Support for a demographically based selection method at University: The role of competition

Building on the instrumental model of group conflict (IMGC), the present experiment investigates the support for discriminatory and meritocratic method of selections at university in a sample of local and immigrant students. Results showed that local students were supporting in a larger proportion selection method that favors them over immigrants in comparison to method that consists in selecting the best applicants without considering his/her origin. Supporting the assumption of the IMGC, this effect was stronger for locals who perceived immigrants as competing for resources. Immigrant students supported more strongly the meritocratic selection method than the one that discriminated them. However, contrasting with the assumption of the IMGC, this effect was only present in students who perceived immigrants as weakly competing for locals' resources. Results demonstrate that selection methods used at university can be perceived differently depending on students' origin. Further, they suggest that the mechanisms underlying the perception of discriminatory and meritocratic selection methods differ between local and immigrant students. Hence, the present experiment makes a theoretical contribution to the IMGC by delimiting its assumptions to the ingroup facing a competitive situation with a relevant outgroup. Practical implication for universities recruitment policies are discussed.

Determining shoal membership: A comparison between momentary and trajectory-based methods

Miller and Gerlai proposed two methods for determining shoal membership in Danio rerio, one based on momentary mean inter-individual distances and the other on post hoc analysis of the trajectories of nearest-neighbor distances. We propose a method based on momentary nearest-neighbor distances and compare the three methods using simulation. In general, our method yielded results that were more similar to their second method than their first one, and is computationally simpler.

CFD simulation of complex phenomena containing suspensions and flow throughporous media

There is an increasing reliance on computers to solve complex engineering problems. This is because computers, in addition to supporting the development and implementation of adequate and clear models, can especially minimize the financial support required. The ability of computers to perform complex calculations at high speed has enabled the creation of highly complex systems to model real-world phenomena. The complexity of the fluid dynamics problem makes it difficult or impossible to solve equations of an object in a flow exactly. Approximate solutions can be obtained by construction and measurement of prototypes placed in a flow, or by use of a numerical simulation. Since usage of prototypes can be prohibitively time-consuming and expensive, many have turned to simulations to provide insight during the engineering process. In this case the simulation setup and parameters can be altered much more easily than one could with a real-world experiment. The objective of this research work is to develop numerical models for different suspensions (fiber suspensions, blood flow through microvessels and branching geometries, and magnetic fluids), and also fluid flow through porous media. The models will have merit as a scientific tool and will also have practical application in industries. Most of the numerical simulations were done by the commercial software, Fluent, and user defined functions were added to apply a multiscale method and magnetic field. The results from simulation of fiber suspension can elucidate the physics behind the break up of a fiber floc, opening the possibility for developing a meaningful numerical model of the fiber flow. The simulation of blood movement from an arteriole through a venule via a capillary showed that the model based on VOF can successfully predict the deformation and flow of RBCs in an arteriole. Furthermore, the result corresponds to the experimental observation illustrates that the RBC is deformed during the movement. The concluding remarks presented, provide a correct methodology and a mathematical and numerical framework for the simulation of blood flows in branching. Analysis of ferrofluids simulations indicate that the magnetic Soret effect can be even higher than the conventional one and its strength depends on the strength of magnetic field, confirmed experimentally by Völker and Odenbach. It was also shown that when a magnetic field is perpendicular to the temperature gradient, there will be additional increase in the heat transfer compared to the cases where the magnetic field is parallel to the temperature gradient. In addition, the statistical evaluation (Taguchi technique) on magnetic fluids showed that the temperature and initial concentration of the magnetic phase exert the maximum and minimum contribution to the thermodiffusion, respectively. In the simulation of flow through porous media, dimensionless pressure drop was studied at different Reynolds numbers, based on pore permeability and interstitial fluid velocity. The obtained results agreed well with the correlation of Macdonald et al. (1979) for the range of actual flow Reynolds studied. Furthermore, calculated results for the dispersion coefficients in the cylinder geometry were found to be in agreement with those of Seymour and Callaghan.

Azolium-based systems: application of an anion exchange resin (A- form) method and 1H NMR analysis of the charged-assisted (CH)+·anion hydrogen bonds

The counteranion exchange of quaternary 1,2,3-triazolium salts was examined using a simple method that permitted halide ions to be swap for a variety of anions using an anion exchange resin (A¯ form). The method was applied to 1,2,3-triazolium-based ionic liquids and the iodideto- anion exchange proceeded in excellent to quantitative yields, concomitantly removing halide impurities. Additionally, an anion exchange resin (N3¯ form) was used to obtain the benzyl azide from benzyl halide under mild reaction. Likewise, following a similar protocol, bis(azidomethyl)arenes were also synthesized in excellent yields. The results of a proton NMR spectroscopic study of simple azolium-based ion pairs are discussed, with attention focused on the significance of the charged-assisted (CH)+···anion hydrogen bonds of simple azolium systems such as 1-butyl-3-methylimidazolium and 1-benzyl-3-methyl-1,2,3-triazolium salts.

Azolium-based systems: application of an anion exchange resin (A- form) method and 1H NMR analysis of the charged-assisted (CH)+·anion hydrogen bonds

The counteranion exchange of quaternary 1,2,3-triazolium salts was examined using a simple method that permitted halide ions to be swap for a variety of anions using an anion exchange resin (A¯ form). The method was applied to 1,2,3-triazolium-based ionic liquids and the iodideto- anion exchange proceeded in excellent to quantitative yields, concomitantly removing halide impurities. Additionally, an anion exchange resin (N3¯ form) was used to obtain the benzyl azide from benzyl halide under mild reaction. Likewise, following a similar protocol, bis(azidomethyl)arenes were also synthesized in excellent yields. The results of a proton NMR spectroscopic study of simple azolium-based ion pairs are discussed, with attention focused on the significance of the charged-assisted (CH)+···anion hydrogen bonds of simple azolium systems such as 1-butyl-3-methylimidazolium and 1-benzyl-3-methyl-1,2,3-triazolium salts.

Azolium-based systems: application of an anion exchange resin (A- form) method and 1H NMR analysis of the charged-assisted (CH)+·anion hydrogen bonds

The counteranion exchange of quaternary 1,2,3-triazolium salts was examined using a simple method that permitted halide ions to be swap for a variety of anions using an anion exchange resin (A¯ form). The method was applied to 1,2,3-triazolium-based ionic liquids and the iodideto- anion exchange proceeded in excellent to quantitative yields, concomitantly removing halide impurities. Additionally, an anion exchange resin (N3¯ form) was used to obtain the benzyl azide from benzyl halide under mild reaction. Likewise, following a similar protocol, bis(azidomethyl)arenes were also synthesized in excellent yields. The results of a proton NMR spectroscopic study of simple azolium-based ion pairs are discussed, with attention focused on the significance of the charged-assisted (CH)+···anion hydrogen bonds of simple azolium systems such as 1-butyl-3-methylimidazolium and 1-benzyl-3-methyl-1,2,3-triazolium salts.

A Method for Sky-Condition Classification from Ground-Based Solar Radiation Measurements

Identification of clouds from satellite images is now a routine task. Observation of clouds from the ground, however, is still needed to acquire a complete description of cloud conditions. Among the standard meteorologicalvariables, solar radiation is the most affected by cloud cover. In this note, a method for using global and diffuse solar radiation data to classify sky conditions into several classes is suggested. A classical maximum-likelihood method is applied for clustering data. The method is applied to a series of four years of solar radiation data and human cloud observations at a site in Catalonia, Spain. With these data, the accuracy of the solar radiation method as compared with human observations is 45% when nine classes of sky conditions are to be distinguished, and it grows significantly to almost 60% when samples are classified in only five different classes. Most errors are explained by limitations in the database; therefore, further work is under way with a more suitable database

PREDICTING THE BOILING POINT OF PCDD/Fs BY THE QSPR METHOD BASED ON THE MOLECULAR DISTANCE-EDGE VECTOR INDEX

The quantitative structure property relationship (QSPR) for the boiling point (Tb) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) was investigated. The molecular distance-edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR) and artificial neural network (ANN), respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

A NOVEL METHOD FOR THE DETERMINATION OF TRACE THORIUM BY DISPERSIVE LIQUID-LIQUID MICROEXTRACTION BASED ON SOLIDIFICATION OF FLOATING ORGANIC DROP

In this study, dispersive liquid-liquid microextraction based on the solidification of floating organic droplets was used for the preconcentration and determination of thorium in the water samples. In this method, acetone and 1-undecanol were used as disperser and extraction solvents, respectively, and the ligand 1-(2-thenoyl)-3,3,3-trifluoracetone reagent (TTA) and Aliquat 336 was used as a chelating agent and an ion-paring reagent, for the extraction of thorium, respectively. Inductively coupled plasma-optical emission spectrometry was applied for the quantitation of the analyte after preconcentration. The effect of various factors, such as the extraction and disperser solvent, sample pH, concentration of TTA and concentration of aliquat336 were investigated. Under the optimum conditions, the calibration graph was linear within the thorium content range of 1.0-250 µg L-1 with a detection limit of 0.2 µg L-1. The method was also successfully applied for the determination of thorium in the different water samples.

Induction Motor Drive Energy Efficiency - Simulation and Analysis

A coupled system simulator, based on analytical circuit equations and a finite element method (FEM) model of the motor has been developed and it is used to analyse a frequency-converterfed industrial squirrel-cage induction motor. Two control systems that emulate the behaviour of commercial direct-torque-controlled (DTC) and vector-controlled industrial frequency converters have been studied, implemented in the simulation software and verified by extensive laboratory tests. Numerous factors that affect the operation of a variable speed drive (VSD) and its energy efficiency have been investigated, and their significance in the simulation of the VSD results has been studied. The dependency of the frequency converter, induction motor and system losses on the switching frequency is investigated by simulations and measurements at different speeds for both the vector control and the DTC. Intensive laboratory measurements have been carried out to verify the simulation results.

Simulation of hydrogen peroxide direct synthesis in a microreactor

A set of models in Aspen plus was built to simulate the direct synthesis process of hydrogen peroxide in a micro-reactor system. This process model can be used to carry out material balance calculation under various experimental conditions. Three thermodynamic property methods were compared by calculating gas solubility and Uniquac-RK method was finally selected for process model. Two different operation modes with corresponding operation conditions were proposed as the starting point of future experiments. Simulations for these two modes were carried out to get the information of material streams. Moreover, some hydrodynamic parameters such as gas/liquid superficial velocity, gas holdup were also calculated with improved process model. These parameters proved the proposed experimental conditions reasonable to some extent. The influence of operation conditions including temperature, pressure and circulation ratio was analyzed for the first operation mode, where pure oxygen was fed into dissolving tank and hydrogen-carbon dioxide mixture was fed into microreactor directly. The preferred operation conditions for the system are low temperature (2°C) and high pressure (30 bar) in dissolving tank. High circulation ratio might be good in the sense that more oxygen could be dissolved and fed into reactor for reactions, but meanwhile hydrodynamics of microreactor should be considered. Furthermore, more operation conditions of reactor gas/liquid feeds in both of two operation modes were proposed to provide guidance for future experiment design and corresponding hydrodynamic parameters were also calculated. Finally, safety issue was considered from thermodynamic point of view and there is no explosion danger at given experimental plan since the released reaction heat will not cause solvent vaporization inside the microchannels. The improvement of process model still needs further study based on the future experimental results.

Electric-drive-based control and electric energy regeneration in a hydraulic system

Over the recent years, development in mobile working machines has concentrated on reducing emissions owing to the tightening rules and needs to improve energy utilization and reduce power losses. This study focuses on energy utilization and regeneration in an electro-hydraulic forklift, which is a lifting equipment application. The study starts from the modelling and simulation of a hydraulic forklift. The energy regeneration from the potential energy of the load was studied. Also a flow-based electric motor speed control was suggested in this thesis instead of the throttle control method or the variable displacement pump control. Topics related to further development in the future are discussed. Finally, a summary and conclusions are presented.

Orthogonal function method in modelling paper web quality variation

This work is devoted to the analysis of signal variation of the Cross-Direction and Machine-Direction measurements from paper web. The data that we possess comes from the real paper machine. Goal of the work is to reconstruct the basis weight structure of the paper and to predict its behaviour to the future. The resulting synthetic data is needed for simulation of paper web. The main idea that we used for describing the basis weight variation in the Cross-Direction is Empirical Orthogonal Functions (EOF) algorithm, which is closely related to Principal Component Analysis (PCA) method. Signal forecasting in time is based on Time-Series analysis. Two principal mathematical procedures that we used in the work are Autoregressive-Moving Average (ARMA) modelling and Ornstein–Uhlenbeck (OU) process.

Learning Robot Environment through Simulation

Traditionally simulators have been used extensively in robotics to develop robotic systems without the need to build expensive hardware. However, simulators can be also be used as a “memory”for a robot. This allows the robot to try out actions in simulation before executing them for real. The key obstacle to this approach is an uncertainty of knowledge about the environment. The goal of the Master’s Thesis work was to develop a method, which allows updating the simulation model based on actual measurements to achieve a success of the planned task. OpenRAVE was chosen as an experimental simulation environment on planning,trial and update stages. Steepest Descent algorithm in conjunction with Golden Section search procedure form the principle part of optimization process. During experiments, the properties of the proposed method, such as sensitivity to different parameters, including gradient and error function, were examined. The limitations of the approach were established, based on analyzing the regions of convergence.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.