Aiyun Hu¹, Sunli Cong^1,*, Jian Ding², Yao Cheng¹, Enock Mpofu³

Computer Systems Science and Engineering, Vol.38, No.1, pp. 65-77, 2021, DOI:10.32604/csse.2021.016404 - 01 April 2021

Abstract In the fed-batch cultivation of Saccharomyces cerevisiae, excessive glucose addition leads to increased ethanol accumulation, which will reduce the efficiency of glucose utilization and inhibit product synthesis. Insufficient glucose addition limits cell growth. To properly regulate glucose feed, a different evolution algorithm based on self-adaptive control strategy was proposed, consisting of three modules (PID, system identification and parameter optimization). Performance of the proposed and conventional PID controllers was validated and compared in simulated and experimental cultivations. In the simulation, cultivation with the self-adaptive control strategy had a more stable glucose feed rate and concentration, more stable More >

Ney Augusto Dumont

The International Conference on Computational & Experimental Engineering and Sciences, Vol.23, No.1, pp. 2-2, 2021, DOI:10.32604/icces.2021.08187

Abstract The mathematical modeling of microdevices, in which structure and microstructure have approximately the same scale of magnitude, as well as of macrostructures of markedly granular or crystal nature (microcomposites), demands a nonlocal approach for strains and stresses. The present proposition is based on a simplified strain gradient theory laid down by Aifantis, which has also been applied mainly by Beskos and collaborators in the context of the boundary element method. This paper is an extension of a presentation made during the ICCES 2014 Conference in Crete, Greece, now relying on machine-precision evaluation of all singular… More >

Chunli Yin^1,*, Jinglong Han²

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 291-307, 2021, DOI:10.32604/cmes.2021.014347 - 30 March 2021

Abstract With the continuous development of artificial intelligence technology, its application field has gradually expanded. To further apply the deep reinforcement learning technology to the field of dynamic pricing, we build an intelligent dynamic pricing system, introduce the reinforcement learning technology related to dynamic pricing, and introduce existing research on the number of suppliers (single supplier and multiple suppliers), environmental models, and selection algorithms. A two-period dynamic pricing game model is designed to assess the optimal pricing strategy for e-commerce platforms under two market conditions and two consumer participation conditions. The first step is to analyze… More >

Lu Li¹, Yuzhen Fan², Xinglang Su^1,*, Gefei Qiu¹

Energy Engineering, Vol.118, No.3, pp. 565-580, 2021, DOI:10.32604/EE.2021.014627 - 22 March 2021

Abstract Because of the randomness and uncertainty, integration of large-scale wind farms in a power system will exert significant influences on the distribution of power flow. This paper uses polynomial normal transformation method to deal with non-normal random variable correlation, and solves probabilistic load flow based on Kriging method. This method is a kind of smallest unbiased variance estimation method which estimates unknown information via employing a point within the confidence scope of weighted linear combination. Compared with traditional approaches which need a greater number of calculation times, long simulation time, and large memory space, Kriging More >

Zhongjia Li¹, Jianfeng Pan^1,*, Hongjun Liu¹, Baowei Fan¹, Wenming Yang², Abiodun Oluwaleke Ojo¹

Energy Engineering, Vol.118, No.3, pp. 581-603, 2021, DOI:10.32604/EE.2021.014378 - 22 March 2021

Abstract In order to improve the performance of the rotary engine, this paper has designed a new type of dual-pit rotary engine combustion chamber structure, and compares the combustion and emission characteristics with the rotary engine with a traditional combustion chamber. The existence of the dual-pit combustion chamber strengthens the overall vortex intensity in the cylinder, effectively promotes the mixing process of fuel and air in the cylinder, the maximum combustion pressure in the cylinder increased by 8.6%, significantly increases the diffusion combustion speed, and significantly improves the dynamic performance of the rotary engine. On this… More >

Taihong Liu¹, Dingchen Wu^2,*, Fei Xu³, Panpan Song², Mingshan Wei², Jian Wu¹, Xiaochun Bai¹

Energy Engineering, Vol.118, No.3, pp. 535-548, 2021, DOI:10.32604/EE.2021.014326 - 22 March 2021

Abstract In view of the Three North areas existing wind power absorption and environment pollution problems, the previous scholars have improved the wind abandon problem by adding electrothermal coupling equipment or optimizing power grid operation. In this paper, an electrothermal integrated energy system including heat pump and thermal storage units was proposed. The scheduling model was based on the load data and the output characteristics of power units, each power unit capacity was programmed without constraints, and the proposed scheduling model was compared with the traditional combined heat and power scheduling model. Results showed that the More >

Mazhar Hussain Malik^1,*, Amjed Sid Ahmed¹, Sulaiman Al Hasani²

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 103-115, 2021, DOI:10.32604/cmc.2021.014562 - 22 March 2021

Abstract The COVID-19 pandemic has caused higher educational institutions around the world to close campus-based activities and move to online delivery. The aim of this paper is to present the case of Global College of Engineering and Technology (GCET) and how its practices including teaching, students/staff support, assessments, and exam policies were affected. The paper investigates the mediating role of no detriment policy impact on students’ result along with the challenges faced by the higher educational institution, recommendations and suggestions. The investigation concludes that the strategies adopted for online delivery, student support, assessments and exam policies… More >

Abdullah Alharbi¹, Wael Alosaimi¹, Hashem Alyami², Mohd Nadeem³, Mohd Faizan³, Alka Agrawal³, Rajeev Kumar^3,4,*, Raees Ahmad Khan³

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 179-194, 2021, DOI:10.32604/iasc.2021.016646 - 17 March 2021

Abstract Security risk evaluation of web-based healthcare applications is important from a design perspective. The developers as well as the users need to make sure that the applications must be secure. Citing the disastrous effects of unsecured web applications, Accuntix Online states that the IT industry has lost millions of dollars due to security theft and malware attacks. Protecting the integrity of patients’ health data is of utmost importance. Thus, assessing the security risk of web-based healthcare applications should be accorded the highest priority while developing the web applications. To fulfill the security requirements, the developers must… More >

Tzer-Long Chen¹, Chien-Yun Chang², Yung-Cheng Yao³, Kuo-Chang Chung^4,*

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 73-82, 2021, DOI:10.32604/iasc.2021.015980 - 17 March 2021

Abstract Artificial intelligence, machine learning, and deep learning have achieved great success in the fields of computer vision and natural language processing, and then extended to various fields, such as biology, chemistry, and civil engineering, including big data in the field of logistics. Therefore, many logistics companies move towards the integration of intelligent transportation systems. Only virtual and physical development can support the sustainable development of the logistics industry. This study aims to: 1.) collect timely information from the block chain, 2.) use deep learning to build a customer database so that sales staff in physical… More >

S. Kalyani^*, A. Mary Sowjanya, K. Venkat Rao

Journal on Internet of Things, Vol.3, No.1, pp. 27-38, 2021, DOI:DOI:10.32604/jiot.2021.013163 - 16 March 2021

Abstract Increased smart devices in various industries are creating numerous sensors in each of the equipment prompting the need for methods and models for sensor data. Current research proposes a systematic approach to analyze the data generated from sensors attached to industrial equipment. The methodology involves data cleaning, preprocessing, basics statistics, outlier, and anomaly detection. Present study presents the prediction of RUL by using various Machine Learning models like Regression, Polynomial Regression, Random Forest, Decision Tree, XG Boost. Hyper Parameter Optimization is performed to find the optimal parameters for each variable. In each of the model More >