Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (17)
  • Open Access

    ARTICLE

    A Novel Proactive AI-Based Agents Framework for an IoE-Based Smart Things Monitoring System with Applications for Smart Vehicles

    Meng-Hua Yen1,*, Nilamadhab Mishra2,*, Win-Jet Luo3, Chu-En Lin1

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1839-1855, 2025, DOI:10.32604/cmc.2025.060903 - 17 February 2025

    Abstract The Internet of Everything (IoE) coupled with Proactive Artificial Intelligence (AI)-Based Learning Agents (PLAs) through a cloud processing system is an idea that connects all computing resources to the Internet, making it possible for these devices to communicate with one another. Technologies featured in the IoE include embedding, networking, and sensing devices. To achieve the intended results of the IoE and ease life for everyone involved, sensing devices and monitoring systems are linked together. The IoE is used in several contexts, including intelligent cars’ protection, navigation, security, and fuel efficiency. The Smart Things Monitoring System… More >

  • Open Access

    ARTICLE

    Enhancing User Experience in AI-Powered Human-Computer Communication with Vocal Emotions Identification Using a Novel Deep Learning Method

    Ahmed Alhussen1, Arshiya Sajid Ansari2,*, Mohammad Sajid Mohammadi3

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2909-2929, 2025, DOI:10.32604/cmc.2024.059382 - 17 February 2025

    Abstract Voice, motion, and mimicry are naturalistic control modalities that have replaced text or display-driven control in human-computer communication (HCC). Specifically, the vocals contain a lot of knowledge, revealing details about the speaker’s goals and desires, as well as their internal condition. Certain vocal characteristics reveal the speaker’s mood, intention, and motivation, while word study assists the speaker’s demand to be understood. Voice emotion recognition has become an essential component of modern HCC networks. Integrating findings from the various disciplines involved in identifying vocal emotions is also challenging. Many sound analysis techniques were developed in the… More >

  • Open Access

    ARTICLE

    Revolutionizing Automotive Security: Connected Vehicle Security Blockchain Solutions for Enhancing Physical Flow in the Automotive Supply Chain

    Khadija El Fellah1,*, Ikram El Azami2,*, Adil El Makrani2, Habiba Bouijij3, Oussama El Azzouzy4

    Computer Systems Science and Engineering, Vol.49, pp. 99-122, 2025, DOI:10.32604/csse.2024.057754 - 03 January 2025

    Abstract The rapid growth of the automotive industry has raised significant concerns about the security of connected vehicles and their integrated supply chains, which are increasingly vulnerable to advanced cyber threats. Traditional authentication methods have proven insufficient, exposing systems to risks such as Sybil, Denial of Service (DoS), and Eclipse attacks. This study critically examines the limitations of current security protocols, focusing on authentication and data exchange vulnerabilities, and explores blockchain technology as a potential solution. Blockchain’s decentralized and cryptographically secure framework can significantly enhance Vehicle-to-Vehicle (V2V) communication, ensure data integrity, and enable transparent, immutable transactions More >

  • Open Access

    ARTICLE

    Deep learning identification of novel autophagic protein-protein interactions and experimental validation of Beclin 2-Ubiquilin 1 axis in triple-negative breast cancer

    XIANG LI1,#, WENKE JIN2,#, LIFENG WU2, HUAN WANG1, XIN XIE1, WEI HUANG1,*, BO LIU2,*

    Oncology Research, Vol.33, No.1, pp. 67-81, 2025, DOI:10.32604/or.2024.055921 - 20 December 2024

    Abstract Background: Triple-negative breast cancer (TNBC), characterized by its lack of traditional hormone receptors and HER2, presents a significant challenge in oncology due to its poor response to conventional therapies. Autophagy is an important process for maintaining cellular homeostasis, and there are currently autophagy biomarkers that play an effective role in the clinical treatment of tumors. In contrast to targeting protein activity, intervention with protein-protein interaction (PPI) can avoid unrelated crosstalk and regulate the autophagy process with minimal interference pathways. Methods: Here, we employed Naive Bayes, Decision Tree, and k-Nearest Neighbors to elucidate the complex PPI… More >

  • Open Access

    REVIEW

    Navigating IoT Security: Insights into Architecture, Key Security Features, Attacks, Current Challenges and AI-Driven Solutions Shaping the Future of Connectivity

    Ali Hassan1, N. Nizam-Uddin2, Asim Quddus3, Syed Rizwan Hassan4, Ateeq Ur Rehman5,*, Salil Bharany6

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3499-3559, 2024, DOI:10.32604/cmc.2024.057877 - 19 December 2024

    Abstract Enhancing the interconnection of devices and systems, the Internet of Things (IoT) is a paradigm-shifting technology. IoT security concerns are still a substantial concern despite its extraordinary advantages. This paper offers an extensive review of IoT security, emphasizing the technology’s architecture, important security elements, and common attacks. It highlights how important artificial intelligence (AI) is to bolstering IoT security, especially when it comes to addressing risks at different IoT architecture layers. We systematically examined current mitigation strategies and their effectiveness, highlighting contemporary challenges with practical solutions and case studies from a range of industries, such More >

  • Open Access

    REVIEW

    AI-Driven Learning Management Systems: Modern Developments, Challenges and Future Trends during the Age of ChatGPT

    Sameer Qazi1,*, Muhammad Bilal Kadri2, Muhammad Naveed1,*, Bilal A. Khawaja3, Sohaib Zia Khan4, Muhammad Mansoor Alam5,6,7, Mazliham Mohd Su’ud6

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3289-3314, 2024, DOI:10.32604/cmc.2024.048893 - 15 August 2024

    Abstract COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus. The foremost and most prime sector among those affected were schools, colleges, and universities. The education system of entire nations had shifted to online education during this time. Many shortcomings of Learning Management Systems (LMSs) were detected to support education in an online mode that spawned the research in Artificial Intelligence (AI) based tools that are being developed by the research community to improve the effectiveness of LMSs. This paper presents a detailed survey of the different enhancements to LMSs, which… More >

  • Open Access

    ARTICLE

    A Gaussian Noise-Based Algorithm for Enhancing Backdoor Attacks

    Hong Huang, Yunfei Wang*, Guotao Yuan, Xin Li

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 361-387, 2024, DOI:10.32604/cmc.2024.051633 - 18 July 2024

    Abstract Deep Neural Networks (DNNs) are integral to various aspects of modern life, enhancing work efficiency. Nonetheless, their susceptibility to diverse attack methods, including backdoor attacks, raises security concerns. We aim to investigate backdoor attack methods for image categorization tasks, to promote the development of DNN towards higher security. Research on backdoor attacks currently faces significant challenges due to the distinct and abnormal data patterns of malicious samples, and the meticulous data screening by developers, hindering practical attack implementation. To overcome these challenges, this study proposes a Gaussian Noise-Targeted Universal Adversarial Perturbation (GN-TUAP) algorithm. This approach… More >

  • Open Access

    ARTICLE

    Real-Time Prediction of Urban Traffic Problems Based on Artificial Intelligence-Enhanced Mobile Ad Hoc Networks (MANETS)

    Ahmed Alhussen1, Arshiya S. Ansari2,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1903-1923, 2024, DOI:10.32604/cmc.2024.049260 - 15 May 2024

    Abstract Traffic in today’s cities is a serious problem that increases travel times, negatively affects the environment, and drains financial resources. This study presents an Artificial Intelligence (AI) augmented Mobile Ad Hoc Networks (MANETs) based real-time prediction paradigm for urban traffic challenges. MANETs are wireless networks that are based on mobile devices and may self-organize. The distributed nature of MANETs and the power of AI approaches are leveraged in this framework to provide reliable and timely traffic congestion forecasts. This study suggests a unique Chaotic Spatial Fuzzy Polynomial Neural Network (CSFPNN) technique to assess real-time data… More >

  • Open Access

    REVIEW

    AI-Based UAV Swarms for Monitoring and Disease Identification of Brassica Plants Using Machine Learning: A Review

    Zain Anwar Ali1,2,*, Dingnan Deng1, Muhammad Kashif Shaikh3, Raza Hasan4, Muhammad Aamir Khan2

    Computer Systems Science and Engineering, Vol.48, No.1, pp. 1-34, 2024, DOI:10.32604/csse.2023.041866 - 26 January 2024

    Abstract Technological advances in unmanned aerial vehicles (UAVs) pursued by artificial intelligence (AI) are improving remote sensing applications in smart agriculture. These are valuable tools for monitoring and disease identification of plants as they can collect data with no damage and effects on plants. However, their limited carrying and battery capacities restrict their performance in larger areas. Therefore, using multiple UAVs, especially in the form of a swarm is more significant for monitoring larger areas such as crop fields and forests. The diversity of research studies necessitates a literature review for more progress and contribution in… More >

  • Open Access

    REVIEW

    Embracing the Future: AI and ML Transforming Urban Environments in Smart Cities

    Gagan Deep*, Jyoti Verma

    Journal on Artificial Intelligence, Vol.5, pp. 57-73, 2023, DOI:10.32604/jai.2023.043329 - 22 September 2023

    Abstract This research explores the increasing importance of Artificial Intelligence (AI) and Machine Learning (ML) with relation to smart cities. It discusses the AI and ML’s ability to revolutionize various aspects of urban environments, including infrastructure, governance, public safety, and sustainability. The research presents the definition and characteristics of smart cities, highlighting the key components and technologies driving initiatives for smart cities. The methodology employed in this study involved a comprehensive review of relevant literature, research papers, and reports on the subject of AI and ML in smart cities. Various sources were consulted to gather information… More >

Displaying 1-10 on page 1 of 17. Per Page