Browsing Computer Science & Engineering by Title
Now showing items 1351-1370 of 2262
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Low complexity closed-loop strategy for mmWave communication in industrial intelligent systems
( John Wiley and Sons Ltd , 2022 , Article)Modern communication and computing technology is the basic support of the industrial intelligent systems (IIS). As a key component of IIS, the smart port is essential to be offered low-complexity and high-reliability ... -
Low complexity target coverage heuristics using mobile cameras
( Institute of Electrical and Electronics Engineers Inc. , 2015 , Conference Paper)Wireless sensor and actuator networks have been extensively deployed for enhancing industrial control processes and supply-chains, and many forms of surveillance and environmental monitoring. The availability of low-cost ... -
Low-quality facial biometric verification via dictionary-based random pooling
( Elsevier Ltd , 2016 , Article)In the past decade, visual surveillance has emerged as an effective tool in public security applications. Due to the technical limitations of both surveillance cameras and transmission speed, videos collected from surveillance ... -
LWKPCA: A New Robust Method for Face Recognition Under Adverse Conditions
( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2022 , Article)Over the last two decades, face recognition (FR) has become one of the most prevailing biometric applications for effective people identification as it offers practical advantages over other biometric modalities. However, ... -
M-LEARNING FOR TRAINING ENGLISH AT WORKPLACE
( 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
( 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
( 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
( 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
( 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
( 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
( 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
( 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
( 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
( 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
( 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
( 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
( 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
( 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
( 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
( 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 ...