Alaa Omran Almagrabi^*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2079-2093, 2023, DOI:10.32604/cmc.2023.039683

Abstract A potential concept that could be effective for multiple applications is a “cyber-physical system” (CPS). The Internet of Things (IoT) has evolved as a research area, presenting new challenges in obtaining valuable data through environmental monitoring. The existing work solely focuses on classifying the audio system of CPS without utilizing feature extraction. This study employs a deep learning method, CNN-LSTM, and two-way feature extraction to classify audio systems within CPS. The primary objective of this system, which is built upon a convolutional neural network (CNN) with Long Short Term Memory (LSTM), is to analyze the vocalization patterns of two different… More >

Sonali S. Patil, Sujit S. Pardeshi, Abhishek D. Patange^*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 177-199, 2023, DOI:10.32604/cmes.2023.025516

Abstract In-process damage to a cutting tool degrades the surface finish of the job shaped by machining and causes a significant financial loss. This stimulates the need for Tool Condition Monitoring (TCM) to assist detection of failure before it extends to the worse phase. Machine Learning (ML) based TCM has been extensively explored in the last decade. However, most of the research is now directed toward Deep Learning (DL). The “Deep” formulation, hierarchical compositionality, distributed representation and end-to-end learning of Neural Nets need to be explored to create a generalized TCM framework to perform efficiently in a high-noise environment of cross-domain… More >

H. M. Shahzad^1,3, Sohail Masood Bhatti^1,3,*, Arfan Jaffar^1,3, Muhammad Rashid²

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1561-1570, 2023, DOI:10.32604/iasc.2023.032525

Abstract In recent years, research on facial expression recognition (FER) under mask is trending. Wearing a mask for protection from Covid 19 has become a compulsion and it hides the facial expressions that is why FER under the mask is a difficult task. The prevailing unimodal techniques for facial recognition are not up to the mark in terms of good results for the masked face, however, a multimodal technique can be employed to generate better results. We proposed a multimodal methodology based on deep learning for facial recognition under a masked face using facial and vocal expressions. The multimodal has been… More >

Le Quang Thao^1,2,*, Duong Duc Cuong², Tran Thi Tuong Anh³, Tran Duc Luong⁴

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1309-1321, 2023, DOI:10.32604/csse.2023.031010

Abstract Noise pollution tends to receive less awareness compared to other types of pollution, however, it greatly impacts the quality of life for humans such as causing sleep disruption, stress or hearing impairment. Profiling urban sound through the identification of noise sources in cities could help to benefit livability by reducing exposure to noise pollution through methods such as noise control, planning of the soundscape environment, or selection of safe living space. In this paper, we proposed a self-attention long short-term memory (LSTM) method that can improve sound classification compared to previous baselines. An attention mechanism will be designed solely to… More >

Narathip Chaobankoh¹, Tallit Jumphoo¹, Monthippa Uthansakul¹, Khomdet Phapatanaburi², Bura Sindthupakorn³, Supakit Rooppakhun⁴, Peerapong Uthansakul^1,*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1269-1282, 2022, DOI:10.32604/cmc.2022.027474

Abstract Recently, the Muscle-Computer Interface (MCI) has been extensively popular for employing Electromyography (EMG) signals to help the development of various assistive devices. However, few studies have focused on ankle foot movement classification considering EMG signals at limb position. This work proposes a new framework considering two EMG signals at a lower-limb position to classify the ankle movement characteristics based on normal walking cycles. For this purpose, we introduce a human ankle-foot movement classification method using a two-dimensional-convolutional neural network (2D-CNN) with low-cost EMG sensors based on lower-limb motion. The time-domain signals of EMG obtained from two sensors belonging to Dorsiflexion,… More >

Laiali Almazaydeh^1,*, Saleh Atiewi², Arar Al Tawil³, Khaled Elleithy⁴

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5443-5458, 2022, DOI:10.32604/cmc.2022.025526

Abstract Genres are one of the key features that categorize music based on specific series of patterns. However, the Arabic music content on the web is poorly defined into its genres, making the automatic classification of Arabic audio genres challenging. For this reason, in this research, our objective is first to construct a well-annotated dataset of five of the most well-known Arabic music genres, which are: Eastern Takht, Rai, Muwashshah, the poem, and Mawwal, and finally present a comprehensive empirical comparison of deep Convolutional Neural Networks (CNNs) architectures on Arabic music genres classification. In this work, to utilize CNNs to develop… More >

Safaa El-Gazar¹, Walid El-Shafai^2,3,*, Ghada El-Banby⁴, Hesham F. A. Hamed¹, Gerges M. Salama¹, Mohammed Abd-Elnaby⁵, Fathi E. Abd El-Samie^2,6

Computer Systems Science and Engineering, Vol.43, No.1, pp. 87-102, 2022, DOI:10.32604/csse.2022.022722

Abstract Biometric authentication is a rapidly growing trend that is gaining increasing attention in the last decades. It achieves safe access to systems using biometrics instead of the traditional passwords. The utilization of a biometric in its original format makes it usable only once. Therefore, a cancelable biometric template should be used, so that it can be replaced when it is attacked. Cancelable biometrics aims to enhance the security and privacy of biometric authentication. Digital encryption is an efficient technique to be used in order to generate cancelable biometric templates. In this paper, a highly-secure encryption algorithm is proposed to ensure… More >

Jae Myung Kim^1,2, Gyu Ho Choi², Min-Gu Kim², Sung Bum Pan^1,2,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1213-1227, 2022, DOI:10.32604/cmc.2022.025213

Abstract Recently, user recognition methods to authenticate personal identity has attracted significant attention especially with increased availability of various internet of things (IoT) services through fifth-generation technology (5G) based mobile devices. The EMG signals generated inside the body with unique individual characteristics are being studied as a part of next-generation user recognition methods. However, there is a limitation when applying EMG signals to user recognition systems as the same operation needs to be repeated while maintaining a constant strength of muscle over time. Hence, it is necessary to conduct research on multidimensional feature transformation that includes changes in frequency features over… More >

Uğur Ayvaz¹, Hüseyin Gürüler², Faheem Khan³, Naveed Ahmed⁴, Taegkeun Whangbo^3,*, Abdusalomov Akmalbek Bobomirzaevich³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5511-5521, 2022, DOI:10.32604/cmc.2022.023278

Abstract Automatic speaker recognition (ASR) systems are the field of Human-machine interaction and scientists have been using feature extraction and feature matching methods to analyze and synthesize these signals. One of the most commonly used methods for feature extraction is Mel Frequency Cepstral Coefficients (MFCCs). Recent researches show that MFCCs are successful in processing the voice signal with high accuracies. MFCCs represents a sequence of voice signal-specific features. This experimental analysis is proposed to distinguish Turkish speakers by extracting the MFCCs from the speech recordings. Since the human perception of sound is not linear, after the filterbank step in the MFCC… More >

Rakesh Kumar¹, Meenu Gupta¹, Shakeel Ahmed^2,*, Abdulaziz Alhumam², Tushar Aggarwal¹

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 693-706, 2022, DOI:10.32604/iasc.2022.019811

Abstract Hearing a species in a tropical rainforest is much easier than seeing them. If someone is in the forest, he might not be able to look around and see every type of bird and frog that are there but they can be heard. A forest ranger might know what to do in these situations and he/she might be an expert in recognizing the different type of insects and dangerous species that are out there in the forest but if a common person travels to a rain forest for an adventure, he might not even know how to recognize these species,… More >