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Investigation of Chaotic Mixing Performance on Characteristic Properties of Cake Batter
(ELECO 2019 - 11th International Conference on Electrical and Electronics Engineering, 2019)
Chaotification is the process of making an originally non-chaotic system being chaotic by applying a suitable control input. The aim of the study was to create a chaotic mixing mechanism using a kitchen type mixer and to ...
Joint Forecasting-Scheduling for the Internet of Things
(2019 IEEE Global Conference on Internet of Things, GCIoT 2019, 2019)
We present a joint forecasting-scheduling (JFS) system, to be implemented at an IoT Gateway, in order to alleviate the Massive Access Problem of the Internet of Things. The existing proposals to solve the Massive Access ...
Searching Optimal Values of Identification and Controller Design Horizon Lengths, and Regularization Parameters in NARMA Based Online Learning Controller Design
(ELECO 2019 - 11th International Conference on Electrical and Electronics Engineering, 2019)
This paper presents an analysis on searching the optimal values of the system identification and tracking window lengths, and regularization parameter for the online learning NARMA controller algorithm. Both window lengths ...
Stochastic Microgrid Control Problems: Effects of Load Distribution and Planning Horizon [Rassal Mikro Şebeke Kontrol Problemleri: Yök Daǧilimi ve Planlama Ufuk Uzunluǧunun Etkileri]
(Proceedings - 2019 Innovations in Intelligent Systems and Applications Conference, ASYU 2019, 2019)
Microgrids enable the integration of distributed energy resources with high renewable penetration into the main power grid. In this study, a microgrid problem that takes into account the stochastic nature of the net load, ...
Development of a Multi-Sensor Fire Detector Based on Machine Learning Models [Makine Öǧrenmesi Modellerine Dayali Çok Sensörlö Bir Yangin Algilayicisi Geliştirilmesi]
(Proceedings - 2019 Innovations in Intelligent Systems and Applications Conference, ASYU 2019, 2019)
This paper proposes a method to reduce false positive fire alarms by fusing data from different sensors using a specific machine learning model. We design an electronic circuit with 6 sensors to detect 7 physical sensory ...
Comparative study of forecasting schemes for IoT device traffic in machine-to-machine communication
(ACM International Conference Proceeding Series, 2019)
We present a comparative study of Autoregressive Integrated Moving Average (ARIMA), Multi-Layer Perceptron (MLP), 1-Dimensional Convolutional Neural Network (1-D CNN), and Long-Short Term Memory (LSTM) models on the problem ...
New CNN and hybrid CNN-LSTM models for learning object manipulation of humanoid robots from demonstration
(Springer, 2021)
As the environments that human live are complex and uncontrolled, the object manipulation with humanoid robots is regarded as one of the most challenging tasks. Learning a manipulation skill from human Demonstration (LfD) ...
Recurrent Trend Predictive Neural Network for Multi-Sensor Fire Detection
(Institute of Electrical and Electronics Engineers Inc., 2021)
We propose a Recurrent Trend Predictive Neural Network (rTPNN) for multi-sensor fire detection based on the trend as well as level prediction and fusion of sensor readings. The rTPNN model significantly differs from the ...
An End-to-End Trainable Feature Selection-Forecasting Architecture Targeted at the Internet of Things
(Institute of Electrical and Electronics Engineers Inc., 2021)
We develop a novel end-to-end trainable feature selection-forecasting (FSF) architecture for predictive networks targeted at the Internet of Things (IoT). In contrast with the existing filter-based, wrapper-based and ...
Bifurcation analysis of bistable and oscillatory dynamics in biological networks using the root-locus method
(IET Systems Biology, 2019)
Most of the biological systems including gene regulatory networks can be described well by ordinary differential equation models with rational non-linearities. These models are derived either based on the reaction kinetics ...
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