Multivariate
statistical process monitoring (MSPM) can conduct
dimensionality reduction on process variables and can obtain low-dimensional
representations that capture most of the information in the original
data space. However, most MSPM models are developed under unsupervised
situations. Therefore, any abandoned information may deteriorate the
process monitoring performance. To address both issues (i.e., dimension
reduction and information preservation), this paper proposes a distributed
statistical process monitoring scheme. The proposed method employs
principal component analysis to derive four distinct and explicable
subspaces from the original process variables according to their relevance
or irrelevance to principal component subspace and residual subspace.
Each subspace serves as a low-dimensional representation of the original
data space, thereby preserving the information of the original data
space without undergoing information loss. A squared Mahalanobis distance,
which is introduced as the monitoring statistic, was calculated directly
in each subspace for fault detection. The Bayesian inference was then
introduced as the decision fusion strategy to obtain a final and unique
probability index. The feasibility and superiority of the proposed
method was investigated by conducting a case study of the well-known
Tennessee Eastman process.
BackgroundPre-diabetes is a growing health concern where a large percentage of these patients develop full type 2 diabetes. Effective interventions on pre-diabetes can prevent or delay the occurrence or development of diabetes. Pharmaco-dynamics and pre-clinical of JinQi-Jiangtang tablets (JQJT) suggest that it could be benefit for pre-diabetes.Methods/DesignRandomized controlled trial (RCT) is implemented in this study. The study term is 24 months (12 months for intervention and 12 months for follow up). Participants are recruited from four cities of China: Beijing, Tianjin, Xi'an and Nanning. Four hundred participants are randomized to treatment group (JQJT tablets) and control group (Placebo); two hundred participants each. People being included in this study must have been diagnosed as pre-diabetes via western medicine criteria and traditional Chinese medicine (TCM) criteria. The end-point indexes include: incidence of diabetes mellitus and reversion rate. Primary outcome indexes include: oral glucose tolerance test; insulin releasing test; glycosylated hemoglobin (HA1c). Secondary outcome indexes include: score of the Short Form 36 Health Survey Questionnaire (SF-36); score of TCM symptoms; blood lipid test. Indexes of safety include: general medical examination; blood and urine regular test; electrocardiogram (ECG), liver function (ALT) and renal function (BUN, Creatinine) test; record of adverse event, such as headache, faint, etc. Qualitative control will be implemented and a number of standard operating processes (SOPs) will be formed throughout the study: laboratory quality control measures; compliance control for researchers and participants; researcher training before study; supervision; investigational drug management and others.DiscussionThe aim of this study is to evaluate the effectiveness and safety of JinQi JiangTang (JQJT) tablets for the treatment of patients with pre-diabetes.Trial registrationChinese clinical trials register ChiCTR-TRC-00000401
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