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Predicting heat transfer for low- and high-frequency central-orifice synthetic jets

Ikhlaq, Muhammad; Ghaffari, Omidreza; Arık, Mehmet (IEEE, 2016-04)

As electronic devices are becoming more compact each day, the more effective and efficient active cooling technologies are needed. Microfluidic devices, such as synthetic jets, serve as a potential candidate to fulfill the ...
Predicting heat transfer from unsteady synthetic jets

Arık, Mehmet; Icoz, T. (ASME, 2012-05-31)

Synthetic jets are piezo-driven, small-scale, pulsating devices capable of producing highly turbulent jets formed by periodic entrainment and expulsion of the fluid in which they are embedded. The compactness of these ...
Predicting pore volume, compressive strength, pore connectivity, and formation factor in cementitious pastes containing fly ash

Bharadwaj, K.; Ghantous, R. M.; Şahan, Feyza Nur; Isgor, O. B.; Weiss, W. J. (Elsevier, 2021-09)

This paper describes the use of thermodynamic modeling to predict the reaction products and properties of cementitious pastes containing fly ash. A pore partitioning model is used to estimate the gel and capillary pore ...
Predicting shuttle arrival time in istanbul

Çoban, Selami; Sanchez-Anguix, V.; Aydoğan, Reyhan (Springer Nature, 2020)

Nowadays, transportation companies look for smart solutions in order to improve quality of their services. Accordingly, an intercity bus company in Istanbul aims to improve their shuttle schedules. This paper proposes ...
Predicting the performance of pressure-swirl atomizers

Nural, Ozan Ekin; Ertunç, Özgür (Begell House Inc., 2018)

The purpose of this study is to evaluate the semiempirical correlations that are found in the literature by comparing them with all of the applicable experimental data that are also taken from the literature. Presentation ...
Predicting the performance of queues–A data analytic approach

Yang, K. K.; Çayırlı, Tuğba; Low, J. M.W. (Elsevier, 2016)

Existing models of multi-server queues with system transience and non-standard assumptions are either too complex or restricted in their assumptions to be used broadly in practice. This paper proposes using data analytics, ...
Predicting the risky encounters without distance knowledge between the ships via machine learning algorithms

Oruç, Muhammet Furkan; Altan, Yiğit Can (Elsevier, 2023-07-01)

As the maritime traffic is getting denser, the number of encounters is increasing. The aim of this study is to develop a prediction model to classify encounters as risky or non-risky when two ships encounter in a certain ...
Prediction algorithm & learner selection for European day-ahead electricity prices

Ülgen, Toygar; El Sayed, Ahmad; Poyrazoğlu, Göktürk (IEEE, 2020-10)

The prediction of day-ahead electricity prices with higher accuracy is always helpful for the market players of the power exchange. This study was intended in the first place to find out the best time series prediction ...
Prediction of active UE number with Bayesian neural networks for self-organizing LTE networks

Narmanlıoğlu, Ö.; Zeydan, E.; Kandemir, Melih; Kranda, T. (IEEE, 2017-01-01)

Internet-empowered electronic gadgets and content rich multimedia applications have expanded exponentially in recent years. As a consequence, heterogeneous network structures introduced with Long Term Evolution (LTE) ...
A predictive multistage postdisaster damage assessment framework for drone routing

Adsanver, Birce; Göktürk, Elvin Çoban; Koyuncu, Burcu Balçık (Wiley, 2024-01)

This study focuses on postdisaster damage assessment operations supported by a set of drones. We propose a multistage framework, consisting of two phases applied iteratively to rapidly gather damage information within an ...
Predictor analysis for electricity price forecasting by multiple linear regression

Ülgen, Toygar; Poyrazoğlu, Göktürk (IEEE, 2020)

This paper examines the multiple linear regression method on electricity price forecasting. Numerous predictors are analyzed to reduce the mean absolute percentage error. The training data includes the dates from September ...
Preface

Maniatakos, M.; Elfadel, I. A. M.; Sonza Reorda, M.; Uğurdağ, Hasan Fatih; Monteiro, J.; Reis, R. (Springer Nature, 2019)

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Kim, S.; Uchitel, S.; Garbervetsky, D.; Aktemur, Tankut Barış; Kroening, D.; Orso, A.; Nagappan, N.; Xie, T.; Mueller, P.; Cataldo, M.; Tillmann, N.; Margaria-Steffen, T.; Tonetta, S.; Bradley, A.; Chen, N.; Caso, G. de; Ferrara, P.; He, N.; Kassios, I.; Kicillof, N.; Lewis, M.; Meyer, D.; Nagel, R.; Nimal, V.; Pandita, R.; Pavese, E.; Rajan, A.; Roveri, M.; Sawadsky, N.; Schapachnik, F.; Seo, H.; Shakya, K.; Song, Y.; Summers, A.; Xiao, X.; Yilmaz, Buse; Zhang, L.; Bishop, J.; Breitman, K.; Notkin, D. (2011)
Preface

Dignum, V.; Noriega, P.; Şensoy, Murat; Sichman, J. S. (Springer International Publishing, 2016)

The pervasiveness of open systems raises a range of challenges and opportunities for research and technological development in the area of autonomous agents and multi-agent systems. Open systems comprise loosely coupled ...
Preface

Orailoğlu, A.; Uğurdağ, Hasan Fatih; Silveira, L. M.; Margala, M.; Reis, R. (Springer Science+Business Media, 2015)
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Kanaan, M.; Tekinay, Şirin (Springer International Publishing, 2011-09)

Developments in the field of wireless communications continue at an unabated pace. During the previous decade starting in the early 1990s, we have seen the introduction and mass market adoption of many different types of ...
Preface

Aydoğan, Reyhan; Ito, T.; Moustafa, A.; Otsuka, T.; Zhang, M. (Springer, 2021)

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Ito, T.; Aydoğan, Reyhan; Zhang, M. (Springer, 2021)

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Mengüç, Mustafa Pınar; Francoeur, M. (Elsevier, 2023-01-01)

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Aydoğan, Reyhan; Criado, N.; Lang, J.; Sanchez-Anguix, V.; Serramia, M. (Springer, 2023)

N/A

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Browsing by Title

Predicting heat transfer for low- and high-frequency central-orifice synthetic jets

Predicting heat transfer from unsteady synthetic jets

Predicting pore volume, compressive strength, pore connectivity, and formation factor in cementitious pastes containing fly ash

Predicting shuttle arrival time in istanbul

Predicting the performance of pressure-swirl atomizers

Predicting the performance of queues–A data analytic approach

Predicting the risky encounters without distance knowledge between the ships via machine learning algorithms

Prediction algorithm & learner selection for European day-ahead electricity prices

Prediction of active UE number with Bayesian neural networks for self-organizing LTE networks

A predictive multistage postdisaster damage assessment framework for drone routing

Predictor analysis for electricity price forecasting by multiple linear regression

Preface

Preface

Preface

Preface

Preface

Preface

Preface

Preface

Preface

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Browsing by Title

Predicting heat transfer for low- and high-frequency central-orifice synthetic jets ﻿

Predicting heat transfer from unsteady synthetic jets ﻿

Predicting pore volume, compressive strength, pore connectivity, and formation factor in cementitious pastes containing fly ash ﻿

Predicting shuttle arrival time in istanbul ﻿

Predicting the performance of pressure-swirl atomizers ﻿

Predicting the performance of queues–A data analytic approach ﻿

Predicting the risky encounters without distance knowledge between the ships via machine learning algorithms ﻿

Prediction algorithm & learner selection for European day-ahead electricity prices ﻿

Prediction of active UE number with Bayesian neural networks for self-organizing LTE networks ﻿

A predictive multistage postdisaster damage assessment framework for drone routing ﻿

Predictor analysis for electricity price forecasting by multiple linear regression ﻿

Preface ﻿

Preface ﻿

Preface ﻿

Preface ﻿

Preface ﻿

Preface ﻿

Preface ﻿

Preface ﻿

Preface ﻿

Predicting heat transfer for low- and high-frequency central-orifice synthetic jets

Predicting heat transfer from unsteady synthetic jets

Predicting pore volume, compressive strength, pore connectivity, and formation factor in cementitious pastes containing fly ash

Predicting shuttle arrival time in istanbul

Predicting the performance of pressure-swirl atomizers

Predicting the performance of queues–A data analytic approach

Predicting the risky encounters without distance knowledge between the ships via machine learning algorithms

Prediction algorithm & learner selection for European day-ahead electricity prices

Prediction of active UE number with Bayesian neural networks for self-organizing LTE networks

A predictive multistage postdisaster damage assessment framework for drone routing

Predictor analysis for electricity price forecasting by multiple linear regression

Preface

Preface

Preface

Preface

Preface

Preface

Preface

Preface

Preface