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  • Open Access

    ARTICLE

    Performance Analysis of Hybrid RR Algorithm for Anomaly Detection in Streaming Data

    L. Amudha1,*, R. PushpaLakshmi2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2299-2312, 2023, DOI:10.32604/csse.2023.031169

    Abstract Automated live video stream analytics has been extensively researched in recent times. Most of the traditional methods for video anomaly detection is supervised and use a single classifier to identify an anomaly in a frame. We propose a 3-stage ensemble-based unsupervised deep reinforcement algorithm with an underlying Long Short Term Memory (LSTM) based Recurrent Neural Network (RNN). In the first stage, an ensemble of LSTM-RNNs are deployed to generate the anomaly score. The second stage uses the least square method for optimal anomaly score generation. The third stage adopts award-based reinforcement learning to update the model. The proposed Hybrid Ensemble… More >

  • Open Access

    ARTICLE

    Intelligent Color Reasoning of IOT Based on P-laws

    HuangJing Yu1, Jinming Qiu1, Ning Cao2,*, Russell Higgs2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 3181-3193, 2023, DOI:10.32604/csse.2023.030985

    Abstract Aiming at the dynamics and uncertainties of natural colors affected by the natural environment, a color P-law generation model based on the natural environment is proposed to develop algorithms and to provide a theoretical basis for plant dynamic color simulation and color sensor data transmission. Based on the HSL (Hue, Saturation, Lightness) color solid, the proposed method uses the function P-set to provide a color P-law generation model and an algorithm of the Dynamic Colors System (DCS), establishing the DCS modeling theory of the natural environment and the color P-reasoning simulation based on the HSL color solid. The experimental results… More >

  • Open Access

    ARTICLE

    N×N Clos Digital Cross-Connect Switch Using Quantum Dot Cellular Automata (QCA)

    Amita Asthana1,*, Anil Kumar1, Preeta Sharan2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2901-2917, 2023, DOI:10.32604/csse.2023.030548

    Abstract Quantum dot cellular automata (QCA) technology is emerging as a future technology which designs the digital circuits at quantum levels. The technology has gained popularity in terms of designing digital circuits, which occupy very less area and less power dissipation in comparison to the present complementary metal oxide semiconductor (CMOS) technology. For designing the routers at quantum levels with non-blocking capabilities various multi-stage networks have been proposed. This manuscript presents the design of the N×N Clos switch matrix as a multistage interconnecting network using quantum-dot cellular automata technology. The design of the Clos switch matrix presented in the article uses… More >

  • Open Access

    ARTICLE

    IOT Assisted Biomedical Monitoring Sensors for Healthcare in Human

    S. Periyanayagi1, V. Nandini2,*, K. Basarikodi3, V. Sumathy4

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2853-2868, 2023, DOI:10.32604/csse.2023.030538

    Abstract The Internet of Things (IoT) is a concept that refers to the deployment of Internet Protocol (IP) address sensors in health care systems to monitor patients’ health. It has the ability to access the Internet and collect data from sensors. Automated decisions are made after evaluating the information of illness people records. Patients’ health and well-being can be monitored through IoT medical devices. It is possible to trace the origins of biological, medical equipment and processes. Human reliability is a major concern in user activity and fitness trackers in day-to-day activities. The fundamental challenge is to measure the efficiency of… More >

  • Open Access

    ARTICLE

    Graph Ranked Clustering Based Biomedical Text Summarization Using Top k Similarity

    Supriya Gupta*, Aakanksha Sharaff, Naresh Kumar Nagwani

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2333-2349, 2023, DOI:10.32604/csse.2023.030385

    Abstract Text Summarization models facilitate biomedical clinicians and researchers in acquiring informative data from enormous domain-specific literature within less time and effort. Evaluating and selecting the most informative sentences from biomedical articles is always challenging. This study aims to develop a dual-mode biomedical text summarization model to achieve enhanced coverage and information. The research also includes checking the fitment of appropriate graph ranking techniques for improved performance of the summarization model. The input biomedical text is mapped as a graph where meaningful sentences are evaluated as the central node and the critical associations between them. The proposed framework utilizes the top… More >

  • Open Access

    ARTICLE

    Usability-Driven Mobile Application Development

    Fadwa Yahya1,2,*, Lassaad Ben Ammar1,2, Gasmi Karim3

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 3165-3180, 2023, DOI:10.32604/csse.2023.030358

    Abstract Recently, a specific interest is being taken in the development of mobile application (app) via Model-Based User Interface Development (MBUID) approach. MBUID allows the generation of mobile apps in the target platform(s) from conceptual models. As such it simplified the development process of mobile app. However, the interest is only focused on the functional aspects of the mobile app while neglecting the non-functional aspects, such as usability. The latter is largely considered as the main factor leading to the success or failure of any software system. This paper aims at addressing non-functional aspects of mobile apps generated using MBUID approach.… More >

  • Open Access

    ARTICLE

    Integrated Approach of Brain Disorder Analysis by Using Deep Learning Based on DNA Sequence

    Ahmed Zohair Ibrahim1,*, P. Prakash2, V. Sakthivel2, P. Prabu3

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2447-2460, 2023, DOI:10.32604/csse.2023.030134

    Abstract In order to research brain problems using MRI, PET, and CT neuroimaging, a correct understanding of brainfunction is required. This has been considered in earlier times with the support of traditional algorithms. Deep learning process has also been widely considered in these genomics data processing system. In this research, brain disorder illness incliding Alzheimer’s disease, Schizophrenia and Parkinson’s diseaseis is analyzed owing to misdetection of disorders in neuroimaging data examined by means fo traditional methods. Moeover, deep learning approach is incorporated here for classification purpose of brain disorder with the aid of Deep Belief Networks (DBN). Images are stored in… More >

  • Open Access

    ARTICLE

    DC–DC Converter with Pi Controller for BLDC Motor Fuzzy Drive System

    S. Pandeeswari1,*, S. Jaganathan2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2811-2825, 2023, DOI:10.32604/csse.2023.029945

    Abstract The Brushless DC Motor drive systems are used widely with renewable energy resources. The power converter controlling technique increases the performance by novel techniques and algorithms. Conventional approaches are mostly focused on buck converter, Fuzzy logic control with various switching activity. In this proposed research work, the QPSO (Quantum Particle Swarm Optimization algorithm) is used on the switching state of converter from the generation unit of solar module. Through the duty cycle pulse from optimization function, the MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor) of the Boost converter gets switched when BLDC (Brushless Direct Current Motor) motor drive system requires power. Voltage Source… More >

  • Open Access

    ARTICLE

    Software Defect Prediction Based Ensemble Approach

    J. Harikiran1,*, B. Sai Chandana1, B. Srinivasarao1, B. Raviteja2, Tatireddy Subba Reddy3

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2313-2331, 2023, DOI:10.32604/csse.2023.029689

    Abstract Software systems have grown significantly and in complexity. As a result of these qualities, preventing software faults is extremely difficult. Software defect prediction (SDP) can assist developers in finding potential bugs and reducing maintenance costs. When it comes to lowering software costs and assuring software quality, SDP plays a critical role in software development. As a result, automatically forecasting the number of errors in software modules is important, and it may assist developers in allocating limited resources more efficiently. Several methods for detecting and addressing such flaws at a low cost have been offered. These approaches, on the other hand,… More >

  • Open Access

    ARTICLE

    Drug Usage Safety from Drug Reviews with Hybrid Machine Learning Approach

    Ernesto Lee1, Furqan Rustam2, Hina Fatima Shahzad2, Patrick Bernard Washington3, Abid Ishaq3, Imran Ashraf4,*

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 3053-3077, 2023, DOI:10.32604/csse.2023.029059

    Abstract With the increasing usage of drugs to remedy different diseases, drug safety has become crucial over the past few years. Often medicine from several companies is offered for a single disease that involves the same/similar substances with slightly different formulae. Such diversification is both helpful and dangerous as such medicine proves to be more effective or shows side effects to different patients. Despite clinical trials, side effects are reported when the medicine is used by the mass public, of which several such experiences are shared on social media platforms. A system capable of analyzing such reviews could be very helpful… More >

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