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  • Open Access


    Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals

    Ayman Altameem1, Jaideep Singh Sachdev2, Vijander Singh2, Ramesh Chandra Poonia3, Sandeep Kumar4, Abdul Khader Jilani Saudagar5,*

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1095-1107, 2022, DOI:10.32604/csse.2022.023256

    Abstract Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG) headsets in the form of EEG signals; these signals can be recorded, processed and classified into different hand movements, which can be used to control other IoT devices. Classification of hand movements will be one step closer to applying these algorithms in real-life situations using EEG headsets. This paper uses different feature extraction techniques and sophisticated machine learning algorithms to classify hand movements from EEG brain signals to control prosthetic hands for amputated persons. To achieve good classification accuracy, denoising and feature extraction of EEG signals… More >

  • Open Access


    Planetscope Nanosatellites Image Classification Using Machine Learning

    Mohd Anul Haq*

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1031-1046, 2022, DOI:10.32604/csse.2022.023221

    Abstract To adopt sustainable crop practices in changing climate, understanding the climatic parameters and water requirements with vegetation is crucial on a spatiotemporal scale. The Planetscope (PS) constellation of more than 130 nanosatellites from Planet Labs revolutionize the high-resolution vegetation assessment. PS-derived Normalized Difference Vegetation Index (NDVI) maps are one of the highest resolution data that can transform agricultural practices and management on a large scale. High-resolution PS nanosatellite data was utilized in the current study to monitor agriculture’s spatiotemporal assessment for the Al-Qassim region, Kingdom of Saudi Arabia (KSA). The time series of NDVI was… More >

  • Open Access


    Research on Ratio of New Energy Vehicles to Charging Piles in China

    Zhiqiu Yu*, Shuo-Yan Chou

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 963-984, 2022, DOI:10.32604/csse.2022.023129

    Abstract With the widespread of new energy vehicles, charging piles have also been continuously installed and constructed. In order to make the number of piles meet the needs of the development of new energy vehicles, this study aims to apply the method of system dynamics and combined with the grey prediction theory to determine the parameters as well as to simulate and analyze the ratio of vehicles to chargers. Through scenario analysis, it is predicted that by 2030, this ratio will gradually decrease from 1.79 to 1. In order to achieve this ratio as 1:1, it More >

  • Open Access


    A Compact Self-Isolated MIMO Antenna System for 5G Mobile Terminals

    Muhannad Y. Muhsin1,*, Ali J. Salim2, Jawad K. Ali2

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 919-934, 2022, DOI:10.32604/csse.2022.023102

    Abstract A compact self-isolated Multi Input Multi Output (MIMO) antenna array is presented for 5G mobile phone devices. The proposed antenna system is operating at the 3.5 GHz band (3400–3600 MHz) and consists of eight antenna elements placed along two side edges of a mobile device, which meets the current trend requirements of full-screen smartphone devices. Each antenna element is divided into two parts, a front part and back part. The front part consists of an I-shaped feeding line and a modified Hilbert fractal monopole antenna, whereas the back part is an L-shaped element shorted to… More >

  • Open Access


    A Model for Cross-Domain Opinion Target Extraction in Sentiment Analysis

    Muhammet Yasin PAK*, Serkan GUNAL

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1215-1239, 2022, DOI:10.32604/csse.2022.023051

    Abstract Opinion target extraction is one of the core tasks in sentiment analysis on text data. In recent years, dependency parser–based approaches have been commonly studied for opinion target extraction. However, dependency parsers are limited by language and grammatical constraints. Therefore, in this work, a sequential pattern-based rule mining model, which does not have such constraints, is proposed for cross-domain opinion target extraction from product reviews in unknown domains. Thus, knowing the domain of reviews while extracting opinion targets becomes no longer a requirement. The proposed model also reveals the difference between the concepts of opinion… More >

  • Open Access


    Cryptographic Lightweight Encryption Algorithm with Dimensionality Reduction in Edge Computing

    D. Jerusha*, T. Jaya

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1121-1132, 2022, DOI:10.32604/csse.2022.022997

    Abstract Edge Computing is one of the radically evolving systems through generations as it is able to effectively meet the data saving standards of consumers, providers and the workers. Requisition for Edge Computing based items have been increasing tremendously. Apart from the advantages it holds, there remain lots of objections and restrictions, which hinders it from accomplishing the need of consumers all around the world. Some of the limitations are constraints on computing and hardware, functions and accessibility, remote administration and connectivity. There is also a backlog in security due to its inability to create a… More >

  • Open Access


    Soft Computing Based Discriminator Model for Glaucoma Diagnosis

    Anisha Rebinth1,*, S. Mohan Kumar2

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 867-880, 2022, DOI:10.32604/csse.2022.022955

    Abstract In this study, a Discriminator Model for Glaucoma Diagnosis (DMGD) using soft computing techniques is presented. As the biomedical images such as fundus images are often acquired in high resolution, the Region of Interest (ROI) for glaucoma diagnosis must be selected at first to reduce the complexity of any system. The DMGD system uses a series of pre-processing; initial cropping by the green channel’s intensity, Spatially Weighted Fuzzy C Means (SWFCM), blood vessel detection and removal by Gaussian Derivative Filters (GDF) and inpainting algorithms. Once the ROI has been selected, the numerical features such as More >

  • Open Access


    Diagnosing Breast Cancer Accurately Based on Weighting of Heterogeneous Classification Sub-Models

    Majdy Mohamed Eltayeb Eltahir1,*, Tarig Mohammed Ahmed2,3

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1257-1272, 2022, DOI:10.32604/csse.2022.022942

    Abstract In developed and developing countries, breast cancer is one of the leading forms of cancer affecting women alike. As a consequence of growing life expectancy, increasing urbanization and embracing Western lifestyles, the high prevalence of this cancer is noted in the developed world. This paper aims to develop a novel model that diagnoses Breast Cancer by using heterogeneous datasets. The model can work as a strong decision support system to help doctors to make the right decision in diagnosing breast cancer patients. The proposed model is based on three datasets to develop three sub-models. Each More >

  • Open Access


    An Intelligent Recommendation System for Real Estate Commodity

    Tsung-Yin Ou1, Guan-Yu Lin2, Hsin-Pin Fu1, Shih-Chia Wei1, Wen-Lung Tsai3,*

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 881-897, 2022, DOI:10.32604/csse.2022.022637

    Abstract Most real estate agents develop new objects by visiting unfamiliar clients, distributing leaflets, or browsing other real estate trading website platforms, whereas consumers often rely on websites to search and compare prices when purchasing real property. In addition to being time consuming, this search process renders it difficult for agents and consumers to understand the status changes of objects. In this study, Python is used to write web crawler and image recognition programs to capture object information from the web pages of real estate agents; perform data screening, arranging, and cleaning; compare the text of… More >

  • Open Access


    Multi-Objective Modified Particle Swarm Optimization for Test Suite Reduction (MOMPSO)

    U. Geetha1,*, Sharmila Sankar2

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 899-917, 2022, DOI:10.32604/csse.2022.022621

    Abstract Software testing plays a pivotal role in entire software development lifecycle. It provides researchers with extensive opportunities to develop novel methods for the optimized and cost-effective test suite Although implementation of such a cost-effective test suite with regression testing is being under exploration still it contains lot of challenges and flaws while incorporating with any of the new regression testing algorithm due to irrelevant test cases in the test suite which are not required. These kinds of irrelevant test cases might create certain challenges such as code-coverage in the test suite, fault-tolerance, defects due to More >

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