, Год журнала: 2023, Номер unknown, С. 98 - 105

Опубликована: Май 21, 2023

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

Язык: Английский

Процитировано

14

AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems DOI Open Access
Iqbal H. Sarker

Опубликована: Фев. 1, 2022

Artificial Intelligence (AI) is a leading technology of the current age Fourth Industrial Revolution (Industry 4.0 or 4IR), with capability incorporating human behavior and intelligence into machines systems. Thus AI-based modeling key to building automated, intelligent, smart systems according today's needs. To solve real-world issues various types AI such as analytical, functional, interactive, textual, visual can be applied enhance capabilities an application. However, developing effective model challenging task due dynamic nature variation in problems data. In this paper, we present comprehensive view on "AI-based Modeling" principles potential techniques that play important role intelligent application areas including business, finance, healthcare, agriculture, cities, cybersecurity many more. We also emphasize highlight research within scope our study. Overall, goal paper provide broad overview used reference guide by academics industry people well decision-makers scenarios domains.

Язык: Английский

Процитировано

17

A Machine Learning Model for Predicting Individual Substance Abuse with Associated Risk-Factors DOI

Uwaise Ibna Islam,

Enamul Haque, Dheyaaldin Alsalman

и другие.

Annals of Data Science, Год журнала: 2022, Номер 10(6), С. 1607 - 1634

Опубликована: Март 23, 2022

Язык: Английский

Процитировано

15

GENERATIVE ARTIFICIAL INTELLIGENCE (AI) NEW VALUE PROPOSITION IN COLLEGE DOI Creative Commons
Suhana Suhana,

Dina Hikmayanti,

Lisania Cahya Agustin

и другие.

Journal of Community Service, Год журнала: 2025, Номер 2(4), С. 154 - 165

Опубликована: Фев. 6, 2025

Background. Learning technology has changed drastically. Lecturers who were previously a source of knowledge their role to become mentors for students. Aims. Such rapid development AI replaced human functions with limited memory. stores data indefinitely. All university lecturers and students need know this progress, so there is socialization event regarding the new value proposition generative artificial intelligence on campus. Method. The method used presentation from students, by whom accompany. Result. In presentation, it was highlighted meaning Gen AI, potential in learning, use policies how change educational landscape caused gene, education organized integration genes, are applicable academic regulations context whether Ai will streamline implementation education, maintain latest learning quality when utilizing AI. brings as actors. that utilizes gives freedom learn anyone anywhere across time space. Conclusion supports more personalized experience according each student's needs. presence online offline form managers, student companions (cognitive presence), guides interaction (social presence) provides lecturers' existence learning.

Язык: Английский

Процитировано

0

Cognitive Technologies: Machine Learning, Artificial Intelligence, and Convolutional Neural Networks in Computer Vision DOI Creative Commons

Hajar El Qasemy

Westcliff International Journal of Applied Research, Год журнала: 2025, Номер 9(1), С. 5 - 17

Опубликована: Март 7, 2025

The research focus was motivated by the limited understanding of cognitive technologies and growing gap between artificial intelligence (AI) human intelligence. is a literature review, its purpose to simplify meaning processes behind technologies, notably, fundamentals machine learning (ML) computer vision with intention briefly address alleged threat AI taking over job market. review peer-reviewed articles retrieved from comparative studies, systematic reviews, meta-analysis, service research, reports, conference proceedings, experimental scientometric analyses, books, multi-case dating years 2018 2024. This defines (ML), (AI), vision, convolutional neural networks (CNNs). It also compares traditional programming reveals types in ML models’ training. correlation are discussed details about theory mind, self-aware AI, reactive machines, memory shared. expounds particularly network (CNN) CNN layers. Recent cutting-edge applications including generative models autonomous systems incorporated. Finally, addresses findings this reveal that becoming new way operating. conclusion shows require significant computation allow computers learn autonomously. Thus, mathematical data perfecting process writing software could be key remaining employable as more jobs expected shifted due tasks automation. Keywords: Cognitive technology, intelligence, learning,

Язык: Английский

Процитировано

0

Machine Learning-Based and AI Powered Satellite Imagery Processing for Global Air Traffic Surveillance Systems DOI
Fredrick Kayusi, Petros Chavula,

Linety Juma

и другие.

LatIA, Год журнала: 2025, Номер 3, С. 82 - 82

Опубликована: Фев. 19, 2025

The unprecedented growth of global air traffic has put immense pressure on the management systems. In light that, situational awareness and surveillance are indispensable, especially for satellite-based aircraft tracking There been some crucial development in field; however, every major player this arena relies a single proprietary, non-transparent data feed. This is where chapter differentiates itself. AIS gaining traction recently same purpose matured considerably over past decade; communication service providers have failed to instrument significant portions world’s oceans. study proposes multimodal artificial intelligence-powered algorithm boost estimates using Global Air Traffic Visualization dataset. Two intelligence agents categorically detect streaks huge collection satellite images notify geospatial temporal statistical agent whenever both modalities concordance. A user can fine-tune threshold hyperparameter based installed detection rate datasets get best satellite-derived estimates.

Язык: Английский

Процитировано

0

Artificial Intelligence Adoption in Service Industries: A Systematic Literature Review of key Drives, Barriers, Challenges, and Strategies DOI

T D C Pushpakumara,

Fazeela Jameel Ahsan

Опубликована: Апрель 7, 2025

Artificial Intelligence (AI) is reshaping service industries by automating processes, enhancing decision-making, and delivering personalized customer experiences across sectors like tourism, healthcare, finance, governance. This systematic literature review consolidates findings from over 100 studies to explore the drivers, barriers, strategies influencing AI adoption. While AI-driven advancements such as robotic process automation (RPA) predictive analytics enable efficiency innovation, significant challenges infrastructural limitations, ethical concerns, organizational resistance hinder its widespread High implementation costs, socio-economic disparities, data privacy issues further complicate integration efforts, particularly in underdeveloped regions resource-constrained industries. To address these study highlights targeted training, policy-driven investments digital ecosystems, robust governance frameworks. Additionally, balancing with human interaction emerges a critical factor for stakeholder trust acceptance. emphasizes importance of interdisciplinary collaboration align technological societal goals, ensuring that adoption fosters sustainability, inclusivity, long-term growth

Язык: Английский

Процитировано

0

Bridging Gaps DOI
Andi Asrifan,

Shafa Shafa,

Widya Rizky Pratiwi

и другие.

Advances in computational intelligence and robotics book series, Год журнала: 2025, Номер unknown, С. 105 - 128

Опубликована: Апрель 30, 2025

Language education accessibility, especially for visually and hearing-impaired pupils, depends on AI. Advanced automated language teaching systems the disabled are limited despite broad technology developments. Manual input makes present solutions challenging limb-impaired people increases remote help. AI, NLP, offers unique diverse demands talents, ensuring learning equality. AI frameworks rarely consider impaired users. The chapter suggests using NLP to personalize learning. These technologies can give audio descriptions, text-to-speech, interactive platforms inclusive that maximizes student potential. AI-driven empower handicapped learners improve their communication, independence, social integration by including beneficiaries, instructors, families cooperating across stakeholders.

Язык: Английский

Процитировано

0

Civil Liability for Damages Caused by Artificial Intelligence in Light of Sustainable Development Goals “SDG3, 9 & 16” “A Legal Analysis Within the Saudi Civil Transactions System DOI

Renad Aldmour

Journal of Lifestyle and SDGs Review, Год журнала: 2025, Номер 5(5), С. e06197 - e06197

Опубликована: Май 6, 2025

Objectives: This study investigates the legal challenges and regulatory gaps in addressing civil liability for damages caused by artificial intelligence (AI) systems, with a specific focus on aligning frameworks United Nations Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health Well-being), 9 (Industry, Innovation Infrastructure), 16 (Peace, Justice Strong Institutions). It further examines applicability of Saudi Civil Transactions System to modern AI-related risks proposes reforms enhance justice, sustainability, innovation. Method: A comparative methodology was adopted, combining doctrinal analysis existing law an international review EU AI Liability Directive, U.S. tort framework, emerging norms. The research also includes content cases simulations AI-induced damage scenarios within contexts. Findings: reveals significant ambiguity regarding law. Only 36% current provisions address fault-based applicable autonomous systems. Furthermore, 72% risk reviewed involve actors or systems unclear accountability. International comparisons show that while is moving toward strict transparency, still lacks “black-box” behavior cross-sectoral management. Although has potential contribute 3, 9, 16, inadequately regulate these intersections. Novelty: uniquely bridges domains law, governance, sustainable development context. introduces "Three-Tier Framework" tailored technologies, balancing preventive assessment responsive redress mechanisms. paper legislative reform pathways increase accountability coverage from 85% introducing clauses high-risk applications mandatory insurance developers operators.

Язык: Английский

Процитировано

0