S. Hariprasad^1,*, T. Deepa¹, N. Bharathiraja²

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1425-1440, 2022, DOI:10.32604/iasc.2022.022856

Abstract The Internet of Things (IoT) is a global information and communication technology which aims to connect any type of device to the internet at any time and in any location. Nowadays billions of IoT devices are connected to the world, this leads to easily cause vulnerability to IoT devices. The increasing of users in different IoT-related applications leads to more data attacks is happening in the IoT networks after the fog layer. To detect and reduce the attacks the deep learning model is used. In this article, a hybrid sample selected recurrent neural network-extreme learning… More >

K. Lavanya^1,*, K. Vimala Devi², B. R. Tapas Bapu³

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 837-848, 2022, DOI:10.32604/iasc.2022.023055

Abstract Multipath TCP (SMPTCP) has gained more attention as a valuable approach for IoT systems. SMPTCP is introduced as an evolution of Transmission Control Protocol (TCP) to pass packets simultaneously across several routes to completely exploit virtual networks on multi-homed consoles and other network services. The current multipath networking algorithms and simulation software strategies are confronted with sub-flow irregularity issues due to network heterogeneity, and routing configuration issues can be fixed adequately. To overcome the issues, this paper proposes a novel deep reinforcement-based extreme learning machines (DRLELM) approach to examine the complexities between routes, pathways, sub-flows, More >

V. Ravindra Krishna Chandar^1,*, M. Thangamani²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 165-181, 2022, DOI:10.32604/iasc.2022.022339

Abstract

During patient monitoring, false alert in the Intensive Care Unit (ICU) becomes a major problem. In the category of alarms, pseudo alarms are regarded as having no clinical or therapeutic significance, and thus they result in fatigue alarms. Artifacts are misrepresentations of tissue structures produced by imaging techniques. These Artifacts can invalidate the Arterial Blood Pressure (ABP) signal. Therefore, it is very important to develop algorithms that can detect artifacts. However, ABP has algorithmic shortcomings and limitations of design. This study is aimed at developing a real-time enhancement of independent component analysis (EICA) and time-domain

… More >

Abdelzahir Abdelmaboud¹, Fahd N. Al-Wesabi^1,2,3, Mesfer Al Duhayyim⁴, Taiseer Abdalla Elfadil Eisa⁵, Manar Ahmed Hamza^6,*, Mohammed Rizwanullah⁶, Abu Serwar Zamani⁶, Radwa Marzouk⁷

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 679-693, 2022, DOI:10.32604/cmc.2022.024240

Abstract Internet of Things (IoT) with e-learning is widely employed to collect data from various smart devices and share it with other ones for efficient e-learning applications. At the same time, machine learning (ML) and data mining approaches are presented for accomplishing prediction and classification processes. With this motivation, this study focuses on the design of intelligent machine learning enabled e-learner non-verbal behaviour detection (IML-ELNVBD) in IoT environment. The proposed IML-ELNVBD technique allows the IoT devices such as audio sensors, cameras, etc. which are then connected to the cloud server for further processing. In addition, the More >

Saima Hassan¹, Mojtaba Ahmadieh Khanesar², Nazar Kalaf Hussein³, Samir Brahim Belhaouari^4,*, Usman Amjad⁵, Wali Khan Mashwani⁶

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3513-3531, 2022, DOI:10.32604/cmc.2022.022018

Abstract The estimation of the fuzzy membership function parameters for interval type 2 fuzzy logic system (IT2-FLS) is a challenging task in the presence of uncertainty and imprecision. Grasshopper optimization algorithm (GOA) is a fresh population based meta-heuristic algorithm that mimics the swarming behavior of grasshoppers in nature, which has good convergence ability towards optima. The main objective of this paper is to apply GOA to estimate the optimal parameters of the Gaussian membership function in an IT2-FLS. The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers… More >

J. Sampathkumar^*, N. Malmurugan

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2107-2123, 2022, DOI:10.32604/cmc.2022.019983

Abstract Wireless Sensor Network is considered as the intermediate layer in the paradigm of Internet of things (IoT) and its effectiveness depends on the mode of deployment without sacrificing the performance and energy efficiency. WSN provides ubiquitous access to location, the status of different entities of the environment and data acquisition for long term IoT monitoring. Achieving the high performance of the WSN-IoT network remains to be a real challenge since the deployment of these networks in the large area consumes more power which in turn degrades the performance of the networks. So, developing the robust… More >

Mustafa Abdul Salam^1,*, Ahmad Taher Azar², Rana Hussien²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6339-6363, 2022, DOI:10.32604/cmc.2022.020583

Abstract Extreme Learning Machine (ELM) is popular in batch learning, sequential learning, and progressive learning, due to its speed, easy integration, and generalization ability. While, Traditional ELM cannot train massive data rapidly and efficiently due to its memory residence, high time and space complexity. In ELM, the hidden layer typically necessitates a huge number of nodes. Furthermore, there is no certainty that the arrangement of weights and biases within the hidden layer is optimal. To solve this problem, the traditional ELM has been hybridized with swarm intelligence optimization techniques. This paper displays five proposed hybrid Algorithms… More >

Muhammad Adnan Khan, Taher M. Ghazal^2,3, Sang-Woong Lee^1,*, Abdur Rehman⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3399-3413, 2022, DOI:10.32604/cmc.2022.020173

Abstract In recent years, the infrastructure of Wireless Internet of Sensor Networks (WIoSNs) has been more complicated owing to developments in the internet and devices’ connectivity. To effectively prepare, control, hold and optimize wireless sensor networks, a better assessment needs to be conducted. The field of artificial intelligence has made a great deal of progress with deep learning systems and these techniques have been used for data analysis. This study investigates the methodology of Real Time Sequential Deep Extreme Learning Machine (RTS-DELM) implemented to wireless Internet of Things (IoT) enabled sensor networks for the detection of… More >

Ahmed Reda^*, Sherif Barakat, Amira Rezk

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1381-1399, 2022, DOI:10.32604/cmc.2022.019809

Abstract Many respiratory infections around the world have been caused by coronaviruses. COVID-19 is one of the most serious coronaviruses due to its rapid spread between people and the lowest survival rate. There is a high need for computer-assisted diagnostics (CAD) in the area of artificial intelligence to help doctors and radiologists identify COVID-19 patients in cloud systems. Machine learning (ML) has been used to examine chest X-ray frames. In this paper, a new transfer learning-based optimized extreme deep learning paradigm is proposed to identify the chest X-ray picture into three classes, a pneumonia patient, a More >

Abdul Majid¹, Muhammad Attique Khan¹, Yunyoung Nam^2,*, Usman Tariq³, Sudipta Roy⁴, Reham R. Mostafa⁵, Rasha H. Sakr⁶

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 319-337, 2021, DOI:10.32604/cmc.2021.016816

Abstract The recent COVID-19 pandemic caused by the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has had a significant impact on human life and the economy around the world. A reverse transcription polymerase chain reaction (RT-PCR) test is used to screen for this disease, but its low sensitivity means that it is not sufficient for early detection and treatment. As RT-PCR is a time-consuming procedure, there is interest in the introduction of automated techniques for diagnosis. Deep learning has a key role to play in the field of medical imaging. The most important issue… More >