Muhammad Usman Ghani Khan¹, Abid Mehmood², Mourad Elhadef², Shehzad Ashraf Chaudhry^2,3,*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2225-2249, 2023, DOI:10.32604/cmc.2023.038303

Abstract The proliferation of deluding data such as fake news and phony audits on news web journals, online publications, and internet business apps has been aided by the availability of the web, cell phones, and social media. Individuals can quickly fabricate comments and news on social media. The most difficult challenge is determining which news is real or fake. Accordingly, tracking down programmed techniques to recognize fake news online is imperative. With an emphasis on false news, this study presents the evolution of artificial intelligence techniques for detecting spurious social media content. This study shows past, current, and possible methods that… More >

D. Vidyabharathi^1,*, V. Mohanraj²

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

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 architectures Recurrent Neural Networks (RNN),… More >

Sarah Alzahrani¹, Joud Alderaan¹, Dalya Alatawi¹, Bandar Alotaibi^1,2,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 651-667, 2023, DOI:10.32604/cmc.2023.035173

Abstract Internet of Things (IoT) devices incorporate a large amount of data in several fields, including those of medicine, business, and engineering. User authentication is paramount in the IoT era to assure connected devices’ security. However, traditional authentication methods and conventional biometrics-based authentication approaches such as face recognition, fingerprints, and password are vulnerable to various attacks, including smudge attacks, heat attacks, and shoulder surfing attacks. Behavioral biometrics is introduced by the powerful sensing capabilities of IoT devices such as smart wearables and smartphones, enabling continuous authentication. Artificial Intelligence (AI)-based approaches introduce a bright future in refining large amounts of homogeneous biometric… More >

Syeda Amna Rizwan¹, Yazeed Yasin Ghadi², Ahmad Jalal¹, Kibum Kim^3,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5235-5252, 2022, DOI:10.32604/cmc.2022.023328

Abstract With the advancement of computer vision techniques in surveillance systems, the need for more proficient, intelligent, and sustainable facial expressions and age recognition is necessary. The main purpose of this study is to develop accurate facial expressions and an age recognition system that is capable of error-free recognition of human expression and age in both indoor and outdoor environments. The proposed system first takes an input image pre-process it and then detects faces in the entire image. After that landmarks localization helps in the formation of synthetic face mask prediction. A novel set of features are extracted and passed to… More >

Gautham Praveen Ramalingam¹, R. Arockia Xavier Annie¹, Shobana Gopalakrishnan^2,*

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1479-1492, 2022, DOI:10.32604/iasc.2022.022211

Abstract Detection of intrusion plays an important part in data protection. Intruders will carry out attacks from a compromised user account without being identified. The key technology is the effective detection of sundry threats inside the network. However, process automation is experiencing expanded use of information communication systems, due to high versatility of interoperability and ease off 34 administration. Traditional knowledge technology intrusion detection systems are not completely tailored to process automation. The combined use of fuzziness-based and RNN-IDS is therefore highly suited to high-precision classification, and its efficiency is better compared to that of conventional machine learning approaches. This model… More >

Wenxiao Wang^1,*, Xiaoyu Li^1,*, Yin Ding¹, Feizhou Wu², Shan Yang³

Journal of Quantum Computing, Vol.3, No.1, pp. 25-33, 2021, DOI:10.32604/jqc.2021.016346

Abstract Due to the increase in the types of business and equipment in telecommunications companies, the performance index data collected in the operation and maintenance process varies greatly. The diversity of index data makes it very difficult to perform high-precision capacity prediction. In order to improve the forecasting efficiency of related indexes, this paper designs a classification method of capacity index data, which divides the capacity index data into trend type, periodic type and irregular type. Then for the prediction of trend data, it proposes a capacity index prediction model based on Recurrent Neural Network (RNN), denoted as RNN-LSTM-LSTM. This model… More >