Disentangling age and cohorts effects on home-ownership and housing wealth in Turkey

This paper analyses the contribution of age and cohort effects on home-ownership and housing wealth in Turkey. I construct a pseudo-panel data set based on birth-year cohorts by using sixteen waves of the Turkish Statistical Institute Household Budget Surveys from 2003 to 2018. The empirical analysis reveals that young cohorts are less likely to own their homes, but they are more likely to have outstanding housing debt. Moreover, they are as willing to invest in second homes as older cohorts. I estimate a Heckman two-step selection model to distinguish the contribution of the improvement in the quality of new buildings to home values. As a result, I find that cohort effects on home values are significantly larger for young households even after controlling for age effects and the improvement in the quality of new buildings. Thus, the empirical findings show that young cohorts have a stronger housing demand than old cohorts.

     

A fuzzy logic based-method for prognostic decision making in breast and prostate cancers

Accurate and reliable decision making in oncological prognosis can help in the planning of suitable surgery and therapy, and generally, improve patient management through the different stages of the disease. In recent years, several prognostic markers have been used as indicators of disease progression in oncology. However, the rapid increase in the discovery of novel prognostic markers resulting from the development in medical technology, has dictated the need for developing reliable methods for extracting clinically significant markers where complex and nonlinear interactions between these markers naturally exist. The aim of this paper is to investigate the fuzzy k-nearest neighbor (FK-NN) classifier as a fuzzy logic method that provides a certainty degree for prognostic decision and assessment of the markers, and to compare it with: 1) logistic regression as a statistical method and 2) multilayer feedforward backpropagation neural networks an artificial neural-network tool, the latter two techniques having been widely used for oncological prognosis. In order to achieve this aim, breast and prostate cancer data sets are considered as benchmarks for this analysis. The overall results obtained indicate that the FK-NN-based method yields the highest predictive accuracy, and that it has produced a more reliable prognostic marker model than both the statistical and artificial neural-network-based methods.     

Optimal Control of the Primary Drying Stage of Freeze Drying of Solutions in Vials Using Variational Calculus

The problem of operating freeze drying of pharmaceutical products in vials placed in trays of a freeze dryer to remove free water (in frozen state) at a minimum time was formulated as an optimal control problem. Two different types of freeze dryer designs were considered. In type I freeze dryer design, upper and lower plate temperatures were controlled together, while in type II freeze dryer design, upper and lower plate temperatures were controlled independently. The heat input to the material being dried and the drying chamber pressure were considered as control variables. Constraints were placed on the system state variables by the melting and scorch temperatures during primary drying stage. Necessary conditions of optimality for the primary drying stage of freeze drying process in vials are derived and presented. Furthermore, an approach for constructing the optimal control policies that would minimize the drying time for the primary drying stage was given. In order to analyze optimal control policy for the primary drying stage of the freeze-drying process in vials, a rigorous multi-dimensional unsteady state mathematical model was used. The theoretical approach presented in this work was applied in the freeze drying of skim milk. Significant reductions in the drying times of primary drying stage of freeze drying process in vials were obtained, as compared to the drying times obtained from conventional operational policies.     

Hazardous waste management problem: The case for incineration

We define the hazardous waste management problem as the combined decisions of selecting the disposal method, siting the disposal plants and deciding on the waste flow structure. The hazardous waste management problem has additional requirements depending on the selected disposal method. In this paper we focus on incineration, for which the main additional requirement is to satisfy the air pollution standards imposed by the governmental restrictions. We propose a cost-based mathematical model in which the satisfaction of air pollution standards is also incorporated. We used the Gaussian Plume equation in measuring the air pollution concentrations at population centers. A large-scale implementation of the proposed model within Turkey is provided.     

Electrical and optical properties of fluorine-doped CdO films deposited by ultrasonic spray pyrolysis

The CdO:F samples have been deposited onto microscope glass substrates at 250 °C by ultrasonic spray pyrolysis method. With the incorporation of fluorine into CdO, the direct optical transition has shifted towards the shorter wavelengths, and the transparency of the material has increased at a given wavelength above the fundamental absorption edge. The shift in the absorption edge is explained by means of the Moss–Burstein effect, which is also supported with the results of the current–voltage characteristics. Here, a correlation has been established between the band broadening and the increase in conductivity due to the increase in carrier density.     

Swoop: A Web Ontology Editing Browser

In this paper, we describe Swoop, a hypermedia inspired Ontology Browser and Editor based on OWL, the recently standardized Web-oriented ontology language. After discussing the design rationale and architecture of Swoop, we focus mainly on its features, using illustrative examples to highlight its use. We demonstrate that with its Web-metaphor, adherence to OWL recommendations and key unique features, such as Collaborative Annotation using Annotea, Swoop acts as a useful and efficient Web Ontology development tool. We conclude with a list of future plans for Swoop, that should further increase its overall appeal and accessibility.     

Assessment of the types of public building maintenance contracts in Saudi Arabia

The study revealed that Fixed Price, Cost Plus and Purchased Labour contracts are the top three maintenance contracts adopted whilst Unit Price, Cost Plus A Percentage Fee contracts are alternatives used in the Kingdom. Some other types of maintenance contract were thought to be inappropriate by ministry departments.     

Face relighting using discriminative 2D spherical spaces for face recognition

As part of the face recognition task in a robust security system, we propose a novel approach for the illumination recovery of faces with cast shadows and specularities. Given a single 2D face image, we relight the face object by extracting the nine spherical harmonic bases and the face spherical illumination coefficients by using the face spherical spaces properties. First, an illumination training database is generated by computing the properties of the spherical spaces out of face albedo and normal values estimated from 2D training images. The training database is then discriminately divided into two directions in terms of the illumination quality and light direction of each image. Based on the generated multi-level illumination discriminative training space, we analyze the target face pixels and compare them with the appropriate training subspace using pre-generated tiles. When designing the framework, practical real-time processing speed and small image size were considered. In contrast to other approaches, our technique requires neither 3D face models nor restricted illumination conditions for the training process. Furthermore, the proposed approach uses one single face image to estimate the face albedo and face spherical spaces. In this work, we also provide the results of a series of experiments performed on publicly available databases to show the significant improvements in the face recognition rates.     

On-line neuro-expert monitoring system for Borssele Nuclear Power Plant

A new method for an on-line monitoring system for the nuclear power plants has been developed utilizing the neural networks and the expert system. The integration of them is expected to enhance a substantial potential of the functionality as operators support.

The recurrent neural network and the feed-forward neural network with adaptive learning are selected for the plant modeling and anomaly detection because of the high capability of modeling for dynamic behavior. The expert system is used as a decision agent, which works on the information space of both the neural networks and the human operators. The information of other sensory signals is also fed to the expert system, together with the outputs that the neural networks generate from the measured plant signals. The expert system can treat almost all known correlation between plant status patterns and operation modes as a priori set of rules.

From the off-line test at Borssele Nuclear Power Plant (PWR 480 MWe) in the Netherlands, it was shown that the neuro-expert system successfully monitored the plant status. The expert system worked satisfactorily in diagnosing the system status by using the outputs of the neural networks and a priori knowledge base from the PWR simulator. The electric power coefficient is simultaneously monitored from the measured reactive and active electric power signals.     

Arduino-based slider setup for gas–liquid mass transfer investigations: Experiments and CFD simulations

The implementation of traditional sensors is a drawback when investigating mass transfer phenomena within microstructured devices, since they disturb the flow and reactor characteristics. An Arduino based slider setup is developed, which is equipped with a computer-vision system to track gas–liquid slug flow. This setup is combined with an optical analytical method allowing to compare experimental results against CFD simulations and investigate the entire lifetime of a single liquid slug with high spatial and temporal resolution. Volumetric mass transfer coefficients are measured and compared with data from literature and the mass transfer contribution of the liquid film is discussed.