Haijie Pan, Lirong Zheng^*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 493-512, 2022, DOI:10.32604/cmes.2022.019069 - 24 January 2022

Abstract The machine learning model converges slowly and has unstable training since large variance by random using a sample estimate gradient in SGD. To this end, we propose a noise reduction method for Stochastic Variance Reduction gradient (SVRG), called N-SVRG, which uses small batches samples instead of all samples for the average gradient calculation, while performing an incremental update of the average gradient. In each round of iteration, a small batch of samples is randomly selected for the average gradient calculation, while the average gradient is updated by rounding of the past model gradients during internal… More >

J. P. Shri Tharanyaa^1,*, D. Sharmila², R. Saravana Kumar³

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2667-2681, 2022, DOI:10.32604/cmc.2022.019889 - 07 December 2021

Abstract With the emergence of the Internet of things (IoT), embedded systems have now changed its dimensionality and it is applied in various domains such as healthcare, home automation and mainly Industry 4.0. These Embedded IoT devices are mostly battery-driven. It has been analyzed that usage of Dynamic Random-Access Memory (DRAM) centered core memory is considered the most significant source of high energy utility in Embedded IoT devices. For achieving the low power consumption in these devices, Non-volatile memory (NVM) devices such as Parameter Random Access Memory (PRAM) and Spin-Transfer Torque Magnetic Random-Access Memory (STT-RAM) are… More >

Yasemin Onal^*

Computer Systems Science and Engineering, Vol.41, No.1, pp. 141-156, 2022, DOI:10.32604/csse.2022.020367 - 08 October 2021

Abstract Predicting the power obtained at the output of the photovoltaic (PV) system is fundamental for the optimum use of the PV system. However, it varies at different times of the day depending on intermittent and nonlinear environmental conditions including solar irradiation, temperature and the wind speed, Short-term power prediction is vital in PV systems to reconcile generation and demand in terms of the cost and capacity of the reserve. In this study, a Gaussian kernel based Support Vector Regression (SVR) prediction model using multiple input variables is proposed for estimating the maximum power obtained from… More >

N. Kanagaraj^*

Computer Systems Science and Engineering, Vol.40, No.2, pp. 517-538, 2022, DOI:10.32604/csse.2022.019149 - 09 September 2021

Abstract In this paper, the hybrid photovoltaic-thermoelectric generator (PV-TEG) combined dynamic voltage restorer (DVR) system is proposed for the power quality disturbances compensation in a single-phase distribution system. The stable and precise level of input voltage is essential for the smooth and trouble-free operation of the electrically sensitive loads which are connected at the utility side to avoid system malfunctions. In this context, the hybrid PV-TEG energy module combined DVR system is proposed in this paper. With the support of the hybrid energy module, the DVR will perform the power quality disturbances compensation effectively with needed… More >

Diantao Hu, Cong Zhang^*, Wenqi Cao, Xintao Lv, Songwu Xie

Journal on Big Data, Vol.3, No.2, pp. 65-76, 2021, DOI:10.32604/jbd.2021.016317 - 13 April 2021

Abstract Grain yield security is a basic national policy of China, and changes in grain yield are influenced by a variety of factors, which often have a complex, non-linear relationship with each other. Therefore, this paper proposes a Grey Relational Analysis–Adaptive Boosting–Support Vector Regression (GRAAdaBoost-SVR) model, which can ensure the prediction accuracy of the model under small sample, improve the generalization ability, and enhance the prediction accuracy. SVR allows mapping to high-dimensional spaces using kernel functions, good for solving nonlinear problems. Grain yield datasets generally have small sample sizes and many features, making SVR a promising… More >

Praveena Rajasekaran^*, Preetha Jaganathan, Anjali Annadurai

Computer Systems Science and Engineering, Vol.36, No.3, pp. 477-484, 2021, DOI:10.32604/csse.2021.014247 - 18 January 2021

Abstract The stabilizing mechanisms of cervical spine spondylosis are involved in the degenerating segmentation vertebra, which often causes pain. Health of the individual is affected, both physically and mentally. Due to depression, nervousness, and psychological damages occur thereby losing their human activity functions. The nucleus pulposus of spinal disc herniation is prolapsed through a deficiency of annulus fibrosus. A jelly-like core part of the disc contains proteins that cause the tissues to become swollen when it touches the nucleus pulposus. The proposed Gradient Linear Classification (GLC) algorithm is used for the efficient automatic classification of disc More >

Raniyah Wazirali^*

Computer Systems Science and Engineering, Vol.36, No.2, pp. 339-351, 2021, DOI:10.32604/csse.2021.014301 - 05 January 2021

Abstract Vision 2030 requires a new generation of people with a wide variety of abilities, talents, and skills. The adoption of augmented reality (AR) and virtual reality is one possible way to align education with Vision 2030. Immersive technologies like AR are rapidly becoming powerful and versatile enough to be adopted in education to achieve this goal. Technologies such as AR could be beneficial tools to enhance maintainable growth in education. We reviewed the most recent studies in augmented reality to check its appropriateness in aligning with the educational goals of Vision 2030. First, the various… More >

Tuan Thanh Le¹, Jong-Beom Jeong², SangSoon Lee¹, Jaehyoun Kim², Eun-Seok Ryu^2,*

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2627-2643, 2021, DOI:10.32604/cmc.2021.013399 - 28 December 2020

Abstract Recent advances in 360 video streaming technologies have enhanced the immersive experience of video streaming services. Particularly, there is immense potential for the application of 360 video encoding formats to achieve highly immersive virtual reality (VR) systems. However, 360 video streaming requires considerable bandwidth, and its performance depends on several factors. Consequently, the optimization of 360 video bitstreams according to viewport texture is crucial. Therefore, we propose an adaptive solution for VR systems using viewport-dependent tiled 360 video streaming. To increase the degrees of freedom of users, the moving picture experts group (MPEG) recently defined… More >

Fadhila Mansour^1,2,*, Abdelhak Lakehal^2,3, Lahcène Nezzal^2,3

Oncologie, Vol.22, No.3, pp. 117-128, 2020, DOI:10.32604/oncologie.2020.014979

Abstract L’objectif de cette étude était de quantifier les délais de prise en charge des femmes atteintes de cancer du sein prises en charge au niveau du centre anticancer de Batna, Algérie. Il s’agissait d’une étude rétrospective à visée descriptive effectuée durant la période Août 2015 à Février 2016. Afin de retracer l’historique du parcours depuis les premiers signes d’apparition du cancer jusqu’aux premiers traitements, un questionnaire a été renseigné à partir des dossiers médicaux et complété par une interview auprès des patientes. 267 patientes ont été incluses dans l’étude. Le délai médian de prise en More >

Peng Tang^∗, Yu Wang, Ning Shen

Computer Systems Science and Engineering, Vol.35, No.4, pp. 237-246, 2020, DOI:10.32604/csse.2020.35.237

Abstract In today’s modern society, the physical fitness of college students is gradually declining. In this paper, a prediction model for college students’ physical fitness is established, in which support vector regression (SVR) and k-means clustering are combined together for the prediction of college students’ fitness. Firstly, the physical measurement data of college students are classified according to gender and class characteristics. Then, the k-means clustering method is used to classify the physical measurement data of college students. Next, the physical characteristics of college students are extracted by SVR to establish the prediction model of physical More >