Farhan Ullah^1,4,*, Abdullah Bajahzar², Hamza Aldabbas³, Muhammad Farhan⁴, Hamad Naeem¹, S. Sabahat H. Bukhari^4,5, Kaleem Razzaq Malik⁶

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 169-180, 2020, DOI:10.31209/2019.100000138

Abstract This research aims to an electronic assessment (e-assessment) of students’ replies in response to the standard answer of teacher’s question to automate the assessment by WordNet semantic similarity. For this purpose, a new methodology for Semantic Similarity through WordNet Semantic Similarity Techniques (SS-WSST) has been proposed to calculate semantic similarity among teacher’ query and student’s reply. In the pilot study-1 42 words’ pairs extracted from 8 students’ replies, which marked by semantic similarity measures and compared with manually assigned teacher’s marks. The teacher is provided with 4 bins of the mark while our designed methodology More >

Peipeng Yu¹, Zhihua Xia^{1, *}, Jianwei Fei¹, Sunil Kumar Jha^{1, 2}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 743-760, 2020, DOI:10.32604/cmc.2020.011391 - 23 July 2020

Abstract Coronaviruses are a well-known family of viruses that can infect humans or animals. Recently, the new coronavirus (COVID-19) has spread worldwide. All countries in the world are working hard to control the coronavirus disease. However, many countries are faced with a lack of medical equipment and an insufficient number of medical personnel because of the limitations of the medical system, which leads to the mass spread of diseases. As a powerful tool, artificial intelligence (AI) has been successfully applied to solve various complex problems ranging from big data analysis to computer vision. In the process More >

Amin Bemani¹, Alireza Baghban², Shahaboddin Shamshirband^{3, 4, *}, Amir Mosavi^{5, 6, 7}, Peter Csiba⁷, Annamaria R. Varkonyi-Koczy^{5, 7}

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1175-1204, 2020, DOI:10.32604/cmc.2020.07723 - 30 April 2020

Abstract In the present work, a novel machine learning computational investigation is carried out to accurately predict the solubility of different acids in supercritical carbon dioxide. Four different machine learning algorithms of radial basis function, multi-layer perceptron (MLP), artificial neural networks (ANN), least squares support vector machine (LSSVM) and adaptive neuro-fuzzy inference system (ANFIS) are used to model the solubility of different acids in carbon dioxide based on the temperature, pressure, hydrogen number, carbon number, molecular weight, and the dissociation constant of acid. To evaluate the proposed models, different graphical and statistical analyses, along with novel More >

Xiangao Jiang¹, Megan Coffee^{2, 3, *}, Anasse Bari^{4, *}, Junzhang Wang⁴, Xinyue Jiang⁵, Jianping Huang¹, Jichan Shi¹, Jianyi Dai¹, Jing Cai¹, Tianxiao Zhang⁶, Zhengxing Wu¹, Guiqing He¹, Yitong Huang⁷

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 537-551, 2020, DOI:10.32604/cmc.2020.010691 - 30 March 2020

Abstract The virus SARS-CoV2, which causes coronavirus disease (COVID-19) has become a pandemic and has spread to every inhabited continent. Given the increasing caseload, there is an urgent need to augment clinical skills in order to identify from among the many mild cases the few that will progress to critical illness. We present a first step towards building an artificial intelligence (AI) framework, with predictive analytics (PA) capabilities applied to real patient data, to provide rapid clinical decision-making support. COVID-19 has presented a pressing need as a) clinicians are still developing clinical acumen to this novel… More >

Hongbo Wang^{1, *}, Qian Xue¹, Tong Cui¹, Yangyang Li², Huacheng Zeng³

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 337-351, 2020, DOI:10.32604/cmc.2020.07290 - 30 March 2020

Abstract As a major function of smart transportation in smart cities, vehicle model recognition plays an important role in intelligent transportation. Due to the difference among different vehicle models recognition datasets, the accuracy of network model training in one scene will be greatly reduced in another one. However, if you don’t have a lot of vehicle model datasets for the current scene, you cannot properly train a model. To address this problem, we study the problem of cold start of vehicle model recognition under cross-scenario. Under the condition of small amount of datasets, combined with the More >

Zheng Xu¹, Qingyuan Zhou², Zhiguo Yan³

Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 1-3, 2019, DOI:10.31209/2019.100000082

Abstract This article has no abstract. More >

Zheng Xu¹, Qingyuan Zhou², Zhiguo Yan³

Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 693-694, 2019, DOI:10.31209/2019.100000072

Abstract This article has no abstract. More >

Jcy Chen^1,*, Wc Chen¹, Tim Chen¹, Alex Wilson², N. Fadilah Jamaludin³, Nertrand Kapron¹, Tim Chen^4,5, John Burno⁵

Sound & Vibration, Vol.53, No.6, pp. 245-250, 2019, DOI:10.32604/sv.2019.04233

Abstract This paper proposes a novel artificial intelligence sythethized controller in the mechanical system which has high speed computation because of the LMI type criterion. The proposed membership functions are adopted and stabilization criterion of the closed-loop T-S fuzzy systems are obtained through a new parametrized LMI (linear matrix) inequality which is rearranged by machine learning membership functions. More >

Youqin Huang¹, Jiayong Li¹, Jiyang Fu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.3, pp. 845-875, 2019, DOI:10.32604/cmes.2019.07653

Abstract In last few years, big data and deep learning technologies have been successfully applied in various fields of civil engineering with the great progress of machine learning techniques. However, until now, there has been no comprehensive review on its applications in civil engineering. To fill this gap, this paper reviews the application and development of artificial intelligence in civil engineering in recent years, including intelligent algorithms, big data and deep learning. Through the work of this paper, the research direction and difficulties of artificial intelligence in civil engineering for the past few years can be More >

Ryuji Shioya and Hongjie Zheng

The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.4, pp. 195-195, 2019, DOI:10.32604/icces.2019.05008

Abstract Oil-filled power transformers play an important role in the modern network system. Stability of power supply can be achieved by early detection of power transformer fault and continuous monitoring of equipment status. Transformers in operation are constantly affected by various types of stresses such as electrical, thermal and mechanical stress. Much attention is needed on maintenance of transformers in order to have fault free electric supply and to maximize the lifetime of a transformer. In recent years, Dissolved gas analysis (DGA) has been widely used for diagnostic fault of power transformers. Although DGA is an… More >