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  • Open Access


    Ensemble Deep Learning Framework for Situational Aspects-Based Annotation and Classification of International Student’s Tweets during COVID-19

    Shabir Hussain1, Muhammad Ayoub2, Yang Yu1, Junaid Abdul Wahid1, Akmal Khan3, Dietmar P. F. Moller4, Hou Weiyan1,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5355-5377, 2023, DOI:10.32604/cmc.2023.036779

    Abstract As the COVID-19 pandemic swept the globe, social media platforms became an essential source of information and communication for many. International students, particularly, turned to Twitter to express their struggles and hardships during this difficult time. To better understand the sentiments and experiences of these international students, we developed the Situational Aspect-Based Annotation and Classification (SABAC) text mining framework. This framework uses a three-layer approach, combining baseline Deep Learning (DL) models with Machine Learning (ML) models as meta-classifiers to accurately predict the sentiments and aspects expressed in tweets from our collected Student-COVID-19 dataset. Using the proposed aspect2class annotation algorithm, we… More >

  • Open Access


    Human Factors While Using Head-Up-Display in Low Visibility Flying Conditions

    Jhulan Kumar1,2, Surender Singh Saini1,2, Divya Agrawal1,2, Vinod Karar1,2,*, Aman Kataria2

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2411-2423, 2023, DOI:10.32604/iasc.2023.034203

    Abstract Flying an aircraft in low visibility is still a challenging task for the pilot. It requires precise and accurate situational awareness (SA) in real-time. A Head-up Display (HUD) is used to project collimated internal and external flight information on a transparent screen in the pilot’s forward field of view, which eliminates the change of eye position between Head-Down-Display (HDD) instruments and outer view through the windshield. Implementation of HUD increases the SA and reduces the workload for the pilot. But to provide a better flying capability for the pilot, projecting extensive information on HUD causes human factor issues that reduce… More >

  • Open Access


    Context-Aware Service Model of a Mobile Library Based on Internet of Things

    Wei Gao1, Haixu Xi1,2,*, Gyun Yeol Park3

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1893-1906, 2022, DOI:10.32604/iasc.2022.023207

    Abstract Appropriate technology needs to be applied in libraries to provide users with more humanized, intelligent, and convenient services to improve service quality. Using theories from library science, management, and modeling, this paper examines library personalized service in the intelligent Internet of Things (IoT) environment using a literature review, comparative analysis, and UML modeling to analyze the influencing factors of mobile library users’ acceptance of personalized recommendation services. Based on the situational awareness framework, the experimental results of the effect of these personalized service recommendations show that the load factor is greater than 0.6, which indicates that the dimensions of a… More >

  • Open Access


    Situation Awareness Data Fusion Method Based on Library Events

    Haixu Xi1,2, Wei Gao2,*, Gyun Yeol Park3

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1047-1061, 2022, DOI:10.32604/csse.2022.022051

    Abstract Microelectronic technology and communication technology are developed in deep manner; the computing mode has been transferred from traditional computer-centered to human centered pervasive. So, the concept of Internet of things (IoT) is gradually put forward, which allows people to access information about their surroundings on demand through different terminals. The library is the major public space for human to read and learn. How to provide a more comfortable library environment to better meet people’s learning requirements is a place where the Internet of things plays its role. The purpose of this paper is to solve the difference between the data… More >

  • Open Access


    A Broadcast Storm Detection and Treatment Method Based on Situational Awareness

    Zhe Zhu1, Mingjian Zhang2, Yong Liu1, Lan Ma1, Xin Liu1,*

    Journal of Information Hiding and Privacy Protection, Vol.3, No.1, pp. 47-54, 2021, DOI:10.32604/jihpp.2021.016690

    Abstract At present, the research of blockchain is very popular, but the practical application of blockchain is very few. The main reason is that the concurrency of blockchain is not enough to support application scenarios. After that, applications such as Intervalue increase the concurrency of blockchain transactions. However, due to the problems of network bandwidth and algorithm performance, there is always a broadcast storm, which affects the normal use of nodes in the whole network. However, the emergence of broadcast storms needs to rely on the node itself, which may be very slow. Even if developers debug the corresponding code, they… More >

  • Open Access


    Research on Prediction Methods of Prevalence Perception under Information Exposure

    Weijin Jiang1, 2, 3, 4, Fang Ye1, 2, *, Wei Liu2, 3, Xiaoliang Liu1, 2, Guo Liang5, Yuhui Xu2, 3, Lina Tan1, 2

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2263-2275, 2020, DOI:10.32604/cmc.2020.010082

    Abstract With the rapid development of information technology, the explosive growth of data information has become a common challenge and opportunity. Social network services represented by WeChat, Weibo and Twitter, drive a large amount of information due to the continuous spread, evolution and emergence of users through these platforms. The dynamic modeling, analysis, and network information prediction, has very important research and application value, and plays a very important role in the discovery of popular events, personalized information recommendation, and early warning of bad information. For these reasons, this paper proposes an adaptive prediction algorithm for network information transmission. A popularity… More >

  • Open Access


    Modeling Impacts on Space Situational Awareness PHD Filter Tracking

    C. Frueh1

    CMES-Computer Modeling in Engineering & Sciences, Vol.111, No.2, pp. 171-201, 2016, DOI:10.3970/cmes.2016.111.171

    Abstract In recent years, probabilistic tracking methods have been becoming increasingly popular for solving the multi-target tracking problem in Space Situational Awareness (SSA). Bayesian frameworks have been used to describe the objects' of interest states and cardinality as point processes. The inputs of the Bayesian framework filters are a probabilistic description of the scene at hand, the probability of clutter during the observation, the probability of detection of the objects, the probability of object survival and birth rates, and in the state update, the measurement uncertainty and process noise for the propagation. However, in the filter derivation, the assumptions of Poisson… More >

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