Digital Transformation Across Generations DOI
Shalom Akhai, Mahapara Abbass,

Preeti Kaur

и другие.

Advances in human and social aspects of technology book series, Год журнала: 2024, Номер unknown, С. 23 - 40

Опубликована: Ноя. 29, 2024

The integration of robotics and artificial intelligence (AI) is transforming industries, enhancing efficiency, safety, productivity. This chapter explores the impact autonomous systems across various sectors, including manufacturing, healthcare, transportation, agriculture. convergence AI enables adaptive to perform complex tasks independently, driving innovation reshaping business operations. Machine learning, computer vision, sensor fusion empower robots learn from data, recognize patterns, interact with humans. Successful applications include self-driving cars, robotic-assisted surgery, precision farming, smart home devices. However, challenges persist, such as reliability, ethics, data privacy, complexity implementation. As continue evolve, they will drive sustainable practices, optimize resource use, encourage interdisciplinary collaboration. Future research should focus on developing robust algorithms, safety protocols, establishing ethical guidelines.

Язык: Английский

A novel deep learning model for stock market prediction using a sentiment analysis system from authoritative financial website’s data DOI Creative Commons
Jitendra Chauhan, Tanveer Ahmed, Amit Sinha

и другие.

Connection Science, Год журнала: 2025, Номер 37(1)

Опубликована: Янв. 24, 2025

Язык: Английский

Процитировано

0

Mitigating Financial Anomalies Dimensions Vulnerability and Stratagem in Service Organizations DOI
Arjun J. Nair,

Satish Rao A. B.

Advances in public policy and administration (APPA) book series, Год журнала: 2025, Номер unknown, С. 361 - 388

Опубликована: Янв. 24, 2025

The chapter examines the intricate landscape of financial fraud within public administration, emphasising vulnerabilities that service organisations face in an increasingly complex environment. It delineates concepts vulnerability and stratagem, elucidating how determinants such as opportunity, pressure, rationalisation contribute to susceptibility. offers a comprehensive exploration effective detection prevention strategies, highlighting importance robust policy frameworks ethical standards. By integrating assessments into operational practices developing strategic responses, administrators fortify their against fraudulent activities. Through illustrative case studies practical applications, underscores critical need for transparency accountability advocates continuous improvement collaboration among stakeholders.

Язык: Английский

Процитировано

0

Efficient Numerical Techniques for Investigating Chaotic Behavior in the Fractional-Order Inverted Rössler System DOI Open Access
Mohamed Elbadri, Dalal Almutairi, D. K. Almutairi

и другие.

Symmetry, Год журнала: 2025, Номер 17(3), С. 451 - 451

Опубликована: Март 18, 2025

In this study, the numerical scheme for Caputo fractional derivative (NCFD) method and He–Laplace (H-LM) are two powerful methods used analyzing fractional-order systems. These approaches in study of complex dynamics inverted Rössler system, particularly detection chaotic behavior. The enhanced NCFD is reliable accurate simulations by capturing intricate Further, analytical solutions obtained using H-LM system. This popular due to its simplicity, stability, ability handle most initial values, yielding very results. Combining insights from with robust accuracy approach yields a comprehensive understanding system’s dynamics. advantages include high capture offers simplicity stability. proposed prove be capable detecting attractors, estimating their behavior correctly, finding solutions. findings confirm that NCFD- H-LM-based promising modeling solution Since these results provide improved broad class models, they will thus greatest use forthcoming applications engineering science.

Язык: Английский

Процитировано

0

Effectiveness of WeChat Official Accounts in health communication: A comparative study of hospitals and centers for disease control and prevention on resident participation in Shenzhen DOI Creative Commons
Fangfang Gong, Li Zeng, Yi Li

и другие.

Digital Health, Год журнала: 2025, Номер 11

Опубликована: Март 1, 2025

As China transitions from a disease-centered to people-centered healthcare model, hospitals are increasingly involved in health education. This study compares the effectiveness of WeChat Official Accounts (WOAs) operated by and Centers for Disease Control Prevention (CDCs) engaging residents identifies strategies enhance dissemination impact hospital WOAs digital communication. observational utilized WcplusPro collect education-related articles posted between July 2023 June 2024 district-level CDCs eight administrative districts Shenzhen, China, excluding affairs-related content. The effects different posting organizations on article reading sharing were compared using chi-square tests multivariable logistic regression R. A total 2270 health-related selected analysis. CDC accounted 59.34% (n = 1347) posts, while 40.66% 923). Articles showed significant positive association with high levels (OR 14.69, 95% CI 9.96-22.25). For levels, 3.56, 2.71-4.72). more likely achieve higher resident engagement (p < 0.05) if they published accounts larger follower bases 59.01), featured interrogative titles 22.19), avoided threatening tones 4.98-15.44), or highlighted as headlines 25.03). Hospital demonstrate promoting participation Hospitals should link services daily life use emotionally resonant narratives. They expand followings, refine headlines, position. Encouraging professionals education can boost participation.

Язык: Английский

Процитировано

0

Physical layer security techniques for grant-free massive Machine-Type Communications in 5G and beyond: A survey, challenges, and future directions DOI
Uchenna P. Enwereonye, Ahmad Salehi S., Hooman Alavizadeh

и другие.

Computer Networks, Год журнала: 2025, Номер unknown, С. 111268 - 111268

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Securing the CAN bus using deep learning for intrusion detection in vehicles DOI Creative Commons

Ritu Rai,

Jyoti Grover, Prinkle Sharma

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 22, 2025

The Controller Area Network (CAN) bus protocol is the essential communication backbone in vehicles within Intelligent Transportation System (ITS), enabling interaction between electronic control units (ECUs). However, CAN messages lack authentication and security, making system vulnerable to attacks such as DoS, fuzzing, impersonation, spoofing. This paper evaluates deep learning methods detect intrusions network. Using Car Hacking, Survival Analysis, OTIDS datasets, we train test models identify automotive cyber threats. We explore recurrent neural network (RNN) variants, including LSTM, GRU, VGG-16, analyze temporal spatial features data. LSTMs GRUs handle long-term dependencies sequential data, them suitable for analyzing messages. Bi-LSTMs enhance this by processing sequences both directions, from past future contexts improve anomaly detection. Our results show that LSTM achieves 99.89% accuracy binary classification, while VGG-16 reaches 100% multiclass classification. These findings demonstrate potential of techniques improving security resilience ITS effectively detecting mitigating attacks.

Язык: Английский

Процитировано

0

AI-Driven Decision-Making in Healthcare Information Systems: A Comprehensive Review DOI
Zahra Mohtasham‐Amiri,

Ali Taghavirashidizadeh,

Parsa Khorrami

и другие.

Journal of Systems and Software, Год журнала: 2025, Номер unknown, С. 112470 - 112470

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Machine-Learning-Powered Information Systems: A Systematic Literature Review for Developing Multi-Objective Healthcare Management DOI Creative Commons
Maryam Bagheri, Mohsen Bagheritabar,

Sohila Alizadeh

и другие.

Applied Sciences, Год журнала: 2024, Номер 15(1), С. 296 - 296

Опубликована: Дек. 31, 2024

The incorporation of machine learning (ML) into healthcare information systems (IS) has transformed multi-objective management by improving patient monitoring, diagnostic accuracy, and treatment optimization. Notwithstanding its revolutionizing capacity, the area lacks a systematic understanding how these models are divided analyzed, leaving gaps in normalization benchmarking. present research usually overlooks holistic for comparing ML-enabled ISs, significantly considering pivotal function criteria like precision, sensitivity, specificity. To address gaps, we conducted broad exploration 306 state-of-the-art papers to novel taxonomy IS management. We categorized studies six key areas, namely systems, treatment-planning monitoring resource allocation preventive hybrid systems. Each category was analyzed depending on significant variables, uncovering that adaptability is most effective parameter throughout all models. In addition, majority were published 2022 2023, with MDPI as leading publisher Python prevalent programming language. This extensive synthesis not only bridges but also proposes actionable insights ML-powered

Язык: Английский

Процитировано

0

Digital Transformation Across Generations DOI
Shalom Akhai, Mahapara Abbass,

Preeti Kaur

и другие.

Advances in human and social aspects of technology book series, Год журнала: 2024, Номер unknown, С. 23 - 40

Опубликована: Ноя. 29, 2024

The integration of robotics and artificial intelligence (AI) is transforming industries, enhancing efficiency, safety, productivity. This chapter explores the impact autonomous systems across various sectors, including manufacturing, healthcare, transportation, agriculture. convergence AI enables adaptive to perform complex tasks independently, driving innovation reshaping business operations. Machine learning, computer vision, sensor fusion empower robots learn from data, recognize patterns, interact with humans. Successful applications include self-driving cars, robotic-assisted surgery, precision farming, smart home devices. However, challenges persist, such as reliability, ethics, data privacy, complexity implementation. As continue evolve, they will drive sustainable practices, optimize resource use, encourage interdisciplinary collaboration. Future research should focus on developing robust algorithms, safety protocols, establishing ethical guidelines.

Язык: Английский

Процитировано

0