السجلات المعروضة 1355 -- 1374 من 2262

    • M-LEARNING FOR TRAINING ENGLISH AT WORKPLACE 

      Samaka, Mohammed; Ismail, Loay; Abu Abdulla, Nosayba; Clark, Brendan ( IATED Digital Library , 2012 , Article)
      The research project described in this paper involves in using of a mobile learning approach to train newly recruited trainees on workplace English, so they can become more effective when communicating in the workplace. ...
    • Machine learning aided load balance routing scheme considering queue utilization 

      Yao, Haipeng; Yuan, Xin; Zhang, Peiying; Wang, Jingjing; Jiang, Chunxiao; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2019 , Article)
      Due to the rapid development of network techniques, packet-switched systems experience high-speed growth of traffic, which imposes a heavy and unbalanced burden on the routers. Hence, efficient routing schemes are required ...
    • Machine Learning and Digital Heritage: The CEPROQHA Project Perspective 

      Belhi, Abdelhak; Gasmi, Houssem; Bouras, Abdelaziz; Alfaqheri, Taha; Aondoakaa, Akuha Solomon; ... more authors ( Springer , 2020 , Conference Paper)
      Through this paper, we aim at investigating the impact of artificial intelligence technologies on cultural heritage promotion and long-term preservation in terms of digitization effectiveness, attractiveness of the assets, ...
    • Machine Learning Based Cloud Computing Anomalies Detection 

      Chkirbene Z.; Erbad A.; Hamila R.; Gouissem A.; Mohamed A.; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)
      Recently, machine learning algorithms have been proposed to design new security systems for anomalies detection as they exhibit fast processing with real-time predictions. However, one of the major challenges in machine ...
    • Machine Learning for Anomaly Detection and Categorization in Multi-Cloud Environments 

      Salman, Tara; Bhamare, Deval; Erbad, Aiman; Jain, Raj; Samaka, Mohammed ( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference Paper)
      Cloud computing has been widely adopted by application service providers (ASPs) and enterprises to reduce both capital expenditures (CAPEX) and operational expenditures (OPEX). Applications and services previously running ...
    • Machine Learning for Healthcare Wearable Devices: The Big Picture 

      Sabry, Farida; Eltaras, Tamer; Labda, Wadha; Alzoubi, Khawla; Malluhi, Qutaibah ( John Wiley and Sons Inc , 2022 , Article Review)
      Using artificial intelligence and machine learning techniques in healthcare applications has been actively researched over the last few years. It holds promising opportunities as it is used to track human activities and ...
    • Machine learning for prediction of the uniaxial compressive strength within carbonate rocks 

      Abdelhedi, Mohamed; Jabbar, Rateb; Said, Ahmed Ben; Fetais, Noora; Abbes, Chedly ( Springer Science and Business Media Deutschland GmbH , 2023 , Article)
      The Uniaxial Compressive Strength (UCS) is an essential parameter in various fields (e.g., civil engineering, geotechnical engineering, mechanical engineering, and material sciences). Indeed, the determination of UCS in ...
    • Machine learning in the Internet of Things: Designed techniques for smart cities 

      Din I.U.; Guizani M.; Rodrigues J.J.P.C.; Hassan S.; Korotaev V.V. ( Elsevier B.V. , 2019 , Article)
      Machine learning is one of the emerging technologies that has grabbed the attention of academicians and industrialists, and is expected to evolve in the near future. Machine learning techniques are anticipated to provide ...
    • Machine Learning Methods for Dysgraphia Screening with Online Handwriting Features 

      Kunhoth, Jayakanth; Al Maadeed, Somaya; Saleh, Moutaz; Akbari, Younus ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference Paper)
      Dysgraphia, a major learning disorder that primarily interferes with writing skills can hinder the academic track of children unless recognized in the early stage. The diversity in the symptoms, as well as the emergence ...
    • Machine Learning Techniques for Detecting Attackers during Quantum Key Distribution in IoT Networks with Application to Railway Scenarios 

      Al-Mohammed, Hasan Abbas; Al-Ali, Afnan; Yaacoub, Elias; Qidwai, Uvais; Abualsaud, Khalid; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)
      Internet of Things (IoT) deployments face significant security challenges due to the limited energy and computational power of IoT devices. These challenges are more serious in the quantum communications era, where certain ...
    • Machine Learning Techniques for Network Anomaly Detection: A Survey 

      Eltanbouly, Sohaila; Bashendy, May; Alnaimi, Noora; Chkirbene, Zina; Erbad, Aiman ( IEEE , 2020 , Conference Paper)
      Nowadays, distributed data processing in cloud computing has gained increasing attention from many researchers. The intense transfer of data has made the network an attractive and vulnerable target for attackers to exploit ...
    • Machine learning-based management of electric vehicles charging: Towards highly-dispersed fast chargers 

      Shibl, M.; Ismail, L.; Massoud, Ahmed ( MDPI AG , 2020 , Article)
      Coordinated charging of electric vehicles (EVs) improves the overall efficiency of the power grid as it avoids distribution system overloads, increases power quality, and decreases voltage fluctuations. Moreover, the ...
    • Machine learning-based multi-target regression to effectively predict turning movements at signalized intersections 

      Shaaban, Khaled; Hamdi, Ali; Ghanim, Mohammad; Shaban, Khaled Bashir ( Elsevier , 2022 , Article)
      Effective prediction of turning movement counts at intersections through efficient and accurate methods is essential and needed for various applications. Commonly predictive methods require extensive data collection, ...
    • Machine Learning-Based Network Vulnerability Analysis of Industrial Internet of Things 

      Zolanvari M.; Teixeira M.A.; Gupta L.; Khan K.M.; Jain R. ( Institute of Electrical and Electronics Engineers Inc. , 2019 , Article)
      It is critical to secure the Industrial Internet of Things (IIoT) devices because of potentially devastating consequences in case of an attack. Machine learning (ML) and big data analytics are the two powerful leverages ...
    • Machine Learning-based Regression and Classification Models for Oil Assessment of Power Transformers 

      Bhatia, Neha Kamalraj; El-Hag, Ayman H.; Shaban, Khaled Bashir ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)
      Expensive and widely used power and distribution transformers need to be monitored to ensure the reliability of the power grid. Evaluating the transformer oil different parameters is vital to determine the transformer ...
    • Machine Learning-Based Software Defect Prediction for Mobile Applications: A Systematic Literature Review 

      Jorayeva, Manzura; Akbulut, Akhan; Catal, Cagatay; Mishra, Alok ( MDPI , 2022 , Article Review)
      Software defect prediction studies aim to predict defect-prone components before the testing stage of the software development process. The main benefit of these prediction models is that more testing resources can be ...
    • Machine unlearning: Its need and implementation strategies 

      Tahiliani, Aman; Hassija, Vikas; Chamola, Vinay; Guizani, Mohsen ( Association for Computing Machinery , 2021 , Conference Paper)
      Generally when users share information about themselves on some online platforms, they knowingly or unknowingly allow this data to be used by the companies behind these companies for various purposes including selling this ...
    • Machine-Learning-Aided Optical Fiber Communication System 

      Pan, X.; Wang, Xishuo; Tian, Bo; Wang, Chuxuan; Zhang, Hongxin; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)
      The fiber optical network offers high speed, large bandwidth, and a high degree of reliability. However, the development of optical communication technology has hit a bottleneck due to several challenges such as energy ...
    • Machine-Learning-Based Efficient and Secure RSU Placement Mechanism for Software-Defined-IoV 

      Anbalagan, Sudha; Bashir, Ali Kashif; Raja, Gunasekaran; Dhanasekaran, Priyanka; Vijayaraghavan, Geetha; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)
      The massive increase in computing and network capabilities has resulted in a paradigm shift from vehicular networks to the Internet of Vehicles (IoV). Owing to the dynamic and heterogeneous nature of IoV, it requires ...
    • Machine-to-Machine (M2M) communications: A survey 

      Verma, Pawan Kumar; Verma, Rajesh; Prakash, Arun; Agrawal, Ashish; Naik, Kshirasagar; ... more authors ( Academic Press , 2016 , Article Review)
      Machine-to-Machine (M2M) communication is a promising technology for next generation communication systems. This communication paradigm facilitates ubiquitous communications with full mechanical automation, where a large ...