@article {1513, title = {Dynamic trade-offs in granulocyte colony-stimulating factor (G-CSF) administration during chemotherapy}, journal = {System Dynamics Review}, volume = {36}, year = {2021}, pages = {397{\textendash}446}, abstract = {

Chemotherapeutic treatment of cancer comes with side effects on the immune system, such as Chemotherapy-Induced Neutropenia (CIN). A recombinant form of Granulocyte Colony-Stimulating Factor (G-CSF) has been used to alleviate CIN. This is a challenging task due to the feedback complexity of the hematological system. A System Dynamics model is constructed to study this system and to derive practical insights for the management of CIN. Stimulation of neutrophil production via G-CSF is observed to propose crucial trade-offs. On one hand, production by stem cells and mobilization from bone marrow should be stimulated to compensate for the impairment caused by chemotherapy. On the other hand, it is important to avoid overstimulation, which reduces the regenerative capacity, as well as draining the much-needed bone-marrow reservoir. Our analysis supports the intuition that the response to G-CSF administration is conditional to patient characteristics, and {\textquotedblleft}one for all{\textquotedblright} treatment protocols are impractical. {\textcopyright} 2021 System Dynamics Society.

}, issn = {10991727}, doi = {10.1002/sdr.1671}, author = {{\.I}rsoy, Orkun and G{\"u}z, {\c S}anser and Akan, Naz Beril and G{\"o}nen{\c c} Y{\"u}cel} } @article {1420, title = {Explainable boosted linear regression for time series forecasting}, journal = {Pattern Recognition}, volume = {120}, year = {2021}, pages = {108144}, abstract = {

Time series forecasting involves collecting and analyzing past observations to develop a model to extrapolate such observations into the future. Forecasting of future events is important in many fields to support decision making as it contributes to reducing the future uncertainty. We propose explainable boosted linear regression (EBLR) algorithm for time series forecasting, which is an iterative method that starts with a base model, and explains the model{\textquoteright}s errors through regression trees. At each iteration, the path leading to highest error is added as a new variable to the base model. In this regard, our approach can be considered as an improvement over general time series models since it enables incorporating nonlinear features by residual explanation. More importantly, use of the single rule that contributes to the error most enables access to interpretable results. The proposed approach extends to probabilistic forecasting through generating prediction intervals based on the empirical error distribution. We conduct a detailed numerical study with EBLR and compare against various other approaches. We observe that EBLR substantially improves the base model performance through extracted features, and provide a comparable performance to other well established approaches. The interpretability of the model predictions and high predictive accuracy of EBLR makes it a promising method for time series forecasting.

}, keywords = {ARIMA, Decision trees, Linear regression, Probabilistic forecasting, Time series regression}, issn = {0031-3203}, doi = {https://doi.org/10.1016/j.patcog.2021.108144}, url = {https://www.sciencedirect.com/science/article/pii/S0031320321003319}, author = {Igor Ilic and Berk G{\"o}rg{\"u}l{\"u} and Mucahit Cevik and Mustafa Gokce Baydogan} } @article {1454, title = {An exact and implementable computation of the final outbreak size distribution under Erlang distributed infectious period}, journal = {Mathematical Biosciences}, volume = {325}, year = {2020}, pages = {108363}, abstract = {

This paper deals with a stochastic SIR (Susceptible{\textendash}Infected{\textendash}Recovered) model with Erlang(k,μ) distributed infectious period commonly referred as SIkR model. We show that using the total number of remaining Erlang stages as the state variable, we do not need to keep track of the stages of individual infections, and can employ a first step analysis to efficiently obtain quantities of interest. We study the distribution of the total number of recovered individuals and the distribution of the maximum number of individuals who are simultaneously infected until the end of the disease. In the literature, final outbreak size is calculated only for a small population size exactly and derivations of approximate analytic solutions from asymptotic results are suggested for larger population sizes. We numerically demonstrate that our methods are implementable on large size problem instances.

}, keywords = {Erlang distributed infectious period, Final size distribution, Markov models, Maximum size distribution, Stochastic SIR}, issn = {0025-5564}, doi = {https://doi.org/10.1016/j.mbs.2020.108363}, url = {https://www.sciencedirect.com/science/article/pii/S0025556420300547}, author = {Zeynep G{\"o}k{\c c}e {\.I}{\c s}lier and Refik G{\"u}ll{\"u} and Wolfgang H{\"o}rmann} } @article {1166, title = {Karbon Vergisi ile Sera Gaz{\i} Emisyonlar{\i}n{\i}n Azalt{\i}m{\i}: Turkiye Vakas{\i}.}, journal = {International Relations/Uluslararasi Iliskiler}, volume = {14}, year = {2017}, author = {G{\"u}rkan Kumbaro{\u g}lu and {\.I}lhan Or and I{\c S}IK, Mine} } @article {icseri2015estimation, title = {Estimation of digraph costs for keyboard layout optimization}, journal = {International Journal of Industrial Ergonomics}, volume = {48}, year = {2015}, pages = {127{\textendash}138}, publisher = {Elsevier}, author = {{\.I}{\c s}eri, Ali and Mahmut Ek{\c s}io{\u g}lu} } @article {ekcsiouglu2015estimation, title = {An Estimation of Finger-Tapping Rates and Load Capacities and the Effects of Various Factors}, journal = {Human Factors: The Journal of the Human Factors and Ergonomics Society}, year = {2015}, pages = {0018720814563976}, publisher = {SAGE Publications}, author = {Mahmut Ek{\c s}io{\u g}lu and {\.I}{\c s}eri, Ali} } @article {icseri2013finger, title = {Finger tapping rates and the effects of various factors}, journal = {Occupational Safety and Hygiene}, year = {2013}, pages = {31}, publisher = {CRC Press}, author = {{\.I}{\c s}eri, A and Mahmut Ek{\c s}io{\u g}lu} } @conference {icseritapping, title = {Tapping Rates of Fingers and the Effects of Age, Gender and Hand Preference}, booktitle = {SHO2013 {\textendash}International Symposium on Occupational Safety and Hygiene}, year = {2013}, author = {{\.I}{\c s}eri, Ali and Mahmut Ek{\c s}io{\u g}lu} } @article {islam1997tabu, title = {A Tabu Search Approach for the Single Machine Mean Tardiness Problem}, journal = {Journal of the Operational Research Society}, volume = {48}, number = {7}, year = {1997}, pages = {751{\textendash}755}, publisher = {Operational Research Society}, author = {Islam, Anvarul and Mahmut Ek{\c s}io{\u g}lu} } @conference {islam1996optimal, title = {Optimal maintenance inspection frequency: A multicriteria approach}, booktitle = {Proceedings of 5th Industrial Engineering Research Conference}, year = {1996}, pages = {639{\textendash}644}, publisher = {GA: Institute of Industrial Engineers}, organization = {GA: Institute of Industrial Engineers}, author = {Islam, Anvarul and Mahmut Ek{\c s}io{\u g}lu} }