Prachi Agrawal¹, Khalid Alnowibet², Ali Wagdy Mohamed^3,4,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2847-2868, 2022, DOI:10.32604/cmc.2022.023126

Abstract This paper presents a novel application of metaheuristic algorithms for solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithm is based on human behavior in which people gain and share their knowledge with others. Different types of stochastic fractional programming problems are considered in this study. The augmented Lagrangian method (ALM) is used to handle these constrained optimization problems by converting them into unconstrained optimization problems. Three examples from the literature are considered and transformed into their deterministic form using the chance-constrained technique. The transformed problems are solved using GSK algorithm and… More >

Nora Shoaip¹, Amira Rezk¹, Shaker EL-Sappagh^2,3, Tamer Abuhmed^4,*, Sherif Barakat¹, Mohammed Elmogy⁵

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3531-3548, 2021, DOI:10.32604/cmc.2021.019069

Abstract Alzheimer’s disease (AD) is a very complex disease that causes brain failure, then eventually, dementia ensues. It is a global health problem. 99% of clinical trials have failed to limit the progression of this disease. The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms. Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction. In this regard, the need becomes more urgent for biomarker-based detection. A key issue in understanding AD is the need to solve complex and high-dimensional… More >

Chaoyu Deng, Guangfu Zeng, Zhiping Cai, Xiaoqiang Xiao^*

Journal on Artificial Intelligence, Vol.2, No.4, pp. 157-166, 2020, DOI:10.32604/jai.2020.011541

Abstract The purpose of automated question answering is to let the machine understand natural language questions and give accurate answers in the form of natural language. This technology requires the machine to store a large amount of background knowledge. In recent years, the rapid development of knowledge graph has made the knowledge based question answering (KBQA) more and more popular. Traditional styles of KBQA methods mainly include semantic parsing, information extraction and vector modeling. With the development of deep learning, KBQA with deep learning has gradually become the mainstream method. This paper introduces the application of deep learning in KBQA mainly… More >

Chuanrong Wu^1,*, Huayi Yin¹, Xiaoming Yang², Zhi Lu³, Mark E. McMurtrey⁴

Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 1173-1184, 2020, DOI:10.32604/iasc.2020.014961

Abstract Nowadays big data knowledge is being bought and sold online for market research, new product development, or other business decisions, especially when customer demands and consumer preferences knowledge for new product development are needed. Previous studies have introduced two commonly used pricing schemes for big data knowledge transactions (e.g., cloud services): Subscription pricing and pay-per-use pricing from a big data knowledge provider’s standpoint. However, few studies to date have investigated a two-part tariff pricing scheme for big data knowledge transactions, albeit this pricing scheme may increasingly attract the big data knowledge providers in this hyper-competitive market. Also, little research has… More >

Elise D. Pieterman^1,2, Ricardo P. J. Budde², Danielle Robbers-Visser^1,2, Ron T. van Domburg³, Willem A. Helbing^1,2

Congenital Heart Disease, Vol.12, No.5, pp. 561-569, 2017, DOI:10.1111/chd.12484

Abstract Objective: Follow-up of right ventricular performance is important for patients with congenital heart disease. Cardiac magnetic resonance imaging is optimal for this purpose. However, observerdependency of manual analysis of right ventricular volumes limit its use. Knowledge-based reconstruction is a new semiautomatic analysis tool that uses a database including knowledge of right ventricular shape in various congenital heart diseases. We evaluated whether knowledge-based reconstruction is a good alternative for conventional analysis.
Design: To assess the inter- and intra-observer variability and agreement of knowledge-based versus conventional analysis of magnetic resonance right ventricular volumes, analysis was done by two observers in a mixed… More >