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An intuitive general rank-based correlation coefficient Research Articles

Divya PANDOVE, Shivani GOEL, Rinkle RANI

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 6,   Pages 699-711 doi: 10.1631/FITEE.1601549

Abstract: We propose a predictive metric to calculate correlations between paired values, known as the generalIt fulfills the five basic criteria of a predictive metric: independence from sample size, value betweenFurthermore, the metric has been validated by performing experiments using a real-time dataset and randomThe comparison results show that the proposed metric fares better than the existing metric on all thepredictive metric criteria.

Keywords： General rank-based correlation coefficient     Multivariate analysis     Predictive metric     Spearman’s rank correlation    

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Face recognition based on subset selection via metric learning on manifold

Hong SHAO,Shuang CHEN,Jie-yi ZHAO,Wen-cheng CUI,Tian-shu YU

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 12,   Pages 1046-1058 doi: 10.1631/FITEE.1500085

Abstract: In this paper, we employ a metric learning approach which helps find the active elements correctly byAfter the metric has been learned, a neighborhood graph is constructed in the projected space.

Keywords： Face recognition     Sparse representation     Manifold structure     Metric learning     Subset selection    

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Real-time mobile robot teleoperation via Internet based on predictive control

WANG Shihua, XU Bugong, WANG Shihua, ZHOU Yeming, LIU YunHui

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 3,   Pages 299-306 doi: 10.1007/s11465-008-0049-7

Abstract: To compensate for the network delay and counteract its impact on the teleoperation system, a predictiveForce feedback and a virtual predictive display are introduced to enhance the real-time efficiency of

Keywords： predictive     feedback     virtual predictive     distance     synchronization algorithm    

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Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

Frontiers in Energy doi: 10.1007/s11708-023-0912-6

Abstract: multi-timescale optimal scheduling model is established for interconnected data centers (IDCs) based on model predictive

Keywords： model predictive control     interconnected data center     multi-timescale     optimized scheduling     distributed    

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The CatMath: an online predictive platform for thermal + electrocatalysis

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 12,   Pages 2156-2160 doi: 10.1007/s11705-023-2371-3

Abstract: The catalytic volcano activity models are the quantified and visualized tools of the Sabatier principle for heterogeneous catalysis, which can depict the intrinsic activity optima and trends of a catalytic reaction as a function of the reaction descriptors, i.e., the bonding strengths of key reaction species. These models can be derived by microkinetic modeling and/or free energy changes in combination with the scaling relations among the reaction intermediates. Herein, we introduce the CatMath—an online platform for generating a variety of common and industrially important thermal + electrocatalysis. With the CatMath, users can request the volcano models for available reactions and analyze their materials of interests as potential catalysts. Besides, the CatMath provides the function of the online generation of Surface Pourbaix Diagram for surface state analysis under electrocatalytic conditions, which is an essential step before analyzing the activity of an electrocatalytic surface. All the model generation and analysis processes are realized by cloud computing via a user-friendly interface.

Keywords： CatMath     catalysis     volcano activity plots     Surface Pourbaix Diagrams     online platform    

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Extended model predictive control scheme for smooth path following of autonomous vehicles

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 1,   Pages 4-4 doi: 10.1007/s11465-021-0660-4

Abstract: This paper presents an extended model predictive control (MPC) scheme for implementing optimal path following

Keywords： autonomous vehicles     vehicle dynamic modeling     model predictive control     path following     optimization    

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machine-learning-based system identification of dynamical systems under control: application towards the model predictive

Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 2,   Pages 237-250 doi: 10.1007/s11705-021-2058-6

Abstract: ., model predictive control, can offer superior control of key process variables for multiple-input multiple-outputblack-box nonlinear continuous-time multiple-input multiple-output system models for nonlinear model predictiveoutput and manipulated variables were trained on simulated data and integrated into a nonlinear model predictiveThis demonstration of how such system models could be identified for nonlinear model predictive control

Keywords： nonlinear model predictive control     black-box modeling     continuous-time system identification     machine    

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Monitoring checkpoint inhibitors: predictive biomarkers in immunotherapy

Min Zhang, Jingwen Yang, Wenjing Hua, Zhong Li, Zenghui Xu, Qijun Qian

Frontiers of Medicine 2019, Volume 13, Issue 1,   Pages 32-44 doi: 10.1007/s11684-018-0678-0

Abstract: Therefore, doctors urgently need reliable predictive biomarkers for checkpoint inhibitor therapies to

Keywords： immune checkpoint     companion diagnosis     PD-L1     tumor mutation burden     immune score    

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Abnormal glycosylated hemoglobin as a predictive factor for glucose metabolism disorders in antipsychotic

XU Leping, JI Juying, DUAN Yiyang, SHI Hui, ZHANG Bin, SHAO Yaqin, SUN Jian

Frontiers of Medicine 2007, Volume 1, Issue 3,   Pages 316-319 doi: 10.1007/s11684-007-0061-z

Abstract: The aim of this study was to observe the changes in glucose metabolism after antipsychotic (APS) therapy, to note the influencing factors, as well as to discuss the relationship between the occurrence of glucose metabolism disorders of APS origin and abnormal glycosylated hemoglobin (HbAc) levels. One hundred and fifty-two patients with schizophrenia, whose fasting plasma glucose (FPG) and 2-h plasma glucose (2hPG) in the oral glucose tolerance test (2HPG) were normal, were grouped according to the HbAc levels, one normal and the other abnormal, and were randomly enrolled into risperidone, clozapine and chlorpromazine treatment for six weeks. The FPG and 2hPG were measured at the baseline and at the end of the study. In the group with abnormal HbA1c and clozapine therapy, 2HPG was higher after the study [(9.5±1.8) mmol/L] than that before the study [(7.2±1.4) mmol/L] and the difference was statistically significant (〈0.01). FPG had no statistically significant difference before and after the study in any group (〉0.05). HbAc levels and drugs contributing to 2HPG at the end of study had statistical cross-action (〈0.01). In the abnormal HbAc group, 2HPG after the study was higher in the clozapine treatment group [(9.5±1.8) mmol/L] than in the risperidone treatment group [(7.4±1.7) mmol/L] and the chlorpromazine treatment group [(7.3±1.6) mmol/L]. The differences were statistically significant (〈0.01). In the normal HbAc group there was no statistically significant difference before and after the study in any group (〉0.05). 2HPG before [(7.1±1.6) mmol/L] and after the study [(8.1±1.9) mmol/L] was higher in the abnormal HbAc group than in the normal HbAc group [(6.2±1.4) mmol/L (6.5±1.4) mmol/L] with the difference being statistically significant (〈0.01 〈0.001). As compared with normal HbAc group, the relative risk (RR) of glucose metabolism disease occurrence was 4.7 in the abnormal HbAc group with the difference being statistically significant (〈0.001). Patients with abnormal HbAc are more likely to have a higher risk of having glucose metabolism disorders after APS treatment.

Keywords： significant difference     occurrence     hemoglobin     risperidone treatment     abnormal    

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A software defect prediction method with metric compensation based on feature selection and transfer Research Article

Jinfu CHEN, Xiaoli WANG, Saihua CAI, Jiaping XU, Jingyi CHEN, Haibo CHEN,caisaih@ujs.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 5,   Pages 715-731 doi: 10.1631/FITEE.2100468

Abstract: training efficiency and thus decrease the prediction accuracy of the model; (2) the distribution of metricbetter results on area under the receiver operating characteristic curve (AUC) value and F1-measure metric

Keywords： Defect prediction     Feature selection     Transfer learning     Metric compensation    

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A comprehensive review and analysis of solar forecasting techniques

Pardeep SINGLA, Manoj DUHAN, Sumit SAROHA

Frontiers in Energy 2022, Volume 16, Issue 2,   Pages 187-223 doi: 10.1007/s11708-021-0722-7

Abstract: In the last two decades, renewable energy has been paid immeasurable attention to toward the attainment of electricity requirements for domestic, industrial, and agriculture sectors. Solar forecasting plays a vital role in smooth operation, scheduling, and balancing of electricity production by standalone PV plants as well as grid interconnected solar PV plants. Numerous models and techniques have been developed in short, mid and long-term solar forecasting. This paper analyzes some of the potential solar forecasting models based on various methodologies discussed in literature, by mainly focusing on investigating the influence of meteorological variables, time horizon, climatic zone, pre-processing techniques, air pollution, and sample size on the complexity and accuracy of the model. To make the paper reader-friendly, it presents all-important parameters and findings of the models revealed from different studies in a tabular mode having the year of publication, time resolution, input parameters, forecasted parameters, error metrics, and performance. The literature studied showed that ANN-based models outperform the others due to their nonlinear complex problem-solving capabilities. Their accuracy can be further improved by hybridization of the two models or by performing pre-processing on the input data. Besides, it also discusses the diverse key constituents that affect the accuracy of a model. It has been observed that the proper selection of training and testing period along with the correlated dependent variables also enhances the accuracy of the model.

Keywords： forecasting techniques     hybrid models     neural network     solar forecasting     error metric     support vector machine    

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The predictive value of chromosome 8p deletion for metastasis of hepatocellular carcinoma: a summary

QIN Lunxiu, TANG Zhaoyou, GUAN Xinyuan, YE Qinghai, JIA Huliang, REN Ning

Frontiers of Medicine 2008, Volume 2, Issue 3,   Pages 211-215 doi: 10.1007/s11684-008-0041-y

Abstract: Hepatocellular carcinoma (HCC) represents an extremely poor prognostic cancer, which is mainly due to the high frequency of metastasis/recurrence after surgical operation. Exploring the molecular mechanisms involved in HCC metastasis could be helpful in the prediction and early diagnosis of HCC recurrence and could also provide new therapeutic targets for HCC metastasis. In the recent decade, we analyzed the genomic aberrations of the clinical specimens, as well as the metastatic models and cell lines of human HCC to identify the genetic markers related to HCC metastasis and to verify their clinical values in the prediction and control of metastasis of HCC. Using the comparative genomic hybridization (CGH) technique, we compared the differences of chromosomal aberrations between primary HCC tumors and their matched metastatic lesions, and found that chromosome 8p deletions might contribute to HCC metastasis. This novel finding was further confirmed by comparison between nude mice models of HCC with different metastatic potentials. By the more sensitive genome-wide microsatellite analysis, 8p deletion was defined to 8p23.3 and 8p11.2, which are two likely regions harboring metastasis-related genes of HCC. Using ‘8p-specific’ microarrays, two novel metastatic suppressors ( and ) were identified, and were proven to suppress invasion and metastasis of HCC. Clinical studies indicate that 8p deletion detected in HCC or circulating plasma DNA of patients is a useful predictor for metastatic recurrence and prognosis, even for patients with early stage HCC. These novel findings are regarded as important advances in the study of the molecular mechanisms of HCC metastasis, which provide not only a holistic view on the molecular cytogenetic bases of HCC metastasis, but also candidate regions for further study to identify metastatic suppressor genes.

Keywords： sensitive genome-wide     prediction     genome-wide microsatellite     frequency     Hepatocellular carcinoma    

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Predictive Analysis and Observational Construction for aLarge-Scale Underground Powerhouse Cavern Complex

Wang Yisen,Liu Sihong

Strategic Study of CAE 2007, Volume 9, Issue 3,   Pages 35-40

Abstract:

In this paper, the predictive analysis and observational constructionThe predictive analysis was carried out in three dimensions by FEM that simulated the actual staged excavation

Keywords： underground cavern complex     predictive analysis     observational construction     rock supportdesign    

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High Precision Adaptive Predictive Control for Cruise Missile

Sun Mingwei,Chen Zengqiang,Yuan Zhuzhi,Ren Qiang,Yang Ming

Strategic Study of CAE 2005, Volume 7, Issue 10,   Pages 23-27

Abstract: their discrete models are served as controlled plant for recursive least square (RLS) based adaptive predictiveOn the basis of missile’s characteristics, generalized predictive control (GPC) is used in innerattitude loop, and an integral form of predictive control is adopted in outter trajectory loop.

Keywords： cruise missile     adaptive control     model based predictive control     robustness    

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Frequency-domain-based Robustness Analysis for PID Generalized Predictive Control

Wang Fanzhen,Chen Zengqiang,Yao Xiangfeng,Yuan Zhuzhi

Strategic Study of CAE 2006, Volume 8, Issue 10,   Pages 66-70

Abstract:

The closed-loop feedback structure of PID generalized predictive control (PID - GPC) is proposed,

Keywords： predictive control     robustness     frequency domain     small-gain criterion     PID control    

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Title Author Date Type Operation

An intuitive general rank-based correlation coefficient

Divya PANDOVE, Shivani GOEL, Rinkle RANI

Journal Article

Face recognition based on subset selection via metric learning on manifold

Hong SHAO,Shuang CHEN,Jie-yi ZHAO,Wen-cheng CUI,Tian-shu YU

Journal Article

Real-time mobile robot teleoperation via Internet based on predictive control

WANG Shihua, XU Bugong, WANG Shihua, ZHOU Yeming, LIU YunHui

Journal Article

Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

Journal Article

The CatMath: an online predictive platform for thermal + electrocatalysis

Journal Article

Extended model predictive control scheme for smooth path following of autonomous vehicles

Journal Article

machine-learning-based system identification of dynamical systems under control: application towards the model predictive

Journal Article

Monitoring checkpoint inhibitors: predictive biomarkers in immunotherapy

Min Zhang, Jingwen Yang, Wenjing Hua, Zhong Li, Zenghui Xu, Qijun Qian

Journal Article

Abnormal glycosylated hemoglobin as a predictive factor for glucose metabolism disorders in antipsychotic

XU Leping, JI Juying, DUAN Yiyang, SHI Hui, ZHANG Bin, SHAO Yaqin, SUN Jian

Journal Article

A software defect prediction method with metric compensation based on feature selection and transfer

Jinfu CHEN, Xiaoli WANG, Saihua CAI, Jiaping XU, Jingyi CHEN, Haibo CHEN,caisaih@ujs.edu.cn

Journal Article

A comprehensive review and analysis of solar forecasting techniques

Pardeep SINGLA, Manoj DUHAN, Sumit SAROHA

Journal Article

The predictive value of chromosome 8p deletion for metastasis of hepatocellular carcinoma: a summary

QIN Lunxiu, TANG Zhaoyou, GUAN Xinyuan, YE Qinghai, JIA Huliang, REN Ning

Journal Article

Predictive Analysis and Observational Construction for aLarge-Scale Underground Powerhouse Cavern Complex

Wang Yisen,Liu Sihong

Journal Article

High Precision Adaptive Predictive Control for Cruise Missile

Sun Mingwei,Chen Zengqiang,Yuan Zhuzhi,Ren Qiang,Yang Ming

Journal Article

Frequency-domain-based Robustness Analysis for PID Generalized Predictive Control

Wang Fanzhen,Chen Zengqiang,Yao Xiangfeng,Yuan Zhuzhi

Journal Article