355 research outputs found
How to Reduce the Impact of Equivalence Scales on Poverty Measurement: Evidence from Turkey
No full textThe main aim of the paper is to contribute to the poverty measurement literature by demonstrating a method to reduce the impact of equivalence scales in poverty measurement. This is accomplished by choosing the most appropriate reference household type. The results showed that one adult household is certainly not suitable for being the reference household type. When one adult household is set as the reference, in the range of no equivalence scale and per capita equivalence scale, poverty head count ratio changes from 1 to 48 %, showing the huge effect of the equivalence scale choice. Also the analyses at household size level showed that one adult household type is not convenient to be the reference household type. On the other hand, no clear distinction could be made between central household types, but the importance of choosing a household type close to the center was demonstrated for Turkish data
Regional differences in equivalence scales in Turkey
No full textEquivalence scales have a crucial role in poverty measurement. For Turkey, there are no available up-todate equivalence scales, representing Turkish data. There were no efforts for calculation of equivalence scales at the regional level. The aim of the paper is to calculate and propose an equivalence scale for Turkey and estimate regional differences. Besides the models with Engel method, different equivalence scales were estimated by Almost Ideal Demand System. The results of the first model of AIDS approach composed of 5 age groups, is proposed for Turkey, but for simplicity the results of the second AIDS model could be used as well. In this model, the equivalence scale for Turkey is calculated as 0.65 for each additional adult after the first one and 0.35 for each child. For regional equivalence scales, we use two methods and comare the results. In the first one, regressions were run for each region separately and in the second one, dummy variables introduced. The highest difference in the results of the two methods was observed in Istanbul region. The findings for the regional scales are less reliable as the household size is bigger. This limitation is due to the relatively small size of the data sets. Having surveys with higher sample sizes would enable better results. After getting the results some conclusions could be drawn especially with regard to child cost differences among regions. It was expected to have higher costs for children in poorer regions and the regional results have confirmed this hypothesis
Characterization of protein-flavor interactions using inverse gas chromatography
No full textIn this research, we investigated the retention/release mechanism of selected flavor compounds on or from protein matrices by establishing quantitative design principles for these interactions. Thermodynamic parameters (partition coefficient Kp, free energy of adsorption ∆Gs and the enthalpy of adsorption ∆Hs) of the interaction between selected flavor compounds (hexane, hexanal, hexanol and d-limonene) and protein systems (soy protein isolate and zein) were determined by using inverse gas chromatography under different temperatures and relatively humid conditions. The inverse gas chromatography system was fitted with an additional humidification system that could maintain the relative humidity of the carrier gas, thus enabling the evaluation of the effect of relative humidity on the measured quantities. Increasing temperature and relative humidity led to less favorable interaction between selected flavors and proteins. Flavor retention at high relative humidity was less than at low relative humidity or at dry conditions. This suggests that flavor compounds and water molecules might be competing to bind to the available sides of the protein. Quantitative characterization of the mechanism and thermodynamics of flavor binding and release in protein matrices will benefit the food industry to efficiently develop flavored foods.M.S.Includes bibliographical referencesby Ozlem Dol
Risk-averse control of undiscounted transient Markov models
No full textThe classical optimal control problems for discrete-time, transient Markov processes are infinite horizon, undiscounted expected total cost or reward models. Some examples of these models are optimal stopping problems and stochastic shortest or longest path problems, which may have applications in health-care, finance, and maintenance. However, such expected value models implicitly assume the decision maker is risk-neutral, so they may not be appropriate for several real-life problems. In this study, we use Markov risk measures to formulate a risk-averse version of the optimal control problem for transient Markov processes with general state and compact control spaces. We derive risk-averse dynamic programming equations and show that they have a unique solution which is also the optimal value of the Markov control problem. Furthermore, it is shown that a randomized policy may be strictly better than deterministic policies, when risk measures are employed. We suggest two algorithms, value iteration and policy iteration methods, for solving the dynamic programming equations and show their convergence. In general, each policy evaluation step of the policy iteration algorithm requires solving a system of nonsmooth equations. We use a version of nonsmooth Newton method to solve these equations and show its global convergence. We further consider a risk-averse finite horizon Markov control problem under randomized policies and derive a value iteration method for its solution. Finally, we work on asset selling, organ transplant, and credit card examples to illustrate the theory for infinite horizon problem, and present numerical results.Ph. D.Includes bibliographical referencesIncludes vitaby Ozlem Cavu
Modeling traveler behavior via day-to-day learning dynamics
No full textTravel behavior lies at the core of analysis and evaluation of transportation related measures aiming to improve urban mobility, environmental quality and a wide variety of social objectives. A better understanding of travel behavior will improve travel demand forecasting and the assessment of emerging transport policies, and will improve our means to increase road safety. The day-to-day models reflect the travelers’ learning and forecasting mechanisms. These models predict travelers’ choices for any given day based on their experienced choices in the previous days. Day-to-day approaches allow the use of wide range of behavioral rules, and levels of aggregation, and capture the heterogeneity in users’ learning and adaptation processes, and behavioral characteristics. This thesis aims to develop a novel framework to model the interdependence between travelers’ choice decisions, learning and adaptation behavior and the day-to-day update mechanism of traffic flows. The novelty of this thesis is that the proposed approach combines traveler heterogeneity and rationality in a single framework to predict travelers’ day-to-day departure time and route decisions, and develops a novel day-to-day dynamic traffic assignment approach. The empirical results obtained from real transportation network, New Jersey Turnpike, confirm that the proposed day-to-day learning and dynamic traffic assignment framework model can successfully capture the significant learning dynamics, demonstrating the possibility of developing a psychological framework (i.e., learning models) as a viable approach to represent travel behavior. The other contributions of this thesis include a novel route choice set generation approach based on stochastic integer programming approach. The proposed methodology takes into account travel time variability and reliability in the transportation network. The path relevance criteria are directly incorporated into the optimization model by minimizing mean travel time, travel time variability and path overlap. Unlike previous approaches in the literature, proposed methodology eliminates the filtering step from the choice set generation and generates paths sets at desired dissimilarity level while minimizing the travel time and variability of these paths. Several case studies show the applicability of the proposed methodology on real transportation networks.Ph.D.Includes bibliographical referencesIncludes vitaby Ozlem Yanmaz-Tuze
Corrigendum to “The status of depression and anxiety in infertile Turkish couples” [Iran J Reprod Med 2011; 9: 99-104]
No full textThe publisher has been informed of an error that occurred on page 99 in which the second authors name must be changed to Ozlem Kayacik Gunday. On behalf of the author, the publisher wishes to apologize for this error. The online version of article has been updated on 31 August 2023 and can be found at https://doi.org/10.18502/ijrm.v9i2.104
What happens when you're lost between happiness and sadness?
No full textTwo experiments examine the effects of dramatic contrast between the music and the message of an ad on consumers' temporal perceptions and memory. Results suggest that individuals' level of discomfort with ambiguity (DWA) plays a significant role in memory and temporal perceptions when being exposed to auditory stimuli that incorporate two oppositely-valenced affective components. Music that creates dramatic contrast with the ad message leads to weaker recall and recognition for the ad messages, and lower ad duration estimates for subjects with high discomfort with ambiguity. Further, results reveal an effect of prior mood on cognitive responses toward stimuli that create dramatic contrast. Participants in a positive (vs. negative) mood report better recall and recognition, and lower but more accurate duration estimates in the case of a stimulus creating dramatic contrast. (C) 2012 Elsevier Inc. All rights reserved
The Association of TLR4 and NOD2 Polymorphisms and Febrile Neutropenia in Children with Burkitt Lymphoma
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Modelling - Simulation and gain flattening improvements for an Erbium Doped Fiber Amplifier
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