Comparison of Two Drying Schedules for European Hophornbeam (Ostrya carpinifolia Scop.) Lumber

Two types of conventional kiln-drying schedules (mild and harsh) based on moisture content (MC) were compared with regard to time, drying quality, and energy cost. The results were evaluated according to the classification of the European Drying Group. Proper drying periods of mild and harsh schedules were found to be 550 and 514 h, respectively. Evaluations in terms of drying quality indicated that better results were achieved with the mild schedule, especially when comparing drying defects and final MC. From an energy efficiency point of view, the harsh schedule, by saving 36 h of drying time, reduced electricity by 594 KWh and was therefore found to be $65 more profitable in this trial.     

The synthesis of block copolyetherketones based on 4,4′‐dichlorodiphenylketone,phenolphthaleine, and bisphenol A and investigation of their properties

Block structured polyethers based on phenolphthaleine, 4,4′‐dichlorodiphenylketone, and bisphenol A with different degrees condensation (n = 1, 5, 10, and 20) were synthesized by means of acceptor‐catalytic polycondensation. Equaimolar quantities of chloranhydrides of iso‐ and terephthalic acids were used. Higher molecular masses were obtained from longer oligoketones with higher condensation degrees. Better molecular packing, increased thermal and mechanical properties were obtained with higher condensation degrees of oligoketones. © 2007 Wiley Periodicals, Inc. JAppl Polym Sci, 2008     

Optimized Machine Learning Algorithms for Investigating the Relationship Between Economic Development and Human Capital

Computational Economics - In Economic Development, human capital was previously seen as production factors but gradually evolved into endogenous growth theories. Most of the previous studies have...     

Change detection in desktop virtual environments: An eye-tracking study

It is common knowledge that attention is important for learning. We need to utilize attention in order to learn something efficiently and effectively. Similarly, we may also need to acquire familiarity with (i.e., learn) our surroundings in order to utilize our attention. In this study, learning is defined as a product of one’s exposure to natural visual stimuli. Using a virtual model of a natural scene, we investigate both attention and its relationship to learning, according to this definition. Specifically, our focus is the effect of environment familiarity on gaze direction. Our findings reveal that the factor of familiarity with one’s surroundings in virtual reality environments exerts a significant influence on peoples’ ability to detect a variety of specific changes that occur within scenes under their observation.     

Combined forecasts in portfolio optimization: A generalized approach

In this paper a general mathematical model for portfolio selection problem is proposed. By considering a forecasting performance according to the distributional properties of residuals, we formulate an extended mean-variance-skewness model with 11 objective functions. Returns and return errors for each asset obtained using different forecasting techniques, are combined in optimal proportions so as to minimize the mean absolute forecast error. These proportions are then used in constructing six criteria related to the mean, variance and skewness of return forecasts of assets in the future and forecasting errors of returns of assets in the past. The obtained multi-objective model is scalarized by using the conic scalarization method which guarantees to find all non-dominated solutions by considering investor preferences in non-convex multi-objective problems. The obtained scalar problem is solved by utilizing F-MSG algorithm. The performance of the proposed approach is tested on a real case problem generated on the data derived from Istanbul Stock Exchange. The comparison is conducted with respect to different levels of investor preferences over return, variance, and skewness and obtained results are summarized.     

Energy- and reliability-aware task scheduling onto heterogeneous MPSoC architectures

Scheduling periodic tasks onto a multiprocessor architecture under several constraints such as performance, cost, energy, and reliability is a major challenge in embedded systems. In this paper, we present an Integer Linear Programming (ILP) based framework that maps a given task set onto an Heterogeneous Multiprocessor System-on-Chip (HMPSoC) architecture. Our framework can be used with several objective functions; minimizing energy consumption, minimizing cost (i.e., the number of heterogeneous processors), and maximizing reliability of the system under performance constraints. We use Dynamic Voltage Scaling (DVS) for reducing energy consumption while we employ task duplication to maximize reliability. We illustrate the effectiveness of our approach through several experiments, each with a different number of tasks to be scheduled. We also propose two heuristics based on Earliest Deadline First (EDF) algorithm for minimizing energy under performance and cost constraints. Our experiments on generated task sets show that ILP-based method reduces the energy consumption up to 62% percent against a method that does not apply DVS. Heuristic methods obtain promising results when compared to optimal results generated by our ILP-based method.     

Dynamic soil–structure interaction analysis of layered unbounded media via a coupled finite element/boundary element/scaled boundary finite element model

In this paper, a coupled model based on finite element method (FEM), boundary element method (BEM) and scaled boundary FEM (SBFEM) (also referred to as the consistent infinitesimal finite element cell method) for dynamic response of 2D structures resting on layered soil media is presented. The SBFEM proposed by Wolf and Song (Finite‐element Modelling of Unbounded Media. Wiley: England, 1996) and BEM are used for modelling the dynamic response of the unbounded media (far‐field). The standard FEM is used for modelling the finite region (near‐field) and the structure. In SBFEM, which is a semi‐analytical technique, the radiation condition at infinity is satisfied exactly without requiring the fundamental solution. This method, also eliminates the need for the discretization of interfaces between different layers. In both SBFEM and BEM, the spatial dimension is decreased by one. The objective of the development of this coupled model is to combine advantages of above‐mentioned three numerical models to solve various soil–structure interaction (SSI) problems efficiently and effectively. These three methods are coupled (FE–BE–SBFEM) via substructuring method, and a computer programme is developed for the harmonic analyses of SSI systems. The coupled model is established in such a way that, depending upon the problem and far‐field properties, one can choose BEM and/or SBFEM in modelling related far‐field region(s). Thus, BEM and/or SBFEM can be used efficiently in modelling the far‐field. The proposed model is applied to investigate dynamic response of rigid and elastic structures resting on layered soil media. To assess the proposed SSI model, several problems existing in the literature are chosen and analysed. The results of the proposed model agree with the results presented in the literature for the chosen problems. The advantages of the model are demonstrated through these comparisons. Copyright © 2004 John Wiley & Sons, Ltd.     

Reconstructing 3D trajectories of independently moving objects using generic constraints

The 3D reconstruction of scenes containing independently moving objects from uncalibrated monocular sequences still poses serious challenges. Even if the background and the moving objects are rigid, each reconstruction is only known up to a certain scale, which results in a one-parameter family of possible, relative trajectories per moving object with respect to the background. In order to determine a realistic solution from this family of possible trajectories, this paper proposes to exploit the increased linear coupling between camera and object translations that tends to appear at false scales. An independence criterion is formulated in the sense of true object and camera motions being minimally correlated. The increased coupling at false scales can also lead to the destruction of special properties such as planarity, periodicity, etc. of the true object motion. This provides us with a second, ‘non-accidentalness’ criterion for the selection of the correct motion among the one-parameter family.     

Computationally highly efficient mixture of adaptive filters

We introduce a new combination approach for the mixture of adaptive filters based on the set-membership filtering (SMF) framework. We perform SMF to combine the outputs of several parallel running adaptive algorithms and propose unconstrained, affinely constrained and convexly constrained combination weight configurations. Here, we achieve better trade-off in terms of the transient and steady-state convergence performance while providing significant computational reduction. Hence, through the introduced approaches, we can greatly enhance the convergence performance of the constituent filters with a slight increase in the computational load. In this sense, our approaches are suitable for big data applications where the data should be processed in streams with highly efficient algorithms. In the numerical examples, we demonstrate the superior performance of the proposed approaches over the state of the art using the well-known datasets in the machine learning literature.