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  • Open Access

    ARTICLE

    News Modeling and Retrieving Information: Data-Driven Approach

    Elias Hossain1, Abdullah Alshahrani2, Wahidur Rahman3,*

    Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 109-123, 2023, DOI:10.32604/iasc.2022.029511

    Abstract This paper aims to develop Machine Learning algorithms to classify electronic articles related to this phenomenon by retrieving information and topic modelling. The Methodology of this study is categorized into three phases: the Text Classification Approach (TCA), the Proposed Algorithms Interpretation (PAI), and finally, Information Retrieval Approach (IRA). The TCA reflects the text preprocessing pipeline called a clean corpus. The Global Vectors for Word Representation (Glove) pre-trained model, FastText, Term Frequency-Inverse Document Frequency (TF-IDF), and Bag-of-Words (BOW) for extracting the features have been interpreted in this research. The PAI manifests the Bidirectional Long Short-Term Memory (Bi-LSTM) and Convolutional Neural Network… More >

  • Open Access

    ARTICLE

    Interval Type-2 Fuzzy Model for Intelligent Fire Intensity Detection Algorithm with Decision Making in Low-Power Devices

    Emmanuel Lule1,2,*, Chomora Mikeka3, Alexander Ngenzi4, Didacienne Mukanyiligira5

    Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 57-81, 2023, DOI:10.32604/iasc.2023.037988

    Abstract Local markets in East Africa have been destroyed by raging fires, leading to the loss of life and property in the nearby communities. Electrical circuits, arson, and neglected charcoal stoves are the major causes of these fires. Previous methods, i.e., satellites, are expensive to maintain and cause unnecessary delays. Also, unit-smoke detectors are highly prone to false alerts. In this paper, an Interval Type-2 TSK fuzzy model for an intelligent lightweight fire intensity detection algorithm with decision-making in low-power devices is proposed using a sparse inference rules approach. A free open–source MATLAB/Simulink fuzzy toolbox integrated into MATLAB 2018a is used… More >

  • Open Access

    ARTICLE

    A Method of Integrating Length Constraints into Encoder-Decoder Transformer for Abstractive Text Summarization

    Ngoc-Khuong Nguyen1,2, Dac-Nhuong Le1, Viet-Ha Nguyen2, Anh-Cuong Le3,*

    Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 1-18, 2023, DOI:10.32604/iasc.2023.037083

    Abstract Text summarization aims to generate a concise version of the original text. The longer the summary text is, the more detailed it will be from the original text, and this depends on the intended use. Therefore, the problem of generating summary texts with desired lengths is a vital task to put the research into practice. To solve this problem, in this paper, we propose a new method to integrate the desired length of the summarized text into the encoder-decoder model for the abstractive text summarization problem. This length parameter is integrated into the encoding phase at each self-attention step and… More >

  • Open Access

    ARTICLE

    Person Re-Identification with Model-Contrastive Federated Learning in Edge-Cloud Environment

    Baixuan Tang1,2,#, Xiaolong Xu1,2,#, Fei Dai3, Song Wang4,*

    Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 35-55, 2023, DOI:10.32604/iasc.2023.036715

    Abstract Person re-identification (ReID) aims to recognize the same person in multiple images from different camera views. Training person ReID models are time-consuming and resource-intensive; thus, cloud computing is an appropriate model training solution. However, the required massive personal data for training contain private information with a significant risk of data leakage in cloud environments, leading to significant communication overheads. This paper proposes a federated person ReID method with model-contrastive learning (MOON) in an edge-cloud environment, named FRM. Specifically, based on federated partial averaging, MOON warmup is added to correct the local training of individual edge servers and improve the model’s… More >

  • Open Access

    ARTICLE

    Hash Table Assisted Efficient File Level De-Duplication Scheme in SD-IoV Assisted Sensing Devices

    Ghawar Said1, Ata Ullah2, Anwar Ghani1,*, Muhammad Azeem1, Khalid Yahya3, Muhammad Bilal4, Sayed Chhattan Shah5,*

    Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 83-99, 2023, DOI:10.32604/iasc.2023.036079

    Abstract The Internet of Things (IoT) and cloud technologies have encouraged massive data storage at central repositories. Software-defined networks (SDN) support the processing of data and restrict the transmission of duplicate values. It is necessary to use a data de-duplication mechanism to reduce communication costs and storage overhead. Existing State of the art schemes suffer from computational overhead due to deterministic or random tree-based tags generation which further increases as the file size grows. This paper presents an efficient file-level de-duplication scheme (EFDS) where the cost of creating tags is reduced by employing a hash table with key-value pair for each… More >

  • Open Access

    ARTICLE

    Binary Archimedes Optimization Algorithm for Computing Dominant Metric Dimension Problem

    Basma Mohamed1,*, Linda Mohaisen2, Mohammed Amin1

    Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 19-34, 2023, DOI:10.32604/iasc.2023.031947

    Abstract In this paper, we consider the NP-hard problem of finding the minimum dominant resolving set of graphs. A vertex set B of a connected graph G resolves G if every vertex of G is uniquely identified by its vector of distances to the vertices in B. A resolving set is dominating if every vertex of G that does not belong to B is a neighbor to some vertices in B. The dominant metric dimension of G is the cardinality number of the minimum dominant resolving set. The dominant metric dimension is computed by a binary version of the Archimedes optimization… More >

  • Open Access

    RETRACTION

    Retraction: Precise Rehabilitation Strategies for Functional Impairment in Children with Cerebral Palsy

    Yaojin Sun1, Nan Jiang1,*, Min Zhu1, Hao Hua2

    Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 105-105, 2023, DOI:10.32604/iasc.2023.047522

    Abstract This article has no abstract. More >

  • Open Access

    CORRECTION

    Correction: Stock Market Index Prediction Using Machine Learning and Deep Learning Techniques

    Abdus Saboor1,4, Arif Hussain2, Bless Lord Y. Agbley3, Amin ul Haq3,*, Jian Ping Li3, Rajesh Kumar1,*

    Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 107-107, 2023, DOI:10.32604/iasc.2023.047463

    Abstract This article has no abstract. More >

  • Open Access

    RETRACTION

    Retraction: Fluid Flow and Mixed Heat Transfer in a Horizontal Channel with an Open Cavity and Wavy Wall

    Tohid Adibi1, Shams Forruque Ahmed2,*, Omid Adibi3, Hassan Athari4, Irfan Anjum Badruddin5, Syed Javed5

    Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 103-103, 2023, DOI:10.32604/iasc.2023.047521

    Abstract This article has no abstract. More >

  • Open Access

    RETRACTION

    Retraction: Marketing Model Analysis of Fashion Communication Based on the Visual Analysis of Neutrosophic Systems

    Fangyu Ye1, Xiaoshu Xu2,*, Yunfeng Zhang3, Yan Ye4, Jingyu Dai5,*

    Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 101-101, 2023, DOI:10.32604/iasc.2023.045930

    Abstract This article has no abstract. More >

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