Tzu-Chia Chen¹, Ngakan Ketut Acwin Dwijendra², I. Wayan Parwata³, Agata Iwan Candra⁴, Elsayed M. Tag El Din^5,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1305-1316, 2023, DOI:10.32604/cmc.2023.033274

Abstract Because solar energy is among the renewable energies, it has traditionally been used to provide lighting in buildings. When solar energy is effectively utilized during the day, the environment is not only more comfortable for users, but it also utilizes energy more efficiently for both heating and cooling purposes. Because of this, increasing the building’s energy efficiency requires first controlling the amount of light that enters the space. Considering that the only parts of the building that come into direct contact with the sun are the windows, it is essential to make use of louvers in order to regulate the… More >

Mehrdad Ahmadi Kamarposhti^1,*, Ilhami Colak², Phatiphat Thounthong³, Kei Eguchi⁴

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4547-4570, 2023, DOI:10.32604/cmc.2023.034082

Abstract The present study suggests that series voltage injection is more effective than parallel current injection to improve voltage quality on the load side. The line voltage can be accurately symmetrized at the connection point by creating and controlling a series voltage component in each phase. This is more reliable and effective than parallel current injection. A dynamic voltage restorer (DVR) and a distribution static synchronous compensator (DSTATCOM) were utilized to provide the required power. The DVR is an effective and modern device utilized in parallel within the grid and can protect sensitive loads from voltage problems in the grid by… 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 >

Haijie Pan, Lirong Zheng^*

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

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 iterations. By suitably reducing the… 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

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 becoming popular among main memory… More >

Yasemin Onal^*

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

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 using perturb observation method in… More >

N. Kanagaraj^*

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

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 voltage and /or power. In… 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

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 application for grain yield datasets.… 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

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 degeneration herniation of Inter vertebral/… More >

Raniyah Wazirali^*

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

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 definitions, terminologies, and technologies of… More >