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  • Open Access

    ARTICLE

    Blood Pressure and Heart Rate Measurements Using Photoplethysmography with Modified LRCN

    Chih-Ta Yen1,*, Cheng-Hong Liao2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1973-1986, 2022, DOI:10.32604/cmc.2022.022679 - 03 November 2021

    Abstract In this study, single-channel photoplethysmography (PPG) signals were used to estimate the heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP). A deep learning model was proposed using a long-term recurrent convolutional network (LRCN) modified from a deep learning algorithm, the convolutional neural network model of the modified inception deep learning module, and a long short-term memory network (LSTM) to improve the model's accuracy of BP and HR measurements. The PPG data of 1,551 patients were obtained from the University of California Irvine Machine Learning Repository. How to design a filter of More >

  • Open Access

    ARTICLE

    A Study on Classification and Detection of Small Moths Using CNN Model

    Sang-Hyun Lee*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1987-1998, 2022, DOI:10.32604/cmc.2022.022554 - 03 November 2021

    Abstract Currently, there are many limitations to classify images of small objects. In addition, there are limitations such as error detection due to external factors, and there is also a disadvantage that it is difficult to accurately distinguish between various objects. This paper uses a convolutional neural network (CNN) algorithm to recognize and classify object images of very small moths and obtain precise data images. A convolution neural network algorithm is used for image data classification, and the classified image is transformed into image data to learn the topological structure of the image. To improve the More >

  • Open Access

    ARTICLE

    Fleet Optimization of Smart Electric Motorcycle System Using Deep Reinforcement Learning

    Patikorn Anchuen, Peerapong Uthansakul*, Monthippa Uthansakul, Settawit Poochaya

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1925-1943, 2022, DOI:10.32604/cmc.2022.022444 - 03 November 2021

    Abstract Smart electric motorcycle-sharing systems based on the digital platform are one of the public transportations that we use in daily lives when the sharing economy is considered. This transportation provides convenience for users with low-cost systems while it also promotes an environmental conservation. Normally, users rent the vehicle to travel from the origin station to another station near their destination with a one-way trip in which the demand of renting and returning at each station is different. This leads to unbalanced vehicle rental systems. To avoid the full or empty inventory, the electric motorcycle-sharing rebalancing… More >

  • Open Access

    Fed-DFE: A Decentralized Function Encryption-Based Privacy-Preserving Scheme for Federated Learning

    Zhe Sun1, Jiyuan Feng1, Lihua Yin1,*, Zixu Zhang2, Ran Li1, Yu Hu1, Chongning Na3

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1867-1886, 2022, DOI:10.32604/cmc.2022.022290 - 03 November 2021

    Abstract Federated learning is a distributed learning framework which trains global models by passing model parameters instead of raw data. However, the training mechanism for passing model parameters is still threatened by gradient inversion, inference attacks, etc. With a lightweight encryption overhead, function encryption is a viable secure aggregation technique in federation learning, which is often used in combination with differential privacy. The function encryption in federal learning still has the following problems: a) Traditional function encryption usually requires a trust third party (TTP) to assign the keys. If a TTP colludes with a server, the… More >

  • Open Access

    ARTICLE

    Autism Spectrum Disorder Prediction by an Explainable Deep Learning Approach

    Anupam Garg1, Anshu Parashar1, Dipto Barman2, Sahil Jain3, Divya Singhal3, Mehedi Masud4, Mohamed Abouhawwash5,6,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1459-1471, 2022, DOI:10.32604/cmc.2022.022170 - 03 November 2021

    Abstract Autism Spectrum Disorder (ASD) is a developmental disorder whose symptoms become noticeable in early years of the age though it can be present in any age group. ASD is a mental disorder which affects the communicational, social and non-verbal behaviors. It cannot be cured completely but can be reduced if detected early. An early diagnosis is hampered by the variation and severity of ASD symptoms as well as having symptoms commonly seen in other mental disorders as well. Nowadays, with the emergence of deep learning approaches in various fields, medical experts can be assisted in… More >

  • Open Access

    ARTICLE

    Hyperuricemia Prediction Using Photoplethysmogram and Arteriograph

    Hafifah Ab Hamid1, Nazrul Anuar Nayan1,*, Mohd Zubir Suboh1, Nurin Izzati Mohamad Azizul1, Mohamad Nazhan Mohd Nizar1, Amilia Aminuddin2, Mohd Shahrir Mohamed Said3, Saharuddin Ahmad4

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 287-304, 2022, DOI:10.32604/cmc.2022.021987 - 03 November 2021

    Abstract Hyperuricemia is an alarming issue that contributes to cardiovascular disease. Uric acid (UA) level was proven to be related to pulse wave velocity, a marker of arterial stiffness. A hyperuricemia prediction method utilizing photoplethysmogram (PPG) and arteriograph by using machine learning (ML) is proposed. From the literature search, there is no available papers found that relates PPG with UA level even though PPG is highly associated with vessel condition. The five phases in this research are data collection, signal preprocessing including denoising and signal quality indexes, features extraction for PPG and SDPPG waveform, statistical analysis… More >

  • Open Access

    ARTICLE

    SMOTEDNN: A Novel Model for Air Pollution Forecasting and AQI Classification

    Mohd Anul Haq*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1403-1425, 2022, DOI:10.32604/cmc.2022.021968 - 03 November 2021

    Abstract Rapid industrialization and urbanization are rapidly deteriorating ambient air quality, especially in the developing nations. Air pollutants impose a high risk on human health and degrade the environment as well. Earlier studies have used machine learning (ML) and statistical modeling to classify and forecast air pollution. However, these methods suffer from the complexity of air pollution dataset resulting in a lack of efficient classification and forecasting of air pollution. ML-based models suffer from improper data pre-processing, class imbalance issues, data splitting, and hyperparameter tuning. There is a gap in the existing ML-based studies on air… More >

  • Open Access

    ARTICLE

    IoT with Evolutionary Algorithm Based Deep Learning for Smart Irrigation System

    P. Suresh1,*, R. H. Aswathy1, Sridevi Arumugam2, Amani Abdulrahman Albraikan3, Fahd N. Al-Wesabi4, Anwer Mustafa Hilal5, Mohammad Alamgeer6

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1713-1728, 2022, DOI:10.32604/cmc.2022.021789 - 03 November 2021

    Abstract In India, water wastage in agricultural fields becomes a challenging issue and it is needed to minimize the loss of water in the irrigation process. Since the conventional irrigation system needs massive quantity of water utilization, a smart irrigation system can be designed with the help of recent technologies such as machine learning (ML) and the Internet of Things (IoT). With this motivation, this paper designs a novel IoT enabled deep learning enabled smart irrigation system (IoTDL-SIS) technique. The goal of the IoTDL-SIS technique focuses on the design of smart irrigation techniques for effectual water… More >

  • Open Access

    ARTICLE

    Optimal Parameter Estimation of Transmission Line Using Chaotic Initialized Time-Varying PSO Algorithm

    Abdullah Shoukat1, Muhammad Ali Mughal1,*, Saifullah Younus Gondal1, Farhana Umer2, Tahir Ejaz3, Ashiq Hussain1

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 269-285, 2022, DOI:10.32604/cmc.2022.021575 - 03 November 2021

    Abstract Transmission line is a vital part of the power system that connects two major points, the generation, and the distribution. For an efficient design, stable control, and steady operation of the power system, adequate knowledge of the transmission line parameters resistance, inductance, capacitance, and conductance is of great importance. These parameters are essential for transmission network expansion planning in which a new parallel line is needed to be installed due to increased load demand or the overhead line is replaced with an underground cable. This paper presents a method to optimally estimate the parameters using… More >

  • Open Access

    ARTICLE

    Artificial Intelligence Based Sentiment Analysis for Health Crisis Management in Smart Cities

    Anwer Mustafa Hilal1, Badria Sulaiman Alfurhood2, Fahd N. Al-Wesabi3,4, Manar Ahmed Hamza1,*, Mesfer Al Duhayyim5, Huda G. Iskandar4,6

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 143-157, 2022, DOI:10.32604/cmc.2022.021502 - 03 November 2021

    Abstract Smart city promotes the unification of conventional urban infrastructure and information technology (IT) to improve the quality of living and sustainable urban services in the city. To accomplish this, smart cities necessitate collaboration among the public as well as private sectors to install IT platforms to collect and examine massive quantities of data. At the same time, it is essential to design effective artificial intelligence (AI) based tools to handle healthcare crisis situations in smart cities. To offer proficient services to people during healthcare crisis time, the authorities need to look closer towards them. Sentiment… More >

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