C. Thiruvengadam^1,*, M. Palanivelan²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2803-2818, 2023, DOI:10.32604/iasc.2023.030493 - 15 March 2023

Abstract There are numerous goals in next-generation cellular networks (5G), which is expected to be available soon. They want to increase data rates, reduce end-to-end latencies, and improve end-user service quality. Modern networks need to change because there has been a significant rise in the number of base stations required to meet these needs and put the operators’ low-cost constraints to the test. Because it can withstand interference from other wireless networks, and Adaptive Complex Multicarrier Modulation (ACMM) system is being looked at as a possible choice for the 5th Generation (5G) of wireless networks. Many… More >

Xiaoyan Zhao^1,*, Lin Zhou², Yue Xie¹, Ying Tong¹, Jingang Shi³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3087-3100, 2023, DOI:10.32604/iasc.2023.030180 - 15 March 2023

Abstract Speech separation is an active research topic that plays an important role in numerous applications, such as speaker recognition, hearing prosthesis, and autonomous robots. Many algorithms have been put forward to improve separation performance. However, speech separation in reverberant noisy environment is still a challenging task. To address this, a novel speech separation algorithm using gate recurrent unit (GRU) network based on microphone array has been proposed in this paper. The main aim of the proposed algorithm is to improve the separation performance and reduce the computational cost. The proposed algorithm extracts the sub-band steered… More >

Quan Yan¹, Yunfan Ye¹, Jing Xia¹, Zhiping Cai^1,*, Zhilin Wang², Qiang Ni³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2545-2558, 2023, DOI:10.32604/iasc.2023.029857 - 15 March 2023

Abstract Computed tomography has made significant advances since its introduction in the early 1970s, where researchers have mainly focused on the quality of image reconstruction in the early stage. However, radiation exposure poses a health risk, prompting the demand of the lowest possible dose when carrying out CT examinations. To acquire high-quality reconstruction images with low dose radiation, CT reconstruction techniques have evolved from conventional reconstruction such as analytical and iterative reconstruction, to reconstruction methods based on artificial intelligence (AI). All these efforts are devoted to constructing high-quality images using only low doses with fast reconstruction More >

B. Sophia^1,*, D. Chitra²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2491-2504, 2023, DOI:10.32604/iasc.2023.029799 - 15 March 2023

Abstract Presently, video surveillance is commonly employed to ensure security in public places such as traffic signals, malls, railway stations, etc. A major challenge in video surveillance is the identification of anomalies that exist in it such as crimes, thefts, and so on. Besides, the anomaly detection in pedestrian walkways has gained significant attention among the computer vision communities to enhance pedestrian safety. The recent advances of Deep Learning (DL) models have received considerable attention in different processes such as object detection, image classification, etc. In this aspect, this article designs a new Panoptic Feature Pyramid… More >

P. Prabhu¹, P. Valarmathie^2,*, K. Dinakaran³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2989-3005, 2023, DOI:10.32604/iasc.2023.028659 - 15 March 2023

Abstract Supportive learning plays a substantial role in providing a quality education system. The evaluation of students’ performance impacts their deeper insight into the subject knowledge. Specifically, it is essential to maintain the baseline foundation for building a broader understanding of their careers. This research concentrates on establishing the students’ knowledge relationship even in reduced samples. Here, Synthetic Minority Oversampling TEchnique (SMOTE) technique is used for pre-processing the missing value in the provided input dataset to enhance the prediction accuracy. When the initial processing is not done substantially, it leads to misleading prediction accuracy. This research… More >

Yuan-Nong Ye^1,2,3,*, Ding-Fa Liang², Abraham Alemayehu Labena⁴, Zhu Zeng^2,*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2731-2741, 2023, DOI:10.32604/iasc.2023.026761 - 15 March 2023

Abstract Essential ncRNA is a type of ncRNA which is indispensable for the survival of organisms. Although essential ncRNAs cannot encode proteins, they are as important as essential coding genes in biology. They have got wide variety of applications such as antimicrobial target discovery, minimal genome construction and evolution analysis. At present, the number of species required for the determination of essential ncRNAs in the whole genome scale is still very few due to the traditional methods are time-consuming, laborious and costly. In addition, traditional experimental methods are limited by the organisms as less than 1%… More >

Emad Abd Al Rahman¹, Nur Intan Raihana Ruhaiyem^1,*, Majed Bouchahma², Kamarul Imran Musa³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3007-3028, 2023, DOI:10.32604/iasc.2023.032580 - 15 March 2023

Abstract This study offers a framework for a breast cancer computer-aided treatment prediction (CATP) system. The rising death rate among women due to breast cancer is a worldwide health concern that can only be addressed by early diagnosis and frequent screening. Mammography has been the most utilized breast imaging technique to date. Radiologists have begun to use computer-aided detection and diagnosis (CAD) systems to improve the accuracy of breast cancer diagnosis by minimizing human errors. Despite the progress of artificial intelligence (AI) in the medical field, this study indicates that systems that can anticipate a treatment… More >

D. Vidyabharathi^1,*, V. Mohanraj²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2559-2573, 2023, DOI:10.32604/iasc.2023.032255 - 15 March 2023

Abstract For training the present Neural Network (NN) models, the standard technique is to utilize decaying Learning Rates (LR). While the majority of these techniques commence with a large LR, they will decay multiple times over time. Decaying has been proved to enhance generalization as well as optimization. Other parameters, such as the network’s size, the number of hidden layers, dropouts to avoid overfitting, batch size, and so on, are solely based on heuristics. This work has proposed Adaptive Teaching Learning Based (ATLB) Heuristic to identify the optimal hyperparameters for diverse networks. Here we consider three More >

A. Selvi^*, S. Thilagamani

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2973-2987, 2023, DOI:10.32604/iasc.2022.029850 - 15 March 2023

Abstract Mammography is considered a significant image for accurate breast cancer detection. Content-based image retrieval (CBIR) contributes to classifying the query mammography image and retrieves similar mammographic images from the database. This CBIR system helps a physician to give better treatment. Local features must be described with the input images to retrieve similar images. Existing methods are inefficient and inaccurate by failing in local features analysis. Hence, efficient digital mammography image retrieval needs to be implemented. This paper proposed reliable recovery of the mammographic image from the database, which requires the removal of noise using Kalman More >

Hosam Alhakami^1,*, Abdullah Baz², Mohammad Al-shareef³, Rajeev Kumar⁴, Alka Agrawal⁵, Raees Ahmad Khan⁵

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2773-2786, 2023, DOI:10.32604/iasc.2023.021560 - 15 March 2023

Abstract Recent transformation of Saudi Arabian healthcare sector into a revenue producing one has signaled several advancements in healthcare in the country. Transforming healthcare management into Smart hospital systems is one of them. Secure hospital management systems which are breach-proof only can be termed as effective smart hospital systems. Given the perspective of Saudi Vision-2030, many practitioners are trying to achieve a cost-effective hospital management system by using smart ideas. In this row, the proposed framework posits the main objectives for creating smart hospital management systems that can only be acknowledged by managing the security of healthcare… More >