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Full-Text Articles in Engineering
Industrial Wireless Sensor Networks 2016, Qindong Sun, Schancang Li, Shanshan Zhao, Hongjian Sun, Li Xu, Arumugam Nallamathan
Industrial Wireless Sensor Networks 2016, Qindong Sun, Schancang Li, Shanshan Zhao, Hongjian Sun, Li Xu, Arumugam Nallamathan
Information Technology & Decision Sciences Faculty Publications
The industrial wireless sensor network (IWSN) is the next frontier in the Industrial Internet of Things (IIoT), which is able to help industrial organizations to gain competitive advantages in industrial manufacturing markets by increasing productivity, reducing the costs, developing new products and services, and deploying new business models.
Semantic Inference On Clinical Documents: Combining Machine Learning Algorithms With An Inference Engine For Effective Clinical Diagnosis And Treatment, Shuo Yang, Ran Wei, Jingzhi Guo, Lida Xu
Semantic Inference On Clinical Documents: Combining Machine Learning Algorithms With An Inference Engine For Effective Clinical Diagnosis And Treatment, Shuo Yang, Ran Wei, Jingzhi Guo, Lida Xu
Information Technology & Decision Sciences Faculty Publications
Clinical practice calls for reliable diagnosis and optimized treatment. However, human errors in health care remain a severe issue even in industrialized countries. The application of clinical decision support systems (CDSS) casts light on this problem. However, given the great improvement in CDSS over the past several years, challenges to their wide-scale application are still present, including: 1) decision making of CDSS is complicated by the complexity of the data regarding human physiology and pathology, which could render the whole process more time-consuming by loading big data related to patients; and 2) information incompatibility among different health information systems (HIS) …
Qos Recommendation In Cloud Services, Xianrong Zheng, Li Da Xu, Sheng Chai
Qos Recommendation In Cloud Services, Xianrong Zheng, Li Da Xu, Sheng Chai
Information Technology & Decision Sciences Faculty Publications
As cloud computing becomes increasingly popular, cloud providers compete to offer the same or similar services over the Internet. Quality of service (QoS), which describes how well a service is performed, is an important differentiator among functionally equivalent services. It can help a firm to satisfy and win its customers. As a result, how to assist cloud providers to promote their services and cloud consumers to identify services that meet their QoS requirements becomes an important problem. In this paper, we argue for QoS-based cloud service recommendation, and propose a collaborative filtering approach using the Spearman coefficient to recommend cloud …