Chao-Lung Yang¹, Yulius Harjoseputro^2,3, Yu-Chen Hu⁴, Yung-Yao Chen^2,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4577-4593, 2022, DOI:10.32604/cmc.2022.031305

Abstract This research proposed an improved transfer-learning bird classification framework to achieve a more precise classification of Protected Indonesia Birds (PIB) which have been identified as the endangered bird species. The framework takes advantage of using the proposed sequence of Batch Normalization Dropout Fully-Connected (BNDFC) layers to enhance the baseline model of transfer learning. The main contribution of this work is the proposed sequence of BNDFC that can be applied to any Convolutional Neural Network (CNN) based model to improve the classification accuracy, especially for image-based species classification problems. The experiment results show that the proposed sequence of BNDFC layers outperform… More >

Manar Ahmed Hamza^1,2,*, Aisha Hassan Abdalla Hashim¹, Heba G. Mohamed³, Saud S. Alotaibi⁴, Hany Mahgoub^5,6, Amal S. Mehanna⁷, Abdelwahed Motwakel²

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6579-6594, 2022, DOI:10.32604/cmc.2022.031303

Abstract Internet of Everything (IoE), the recent technological advancement, represents an interconnected network of people, processes, data, and things. In recent times, IoE gained significant attention among entrepreneurs, individuals, and communities owing to its realization of intense values from the connected entities. On the other hand, the massive increase in data generation from IoE applications enables the transmission of big data, from context-aware machines, into useful data. Security and privacy pose serious challenges in designing IoE environment which can be addressed by developing effective Intrusion Detection Systems (IDS). In this background, the current study develops Intelligent Multiverse Optimization with Deep Learning… More >

Hasnain Kashif^*, Muhammad Nasir Khan

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6001-6017, 2022, DOI:10.32604/cmc.2022.031291

Abstract Recently, free space optical (FSO) communication is gaining much attention towards the research community. The reason for this attention is the promises of high data-rate, license-free deployment, and non-interfering links. It can, however, give rise to major system difficulties concerning alignment and atmospheric turbulence. FSO is the degradation in the signal quality because of atmospheric channel impairments and conditions. The worst effect is due to fog particles. Though, Radio Frequency (RF) links are able to transmit the data in foggy conditions but not in rain. To overcome these issues related to both the FSO and RF links. A free space… More >

Dalwinder Singh¹, Deepak Prashar¹, Jimmy Singla¹, Arfat Ahmad Khan², Mohammed Al-Sarem^3,4,*, Neesrin Ali Kurdi³

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6047-6068, 2022, DOI:10.32604/cmc.2022.031255

Abstract The hepatitis B virus is the most deadly virus, which significantly affects the human liver. The termination of the hepatitis B virus is mandatory and can be done by taking precautions as well as a suitable cure in its introductory stage; otherwise, it will become a severe problem and make a human liver suffer from the most dangerous diseases, such as liver cancer. In this paper, two medical diagnostic systems are developed for the diagnosis of this life-threatening virus. The methodologies used to develop these models are fuzzy logic and the neuro-fuzzy technique. The diverse parameters that assist in the… More >

K. Shankar¹, E. Laxmi Lydia², Sachin Kumar^1,*, Ali S. Abosinne³, Ahmed alkhayyat⁴, A. H. Abbas⁵, Sarmad Nozad Mahmood⁶

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4541-4557, 2022, DOI:10.32604/cmc.2022.031247

Abstract Oral Squamous Cell Carcinoma (OSCC) is a type of Head and Neck Squamous Cell Carcinoma (HNSCC) and it should be diagnosed at early stages to accomplish efficient treatment, increase the survival rate, and reduce death rate. Histopathological imaging is a wide-spread standard used for OSCC detection. However, it is a cumbersome process and demands expert’s knowledge. So, there is a need exists for automated detection of OSCC using Artificial Intelligence (AI) and Computer Vision (CV) technologies. In this background, the current research article introduces Improved Slime Mould Algorithm with Artificial Intelligence Driven Oral Cancer Classification (ISMA-AIOCC) model on Histopathological images… More >

Ahmed Ali Ajmi^1,2, Noor Shakir Mahmood^1,2, Khairur Rijal Jamaludin^1,*, Hayati Habibah Abdul Talib¹, Shamsul Sarip¹, Hazilah Mad Kaidi¹

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5025-5039, 2022, DOI:10.32604/cmc.2022.031239

Abstract The literature that a lack of integration between the performance shaping factors (PSFs) and the energy management performance (EMP) is one of the critical problems that prevent performance improvement and reduces the power plant’s efficiency. To solve this problem, this article aims to achieve two main objectives: (1) Systematically investigate and identify the critical success factors (CSFs) for integration with PSFs and EMP; (2) Develop a novel modelling approach to predict the performance of power plants based on innovative integrated strategies. The research methodology is grounded on the theoretical and practical approach to improving performance. The Newcastle Ottawa Scale (NOS)… More >

Abhishek Sharma¹, Sushank Chaudhary^2,*, Jyoteesh Malhotra³, Muhammad Saadi⁴, Sattam Al Otaibi⁵, Lunchakorn Wuttisittikulkij²

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5399-5410, 2022, DOI:10.32604/cmc.2022.031173

Abstract Recent reports from World Health Organization (WHO) show the impact of human negligence as a serious concern for road accidents and casualties worldwide. There are number of reasons which led to this negligence; hence, need of intelligent transportation system (ITS) gains more attention from researchers worldwide. For achieving such autonomy different sensors are involved in autonomous vehicles which can sense road conditions and warn the control system about possible hazards. This work is focused on designing one such sensor system which can detect and range multiple targets under the impact of adverse atmospheric conditions. A high-speed Linear Frequency Modulated Continuous… More >

Settawit Poochaya^1,*, Peerapong Uthansakul¹, Monthippa Uthansakul¹, Patikorn Anchuen², Kontorn Thammakul³, Arfat Ahmad Khan⁴, Niwat Punanwarakorn⁵, Pech Sirivoratum⁵, Aranya Kaewkrad⁵, Panrawee Kanpan⁵, Apichart Wantamee⁵

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5845-5862, 2022, DOI:10.32604/cmc.2022.031162

Abstract The number of accidents in the campus of Suranaree University of Technology (SUT) has increased due to increasing number of personal vehicles. In this paper, we focus on the development of public transportation system using Intelligent Transportation System (ITS) along with the limitation of personal vehicles using sharing economy model. The SUT Smart Transit is utilized as a major public transportation system, while MoreSai@SUT (electric motorcycle services) is a minor public transportation system in this work. They are called Multi-Mode Transportation system as a combination. Moreover, a Vehicle to Network (V2N) is used for developing the Multi-Mode Transportation system in… More >

Abdullah A Asiri¹, Akhtar Badshah², Fazal Muhammad^3,*, Hassan A Alshamrani¹, Khalil Ullah⁴, Khalaf A Alshamrani¹, Samar Alqhtani⁵, Muhammad Irfan⁶, Hanan Talal Halawani⁷, Khlood M Mehdar⁸

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5075-5089, 2022, DOI:10.32604/cmc.2022.031156

Abstract Electroencephalogram (EEG) is a medical imaging technology that can measure the electrical activity of the scalp produced by the brain, measured and recorded chronologically the surface of the scalp from the brain. The recorded signals from the brain are rich with useful information. The inference of this useful information is a challenging task. This paper aims to process the EEG signals for the recognition of human emotions specifically happiness, anger, fear, sadness, and surprise in response to audiovisual stimuli. The EEG signals are recorded by placing neurosky mindwave headset on the subject’s scalp, in response to audiovisual stimuli for the… More >

Abeer Abdulaziz AlArfaj, Hanan Ahmed Hosni Mahmoud^*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5655-5669, 2022, DOI:10.32604/cmc.2022.031135

Abstract Lie detection test is highly significant task due to its impact on criminology and society. Computerized lie detection test model using electroencephalogram (EEG) signals is studied in literature. In this paper we studied deep learning framework in lie detection test paradigm. First, we apply a preprocessing technique to utilize only a small fragment of the EEG image instead of the whole image. Our model describes a temporal feature map of the EEG signals measured during the lie detection test. A deep learning attention model (V-TAM) extracts the temporal map vector during the learning process. This technique reduces computational time and… More >