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A. Manju¹, A. Revathi², M. Arivukarasi¹, S. Hariharan³, V. Umarani⁴, Shih-Yu Chen^5,*, 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 >

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Wenbo Li, Qi Wang^*, Shang Gao
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 921-938, 2023, DOI:10.32604/iasc.2023.038257
（This article belongs to the Special Issue: Optimization Algorithm for Intelligent Computing Application)
Abstract Infrared target detection models are more required than ever before to be deployed on embedded platforms, which requires models with less memory consumption and better real-time performance while considering accuracy. To address the above challenges, we propose a modified You Only Look Once (YOLO) algorithm PF-YOLOv4-Tiny. The algorithm incorporates spatial pyramidal pooling (SPP) and squeeze-and-excitation (SE) visual attention modules to enhance the target localization capability. The PANet-based-feature pyramid networks (P-FPN) are proposed to transfer semantic information and location information simultaneously to ameliorate detection accuracy. To lighten the network, the standard convolutions other than the backbone network are replaced with depthwise… More >

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Alia Alshehri, Duaa AlSaeed^*
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 939-970, 2023, DOI:10.32604/iasc.2023.037096
Abstract One of the most prevalent cancers in women is breast cancer. Early and accurate detection can decrease the mortality rate associated with breast cancer. Governments and health organizations emphasize the significance of early breast cancer screening since it is associated to a greater variety of available treatments and a higher chance of survival. Patients have the best chance of obtaining effective treatment when they are diagnosed early. The detection and diagnosis of breast cancer have involved using various image types and imaging modalities. Breast “infrared thermal” imaging is one of the imaging modalities., a screening instrument used to measure the… More >

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389

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Zhipeng Bin¹, Huihuang Zhao^1,2,*, Xiaoman Liang^1,2, Wenli Chen¹
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 971-983, 2023, DOI:10.32604/iasc.2023.037270
Abstract The main challenges in face swapping are the preservation and adaptive superimposition of attributes of two images. In this study, the Face Swapping Attention Network (FSA-Net) is proposed to generate photorealistic face swapping. The existing face-swapping methods ignore the blending attributes or mismatch the facial keypoint (cheek, mouth, eye, nose, etc.), which causes artifacts and makes the generated face silhouette non-realistic. To address this problem, a novel reinforced multi-aware attention module, referred to as RMAA, is proposed for handling facial fusion and expression occlusion flaws. The framework includes two stages. In the first stage, a novel attribute encoder is proposed… More >

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Rakhshan Zulfiqar^1,2, Tariq Javed¹, Zain Anwar Ali^2,*, Eman H. Alkhammash³, Myriam Hadjouni⁴
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 985-1000, 2023, DOI:10.32604/iasc.2023.037248
Abstract The deployment of sensor nodes is an important aspect in mobile wireless sensor networks for increasing network performance. The longevity of the networks is mostly determined by the proportion of energy consumed and the sensor nodes’ access network. The optimal or ideal positioning of sensors improves the portable sensor networks effectiveness. Coverage and energy usage are mostly determined by successful sensor placement strategies. Nature-inspired algorithms are the most effective solution for short sensor lifetime. The primary objective of work is to conduct a comparative analysis of nature-inspired optimization for wireless sensor networks (WSNs’) maximum network coverage. Moreover, it identifies quantity… More >

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P. Venkatesh^1,*, N. Visali²
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1001-1012, 2023, DOI:10.32604/iasc.2023.036268
Abstract In the conventional technique, in the evaluation of the severity index, clustering and loading suffer from more iteration leading to more computational delay. Hence this research article identifies, a novel progression for fast predicting the severity of the line and clustering by incorporating machine learning aspects. The polynomial load modelling or ZIP (constant impedances (Z), Constant Current (I) and Constant active power (P)) is developed in the IEEE-14 and Indian 118 bus systems considered for analysis of power system security. The process of finding the severity of the line using a Hybrid Line Stability Ranking Index (HLSRI) is used for… More >

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S. Deva Kumar, S. Venkatramaphanikumar^*, K. Venkata Krishna Kishore
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1013-1032, 2023, DOI:10.32604/iasc.2023.038165
Abstract Type 2 diabetes patients often suffer from microvascular complications of diabetes. These complications, in turn, often lead to vision impairment. Diabetic Retinopathy (DR) detection in its early stage can rescue people from long-term complications that could lead to permanent blindness. In this study, we propose a complex deep convolutional neural network architecture with an inception module for automated diagnosis of DR. The proposed novel Hybrid Inception U-Net (HIUNET) comprises various inception modules connected in the U-Net fashion using activation maximization and filter map to produce the image mask. First, inception blocks were used to enlarge the model’s width by substituting… More >

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328

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Kunfu Wang, Yongsheng Hao, Jie Cao^*
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1033-1052, 2023, DOI:10.32604/iasc.2023.038036
Abstract Meteorological model tasks require considerable meteorological basis data to support their execution. However, if the task and the meteorological datasets are located on different clouds, that enhances the cost, execution time, and energy consumption of execution meteorological tasks. Therefore, the data layout and task scheduling may work together in the meteorological cloud to avoid being in various locations. To the best of our knowledge, this is the first paper that tries to schedule meteorological tasks with the help of the meteorological data set layout. First, we use the FP-Growth-M (frequent-pattern growth for meteorological model datasets) method to mine the relationship… More >

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296

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Shen Guo^*, Jiaying Lin, Shuaitao Bai, Jichuan Zhang, Peng Wang
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1053-1066, 2023, DOI:10.32604/iasc.2023.038332
Abstract The main function of the power communication business is to monitor, control and manage the power communication network to ensure normal and stable operation of the power communication network. Communication services related to dispatching data networks and the transmission of fault information or feeder automation have high requirements for delay. If processing time is prolonged, a power business cascade reaction may be triggered. In order to solve the above problems, this paper establishes an edge object-linked agent business deployment model for power communication network to unify the management of data collection, resource allocation and task scheduling within the system, realizes… More >

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323

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Qiang Xu^*, Wei Zhang, Hui Ding, Shengwei Ji
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1067-1080, 2023, DOI:10.32604/iasc.2023.037599
Abstract Currently, the amount of sports news is increasing, given the number of sports available. As a result, manually writing sports news requires high labor costs to achieve the intended efficiency. Therefore, it is necessary to develop the automatic generation of sports news. Most available news generation methods mainly rely on real-time commentary sentences, which have the following limitations: (1) unable to select suitable commentary sentences for news generation, and (2) the generated sports news could not accurately describe game events. Therefore, this study proposes a sports news generation with text-editing model (SNG-TE) is proposed to generate sports news, which includes… More >

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465

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Manjiang Xing^*
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1081-1090, 2023, DOI:10.32604/iasc.2023.034750
Abstract At present, the database cache model of power information system has problems such as slow running speed and low database hit rate. To this end, this paper proposes a database cache model for power information systems based on deep machine learning. The caching model includes program caching, Structured Query Language (SQL) preprocessing, and core caching modules. Among them, the method to improve the efficiency of the statement is to adjust operations such as multi-table joins and replacement keywords in the SQL optimizer. Build predictive models using boosted regression trees in the core caching module. Generate a series of regression tree… More >

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Shekaina Justin^1,*, Wafaa Saleh^1,2, Tasneem Al Ghamdi¹, J. Shermina³
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1091-1109, 2023, DOI:10.32604/iasc.2023.032589
Abstract Renewable energy has become a solution to the world’s energy concerns in recent years. Photovoltaic (PV) technology is the fastest technique to convert solar radiation into electricity. Solar-powered buses, metros, and cars use PV technology. Such technologies are always evolving. Included in the parameters that need to be analysed and examined include PV capabilities, vehicle power requirements, utility patterns, acceleration and deceleration rates, and storage module type and capacity, among others. PVPG is intermittent and weather-dependent. Accurate forecasting and modelling of PV system output power are key to managing storage, delivery, and smart grids. With unparalleled data granularity, a data-driven… More >

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346

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M. Muthukumar¹, Rajasekar Rangasamy², Irshad Hussain^3,4, Salman A. AlQahtani^4,*
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1111-1127, 2023, DOI:10.32604/iasc.2023.034369
Abstract The purpose of this article is to propose Stability-based Energy-Efficient Link-State Hybrid Routing (S-ELHR), a low latency routing protocol that aims to provide a stable mechanism for routing in unmanned aerial vehicles (UAV). The S-ELHR protocol selects a number of network nodes to create a Connected Dominating Set (CDS) using a parameter known as the Stability Metric (SM). The SM considers the node’s energy usage, connectivity time, and node’s degree. Only the highest SM nodes are chosen to form CDS. Each node declares a Willingness to indicate that it is prepared to serve as a relay for its neighbors, by… More >

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316

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R. D. Dhaniya¹, K. M. Umamaheswari^2,*
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1129-1143, 2023, DOI:10.32604/iasc.2023.035905
Abstract Current revelations in medical imaging have seen a slew of computer-aided diagnostic (CAD) tools for radiologists developed. Brain tumor classification is essential for radiologists to fully support and better interpret magnetic resonance imaging (MRI). In this work, we reported on new observations based on binary brain tumor categorization using HYBRID CNN-LSTM. Initially, the collected image is pre-processed and augmented using the following steps such as rotation, cropping, zooming, CLAHE (Contrast Limited Adaptive Histogram Equalization), and Random Rotation with panoramic stitching (RRPS). Then, a method called particle swarm optimization (PSO) is used to segment tumor regions in an MR image. After… More >

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339

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H. Shalma, P. Selvaraj^*
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1145-1161, 2023, DOI:10.32604/iasc.2023.036853
Abstract The creation of the 3D rendering model involves the prediction of an accurate depth map for the input images. A proposed approach of a modified semi-global block matching algorithm with variable window size and the gradient assessment of objects predicts the depth map. 3D modeling and view synthesis algorithms could effectively handle the obtained disparity maps. This work uses the consistency check method to find an accurate depth map for identifying occluded pixels. The prediction of the disparity map by semi-global block matching has used the benchmark dataset of Middlebury stereo for evaluation. The improved depth map quality within a… More >

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312

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Suhang Li¹, Yunzuo Zhang^1,*, Ruixue Liu², Jiayu Zhang¹, Zhouchen Song¹, Yutai Wang¹
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1163-1180, 2023, DOI:10.32604/iasc.2023.037902
Abstract The communication system of high-speed trains in railway tunnels needs to be built with leaky cables fixed on the tunnel wall with special fixtures. To ensure safety, checking the regular leaky cable fixture is necessary to eliminate the potential danger. At present, the existing fixture detection algorithms are difficult to take into account detection accuracy and speed at the same time. The faulty fixture is also insufficient and difficult to obtain, seriously affecting the model detection effect. To solve these problems, an innovative detection method is proposed in this paper. Firstly, we presented the Res-Net and Wasserstein-Deep Convolution GAN (RW-DCGAN)… More >

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Wei Sun¹, Zhanhe Du^2,*
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1181-1195, 2023, DOI:10.32604/iasc.2023.037497
Abstract Currently, it is difficult to extract the depth feature of the frontal emergency stops dangerous activity signal, which leads to a decline in the accuracy and efficiency of the frontal emergency stops the dangerous activity. Therefore, a recognition for frontal emergency stops dangerous activity algorithm based on Nano Internet of Things Sensor (NIoTS) and transfer learning is proposed. First, the NIoTS is installed in the athlete’s leg muscles to collect activity signals. Second, the noise component in the activity signal is removed using the de-noising method based on mathematical morphology. Finally, the depth feature of the activity signal is extracted… More >

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290

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Babu H. Soumya^1,*, N. Vijayakumar², K. Gopakumar³
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1197-1207, 2023, DOI:10.32604/iasc.2023.031575
Abstract The Henon map forms one of the most-studied two-dimensional discrete-time dynamical systems that exhibits chaotic behavior. The Henon map takes a point in the plane and maps it to a new point . In this paper, a chaotic pulse generator based on the chaotic Henon map is proposed. It consists of a Henon map function subcircuit to realize the Henon map and another subcircuit to perform the iterative operation. The Henon map subcircuit comprises operational amplifiers, multipliers, delay elements and resistors, whereas, the iterative subcircuit is implemented with a simple design that comprises of an edge forming circuit followed by… More >

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309

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Hasan Han¹, Oguzcan Karadeniz¹, Tugba Dalyan^2,*, Elena Battini Sonmez², Baykal Sarioglu¹
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1209-1224, 2023, DOI:10.32604/iasc.2023.030674
Abstract Robot companions will soon be part of our everyday life and students in the engineering faculty must be trained to design, build, and interact with them. The two affordable robots presented in this paper have been designed and constructed by two undergraduate students; one artificial agent is based on the Nvidia Jetson Nano development board and the other one on a remote computer system. Moreover, the robots have been refined with an empathetic system, to make them more user-friendly. Since automatic facial expression recognition skills is a necessary pre-processing step for acknowledging emotions, this paper tested different variations of Convolutional… More >

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410

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Payal Soni, J. Subhashini^*
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1225-1242, 2023, DOI:10.32604/iasc.2023.038155
Abstract In the current context, a smart grid has replaced the conventional grid through intelligent energy management, integration of renewable energy sources (RES) and two-way communication infrastructures from power generation to distribution. Energy management from the distribution side is a critical problem for balancing load demand. A unique energy management strategy (EMS) is being developed for office building equipment. That includes renewable energy integration, automation, and control based on the Artificial Neural Network (ANN) system using Matlab Simulink. This strategy reduces electric power consumption and balances the load demand of the traditional grid. This strategy is developed by taking inputs from… More >

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