Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (22,225)
  • Open Access

    ARTICLE

    Autism Spectrum Disorder Diagnosis Using Ensemble ML and Max Voting Techniques

    A. Arunkumar1,*, D. Surendran2

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 389-404, 2022, DOI:10.32604/csse.2022.020256

    Abstract Difficulty in communicating and interacting with other people are mainly due to the neurological disorder called autism spectrum disorder (ASD) diseases. These diseases can affect the nerves at any stage of the human being in childhood, adolescence, and adulthood. ASD is known as a behavioral disease due to the appearances of symptoms over the first two years that continue until adulthood. Most of the studies prove that the early detection of ASD helps improve the behavioral characteristics of patients with ASD. The detection of ASD is a very challenging task among various researchers. Machine learning (ML) algorithms still act very… More >

  • Open Access

    ARTICLE

    Classification of Foot Pressure Images Using Machine Learning Algorithm

    P. Ramya1, B. Padmapriya2, S. Poornachandra3

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 187-196, 2022, DOI:10.32604/csse.2022.020185

    Abstract Arthritis is an acute systemic disease of a joint accompanied by pain. In developed countries, it mainly causes disability among people over 50 years of age. Rheumatoid Arthritis is a type of arthritis that occurs commonly among elders. The incidence of arthritis is higher in females than in males. There is no permanent diagnosis method for arthritis, but if it was identified in the early stages based on the foot pressure, it can be diagnosed before attaining the critical stage of Rheumatoid Arthritis. The analysis and study of arthritis patients were done using design thinking methodology. Design thinking is a… More >

  • Open Access

    ARTICLE

    Short Text Mining for Classifying Educational Objectives and Outcomes

    Yousef Asiri*

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 35-50, 2022, DOI:10.32604/csse.2022.020100

    Abstract Most of the international accreditation bodies in engineering education (e.g., ABET) and outcome-based educational systems have based their assessments on learning outcomes and program educational objectives. However, mapping program educational objectives (PEOs) to student outcomes (SOs) is a challenging and time-consuming task, especially for a new program which is applying for ABET-EAC (American Board for Engineering and Technology the American Board for Engineering and Technology—Engineering Accreditation Commission) accreditation. In addition, ABET needs to automatically ensure that the mapping (classification) is reasonable and correct. The classification also plays a vital role in the assessment of students’ learning. Since the PEOs are… More >

  • Open Access

    ARTICLE

    Statistical Inference of Sine Inverse Rayleigh Distribution

    Abdullah, Ali H. Ahmadini*

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 405-414, 2022, DOI:10.32604/csse.2022.020079

    Abstract We study in this manuscript a new one-parameter model called sine inverse Rayleigh (SIR) model that is a new extension of the classical inverse Rayleigh model. The sine inverse Rayleigh model is aiming to provide more fitting for real data sets of purposes. The proposed extension is more flexible than the original inverse Rayleigh (IR) model and it hasmany applications in physics and medicine. The sine inverse Rayleigh distribution can havea uni-model and right skewed probability density function (PDF). The hazard rate function (HRF) of sine inverse Rayleigh distribution can be increasing and J-shaped. Several of thenew model’s fundamental characteristics,… More >

  • Open Access

    ARTICLE

    Secured Data Storage Using Deduplication in Cloud Computing Based on Elliptic Curve Cryptography

    N. Niyaz Ahamed*, N. Duraipandian

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 83-94, 2022, DOI:10.32604/csse.2022.020071

    Abstract The tremendous development of cloud computing with related technologies is an unexpected one. However, centralized cloud storage faces few challenges such as latency, storage, and packet drop in the network. Cloud storage gets more attention due to its huge data storage and ensures the security of secret information. Most of the developments in cloud storage have been positive except better cost model and effectiveness, but still data leakage in security are billion-dollar questions to consumers. Traditional data security techniques are usually based on cryptographic methods, but these approaches may not be able to withstand an attack from the cloud server's… More >

  • Open Access

    ARTICLE

    Ensemble Variable Selection for Naive Bayes to Improve Customer Behaviour Analysis

    R. Siva Subramanian1,*, D. Prabha2

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 339-355, 2022, DOI:10.32604/csse.2022.020043

    Abstract Executing customer analysis in a systemic way is one of the possible solutions for each enterprise to understand the behavior of consumer patterns in an efficient and in-depth manner. Further investigation of customer patterns helps the firm to develop efficient decisions and in turn, helps to optimize the enterprise’s business and maximizes consumer satisfaction correspondingly. To conduct an effective assessment about the customers, Naive Bayes(also called Simple Bayes), a machine learning model is utilized. However, the efficacious of the simple Bayes model is utterly relying on the consumer data used, and the existence of uncertain and redundant attributes in the… More >

  • Open Access

    ARTICLE

    Consensus-Based Ensemble Model for Arabic Cyberbullying Detection

    Asma A. Alhashmi*, Abdulbasit A. Darem

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 241-254, 2022, DOI:10.32604/csse.2022.020023

    Abstract Due to the proliferation of internet-enabled smartphones, many people, particularly young people in Arabic society, have widely adopted social media platforms as a primary means of communication, interaction and friendship making. The technological advances in smartphones and communication have enabled young people to keep in touch and form huge social networks from all over the world. However, such networks expose young people to cyberbullying and offensive content that puts their safety and emotional well-being at serious risk. Although, many solutions have been proposed to automatically detect cyberbullying, most of the existing solutions have been designed for English speaking consumers. The… More >

  • Open Access

    ARTICLE

    A Secure IoT-Cloud Based Healthcare System for Disease Classification Using Neural Network

    M. Vedaraj*, P. Ezhumalai

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 95-108, 2022, DOI:10.32604/csse.2022.019976

    Abstract The integration of the Internet of Things (IoT) and cloud computing is the most popular growing technology in the IT world. IoT integrated cloud computing technology can be used in smart cities, health care, smart homes, environmental monitoring, etc. In recent days, IoT integrated cloud can be used in the health care system for remote patient care, emergency care, disease prediction, pharmacy management, etc. but, still, security of patient data and disease prediction accuracy is a major concern. Numerous machine learning approaches were used for effective early disease prediction. However, machine learning takes more time and less performance while classification.… More >

  • Open Access

    ARTICLE

    Secured Vehicle Life Cycle Tracking Using Blockchain and Smart Contract

    Srinivasan Ananthanarayanan Bragadeesh, Arumugam Umamakeswari*

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 1-18, 2022, DOI:10.32604/csse.2022.019842

    Abstract Life Cycle Tracking (LCT) involves continuous monitoring and analysis of various activities associated with a vehicle. The crucial factor in the LCT is to ensure the validity of gathered data as numerous supply chain phases are involved and the data is assessed by multiple stakeholders. Frauds and swindling activities can be prevented if the history of the vehicles is made available to the interested parties. Blockchain provides a way of enforcing trustworthiness to the supply chain participants and the data associated with the various actions performed. Machine learning techniques when combined decentralized nature of blockchains can be used to develop… More >

  • Open Access

    ARTICLE

    Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

    I. Kalphana1,*, T. Kesavamurthy2

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 171-185, 2022, DOI:10.32604/csse.2022.019799

    Abstract Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from… More >

Displaying 10561-10570 on page 1057 of 22225. Per Page