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ARTICLE

Ngoc-Khuong Nguyen^1,2, Dac-Nhuong Le¹, Viet-Ha Nguyen², Anh-Cuong Le^3,*
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 >

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ARTICLE

Basma Mohamed^1,*, Linda Mohaisen², Mohammed Amin¹
Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 19-34, 2023, DOI:10.32604/iasc.2023.031947
（This article belongs to the Special Issue: Soft Computing Methods for Intelligent Automation Systems)
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 >

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111

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ARTICLE

Baixuan Tang^1,2,#, Xiaolong Xu^1,2,#, Fei Dai³, Song Wang^4,*
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 >

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114

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Emmanuel Lule^1,2,*, 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 >

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131

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Ghawar Said¹, Ata Ullah², Anwar Ghani^1,*, Muhammad Azeem¹, Khalid Yahya³, Muhammad Bilal⁴, Sayed Chhattan Shah^5,*
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 >

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Fangyu Ye¹, Xiaoshu Xu^2,*, Yunfeng Zhang³, Yan Ye⁴, Jingyu Dai^5,*
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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165

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Tohid Adibi¹, Shams Forruque Ahmed^2,*, 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 >

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509

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166

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Yaojin Sun¹, Nan Jiang^1,*, 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 >

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146

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Abdus Saboor^1,4, Arif Hussain², Bless Lord Y. Agbley³, Amin ul Haq^3,*, Jian Ping Li³, Rajesh Kumar^1,*
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 >

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