Methods of Regularities Searching Based on Optimal Partitioning

The purpose of discussed optimal valid partitioning (OVP) methods is uncovering of ordinal or continuous explanatory variables effect on outcome variables of different types. The OVP approach is based on searching partitions of explanatory variables space that in the best way separate observations with different levels of outcomes. Partitions of single variables ranges or two-dimensional admissible areas for pairs of variables are searched inside corresponding families. Statistical validity associated with revealed regularities is estimated with the help of permutation test repeating search of optimal partition for each permuted dataset. Method for output regularities selection is discussed that is based on validity evaluating with the help of two types of permutation tests.

Fibre optic sensors for high speed hypervelocity impact studies and low velocity drop tests

The initial aim of this project was to develop a non-contact fibre optic based displacement sensor to operate in the harsh environment of a 'Light Gas Gun' (LGG), which can 'fire' small particles at velocities ranging from 1-8.4 km/s. The LGG is used extensively for research in aerospace to analyze the effects of high speed impacts on materials. Ideally the measurement should be made close to the centre of the impact to minimise corruption of the data from edge effects and survive the impact. A further requirement is that it should operate at a stand-off distance of ~ 8cm. For these reasons we chose to develop a pseudo con-focal intensity sensor, which demonstrated resolution comparable with conventional PVDF sensors combined with high survivability and low cost. A second sensor was developed based on 'Fibre Bragg Gratings' (FBG) which although requiring contact with the target the low weight and very small contact area had minimal effect on the dynamics of the target. The FBG was mounted either on the surface of the target or tangentially between a fixed location. The output signals from the FBG were interrogated in time by a new method. Measurements were made on composite and aluminium plates in the LGG and on low speed drop tests. The particle momentum for the drop tests was chosen to be similar to that of the particles used in the LGG.

Microstructure-based inherent anisotropy of asphalt mixtures

Asphalt mixtures have been demonstrated to be anisotropic materials in both laboratory and field tests. The anisotropy of asphalt mixtures consists of inherent anisotropy and stress-induced anisotropy. In previous work, the inherent anisotropy of asphalt mixtures was quantified by using only the inclination angles of the coarse aggregate particles in the asphalt mixtures. However, the inclination of fine aggregates also has a contribution to the inherent anisotropy. Moreover, the contribution to the inherent anisotropy of each aggregate may not be the same as in the previous work but will depend on the size, orientation, and sphericity of the aggregate particle. This paper quantifies the internal microstructure of the aggregates in asphalt mixtures by using an aggregate-related geometric parameter, the vector magnitude. The original formulation of the vector magnitude, which addresses only the orientation of coarse aggregates, is modified to account for not only the coarse aggregate orientation, but also the size, orientation, and sphericity of coarse and fine aggregates. This formulation is applied to cylindrical lab-mixed lab-compacted asphalt mixture specimens varying in asphalt binder type, air void content, and aging period. The vertical modulus and the horizontal modulus are also measured by using nondestructive tests. A relationship between the modified vector magnitude and the modulus ratio of the vertical modulus to the horizontal modulus is developed to quantify the influence of the inherent microstructure of the aggregates on the anisotropy of the mixtures. The modulus ratio is found to depend solely on the aggregate characteristics including the inclination angle, size, and sphericity, and it is independent of the asphalt binder type, air void content, and aging period. The inclination angle, itself, proves to be insufficient to quantify the inherent anisotropy of the asphalt mixtures. © 2011 American Society of Civil Engineers.

A laser induced breakdown spectroscopy quantitative analysis method based on the robust least squares support vector machine regression model

Data fluctuation in multiple measurements of Laser Induced Breakdown Spectroscopy (LIBS) greatly affects the accuracy of quantitative analysis. A new LIBS quantitative analysis method based on the Robust Least Squares Support Vector Machine (RLS-SVM) regression model is proposed. The usual way to enhance the analysis accuracy is to improve the quality and consistency of the emission signal, such as by averaging the spectral signals or spectrum standardization over a number of laser shots. The proposed method focuses more on how to enhance the robustness of the quantitative analysis regression model. The proposed RLS-SVM regression model originates from the Weighted Least Squares Support Vector Machine (WLS-SVM) but has an improved segmented weighting function and residual error calculation according to the statistical distribution of measured spectral data. Through the improved segmented weighting function, the information on the spectral data in the normal distribution will be retained in the regression model while the information on the outliers will be restrained or removed. Copper elemental concentration analysis experiments of 16 certified standard brass samples were carried out. The average value of relative standard deviation obtained from the RLS-SVM model was 3.06% and the root mean square error was 1.537%. The experimental results showed that the proposed method achieved better prediction accuracy and better modeling robustness compared with the quantitative analysis methods based on Partial Least Squares (PLS) regression, standard Support Vector Machine (SVM) and WLS-SVM. It was also demonstrated that the improved weighting function had better comprehensive performance in model robustness and convergence speed, compared with the four known weighting functions.

Comparison of Multivariate and Univariate Models for Genetic Evaluation of Milk Yield based on Test Day Data

2000 Mathematics Subject Classification: 62H12, 62P99

Probabilistic Models in Cryptography, Coding Theory and Tests for PRNG

2000 Mathematics Subject Classification: 94A29, 94B70

Implementation of pseudo J-integral based Paris’ law for fatigue cracking in asphalt mixtures and pavements

Pavement analysis and design for fatigue cracking involves a number of practical problems like material assessment/screening and performance prediction. A mechanics-aided method can answer these questions with satisfactory accuracy in a convenient way when it is appropriately implemented. This paper presents two techniques to implement the pseudo J-integral based Paris’ law to evaluate and predict fatigue cracking in asphalt mixtures and pavements. The first technique, quasi-elastic simulation, provides a rational and appropriate reference modulus for the pseudo analysis (i.e., viscoelastic to elastic conversion) by making use of the widely used material property: dynamic modulus. The physical significance of the quasi-elastic simulation is clarified. Introduction of this technique facilitates the implementation of the fracture mechanics models as well as continuum damage mechanics models to characterize fatigue cracking in asphalt pavements. The second technique about modeling fracture coefficients of the pseudo J-integral based Paris’ law simplifies the prediction of fatigue cracking without performing fatigue tests. The developed prediction models for the fracture coefficients rely on readily available mixture design properties that directly affect the fatigue performance, including the relaxation modulus, air void content, asphalt binder content, and aggregate gradation. Sufficient data are collected to develop such prediction models and the R2 values are around 0.9. The presented case studies serve as examples to illustrate how the pseudo J-integral based Paris’ law predicts fatigue resistance of asphalt mixtures and assesses fatigue performance of asphalt pavements. Future applications include the estimation of fatigue life of asphalt mixtures/pavements through a distinct criterion that defines fatigue failure by its physical significance.

Cultural value orientations of the former communist countries:a gender-based analysis

This study examines the cultural value orientations of employees working in major industrial and commercial centers of six ex-communist Central Eastern European Countries (CEECs) and Euro-Asian countries, in particular the former Soviet Republics (FSRs). The analysis is based on a questionnaire survey administered with 1052 respondents. The study tests a number of hypotheses regarding the cultural orientations of the sample populations, using gender as the core variable. The study reports cultural dimensions on which the female respondents clearly differ from their male counterparts, and there is more cultural homogeneity among males than among females within the CEECs and FSRs. Furthermore, the findings show similar cultural patterns emerging between the Czech Republic, former East Germany (FEG), and Poland on the one hand and Georgia and Uzbekistan on the other, whereas Russia culturally stands between the two groups. The research also highlights the basis of cultural aspects from which both national and managerial cultures of each research country are emerging. It brings to light the methods employed by management toward human resources in these countries, and also identifies key issues for overseas operators currently undertaking a business or planning to establish one in these countries. © 2011 Taylor & Francis.

A virtual species set for robust and reproducible species distribution modelling tests

Predicting species potential and future distribution has become a relevant tool in biodiversity monitoring and conservation.In this data article we present the suitability map of a virtual species generated based on two bioclimatic variables, and a dataset containing more than 700,000 random observations at the extent of Europe. The dataset includes spatial attributes such as: distance to roads, protected areas, country codes, and the habitat suitability of two spatially clustered species (grassland and forest species) and a wide-spread species.

DFIG machine design for maximizing power output based on surrogate optimization algorithm

This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine's previous operational performance, the DFIG's stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.

Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions

This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array.

Identifying PV module mismatch faults by a thermography-based temperature distribution analysis

Photovoltaic (PV) solar power generation is proven to be effective and sustainable but is currently hampered by relatively high costs and low conversion efficiency. This paper addresses both issues by presenting a low-cost and efficient temperature distribution analysis for identifying PV module mismatch faults by thermography. Mismatch faults reduce the power output and cause potential damage to PV cells. This paper first defines three fault categories in terms of fault levels, which lead to different terminal characteristics of the PV modules. The investigation of three faults is also conducted analytically and experimentally, and maintenance suggestions are also provided for different fault types. The proposed methodology is developed to combine the electrical and thermal characteristics of PV cells subjected to different fault mechanisms through simulation and experimental tests. Furthermore, the fault diagnosis method can be incorporated into the maximum power point tracking schemes to shift the operating point of the PV string. The developed technology has improved over the existing ones in locating the faulty cell by a thermal camera, providing a remedial measure, and maximizing the power output under faulty conditions.

A comparison of a distance education and locally based course in an urban university setting

The purpose of this research was to compare the academic performance and attitudes of students at the instructor-based site of a televised course and the distant site. An earlier pilot program indicated the need for certain technical and structural interventions at the distant site such as multiple "press-to-touch" microphones, a site-administrator and participative seating arrangements. At the beginning of the class, demographic data were collected from the students at both sites through a questionnaire and supplemented with information from students' records. Factors such as age, gender, ethnicity, marital status, number of children, current class status, major, work status and CLAST scores (achievement tests) were examined. There were no significant differences between the students at the sites except ethnicity and reading CLAST scores. The instructor-based site had a higher percentage of Hispanic students and the distant site had a larger percentage of Caucasian and Black Americans. The distant site scored significantly better on the reading section of the CLAST achievement test. An evaluation instrument was distributed to both sites, at the midpoint of the semester, measuring their attitude toward the organizational, technical, and pedagogical factors of the course. A second evaluation instrument, measuring similar factors, but more in-depth, was distributed to both sites near the end of the term. Nine students at the distant site were interviewed along with the site administrator to collect additional information.^ Course completion rates, dropout rates, pass rates and final grades of students at both sites were compared. There were no significant differences in academic performance between the students at both sites, however, there were significant differences in their attitudes. Those at the instructor-based site gave better ratings to most of items in the evaluation instruments. Problems at the distant site included audio and visual clarity, lack of available assistance, too much nonrelated talking, not enough opportunities to ask questions or to interact with the instructor during class. ^