Zhijie Zheng¹, Song Zhang¹, Xiaolei Zhang², Bo Yang¹, Fang Yan³, Xiaoning Ge^3,*

Energy Engineering, Vol.120, No.3, pp. 633-647, 2023, DOI:10.32604/ee.2022.024081

Abstract The DC distribution network system equipped with a large number of power electronic equipment exhibits weak damping characteristics and is prone to low-frequency and high-frequency unstable oscillations. The current interpretation of the oscillation mechanism has not been unified. Firstly, this paper established the complete state-space model of the distribution system consisting of a large number of electric vehicles, characteristic equation of the distribution network system is derived by establishing a state-space model, and simplified reduced-order equations describing the low-frequency oscillation and the high-frequency oscillation are obtained. Secondly, based on eigenvalue analysis, the oscillation modes and the influence of the key… More >

Yong Wang¹, Dong Sun^1,*, Anand Thirupathi¹, Julien S. Baker², Yaodong Gu^1,*

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 >

Aysha Shabana^1,2,*, 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 >

A. Venkatesh¹, S. Asha^2,*

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 >

Huda Basloom^1,*, 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 >

D. Bensiker Raja Singh^1,*, 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 >

Muhammad Hasnain¹, Imran Ghani², Seung Ryul Jeong^3,*, 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 >

Baoge Zhang¹, Shanyan Ping^1,*, 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 >

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 >

A. K. S. Saranya^1,*, 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 >