Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (13)
  • Open Access

    ARTICLE

    Fuzzy Rule-Based Model to Train Videos in Video Surveillance System

    A. Manju1, A. Revathi2, M. Arivukarasi1, S. Hariharan3, V. Umarani4, Shih-Yu Chen5,*, Jin Wang6

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 905-920, 2023, DOI:10.32604/iasc.2023.038444

    Abstract With the proliferation of the internet, big data continues to grow exponentially, and video has become the largest source. Video big data introduces many technological challenges, including compression, storage, transmission, analysis, and recognition. The increase in the number of multimedia resources has brought an urgent need to develop intelligent methods to organize and process them. The integration between Semantic link Networks and multimedia resources provides a new prospect for organizing them with their semantics. The tags and surrounding texts of multimedia resources are used to measure their semantic association. Two evaluation methods including clustering and retrieval are performed to measure… More >

  • Open Access

    ARTICLE

    A Novel Belief Rule-Based Fault Diagnosis Method with Interpretability

    Zhijie Zhou1, Zhichao Ming1,*, Jie Wang1, Shuaiwen Tang1, You Cao1, Xiaoxia Han1, Gang Xiang2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1165-1185, 2023, DOI:10.32604/cmes.2023.025399

    Abstract Fault diagnosis plays an irreplaceable role in the normal operation of equipment. A fault diagnosis model is often required to be interpretable for increasing the trust between humans and the model. Due to the understandable knowledge expression and transparent reasoning process, the belief rule base (BRB) has extensive applications as an interpretable expert system in fault diagnosis. Optimization is an effective means to weaken the subjectivity of experts in BRB, where the interpretability of BRB may be weakened. Hence, to obtain a credible result, the weakening factors of interpretability in the BRB-based fault diagnosis model are firstly analyzed, which are… More > Graphic Abstract

    A Novel Belief Rule-Based Fault Diagnosis Method with Interpretability

  • Open Access

    ARTICLE

    A Rule-Based Approach for Grey Hole Attack Prediction in Wireless Sensor Networks

    C. Gowdham*, S. Nithyanandam

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3815-3827, 2023, DOI:10.32604/iasc.2023.031876

    Abstract The Wireless Sensor Networks (WSN) are vulnerable to assaults due to the fact that the devices connected to them have a reliable connection to the internet. A malicious node acts as the controller and uses a grey hole attack to get the data from all of the other nodes in the network. Additionally, the nodes are discarding and modifying the data packets according to the requirements of the system. The assault modifies the fundamental concept of the WSNs, which is that different devices should communicate with one another. In the proposed system, there is a fuzzy idea offered for the… More >

  • Open Access

    ARTICLE

    Multi Layered Rule-Based Technique for Explicit Aspect Extraction from Online Reviews

    Mubashar Hussain1, Toqir A. Rana2,3, Aksam Iftikhar4, M. Usman Ashraf5,*, Muhammad Waseem Iqbal6, Ahmed Alshaflut7, Abdullah Alourani8

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4641-4656, 2022, DOI:10.32604/cmc.2022.024759

    Abstract In the field of sentiment analysis, extracting aspects or opinion targets from user reviews about a product is a key task. Extracting the polarity of an opinion is much more useful if we also know the targeted Aspect or Feature. Rule based approaches, like dependency-based rules, are quite popular and effective for this purpose. However, they are heavily dependent on the authenticity of the employed parts-of-speech (POS) tagger and dependency parser. Another popular rule based approach is to use sequential rules, wherein the rules formulated by learning from the user’s behavior. However, in general, the sequential rule-based approaches have poor… More >

  • Open Access

    ARTICLE

    Employing Lexicalized Dependency Paths for Active Learning of Relation Extraction

    Huiyu Sun*, Ralph Grishman

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1415-1423, 2022, DOI:10.32604/iasc.2022.030794

    Abstract Active learning methods which present selected examples from the corpus for annotation provide more efficient learning of supervised relation extraction models, but they leave the developer in the unenviable role of a passive informant. To restore the developer’s proper role as a partner with the system, we must give the developer an ability to inspect the extraction model during development. We propose to make this possible through a representation based on lexicalized dependency paths (LDPs) coupled with an active learner for LDPs. We apply LDPs to both simulated and real active learning with ACE as evaluation and a year’s newswire… More >

  • Open Access

    ARTICLE

    Lexicalized Dependency Paths Based Supervised Learning for Relation Extraction

    Huiyu Sun*, Ralph Grishman

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 861-870, 2022, DOI:10.32604/csse.2022.030759

    Abstract Log-linear models and more recently neural network models used for supervised relation extraction requires substantial amounts of training data and time, limiting the portability to new relations and domains. To this end, we propose a training representation based on the dependency paths between entities in a dependency tree which we call lexicalized dependency paths (LDPs). We show that this representation is fast, efficient and transparent. We further propose representations utilizing entity types and its subtypes to refine our model and alleviate the data sparsity problem. We apply lexicalized dependency paths to supervised learning using the ACE corpus and show that… More >

  • Open Access

    ARTICLE

    A New Color Model for Fire Pixels Detection in PJF Color Space

    Amal Ben Hamida1,*, Chokri Ben Amar2, Yasser Albagory2

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1607-1621, 2022, DOI:10.32604/iasc.2022.024939

    Abstract Since the number of fires in the world is rising rapidly, automatic fire detection is getting more and more interest in computer vision community. Instead of the usual inefficient sensors, captured videos by video surveillance cameras can be analyzed to quickly detect fires and prevent damages. This paper presents an early fire-alarm raising method based on image processing. The developed work is able to discriminate fire and non-fire pixels. Fire pixels are identified thanks to a rule-based color model built in the PJF color space. PJF is a newly designed color space that enables to better reflect the structure of… More >

  • Open Access

    ARTICLE

    Rule-Based Anomaly Detection Model with Stateful Correlation Enhancing Mobile Network Security

    Rafia Afzal, Raja Kumar Murugesan*

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1825-1841, 2022, DOI:10.32604/iasc.2022.020598

    Abstract The global Signalling System No. 7 (SS7) network protocol standard has been developed and regulated based only on trusted partner networks. The SS7 network protocol by design neither secures the communication channel nor verifies the entire network peers. The SS7 network protocol used in telecommunications has deficiencies that include verification of actual subscribers, precise location, subscriber’s belonging to a network, absence of illegitimate message filtering mechanism, and configuration deficiencies in home routing networks. Attackers can take advantage of these deficiencies and exploit them to impose threats such as subscriber or network data disclosure, intercept mobile traffic, perform account frauds, track… More >

  • Open Access

    ARTICLE

    Intelligent Identification and Resolution of Software Requirement Conflicts: Assessment and Evaluation

    Maysoon Aldekhail1, Marwah Almasri2,*

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 469-489, 2022, DOI:10.32604/csse.2022.018269

    Abstract Considerable research has demonstrated how effective requirements engineering is critical for the success of software projects. Requirements engineering has been established and recognized as one of the most important aspects of software engineering as of late. It is noteworthy to mention that requirement consistency is a critical factor in project success, and conflicts in requirements lead to waste of cost, time, and effort. A considerable number of research studies have shown the risks and problems caused by working with requirements that are in conflict with other requirements. These risks include running overtime or over budget, which may lead to project… More >

  • Open Access

    ARTICLE

    Alzheimer’s Disease Diagnosis Based on a Semantic Rule-Based Modeling and Reasoning Approach

    Nora Shoaip1, Amira Rezk1, Shaker EL-Sappagh2,3, Tamer Abuhmed4,*, Sherif Barakat1, Mohammed Elmogy5

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3531-3548, 2021, DOI:10.32604/cmc.2021.019069

    Abstract Alzheimer’s disease (AD) is a very complex disease that causes brain failure, then eventually, dementia ensues. It is a global health problem. 99% of clinical trials have failed to limit the progression of this disease. The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms. Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction. In this regard, the need becomes more urgent for biomarker-based detection. A key issue in understanding AD is the need to solve complex and high-dimensional… More >

Displaying 1-10 on page 1 of 13. Per Page