Noman Shabbir¹, Lauri Kütt¹, Muhammad Jawad², Oleksandr Husev¹, Ateeq Ur Rehman³, Akber Abid Gardezi⁴, Muhammad Shafiq⁵, Jin-Ghoo Choi^5,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1017-1033, 2022, DOI:10.32604/cmc.2022.024576

Abstract Wind energy is featured by instability due to a number of factors, such as weather, season, time of the day, climatic area and so on. Furthermore, instability in the generation of wind energy brings new challenges to electric power grids, such as reliability, flexibility, and power quality. This transition requires a plethora of advanced techniques for accurate forecasting of wind energy. In this context, wind energy forecasting is closely tied to machine learning (ML) and deep learning (DL) as emerging technologies to create an intelligent energy management paradigm. This article attempts to address the short-term wind energy forecasting problem in… More >

S. Nithyanantham^1,*, G. Singaravel²

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1905-1919, 2022, DOI:10.32604/iasc.2022.022499

Abstract In recent times, a huge amount of data is being created from different sources and the size of the data generated on the Internet has already surpassed two Exabytes. Big Data processing and analysis can be employed in many disciplines which can aid the decision-making process with privacy preservation of users’ private data. To store large quantity of data, Geo-Distributed Data Centres (GDDC) are developed. In recent times, several applications comprising data analytics and machine learning have been designed for GDDC. In this view, this paper presents a hybrid deep learning framework for privacy preservation in distributed DCs. The proposed… More >

Shaleeza Sohail¹, Atif Alvi^2,*, Aasia Khanum³

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3211-3225, 2022, DOI:10.32604/cmc.2022.023560

Abstract Major issues currently restricting the use of learning analytics are the lack of interpretability and adaptability of the machine learning models used in this domain. Interpretability makes it easy for the stakeholders to understand the working of these models and adaptability makes it easy to use the same model for multiple cohorts and courses in educational institutions. Recently, some models in learning analytics are constructed with the consideration of interpretability but their interpretability is not quantified. However, adaptability is not specifically considered in this domain. This paper presents a new framework based on hybrid statistical fuzzy theory to overcome these… More >

Malini M. Patil^1,*, P. M. Rekha¹, Arun Solanki², Anand Nayyar^3,4, Basit Qureshi⁵

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2347-2361, 2022, DOI:10.32604/cmc.2022.021447

Abstract In the past few decades, climatic changes led by environmental pollution, the emittance of greenhouse gases, and the emergence of brown energy utilization have led to global warming. Global warming increases the Earth's temperature, thereby causing severe effects on human and environmental conditions and threatening the livelihoods of millions of people. Global warming issues are the increase in global temperatures that lead to heat strokes and high-temperature-related diseases during the summer, causing the untimely death of thousands of people. To forecast weather conditions, researchers have utilized machine learning algorithms, such as autoregressive integrated moving average, ensemble learning, and long short-term… More >

Suraya Hamid¹, Shahrul Nizam Ismail¹, Muzaffar Hamzah^2,*, Asad W. Malik³

Computer Systems Science and Engineering, Vol.42, No.1, pp. 335-350, 2022, DOI:10.32604/csse.2022.021927

Abstract Learning analytics is an emerging technique of analysing student participation and engagement. The recent COVID-19 pandemic has significantly increased the role of learning management systems (LMSs). LMSs previously only complemented face-to-face teaching, something which has not been possible between 2019 to 2020. To date, the existing body of literature on LMSs has not analysed learning in the context of the pandemic, where an LMS serves as the only interface between students and instructors. Consequently, productive results will remain elusive if the key factors that contribute towards engaging students in learning are not first identified. Therefore, this study aimed to perform… More >

Nur-Hana Samsudin^1,*, Mark Lee²

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1025-1039, 2022, DOI:10.32604/iasc.2022.022180

Abstract In a polyglot speech synthesis, it is possible to use one language resource for another language. However, if the adaptation is not implemented carefully, the foreignness of the sound will be too noticeable for the listeners. This paper presents the analysis of respondents’ acceptance of a series of listening tests. The research goal was to find out in the absence of phonemes of a particular language, would it be possible for the phonemes to be replaced with another language’s phonemes. This will be especially beneficial for under-resourced language either in the case for 1) the language has not yet well… More >

S. Benila^1,*, N. Usha Bhanu²

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1277-1291, 2022, DOI:10.32604/iasc.2022.021920

Abstract Many physical objects are connected to the internet in this modern day to make things easier to work based on the convenience of the user, which reduces human involvement with the help of Internet of Things (IoT) technology.This aids in the capture of large amounts of data, the interchange of information via the internet, and the remote operation of machines. IoT health data is typically in the form of big data and is frequently coupled with the cloud for secure storage. Cloud technology provides a wide range of technological services via the internet, and it is a highly interoperable and… More >

Yuan Ai Ho¹, Chee Keong Tan^1,*, Yin Hoe Ng²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 907-924, 2022, DOI:10.32604/cmc.2022.021756

Abstract The world is experiencing the unprecedented time of a pandemic caused by the coronavirus disease (i.e., COVID-19). As a countermeasure, contact tracing and social distancing are essential to prevent the transmission of the virus, which can be achieved using indoor location analytics. Based on the indoor location analytics, the human mobility on a site can be monitored and planned to minimize human’s contact and enforce social distancing to contain the transmission of COVID-19. Given the indoor location data, the clustering can be applied to cluster spatial data, spatio-temporal data and movement behavior features for proximity detection or contact tracing applications.… More >

P. N. Palanisamy^*, N. Malmurugan

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 791-808, 2022, DOI:10.32604/cmc.2022.019921

Abstract In recent years, deep neural networks have become a fascinating and influential research subject, and they play a critical role in video processing and analytics. Since, video analytics are predominantly hardware centric, exploration of implementing the deep neural networks in the hardware needs its brighter light of research. However, the computational complexity and resource constraints of deep neural networks are increasing exponentially by time. Convolutional neural networks are one of the most popular deep learning architecture especially for image classification and video analytics. But these algorithms need an efficient implement strategy for incorporating more real time computations in terms of… More >

Nithya Rekha Sivakumar^1,*, Ahmed Zohair Ibrahim²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4467-4483, 2022, DOI:10.32604/cmc.2022.019041

Abstract

Tele health utilizes information and communication mechanisms to convey medical information for providing clinical and educational assistances. It makes an effort to get the better of issues of health service delivery involving time factor, space and laborious terrains, validating cost-efficiency and finer ingress in both developed and developing countries. Tele health has been categorized into either real-time electronic communication, or store-and-forward communication. In recent years, a third-class has been perceived as remote healthcare monitoring or tele health, presuming data obtained via Internet of Things (IOT). Although, tele health data analytics and machine learning have been researched in great depth, there… More >