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Journal Article 4

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Being-with 1

Consideration of others 1

GMDH model 1

GP model 1

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Social media 1

artificial neural networks 1

liver abscess 1

locally advanced colon cancer 1

multiorganic invasion 1

multiple logistic regression 1

pedestrian density 1

regression analysis 1

rural accidents 1

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Pyogenic liver abscess as initial presentation in locally advanced right colon cancer invading the liver

Kai Qu, Chang Liu, Aasef M A Mansoor, Bo Wang, Jincai Chen, Liang Yu, Yi Lv

Frontiers of Medicine 2011, Volume 5, Issue 4,   Pages 434-437 doi: 10.1007/s11684-011-0157-3

Abstract: Locally advanced colorectal cancer complicated with adjacent organic invasion may remain confined to the local area with minimal metastasis. In the present paper, we report on a patient with advanced right colon cancer, including liver, gallbladder, and duodenal invasion behind the scene of liver abscess. resection was performed on the patient, with right-hemicolectomy, cholecystectomy, partial duodental resection, and hepatectomy. Postoperative management was administered, including nutritional support in the early postoperative period, effective anti-infection treatment, and adjuvant chemotherapy (FOLFOX4). The patient survived for 16 months after the operation. Common clinical manifestations of colorectal cancer were digestive symptoms and changes in defecation. However, the clinical manifestation of locally advanced colon cancer was extremely complicated. Extended or multivisceral resection may offer patients a chance to survive an acute crisis and allow for treatment with adjuvant therapy.

Keywords： liver abscess     locally advanced colon cancer     multiorganic invasion    

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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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Presentation of machine learning methods to determine the most important factors affecting road traffic

Hamid MIRZAHOSSEIN; Milad SASHURPOUR; Seyed Mohsen HOSSEINIAN; Vahid Najafi Moghaddam GILANI

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 5,   Pages 657-666 doi: 10.1007/s11709-022-0827-z

Abstract: The purpose of this research was to develop statistical and intelligent models for predicting the severity of road traffic accidents (RTAs) on rural roads. Multiple Logistic Regression (MLR) was used to predict the likelihood of RTAs. For more accurate prediction, Multi-Layer Perceptron (MLP) and Radius Basis Function (RBF) neural networks were applied. Results indicated that in MLR, the model obtained from the backward method with the correct percent of 84.7% and R2 value of 0.893 was the best method for predicting the likelihood of RTAs. Also, MLR showed that the variables of not paying attention to the front not paying attention to the frontroad ahead, followed byand then vehicle-motorcycle/bike accidents were the greatest problems. Among the models, MLP had a better performance, so that the prediction accuracy of MLR, MLP, and RBF were 84.7%, 96.7%, and 92.1%, respectively. MLP model, due to higher accuracy, showed that the variable of reason of accident had the highest effect on the prediction of accidents, and considering MLR results, the variables of not paying attention to the front and then vehicle-motorcycle/bike accidents had the most influence on the occurrence of accidents. Therefore, motorcyclists and cyclists are more prone to accidents, and appropriate solutions should be adopted to enhance their safety.

Keywords： safety     rural accidents     multiple logistic regression     artificial neural networks    

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Theories of Social Media: Philosophical Foundations Article

Jiayin Qi, Emmanuel Monod, Binxing Fang, Shichang Deng

Engineering 2018, Volume 4, Issue 1,   Pages 94-102 doi: 10.1016/j.eng.2018.02.009

Abstract: framework where different archetypal theories applied to social media may be compared: Goffman’s presentation

Keywords： Social media     Lifeworld     Consideration of others     Rationality     Historicity     Instrumentalism     Being-with     Presentation    

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Title Author Date Type Operation

Pyogenic liver abscess as initial presentation in locally advanced right colon cancer invading the liver

Kai Qu, Chang Liu, Aasef M A Mansoor, Bo Wang, Jincai Chen, Liang Yu, Yi Lv

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

Presentation of machine learning methods to determine the most important factors affecting road traffic

Hamid MIRZAHOSSEIN; Milad SASHURPOUR; Seyed Mohsen HOSSEINIAN; Vahid Najafi Moghaddam GILANI

Journal Article

Theories of Social Media: Philosophical Foundations

Jiayin Qi, Emmanuel Monod, Binxing Fang, Shichang Deng

Journal Article