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Temperature Prediction for Sun Synchronous Satellite on Orbit

Wei Chuanfeng,Li Yunze,Yuan Lingshuang,Wang Jun,Ning Xianwen

Strategic Study of CAE 2005, Volume 7, Issue 2,   Pages 73-75

Abstract:

Temperature prediction on-line for sun synchronous satellite is very essential.In this paper, satellite's temperature is predicted on-line after the analysis to the cycles of orbitalexternal thermal current and average temperature.Temperature distribution predicted by last two circles can be the basis on thermal fault diagnosis for

Keywords： sun synchronous satellite     on orbit     temperature predict    

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Potential indicators predict progress after surgical resection of gastrointestinal stromal tumors

Qinggang Hu, Shanglong Liu, Jianwei Jiang, Chen Zhang, Xiaowei Liu, Qichang Zheng

Frontiers of Medicine 2012, Volume 6, Issue 3,   Pages 317-321 doi: 10.1007/s11684-012-0203-9

Abstract:

In order to find out the potential indicators predicting prognosis of malignant gastrointestinal stromal tumors (GISTs) after surgical resection, we collected clinical records of 80 patients with malignant GISTs. Tumor location, size, mitotic index, necrosis were compared with the prognosis of malignant GISTs by Kaplan-Meier method and log-rank test. After a median follow-up of 844 days (52–2 145), we found that as National Institutes of Health suggested, tumors with intermediate risk had more favorable prognosis than that with high risk. Their 3-year survival rate were 65.3% and 41.3%, respectively (P<0.001). Moreover, tumor size and mitotic index were associated with free survival. The 3-year survival rate for patients with tumor size≤10 cm and>10 cm were 62.3% and 41.8%, respectively (P = 0.002), Tumors with mitotic index≤5/50 HPF had a higher 3-year survival rate than tumors with mitotic index>5/50 HPF (67.1% versus 40.7%, P = 0.005). The presence of necrosis was directly related to the malignant behavior. The 3-year survival rate for presence and absence necrosis were 50.8% and 64.8% (P = 0.008). From the present study, we can conclude that besides tumors size and mitotic index, tumor location and necrosis also influence on the long-term survival of patient with malignant GISTs after surgical resection.

Keywords： gastrointestinal stromal tumors     surgery     survival    

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An improved design method to predict the E-modulus and strength of FRP composites at different temperatures

Mohammed FARUQI, Gobishanker RAJASKANTHAN, Breanna BAILEY, Francisco AGUINIGA

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 12,   Pages 1654-1654 doi: 10.1007/s11709-020-0622-7

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An improved design method to predict the E-modulus and strength of FRP composites at different temperatures

Mohammed FARUQI, Gobishanker RAJASKANTHAN, Breanna BAILEY, Francisco AGUINIGA

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 12,   Pages 1653-1653 doi: 10.1007/s11709-019-0578-7

Abstract: In recent years, there has been an increased interest in the use of fiber reinforced polymer (FRP) in the construction industry. However, the E-modulus and strength of such members at high service temperatures is still unknown. Modulus and strength of FRP at high service temperatures are highly required parameters for full design. The knowledge and application of this could lead to a cost effective and practical consideration in fire safety design. Thus, this paper proposes design methods for calculating the E-modulus and strength of FRP members at different temperatures. Experimental data from literature were normalized and compared with the results predicted by this method. It was found that the proposed design methods conservatively estimate the E-modulus and strength of FRP structural members. In addition, comparison was also made with direct references to the real behavior of materials. It was found to be satisfactory. Finally, an application is provided.

Keywords： concrete     fiber reinforced polymer     E-modulus     strength     temperatures    

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A hierarchical system to predict behavior of soil and cantilever sheet wall by data-driven models

Nang Duc BUI; Hieu Chi PHAN; Tiep Duc PHAM; Ashutosh Sutra DHAR

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 6,   Pages 667-684 doi: 10.1007/s11709-022-0822-4

Abstract: Consequently, a system containing three trained ML models is proposed to first predict the stability

Keywords： finite element analysis     cantilever sheet wall     machine learning     artificial neural network     random forest    

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Particle swarm optimization model to predict scour depth around a bridge pier

Shahaboddin SHAMSHIRBAND, Amir MOSAVI, Timon RABCZUK

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 4,   Pages 855-866 doi: 10.1007/s11709-020-0619-2

Abstract: paper aims to develop new equations using particle swarm optimization as a metaheuristic approach to predict

Keywords： scour depth     bridge design and construction     particle swarm optimization     computational mechanics     artificial intelligence     bridge pier    

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Elevated C-reactive protein levels predict worsening prognosis in Chinese patients with first-onset stroke

Jiangtao YAN, Rutai HUI, Daowen WANG

Frontiers of Medicine 2009, Volume 3, Issue 1,   Pages 30-35 doi: 10.1007/s11684-009-0005-x

Abstract: The role of high sensitivity C-reactive protein (hsCRP) in predicting prognosis after stroke in the Asian population has not been investigated. We hypothesized that elevated levels of hsCRP were associated with worsening prognosis after stroke in Chinese patients. Two hundred and ninety consecutive patients with first-onset stroke and 290 age- and gender-matched control subjects without any cerebrovascular disease were enrolled for study. Plasma hsCRP level was detected and subsequent vascular events and death were recorded in both groups over a 5-year period. Compared to control group, patients presenting with stroke had higher plasma hsCRP level (3.3 ± 3.8 1.3 ± 2.2 mg/L, < 0.01). Furthermore, in the group of patients with stroke, the mean plasma hsCRP level was higher in patients who developed subsequent vascular diseases or died as compared with the patients without further complications (4.4 ± 4.3 2.7 ± 3.3 mg/L, < 0.01). Compared to the lowest tertile of hsCRP level, the relative risk for vascular events or death in stroke patients was 2.91 in the highest tertile of hsCRP (95% CI, 1.54–5.50, = 0.001). This increase in relative risk for vascular events or death in stroke patients continued after adjustment for age, sex and other cardiovascular risk factors such as hypertension and diabetes ( : 2.771, 95% CI: 1.367–5.617, = 0.005). These findings indicate that increased hsCRP level is associated with worsening prognosis after stroke in Chinese patients and suggests that inflammation is correlated with stroke outcome.

Keywords： C-reactive protein     inflammation     stroke    

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A method to predict cooling load of large commercial buildings based on weather forecast and internal

Junbao JIA,Jincheng XING,Jihong LING,Ren PENG

Frontiers in Energy 2016, Volume 10, Issue 4,   Pages 459-465 doi: 10.1007/s11708-016-0424-8

Abstract: The multiple linear feedback regression model was applied to predict, with precision, the air conditioning

Keywords： commercial building     load prediction     multiple linear regression    

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Development of deep neural network model to predict the compressive strength of FRCM confined columns

Khuong LE-NGUYEN; Quyen Cao MINH; Afaq AHMAD; Lanh Si HO

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 10,   Pages 1213-1232 doi: 10.1007/s11709-022-0880-7

Abstract: The ANN model with double hidden layers (APDL-1) was shown to be the best to predict the compressive

Keywords： FRCM     deep neural networks     confinement effect     strength model     confined concrete    

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Presentation of regression analysis, GP and GMDH models to predict the pedestrian density in various

Iraj BARGEGOL; Seyed Mohsen HOSSEINIAN; Vahid NAJAFI MOGHADDAM GILANI; Mohammad NIKOOKAR; Alireza OROUEI

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 2,   Pages 250-265 doi: 10.1007/s11709-021-0785-x

Abstract: In this study, the relationship between space mean speed (SMS), flow rate and density of pedestrians was investigated in different pedestrian facilities, including 1 walkway, 2 sidewalks, 2 signalized crosswalks and 2 mid-block crosswalks. First, statistical analysis was performed to investigate the normality of data and correlation of variables. Regression analysis was then applied to determine the relationship between SMS, flow rate, and density of pedestrians. Finally, two prediction models of density were obtained using genetic programming (GP) and group method of data handling (GMDH) models, and k-fold and holdout cross-validation methods were used to evaluate the models. By the use of regression analysis, the mathematical relationships between variables in all facilities were calculated and plotted, and the best relationships were observed in flow rate-density diagrams. Results also indicated that GP had a higher R2 than GMDH in the prediction of pedestrian density in terms of flow rate and SMS, suggesting that GP was better able to model SMS and pedestrian density. Moreover, the application of k-fold cross-validation method in the models led to better performances compared to the holdout cross-validation method, which shows that the prediction models using k-fold were more reliable. Finally, density relationships in all facilities were obtained in terms of SMS and flow rate.

Keywords： pedestrian density     regression analysis     GP model     GMDH model    

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on coupled physical and mechanical, chemical and biological soil processes: how can we maintain and predict

Rainer HORN, Winfried E. H. BLUM

Frontiers of Agricultural Science and Engineering 2020, Volume 7, Issue 3,   Pages 243-245 doi: 10.15302/J-FASE-2020334

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Using hybrid models to predict blood pressure reactivity to unsupported back based on anthropometric

Gurmanik KAUR,Ajat Shatru ARORA,Vijender Kumar JAIN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 6,   Pages 474-485 doi: 10.1631/FITEE.1400295

Abstract: Accurate blood pressure (BP) measurement is essential in epidemiological studies, screening programmes, and research studies as well as in clinical practice for the early detection and prevention of high BP-related risks such as coronary heart disease, stroke, and kidney failure. Posture of the participant plays a vital role in accurate measurement of BP. Guidelines on measurement of BP contain recommendations on the position of the back of the participants by advising that they should sit with supported back to avoid spuriously high readings. In this work, principal component analysis (PCA) is fused with forward stepwise regression (SWR), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and the least squares support vector machine (LS-SVM) model for the prediction of BP reactivity to an unsupported back in normotensive and hypertensive participants. PCA is used to remove multi-collinearity among anthropometric predictor variables and to select a subset of components, termed ‘principal components’ (PCs), from the original dataset. The selected PCs are fed into the proposed models for modeling and testing. The evaluation of the performance of the constructed models, using appropriate statistical indices, shows clearly that a PCA-based LS-SVM (PCA-LS-SVM) model is a promising approach for the prediction of BP reactivity in comparison to others. This assessment demonstrates the importance and advantages posed by hybrid models for the prediction of variables in biomedical research studies.

Keywords： Blood pressure (BP)     Principal component analysis (PCA)     Forward stepwise regression     Artificial neural network (ANN)     Adaptive neuro-fuzzy inference system (ANFIS)     Least squares support vector machine (LS-SVM)    

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Symptom network topological features predict the effectiveness of herbal treatment for pediatric cough

Mengxue Huang, Jingjing Wang, Runshun Zhang, Zhuying Ni, Xiaoying Liu, Wenwen Liu, Weilian Kong, Yao Chen, Tiantian Huang, Guihua Li, Dan Wei, Jianzhong Liu, Xuezhong Zhou

Frontiers of Medicine 2020, Volume 14, Issue 3,   Pages 357-367 doi: 10.1007/s11684-019-0699-3

Abstract: Pediatric cough is a heterogeneous condition in terms of symptoms and the underlying disease mechanisms. Symptom phenotypes hold complicated interactions between each other to form an intricate network structure. This study aims to investigate whether the network structure of pediatric cough symptoms is associated with the prognosis and outcome of patients. A total of 384 cases were derived from the electronic medical records of a highly experienced traditional Chinese medicine (TCM) physician. The data were divided into two groups according to the therapeutic effect, namely, an invalid group (group A with 40 cases of poor efficacy) and a valid group (group B with 344 cases of good efficacy). Several well-established analysis methods, namely, statistical test, correlation analysis, and complex network analysis, were used to analyze the data. This study reports that symptom networks of patients with pediatric cough are related to the effectiveness of treatment: a dense network of symptoms is associated with great difficulty in treatment. Interventions with the most different symptoms in the symptom network may have improved therapeutic effects.

Keywords： pediatric cough     complex network     symptoms     traditional Chinese medicine     electronic medical records    

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Positive stool culture could predict the clinical outcomes of haploidentical hematopoietic stem cell

Lijuan Hu, Qi Wang, Xiaohui Zhang, Lanping Xu, Yu Wang, Chenhua Yan, Huan Chen, Yuhong Chen, Kaiyan Liu, Hui Wang, Xiaojun Huang, Xiaodong Mo

Frontiers of Medicine 2019, Volume 13, Issue 4,   Pages 492-503 doi: 10.1007/s11684-019-0681-0

Abstract: We aimed to identify the effect of positive stool cultures (PSCs) on the clinical outcomes of patients undergoing haploidentical hematopoietic stem cell transplantation (haplo-HSCT) ( = 332). PSCs were observed in 61 patients (PSC group, 18.4%). Enterobacteriaceae in stool specimens was associated with a higher risk of bloodstream infection, and in stool specimens was related to a higher risk of platelet engraftment failure. The cumulative incidence of infection-related mortality 1 year after haplo-HSCT in the PSC group was higher than that of the patients who showed persistently negative stool cultures (NSC group; 19.2% vs. 8.9%, = 0.017). The probabilities of overall survival (71.4% vs. 83.8%, = 0.031) and disease-free survival (69.6% vs. 81.0%, = 0.048) 1 year after haplo-HSCT for the PSC group were significantly lower than those for the NSC group, particularly for patients who had in their stool specimens. In multivariate analysis, in stool specimens significantly increased the risk of mortality and was associated with poorer survival. Our results showed that PSC influenced the clinical outcomes after haplo-HSCT, particularly those who had in their stool specimens.

Keywords： haploidentical     hematopoietic stem cell transplantation     stool culture     Candida    

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Emerging challenges to structural integrity technology for high-temperature applications

TU Shantung

Frontiers of Mechanical Engineering 2007, Volume 2, Issue 4,   Pages 375-387 doi: 10.1007/s11465-007-0066-y

Abstract: The modern needs of structural integrity technology are largely attributed to the increase of service temperatureBesides the needs arising from large-scale high-temperature plants, the high tech developments, suchin large process plants and the aviation industry, micro chemo-mechanical systems, fuel cells, high-temperatureThe state-of-the-art of structural integrity technology for high temperature applications is reviewed

Keywords： manufacture     aviation industry     conversion     petrochemical     temperature    

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Title Author Date Type Operation

Temperature Prediction for Sun Synchronous Satellite on Orbit

Wei Chuanfeng,Li Yunze,Yuan Lingshuang,Wang Jun,Ning Xianwen

Journal Article

Potential indicators predict progress after surgical resection of gastrointestinal stromal tumors

Qinggang Hu, Shanglong Liu, Jianwei Jiang, Chen Zhang, Xiaowei Liu, Qichang Zheng

Journal Article

An improved design method to predict the E-modulus and strength of FRP composites at different temperatures

Mohammed FARUQI, Gobishanker RAJASKANTHAN, Breanna BAILEY, Francisco AGUINIGA

Journal Article

An improved design method to predict the E-modulus and strength of FRP composites at different temperatures

Mohammed FARUQI, Gobishanker RAJASKANTHAN, Breanna BAILEY, Francisco AGUINIGA

Journal Article

A hierarchical system to predict behavior of soil and cantilever sheet wall by data-driven models

Nang Duc BUI; Hieu Chi PHAN; Tiep Duc PHAM; Ashutosh Sutra DHAR

Journal Article

Particle swarm optimization model to predict scour depth around a bridge pier

Shahaboddin SHAMSHIRBAND, Amir MOSAVI, Timon RABCZUK

Journal Article

Elevated C-reactive protein levels predict worsening prognosis in Chinese patients with first-onset stroke

Jiangtao YAN, Rutai HUI, Daowen WANG

Journal Article

A method to predict cooling load of large commercial buildings based on weather forecast and internal

Junbao JIA,Jincheng XING,Jihong LING,Ren PENG

Journal Article

Development of deep neural network model to predict the compressive strength of FRCM confined columns

Khuong LE-NGUYEN; Quyen Cao MINH; Afaq AHMAD; Lanh Si HO

Journal Article

Presentation of regression analysis, GP and GMDH models to predict the pedestrian density in various

Iraj BARGEGOL; Seyed Mohsen HOSSEINIAN; Vahid NAJAFI MOGHADDAM GILANI; Mohammad NIKOOKAR; Alireza OROUEI

Journal Article

on coupled physical and mechanical, chemical and biological soil processes: how can we maintain and predict

Rainer HORN, Winfried E. H. BLUM

Journal Article

Using hybrid models to predict blood pressure reactivity to unsupported back based on anthropometric

Gurmanik KAUR,Ajat Shatru ARORA,Vijender Kumar JAIN

Journal Article

Symptom network topological features predict the effectiveness of herbal treatment for pediatric cough

Mengxue Huang, Jingjing Wang, Runshun Zhang, Zhuying Ni, Xiaoying Liu, Wenwen Liu, Weilian Kong, Yao Chen, Tiantian Huang, Guihua Li, Dan Wei, Jianzhong Liu, Xuezhong Zhou

Journal Article

Positive stool culture could predict the clinical outcomes of haploidentical hematopoietic stem cell

Lijuan Hu, Qi Wang, Xiaohui Zhang, Lanping Xu, Yu Wang, Chenhua Yan, Huan Chen, Yuhong Chen, Kaiyan Liu, Hui Wang, Xiaojun Huang, Xiaodong Mo

Journal Article

Emerging challenges to structural integrity technology for high-temperature applications

TU Shantung

Journal Article