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  • Open Access

    ARTICLE

    The Effect of Specialized Digital Training on Double Poling Technique for Para Seated Cross-Country Skiing Athletes

    Yong Wang1, Dong Sun1,*, Anand Thirupathi1, Julien S. Baker2, Yaodong Gu1,*

    Molecular & Cellular Biomechanics, Vol.19, No.4, pp. 177-189, 2022, DOI:10.32604/mcb.2022.021764

    Abstract Purpose: In order to satisfy the requirements of Chinese Para seated cross-country skiers special training for Double poling scientifically, and the individualized strength training of Paralympic athletes, this study aims to explore the effect of the full-dimensional servo-driven intelligent training system on para cross-country skiers’ strength training. Methods: 12 Para seated cross-country skiing athletes were included (6 males and 6 females: LW10.5-LW12), 4 weeks of training of the Double poling based on the centripetal isotonic mode of the full-dimensional servo-driven intelligent training system, the special strength quality indicators include the speed and power of the Double poling in the centripetal… More >

  • Open Access

    ARTICLE

    Computation of Stiffness and Damping Derivatives of an Ogive in a Limiting Case of Mach Number and Specific Heat Ratio

    Aysha Shabana1,2,*, Asha Crasta1, Sher Afghan Khan3, Abdul Aabid4, Muneer Baig4

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.5, pp. 1249-1267, 2023, DOI:10.32604/fdmp.2023.023158

    Abstract This work aims to compute stability derivatives in the Newtonian limit in pitch when the Mach number tends to infinity. In such conditions, these stability derivatives depend on the Ogive’s shape and not the Mach number. Generally, the Mach number independence principle becomes effective from M = 10 and above. The Ogive nose is obtained through a circular arc on the cone surface. Accordingly, the following arc slopes are considered λ = 5, 10, 15, −5, −10, and −15. It is found that the stability derivatives decrease due to the growth in λ from 5 to 15 and vice versa.… More >

  • Open Access

    ARTICLE

    DERNNet: Dual Encoding Recurrent Neural Network Based Secure Optimal Routing in WSN

    A. Venkatesh1, S. Asha2,*

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1375-1392, 2023, DOI:10.32604/csse.2023.030944

    Abstract A Wireless Sensor Network (WSN) is constructed with numerous sensors over geographical regions. The basic challenge experienced while designing WSN is in increasing the network lifetime and use of low energy. As sensor nodes are resource constrained in nature, novel techniques are essential to improve lifetime of nodes in WSN. Nodes energy is considered as an important resource for sensor node which are battery powered based. In WSN, energy is consumed mainly while data is being transferred among nodes in the network. Several research works are carried out focusing on preserving energy of nodes in the network and made network… More >

  • Open Access

    ARTICLE

    A Parallel Hybrid Testing Technique for Tri-Programming Model-Based Software Systems

    Huda Basloom1,*, Mohamed Dahab1, Abdullah Saad AL-Ghamdi2, Fathy Eassa1, Ahmed Mohammed Alghamdi3, Seif Haridi4

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4501-4530, 2023, DOI:10.32604/cmc.2023.033928

    Abstract Recently, researchers have shown increasing interest in combining more than one programming model into systems running on high performance computing systems (HPCs) to achieve exascale by applying parallelism at multiple levels. Combining different programming paradigms, such as Message Passing Interface (MPI), Open Multiple Processing (OpenMP), and Open Accelerators (OpenACC), can increase computation speed and improve performance. During the integration of multiple models, the probability of runtime errors increases, making their detection difficult, especially in the absence of testing techniques that can detect these errors. Numerous studies have been conducted to identify these errors, but no technique exists for detecting errors… More >

  • Open Access

    ARTICLE

    Improved Clamped Diode Based Z-Source Network for Three Phase Induction Motor

    D. Bensiker Raja Singh1,*, R. Suja Mani Malar2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 683-702, 2023, DOI:10.32604/iasc.2023.028492

    Abstract The 3Φ induction motor is a broadly used electric machine in industrial applications, which plays a vital role in industries because of having plenty of beneficial impacts like low cost and easiness but the problems like decrease in motor speed due to load, high consumption of current and high ripple occurrence of ripples have reduced its preferences. The ultimate objective of this study is to control change in motor speed due to load variations. An improved Trans Z Source Inverter (ΓZSI) with a clamping diode is employed to maintain constant input voltage, reduce ripples and voltage overshoot. To operate induction… More >

  • Open Access

    ARTICLE

    Empirical Analysis of Software Success Rate Forecasting During Requirement Engineering Processes

    Muhammad Hasnain1, Imran Ghani2, Seung Ryul Jeong3,*, Muhammad Fermi Pasha4, Sardar Usman5, Anjum Abbas6

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 783-799, 2023, DOI:10.32604/cmc.2023.030162

    Abstract Forecasting on success or failure of software has become an interesting and, in fact, an essential task in the software development industry. In order to explore the latest data on successes and failures, this research focused on certain questions such as is early phase of the software development life cycle better than later phases in predicting software success and avoiding high rework? What human factors contribute to success or failure of a software? What software practices are used by the industry practitioners to achieve high quality of software in their day-to-day work? In order to conduct this empirical analysis a… More >

  • Open Access

    ARTICLE

    Research on VSG Frequency Characteristics and Energy Storage Device Capacity and Charge-Discharge Characteristics Based on Feedforward Branch

    Baoge Zhang1, Shanyan Ping1,*, Haoliang Shi2, Yi Long1, Boxiang Wu1, Yuemin Jiao1

    Energy Engineering, Vol.119, No.6, pp. 2347-2367, 2022, DOI:10.32604/ee.2022.021693

    Abstract Renewable energy is connected to the grid through the inverter, which in turn reduces the inertia and stability of the power grid itself. The traditional grid-connected inverter does not have the function of voltage regulation and frequency regulation and can therefore no longer adapt to the new development. The virtual synchronous generator (VSG) has the function of voltage regulation and frequency regulation, which has more prominent advantages than traditional inverters. Based on the principle of VSG, the relationship between the frequency characteristics and the energy storage capacity of the feedforward branch-based virtual synchronous machine (FVSG) is derived when the input… More >

  • Open Access

    ARTICLE

    A Hybrid BPNN-GARF-SVR Prediction Model Based on EEMD for Ship Motion

    Hao Han, Wei Wang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1353-1370, 2023, DOI:10.32604/cmes.2022.021494

    Abstract Accurate prediction of ship motion is very important for ensuring marine safety, weapon control, and aircraft carrier landing, etc. Ship motion is a complex time-varying nonlinear process which is affected by many factors. Time series analysis method and many machine learning methods such as neural networks, support vector machines regression (SVR) have been widely used in ship motion predictions. However, these single models have certain limitations, so this paper adopts a multi-model prediction method. First, ensemble empirical mode decomposition (EEMD) is used to remove noise in ship motion data. Then the random forest (RF) prediction model optimized by genetic algorithm… More >

  • Open Access

    ARTICLE

    Early Detection of Heartbeat from Multimodal Data Using RPA Learning with KDNN-SAE

    A. K. S. Saranya1,*, T. Jaya2

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 545-562, 2023, DOI:10.32604/csse.2023.029975

    Abstract Heartbeat detection stays central to cardiovascular an electrocardiogram (ECG) is used to help with disease diagnosis and management. Existing Convolutional Neural Network (CNN)-based methods suffer from the less generalization problem thus; the effectiveness and robustness of the traditional heartbeat detector methods cannot be guaranteed. In contrast, this work proposes a heartbeat detector Krill based Deep Neural Network Stacked Auto Encoders (KDNN-SAE) that computes the disease before the exact heart rate by combining features from multiple ECG Signals. Heartbeats are classified independently and multiple signals are fused to estimate life threatening conditions earlier without any error in classification of heart beat.… More >

  • Open Access

    ARTICLE

    Algorithms for Pre-Compiling Programs by Parallel Compilers

    Fayez AlFayez*

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2165-2176, 2023, DOI:10.32604/csse.2023.026238

    Abstract The paper addresses the challenge of transmitting a big number of files stored in a data center (DC), encrypting them by compilers, and sending them through a network at an acceptable time. Face to the big number of files, only one compiler may not be sufficient to encrypt data in an acceptable time. In this paper, we consider the problem of several compilers and the objective is to find an algorithm that can give an efficient schedule for the given files to be compiled by the compilers. The main objective of the work is to minimize the gap in the… More >

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