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Aggregation for Computing Multi-Modal Stationary Distributions in 1-D Gene Regulatory Networks 

Avcu, N.; Pekergin, N.; Pekergin, F.; Guzelis, C. (IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018)
This paper proposes aggregation-based, three-stage algorithms to overcome the numerical problems encountered in computing stationary distributions and mean first passage times for multi-modal birth-death processes of large ...
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Effect of chaotic mixing on the rheological characterization of mayonnaise 

Genc, S.; Izmir, T.T.; Uzel, R.A.; Demirkiran, G.; Sahin, S.; Guzelis, C. (2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017, 2018)
In this study, a new mixing method for mayonnaise was developed. A chaotic hand mixer was designed. The speed of the mixer rotor was chaotically changed with the proposed method. Performance of the mixed mayonnaise was ...
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A comparison of feature selection algorithms for cancer classification through gene expression data: Leukemia case 

Tasci, A.; Ince, T.; Guzelis, C. (2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017, 2018)
In this study, three different feature selection algorithms are compared using Support Vector Machines as classifier for cancer classification through gene expression data. The ability of feature selection algorithms to ...
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Object recognition and detection with deep learning for autonomous driving applications 

Ucar, A.; Demir, Y.; Guzelis, C. (Simulation, 2017)
Autonomous driving requires reliable and accurate detection and recognition of surrounding objects in real drivable environments. Although different object detection algorithms have been proposed, not all are robust enough ...
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Online Learning ARMA Controllers with Guaranteed Closed-Loop Stability 

Sahin, S.; Guzelis, C. (IEEE Transactions on Neural Networks and Learning Systems, 2016)
This paper presents a novel online block adaptive learning algorithm for autoregressive moving average (ARMA) controller design based on the real data measured from the plant. The method employs ARMA input-output models ...
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Design and implementation of chaotic system based robust delta robot for blending graphene nanoplatelets 

Kavur, A.E.; Demiroglu, S.; Seydibeyoglu, M.O.; Baser, O.; Guzelis, C.; Sahin, A.S. (2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016, 2016)
In this paper, a new blending method for Graphene nanoplatelets was developed. A chaotic system based robust delta robot was designed. Both the speed of the mixer motor and position of the propeller were chaotically changed. ...
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Discriminant-based bistability analysis of a TMG-induced lac operon model supported with boundedness and local stability results 

Avcu, N.; Demir, G.K.; Pekergin, F.; Alyuruk, H.; Cavas, L.; Guzelis, C. (Turkish Journal of Electrical Engineering and Computer Sciences, 2016)
This paper presents the results of a theoretical and numerical study on the analysis of bistable behavior of the most studied gene regulatory network, the lac operon, in terms of the model parameters. The boundedness of ...
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A Multiscale Algorithm for Joint Forecasting-Scheduling to Solve the Massive Access Problem of IoT 

Rodoplu, V.; Nakip, M.; Eliiyi, D.T.; Guzelis, C. (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2020)
The massive access problem of the Internet of Things (IoT) is the problem of enabling the wireless access of a massive number of IoT devices to the wired infrastructure. In this article, we describe a multiscale algorithm ...
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Conditional Weighted Ensemble of Transferred Models for Camera Based Onboard Pedestrian Detection in Railway Driver Support Systems 

Toprak, T.; Belenlioglu, B.; Aydin, B.; Guzelis, C.; Selver, M.A. (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2020)
Pedestrian Detection (PD) is one of the most studied issues of driver assistance systems. Although a tremendous effort is already given to create datasets and to develop classifiers for cars, studies about railway systems ...
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Coupling of cell fate selection model enhances DNA damage response and may underlie BE phenomenon 

Demirkiran, G.; Demir, G.K.; Guzelis, C. (INST ENGINEERING TECHNOLOGY-IET, 2020)
Double-strand break-induced (DSB) cells send signal that induces DSBs in neighbour cells, resulting in the interaction among cells sharing the same medium. Since p53 network gives oscillatory response to DSBs, such interaction ...
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Guzelis, C. (59)
Demirkiran, G. (16)Sahin, S. (13)Demir, G.K. (12)Nakip, M. (9)Bulucu, P. (8)Kocaoglu, A. (8)Soydemir, M.U. (8)Avcu, N. (6)Rodoplu, V. (6)... View MoreSubjectHumanoid robots (3)Convolution neural networks (2)Forecasting (2)Artificial Neural Network (ANN) (1)Computer architecture (1)DDPG (1)Deep semantic segmentation (1)DQN (1)Feature extraction (1)Fire detection (1)... View MoreDate Issued2020 - 2021 (16)2010 - 2019 (42)2007 - 2009 (1)Has File(s)No (52)Yes (7)

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