Ahmed A. M. Jamel^1,∗, Bahriye Akay^2,†

Computer Systems Science and Engineering, Vol.34, No.5, pp. 259-281, 2019, DOI:10.32604/csse.2019.34.259

Abstract Parallel processing has turned into one of the emerging fields of machine learning due to providing consistent work by performing several tasks simultaneously, enhancing reliability (the presence of more than one device ensures the workflow even if some devices disrupted), saving processing time and introducing low cost and high-performance computation units. This research study presents a survey of parallel K-means and Fuzzy-c-means clustering algorithms based on their implementations in parallel environments such as Hadoop, MapReduce, Graphical Processing Units, and multi-core systems. Additionally, the enhancement in parallel clustering algorithms is investigated as hybrid approaches in which K-means and Fuzzy-c-means clustering algorithms… More >

Meng Wei^*, Ningxin Zhang, Yuan Tong, Yu Song

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 597-607, 2020, DOI:10.32604/iasc.2020.013938

Abstract The traditional radar signal detection mode of the analog digital converter (ADC) has a low prediction efficiency. Therefore, the advanced prediction model of the tunnel geological radar based on the cluster computing was designed. The completeness factor of the detection radar signal was calculated by the computer cluster effect, and then the information extraction and information integration of the radar pulse for the radar detection signal was determined. Moreover, the multi-order nonlinear regression forecasting model restructured the received signal. Thus, the prediction of the radar detection signal was achieved. In order to ensure the effectiveness of the design, the simulation… More >

Xiubin Lin^1,3, Joshua Swift², Yin Cheng^1,3, Qin An⁴, Hong Liang⁵, Yangsheng Wang³, Xiaoming Jia^4,*

International Journal of Mental Health Promotion, Vol.22, No.3, pp. 109-113, 2020, DOI:10.32604/IJMHP.2020.011128

Abstract The outbreak of the COVID-19 pandemic has provoked a significant amount of panic due to dramatic changes in daily routines for residents all over China. In response, more than 600 psychological hotlines have been built or modified and have supplied mental health services for the public. Regarding the service quality of the hotlines, a survey has been conducted to investigate the running of hotline services during the COVID-19 pandemic. The results reveal that the more successful hotlines all had better trained hotline counselors, and in the meanwhile, the key features of providing supervision arrangements and training resources. Moreover, the referral… More >

Samia Allaoua Chelloug^a, Mohamed A. El-Zawawy^b,c

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 309-318, 2018, DOI:10.1080/10798587.2017.1290328

Abstract The Internet of things (IoT) applications span many potential fields. Furthermore, smart homes, smart cities, smart vehicular networks, and healthcare are very attractive and intelligent applications. In most of these applications, the system consists of smart objects that are equipped by sensors and Radio Frequency Identification (RFID) and may rely on other technological computing and paradigm solutions such as M2 M (machine to machine) computing, Wifi, Wimax, LTE, cloud computing, etc. Thus, the IoT vision foresees that we can shift from traditional sensor networks to pervasive systems, which deliver intelligent automation by running services on objects. Actually, a significant attention has… More >

Hangjun Zhou¹, Tingting Shen^{1, *}, Xinglian Liu¹, Yurong Zhang¹, Peng Guo^{1, 2}, Jianjun Zhang³

Journal on Artificial Intelligence, Vol.2, No.2, pp. 89-101, 2020, DOI:10.32604/jai.2020.09968

Abstract With the advent of the era of big data, knowledge engineering has received extensive attention. How to extract useful knowledge from massive data is the key to big data analysis. Knowledge graph technology is an important part of artificial intelligence, which provides a method to extract structured knowledge from massive texts and images, and has broad application prospects. The knowledge base with semantic processing capability and open interconnection ability can be used to generate application value in intelligent information services such as intelligent search, intelligent question answering and personalized recommendation. Although knowledge graph has been applied to various systems, the… More >

Wei Fang^{1, 2, 3, ∗}, Lin Pang¹, Weinan Yi¹

Journal on Artificial Intelligence, Vol.2, No.1, pp. 39-58, 2020, DOI:10.32604/jai.2020.09789

Abstract In recent years, with the rapid development of human society, more and more complex tasks have emerged that require deep learning to automatically extract abstract feature representations from a large amount of data, and use reinforcement learning to learn the best strategy to complete the task. Through the combination of deep learning and reinforcement learning, end-to-end input and output can be achieved, and substantial breakthroughs have been made in many planning and decision-making systems with infinite states, such as games, in particular, AlphaGo, robotics, natural language processing, dialogue systems, machine translation, and computer vision. In this paper we have summarized… More >

Bing Wang^1,2,*, Yao Yao¹, Liting He¹, Xiangqian Pei¹

Energy Engineering, Vol.117, No.3, pp. 111-128, 2020, DOI:10.32604/EE.2020.010474

Abstract With the huge increase in natural gas consumption, the distortion of natural gas prices, especially in the residential sector, is prominently shaped into a heavy burden for public finance. Although city gate price and a price linkage mechanism have been established, the price tolerance of residential natural gas should be considered when the price of residential gas fluctuates with the upstream gas price. Determinants of the price affordability of residential natural gas consumption at different economic development levels (Beijing, Nanjing, Zhengzhou) are investigated by field survey and online investigation and analyzed by a factor analysis and discriminant analysis. The results… More >

Hitesh Agrawal^1,2, Oriana K. Wright³, Kathleen E. Carberry^1,4, S. Kristen Sexson Tejtel^1,2, Carlos M. Mery^1,5, Silvana Molossi^1,2

Congenital Heart Disease, Vol.12, No.6, pp. 721-725, 2017, DOI: 10.1111/chd.12473

Abstract Background: Long-term outcome data on patients with anomalous aortic origin of coronary arteries (AAOCA) is sparse and they are often managed in a nonuniform manner. There is subjective perception of anxiety and unmet needs in these patients and families.
Methods: An online survey of 13 questions was sent to 74 families of patients with AAOCA between May and October 2015. Descriptive statistics were performed.
Results: A total of 31 (47%) families responded. Of these, 27 expressed the need to interact with other patients/families with AAOCA. The majority were interested in either face-to-face meetings (77%) or online support groups (71%). Regarding… More >

Hitesh Agrawal^1,2, Carlos M. Mery^1,3, Patrick E. Day⁴, S. Kristen Sexson Tejtel^1,2, E. Dean McKenzie^1,3,5, Charles D. Fraser Jr^1,3, Athar M. Qureshi^1,2, Silvana Molossi^1,2

Congenital Heart Disease, Vol.12, No.5, pp. 610-614, 2017, DOI:10.1111/chd.12511

Abstract Background: Anomalous aortic origin of a coronary artery (AAOCA) is the second leading cause of sudden cardiac death in young athletes in the USA. Long-term outcome data for these patients are lacking to date. There is insufficient knowledge on the best approach to these patients and they are managed in a nonuniform manner.
Methods: An online survey of 15 questions regarding management of AAOCA was sent out to 198 cardiac healthcare providers. The goal was to define gaps in knowledge to justify a dedicated scientific forum for discussion of AAOCA. Descriptive statistics were performed.
Results: A total of 91 providers… More >

Karrie F. Downing^1,2, Matthew E. Oster^1,3, Sherry L. Farr¹

Congenital Heart Disease, Vol.12, No.4, pp. 497-506, 2017, DOI:10.1111/chd.12476

Abstract Objective: A substantial percentage of children with congenital heart disease (CHD) fail to transfer to adult care, resulting in increased risk of morbidity and mortality. Transition planning discussions with a provider may increase rates of transfer, yet little is known about frequency and content of these discussions. We assessed prevalence and predictors of transition-related discussions between providers and parents of children with special healthcare needs (CSHCN) and heart problems, including CHD.
Design: Using parent-reported data on 12- to 17-year-olds from the 2009–2010 National Survey of CSHCN, we calculated adjusted prevalence ratios (aPR) for associations between demographic factors and provider discussions… More >