Hasanov M.,Okan University
Energy Sources, Part B: Economics, Planning and Policy | Year: 2017
In this paper, we analyze the economic consequences of full import liberalization of the Turkish natural gas market. For this purpose, we build a simple game-theoretic model where exporters of natural gas may face supply constraints. We first derive equilibrium quantity and market price analytically with and without capacity constraints of the exporters. Then, we compute estimates of equilibrium quantity and prices using calibrated demand functions. Our results suggest that full market liberalization will bring huge economic gains to the Turkish consumers. © 2017 Taylor & Francis Group, LLC.
News Article | May 13, 2017
Nursing-2017 features highly enlightening and interactive sessions to encourage the exchange of ideas across a wide range of disciplines in the field of nursing. They invite the contributions related to nursing research. You can submit your work in these broad themes. For conference themes please see: http://nursing.madridge.com/conference-themes.php The 1st International Conference on Nursing event was a huge success; they also welcomed the exposure to the new research and advancements presented during the 3 day conference. The conference has a gathering of 200 nursing professionals from 18 different countries all over the world. Nursing-2016 Speakers and Delegates: · Nezam Al-Nsair, University of Mount Union, USA · Phyllis Hansell, Seton Hall University, USA · Yvonne Ramlall, Sunnybrook Health Sciences Centre, Canada · Michael Jacqueline Lall, University of Texas at Arlington, USA · Khlood Salman, Duquesne University, USA · Jih-Yuan Chen, Kaohsiung Medical University, Taiwan · Claire Donnellan, Trinity College, Ireland · Francis Florencio, AUT University, Newzealand · Maude Hebert, University of Quebec in Trois-Rivieres, Canada · Julie Slade, Chatham University, USA · Manal Alatrash, Western University of Health Sciences/College of Graduate Nursing, USA · Amera Rashed, Menoufyia University, Egypt · Shauna Davies, University of Regina, Canada · Muder Alkrisat, Chamberlain College of Nursing, USA · Linda J. Ulak, Seton Hall University, USA · Dawn Marie Nair, St. Vincent's College, USA · Kristen Crusoe, Oregon Health & Sciences University, USA · Ma'en ZaidAbu-Qamar, Edith Cowan University, Australia · Pia Yngman-Uhlin, Linköping University, Sweden · Ana Peliteiro Neto, Emirates Home Nursing, Saudi Arabia · Seamus Cowman, Royal College of Surgeons Ireland Bahrain, Bahrain · Audrey Cund, University of the West of Scotland, UK · Louise Johnston, University of the West of Scotland, UK · Sherry Arvidson, University of Regina, Canada · Laureen Turner, University of San Francisco, USA · Hazel Kyle, University of the West of Scotland, UK · Johanna McMullan, Queens University, uk · Nasreena Waheed, Charles Dawin University, Australia · Maryann Godshall, Drexel University, USA · Muyssar Sabri Awadhalla, University of Bahrain, Bahrain · Kristina Schildmeijer, Linnaeus University, Sweden · Susan Carlisle, Queen's University Belfast , UK · Carin Ericsson, Linköping University, Sweden · Ghada ghamdi, University of Dhammam, Saudi Arabia · Janna Skagerström, Linköping University, Sweden · Sylvia Godelia, Sunnybrook Health Sciences Centre, Canada · Ahmed Maghari, Merck KSA · Ahmed Naser, Merck KSA · Ahmed Niaze, Merck KSA · Aida Mohamed, Merck KSA · Areej Khan, Merck KSA · Faten Ahmad, Merck KSA · Faten Ezzeddine, Merck KSA · Fatima Al Maghrabi, Merck KSA · Fayza Hassanin, Merck KSA · Hani Alismaeel, Merck KSA Nursing-2017 Organizing Committee: · Sheila Ryan, University of Nebraska Medical Center, USA · Samy A. Azer, King Saud University, Saudi Arabia · Vivien Dee, Azusa Pacific University, USA · Birsen Yurugen, Okan University of Health Sciences, Turkey · Amal Kadry Nicola Attia, University of Sharjah, Saudi Arabia · Nurhan Bayraktar, Near East University, Turkey · Esther Christian Sellars, The University of Tennessee at Martin, USA · Nezam Al-Nsair, University of Mount Union, USA · Khlood Salman, Duquesne University, USA · Michael Jacqueline Lall, The University of Texas at Arlington,USA · Mohammad Al Qadire, Al Al-Bayt University, Jordan · Aysegel Durmaz, Dumlupinar University, Turkey Nursing-2017 is organizing an outstanding Scientific Exhibition/Program and anticipates the world’s leading specialists involved in Nursing Research. They welcome Sponsorship and Exhibitions from the Companies and Organizations who wish to showcase their products at this exciting event. Register for the conference and book your slots at: http://nursing.madridge.com/register.php Contact person: Bhagya Rekha email@example.com firstname.lastname@example.org Naples, FL, May 13, 2017 --( PR.com )-- 2nd International Nursing Conference is going to be held during November 1-3, 2017 at Barcelona, Spain.Nursing-2017 features highly enlightening and interactive sessions to encourage the exchange of ideas across a wide range of disciplines in the field of nursing.They invite the contributions related to nursing research. You can submit your work in these broad themes. For conference themes please see:The 1st International Conference on Nursing event was a huge success; they also welcomed the exposure to the new research and advancements presented during the 3 day conference. The conference has a gathering of 200 nursing professionals from 18 different countries all over the world.Nursing-2016 Speakers and Delegates:· Nezam Al-Nsair, University of Mount Union, USA· Phyllis Hansell, Seton Hall University, USA· Yvonne Ramlall, Sunnybrook Health Sciences Centre, Canada· Michael Jacqueline Lall, University of Texas at Arlington, USA· Khlood Salman, Duquesne University, USA· Jih-Yuan Chen, Kaohsiung Medical University, Taiwan· Claire Donnellan, Trinity College, Ireland· Francis Florencio, AUT University, Newzealand· Maude Hebert, University of Quebec in Trois-Rivieres, Canada· Julie Slade, Chatham University, USA· Manal Alatrash, Western University of Health Sciences/College of Graduate Nursing, USA· Amera Rashed, Menoufyia University, Egypt· Shauna Davies, University of Regina, Canada· Muder Alkrisat, Chamberlain College of Nursing, USA· Linda J. Ulak, Seton Hall University, USA· Dawn Marie Nair, St. Vincent's College, USA· Kristen Crusoe, Oregon Health & Sciences University, USA· Ma'en ZaidAbu-Qamar, Edith Cowan University, Australia· Pia Yngman-Uhlin, Linköping University, Sweden· Ana Peliteiro Neto, Emirates Home Nursing, Saudi Arabia· Seamus Cowman, Royal College of Surgeons Ireland Bahrain, Bahrain· Audrey Cund, University of the West of Scotland, UK· Louise Johnston, University of the West of Scotland, UK· Sherry Arvidson, University of Regina, Canada· Laureen Turner, University of San Francisco, USA· Hazel Kyle, University of the West of Scotland, UK· Johanna McMullan, Queens University, uk· Nasreena Waheed, Charles Dawin University, Australia· Maryann Godshall, Drexel University, USA· Muyssar Sabri Awadhalla, University of Bahrain, Bahrain· Kristina Schildmeijer, Linnaeus University, Sweden· Susan Carlisle, Queen's University Belfast , UK· Carin Ericsson, Linköping University, Sweden· Ghada ghamdi, University of Dhammam, Saudi Arabia· Janna Skagerström, Linköping University, Sweden· Sylvia Godelia, Sunnybrook Health Sciences Centre, Canada· Ahmed Maghari, Merck KSA· Ahmed Naser, Merck KSA· Ahmed Niaze, Merck KSA· Aida Mohamed, Merck KSA· Areej Khan, Merck KSA· Faten Ahmad, Merck KSA· Faten Ezzeddine, Merck KSA· Fatima Al Maghrabi, Merck KSA· Fayza Hassanin, Merck KSA· Hani Alismaeel, Merck KSANursing-2017 Organizing Committee:· Sheila Ryan, University of Nebraska Medical Center, USA· Samy A. Azer, King Saud University, Saudi Arabia· Vivien Dee, Azusa Pacific University, USA· Birsen Yurugen, Okan University of Health Sciences, Turkey· Amal Kadry Nicola Attia, University of Sharjah, Saudi Arabia· Nurhan Bayraktar, Near East University, Turkey· Esther Christian Sellars, The University of Tennessee at Martin, USA· Nezam Al-Nsair, University of Mount Union, USA· Khlood Salman, Duquesne University, USA· Michael Jacqueline Lall, The University of Texas at Arlington,USA· Mohammad Al Qadire, Al Al-Bayt University, Jordan· Aysegel Durmaz, Dumlupinar University, TurkeyNursing-2017 is organizing an outstanding Scientific Exhibition/Program and anticipates the world’s leading specialists involved in Nursing Research. They welcome Sponsorship and Exhibitions from the Companies and Organizations who wish to showcase their products at this exciting event.Register for the conference and book your slots at:Contact person:Bhagya Rekha Click here to view the company profile of topseos.com Click here to view the list of recent Press Releases from topseos.com
Agency: European Commission | Branch: H2020 | Program: IA | Phase: GV-6-2015 | Award Amount: 5.39M | Year: 2016
The automotive industry has made a substantial effort in recent years in developing powertrain technologies to improve fuel efficiency on Heavy-Duty Vehicles (HDVs). Due to increasing road freight traffic, however, projections indicate that total HDV energy use and CO2 emissions are expected to remain stable at the current level over the long term, if no policy action is taken. This is clearly incompatible with the goal of reducing greenhouse gas emissions from transport by around 60% below 1990 levels by 2050. The overall objective of optiTruck is to further improve energy efficiency by at least 20% on Euro VI HDVs (40t). To achieve this, optiTruck will develop a global optimiser which brings together the most advanced technologies from powertrain control and intelligent transport systems, with a number of innovative and complementary elements to maximise the potential utilisation of individual innovations. Through real driving trials, optiTruck will demonstrate this objective, taking account road topography, traffic and weather condition, vehicle configuration and transport mission. optiTruck will develop a comprehensive impact assessment methodology to extend this local and small-scale demonstration to a wider evaluation to explore potential benefits of using the rich cloud data sources and powerful computing facilities for fast-than-real-time modelling and simulation. It will also take account of social equity, economic, and environmental factors in the assessment to address the main societal challenges for the sector. optiTruck will facilitate the creation of a global platform not only for exchanging existing knowledge between automotive industries, but also for promoting horizontal collaboration in new ways essential for wider uptake of energy saving solutions across the sector, Europe and the world, which is the ultimate goal the optiTruck partners strive to achieve within and beyond this project.
Agency: European Commission | Branch: FP7 | Program: BSG-SME | Phase: SME-1 | Award Amount: 1.47M | Year: 2008
The 24-month ELEVATE project proposes a hybrid training and certification environment, which integrates the application software to be taught in the pedagogical-documented educational process, allowing the software development SMEs to deliver innovative e-training services and to address (more than adequately) the needs of their business partners and customers. Thus, the ELEVATE project addresses the business needs of the software development SMEs participating in the project in the field of application software training through their business partners and customers networks. As the software development SMEs have restricted resources to allocate in research and development (R&D) activities with regard to secondary corporate objectives, including e-training in the produced application software products, the proposed ELEVATE project provides participating SMEs with potentials and financial support to outsource a critical mass of research and technological development (RTD) activities to industrial companies and universities with larger research capacity and proved, successful experience in R&D, European-wide initiatives. The ELEVATE RTD performers will undertake significant research activities on behalf of the participating SMEs and deliver technology know-how in the fields of e-learning, educational content aggregation and material creation, learning management system and application software integration, and pedagogic standards and models. Led by CAS Software AG, the consortium consists of 8 partners from 7 EC member and associated countries (Germany, Belgium, Swiss, Greece, Cyprus, Italy and Turkey), including software development SMEs, industrial companies and universities.
Aptoula E.,Okan University
IEEE Transactions on Geoscience and Remote Sensing | Year: 2014
In this paper, we present the results of applying global morphological texture descriptors to the problem of content-based remote sensing image retrieval. Specifically, we explore the potential of recently developed multiscale texture descriptors, namely, the circular covariance histogram and the rotation-invariant point triplets. Moreover, we introduce a couple of new descriptors, exploiting the Fourier power spectrum of the quasi-flat-zone-based scale space of their input. The descriptors are evaluated with the UC Merced Land Use-Land Cover data set, which has been only recently made public. The proposed approach is shown to outperform the best known retrieval scores, despite its shorter feature vector length, thus asserting the practical interest of global content descriptors as well as of mathematical morphology in this context. © 1980-2012 IEEE.
Ozturk S.B.,Okan University |
Toliyat H.A.,Texas A&M University
IEEE/ASME Transactions on Mechatronics | Year: 2011
In this paper, the position-sensorless direct torque and indirect flux control of brushless dc (BLDC) motor with nonsinusoidal back electromotive force (EMF) has been extensively investigated. In the literature, several methods have been proposed for BLDC motor drives to obtain optimum current and torque control with minimum torque pulsations. Most methods are complicated and do not consider the stator flux linkage control, therefore, possible high-speed operations are not feasible. In this study, a novel and simple approach to achieve a low-frequency torque ripple-free direct torque control (DTC) with maximum efficiency based on dq reference frame is presented. The proposed sensorless method closely resembles the conventional DTC scheme used for sinusoidal ac motors such that it controls the torque directly and stator flux amplitude indirectly using d-axis current. This method does not require pulsewidth modulation and proportional plus integral regulators and also permits the regulation of varying signals. Furthermore, to eliminate the low-frequency torque oscillations, two actual and easily available line-to-line back EMF constants (kba and kca) according to electrical rotor position are obtained offline and converted to the dq frame equivalents using the new line-to-line park transformation. Then, they are set up in the look-up table for torque estimation. The validity and practical applications of the proposed sensorless three-phase conduction DTC of BLDC motor drive scheme are verified through simulations and experimental results. © 2010 IEEE.
Aptoula E.,Okan University
Journal of Visual Communication and Image Representation | Year: 2012
The two principal morphological texture descriptors, granulometry and morphological covariance, rely on the common principle of successive filtering of an image using a variety of structuring elements, from which feature vectors are subsequently computed. A crucial stage of their computation is the numerical characterization or parameterization of each of the filtered images. In this regard, the zero-th statistical moment is the traditional measure, while the use of higher order moments has also been reported. In this paper, we present the results of a comparative study, concentrating on the potential of various statistical moments for the task of parameterization, while additionally investigating the contribution of Fourier transform moments. The experiments are conducted with focus on texture description effectiveness and on noise robustness, using publicly available texture collections: Outex, CUReT and KTH-TIPS2b, where it is shown that the combination of moments leads to superior classification performance even at high noise levels. © 2012 Elsevier Inc. All rights reserved.
Yarman T.,Okan University
Physics Essays | Year: 2014
Based on the principal proofs we have provided in a previous article, herein we draw a unique quantum mechanical architecture, matter is made of. We call it "universal matter architecture" (UMA). It is this architecture that principally works as the internal machinery of the end results of the special theory of relativity, were the object brought to a uniform translational motion, or that of the end results of the general theory of relativity, were the object at hand embedded in a gravitational field, in effect, any field the object can interact with. Herein effort is devoted particularly to disclose UMA, chiefly on the basis of the structure of diatomic molecules, which well yields an unequal systematization of these molecules, in fact, also that of polyatomic molecules. We show how UMA provides with the opportunity of resuming the mysterious retardation of the bound muon decay rate. It is further amazing that a gas made of billion times billion times billion molecules is also structured in accordance with the matter architecture we disclose. © 2014 Physics Essays Publication.
Dundar S.,Okan University |
Sahin T.,Yildiz Technical University
Transportation Research Part C: Emerging Technologies | Year: 2013
Train re-scheduling problems are popular among researchers who have interest in the railway planning and operations fields. Deviations from normal operation may cause inter-train conflicts which have to be detected and timely resolved. Except for very few applications, these tasks are usually performed by train dispatchers. Due to the complexity of re-scheduling problems, dispatchers utilize some simplifying rules to resolve conflicts and implement their decisions accordingly. From the system effectiveness and efficiency point of view, their decisions should be supported with appropriate tools because their immediate decisions may cause considerable train delays in future interferences. Such a decision support tool should be able to predict overall implications of the alternative solutions. Genetic algorithms (GAs) for conflict resolutions were developed and evaluated against the dispatchers' and the exact solutions. The comparison measures are the computation time and total (weighted) delay due to conflict resolutions. For benchmarking purposes, artificial neural networks (ANNs) were developed to mimic the decision behavior of train dispatchers so as to reproduce their conflict resolutions. The ANN was trained and tested with data extracted from conflict resolutions in actual train operations in Turkish State Railways. The GA developed was able to find the optimal solutions for small sized problems in short times, and to reduce total delay times by around half in comparison to the ANN (i.e., train dispatchers). © 2012 Elsevier Ltd.
Cifter A.,Okan University
Physica A: Statistical Mechanics and its Applications | Year: 2011
This paper introduces wavelet-based extreme value theory (EVT) for univariate value-at-risk estimation. Wavelets and EVT are combined for volatility forecasting to estimate a hybrid model. In the first stage, wavelets are used as a threshold in generalized Pareto distribution, and in the second stage, EVT is applied with a wavelet-based threshold. This new model is applied to two major emerging stock markets: the Istanbul Stock Exchange (ISE) and the Budapest Stock Exchange (BUX). The relative performance of wavelet-based EVT is benchmarked against the Riskmetrics-EWMA, ARMAGARCH, generalized Pareto distribution, and conditional generalized Pareto distribution models. The empirical results show that the wavelet-based extreme value theory increases predictive performance of financial forecasting according to number of violations and tail-loss tests. The superior forecasting performance of the wavelet-based EVT model is also consistent with Basel II requirements, and this new model can be used by financial institutions as well. © 2011 Elsevier B.V. All rights reserved.