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Article Citation - WoS: 17Citation - Scopus: 17A New Outlier Detection Method Based on Convex Optimization: Application To Diagnosis of Parkinson's Disease(Taylor & Francis Ltd, 2021) Taylan, Pakize; Yerlikaya-Ozkurt, Fatma; Bilgic Ucak, Burcu; Weber, Gerhard-WilhelmNeuroscience is a combination of different scientific disciplines which investigate the nervous system for understanding of the biological basis. Recently, applications to the diagnosis of neurodegenerative diseases like Parkinson's disease have become very promising by considering different statistical regression models. However, well-known statistical regression models may give misleading results for the diagnosis of the neurodegenerative diseases when experimental data contain outlier observations that lie an abnormal distance from the other observation. The main achievements of this study consist of a novel mathematics-supported approach beside statistical regression models to identify and treat the outlier observations without direct elimination for a great and emerging challenge in humankind, such as neurodegenerative diseases. By this approach, a new method named as CMTMSOM is proposed with the contributions of the powerful convex and continuous optimization techniques referred to as conic quadratic programing. This method, based on the mean-shift outlier regression model, is developed by combining robustness of M-estimation and stability of Tikhonov regularization. We apply our method and other parametric models on Parkinson telemonitoring dataset which is a real-world dataset in Neuroscience. Then, we compare these methods by using well-known method-free performance measures. The results indicate that the CMTMSOM method performs better than current parametric models.Article Citation - WoS: 18Creep and Shrinkage Behavior of High-Strength Concrete and Minimum Reinforcement Ratio for Bridge Columns(Precast/prestressed Concrete inst, 2010) Mertol, Halit Cenan; Rizkalla, Sami; Zia, Paul; Mirmiran, AmirThis paper summarizes the findings of an extensive research program that examined the shrinkage and creep behavior of high-strength concrete (HSC) up to a strength of 18 ksi (124 MPa). Creep and shrinkage strains of 60 specimens were monitored for up to two years. The variables considered in this investigation were the concrete compressive strength, specimen size, curing type, age of concrete at loading, and loading stress level. Research findings indicate that the current American Association of State Highway and Transportation Officials' AASHTO LRFD Bridge Design Specifications could be used to estimate the creep coefficient and shrinkage strain of HSC up to 15 ksi (103 MPa). However, the current AASHTO LRFD specifications do not provide appropriate predictions for concrete compressive strength greater than 15 ksi (103 MPa). A revised time-development correction factor is proposed to obtain better predictions for HSC up to 18 ksi (124 MPa). For HSC compression members, the current AASHTO LRFD specifications require an excessive amount of minimum longitudinal reinforcement to account for the long-term effects due to shrinkage and creep. Based on an analysis, a new relationship is proposed for the required minimum reinforcement ratio.
