Validation of the Item-Attribute Matrix in TIMSS-Mathematics Using Multiple Regression and the LSDM

For many cognitive diagnostic models, the item-attribute matrix (or Q-matrix) is an essential component which displays the relationship between items and their latent attributes or skills in knowledge and cognitive processes. However, it is a challenge to develop an effective Q-matrix.The purposes of this study were (1) to validate of the item-attribute matrix using two levels of attributes (Level 1 attributes and Level 2 sub-attributes), and (2) through retrofitting the diagnostic models to the mathematics test of the Trends in International Mathematics and Science Study (TIMSS), to evaluate the construct validity of TIMSS mathematics assessment by comparing the results of two assessment booklets. Item data were extracted from Booklets 2 and 3 for the 8th grade in TIMSS 2007, which included a total of 49 mathematics items and every student\u27s response to every item. The study developed three categories of attributes at two levels: content, cognitive process (TIMSS or new), and comprehensive cognitive process (or IT) based on the TIMSS assessment framework, cognitive procedures, and item type. At level one, there were 4 content attributes (number, algebra, geometry, and data and chance), 3 TIMSS process attributes (knowing, applying, and reasoning), and 4 new process attributes (identifying, computing, judging, and reasoning). At level two, the level 1 attributes were further divided into 32 sub-attributes. There was only one level of IT attributes (multiple steps/responses, complexity, and constructed-response). Twelve Q-matrices (4 originally specified, 4 random, and 4 revised) were investigated with eleven Q-matrix models (QM1 ~ QM11) using multiple regression and the least squares distance method (LSDM). Comprehensive analyses indicated that the proposed Q-matrices explained most of the variance in item difficulty (i.e., 64% to 81%). The cognitive process attributes contributed to the item difficulties more than the content attributes, and the IT attributes contributed much more than both the content and process attributes. The new retrofitted process attributes explained the items better than the TIMSS process attributes. Results generated from the level 1 attributes and the level 2 attributes were consistent. Most attributes could be used to recover students\u27 performance, but some attributes\u27 probabilities showed unreasonable patterns. The analysis approaches could not demonstrate if the same construct validity was supported across booklets. The proposed attributes and Q-matrices explained the items of Booklet 2 better than the items of Booklet 3. The specified Q-matrices explained the items better than the random Q-matrices

Intracranial fluids dynamics: a quantitative evaluation by means of phase-contrast magnetic resonance imaging

El volumen intracraneal lo integran el volumen de líquido cefalorraquídeo (LCR), el de la sangre y el del parénquima cerebral. La entrada de sangre al cráneo en la sístole incrementa el volumen intracraneal. Según la ley de Monroe-Kellie debe ocurrir una descompensación en los volúmenes restantes para mantener constante el volumen total. Los desequilibrios que se producen en este proceso de la homeostasis cerebral se han asociado tanto a enfermedades neurodegenerativas como a cerebrovasculares. Por tanto, es necesario contar con metodologías adecuadas para analizar la dinámica de los fluidos intracraneales (LCR y sangre). Las secuencias dinámicas de resonancia magnética en contraste de fase (RM-CF) con sincronismo cardíaco permiten cuantificar el flujo de LCR y de sangre durante un ciclo cardíaco. La medición de flujo mediante secuencias de RM-CF es precisa y reproducible siempre que se use un protocolo de adquisición adecuado. La reproducibilidad y exactitud de las medidas dependen también del uso de técnicas adecuadas de posproceso que permitan segmentar las regiones de interés (ROI) independientemente del operador y admitan corregir los errores de fondo introducidos por la supresión imperfecta de las corrientes inducidas y la contribución a la señal de los pequeños movimientos que presenta el mesencéfalo por la transmisión del pulso vascular así como el submuestreo (aliasing), reflejado como un cambio abrupto y opuesto del sentido original del flujo. Estas técnicas de análisis deben también tener en cuenta los errores relacionados con el efecto de volumen parcial (EVP), causado por la presencia de tejido estacionario y de flujo en el interior de los vóxeles de la periferia de la región a estudiar El objetivo principal de esta tesis es desarrollar una metodología reproducible para evaluar cuantitativamente la dinámica de los fluidos intracraneales dentro de espacios de LCR (acueducto de Silvio, cisterna prepontina y espacio perimedular C2C3) y principales vaFlórez Ordóñez, YN. (2009). Intracranial fluids dynamics: a quantitative evaluation by means of phase-contrast magnetic resonance imaging [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/6029Palanci

A new in-camera color imaging model for computer vision

Ph.DDOCTOR OF PHILOSOPH

Molecular Dynamics Simulation

Condensed matter systems, ranging from simple fluids and solids to complex multicomponent materials and even biological matter, are governed by well understood laws of physics, within the formal theoretical framework of quantum theory and statistical mechanics. On the relevant scales of length and time, the appropriate ‘first-principles’ description needs only the Schroedinger equation together with Gibbs averaging over the relevant statistical ensemble. However, this program cannot be carried out straightforwardly—dealing with electron correlations is still a challenge for the methods of quantum chemistry. Similarly, standard statistical mechanics makes precise explicit statements only on the properties of systems for which the many-body problem can be effectively reduced to one of independent particles or quasi-particles. [...

OPTIMIZATION OF STATION LOCATIONS AND TRACK ALIGNMENTS FOR RAIL TRANSIT LINES

Designing urban rail transit systems is a complex problem, which involves the determination of station locations, track geometry, right-of-way type, and various other system characteristics. The existing studies overlook the complex interactions between railway alignments and station locations in a practical design process. This study proposes a comprehensive methodology that helps transit planners to concurrently optimize station locations and track alignments for an urban rail transit line. The modeling framework resolves the essential trade-off between an economically efficient system with low initial and operation cost and an effective system that provides convenient service for the public. The proposed method accounts for various geometric requirements and real-world design constraints for track alignment and stations plans. This method integrates a genetic algorithm (GA) for optimization with comprehensive evaluation of various important measures of effectiveness based on processing Geographical Information System (GIS) data. The base model designs the track alignment through a sequence of preset stations. Detailed assumptions and formulations are presented for geometric requirements, design constraints, and evaluation criteria. Three extensions of the base model are proposed. The first extension explicitly incorporates vehicle dynamics in the design of track alignments, with the objective of better balancing the initial construction cost with the operation and user costs recurring throughout the system's life cycle. In the second extension, an integrated optimization model of rail transit station locations and track alignment is formulated for situations in which the locations of major stations are not preset. The concurrent optimization model searches through additional decision variables for station locations and station types, estimate rail transit demand, and incorporates demand and station cost in the evaluation framework. The third extension considers the existing road network when selecting sections of the alignment. Special algorithms are developed to allow the optimized alignment to take advantage of links in an existing network for construction cost reduction, and to account for disturbances of roadway traffic at highway/rail crossings. Numerical results show that these extensions have significantly enhanced the applicability of the proposed optimization methodology in concurrently selecting rail transit station locations and generating track alignment

A study of the mechanics of microcantilever sensors

Microcantilever sensors are being studied as a new platform for chemical vapor detection. It has been demonstrated by many groups that they have the potential to detect a wide range of chemicals with high sensitivity. Since these sensors do not offer any intrinsic chemical selectivity, immobilized chemical interfaces coupled with pattern recognition algorithms are often employed. Selectivity based on these chemical coatings often fails due to the lack of orthogonality in the chemical interactions. However, the use of adsorption-induced signals based on physical properties can offer additional complementary information. To successfully employ these versatile sensors, a comprehensive investigation of the mechanics of microcantilevers is necessary to understand their responses. Such an investigation is presented in this work. Both dynamic and static microcantilever theory is addressed as well as nonlinear dynamics resulting from large amplitude oscillations. Experimental data is presented and compared to modeled data for verification. Finally, an application of microcantilever sensors in photothermal deflection spectroscopy (PDS) is given. The detection of explosive compounds with PDS is demonstrated

Doctor of Philosophy

dissertationThe continuous growth of wireless communication use has largely exhausted the limited spectrum available. Methods to improve spectral efficiency are in high demand and will continue to be for the foreseeable future. Several technologies have the potential to make large improvements to spectral efficiency and the total capacity of networks including massive multiple-input multiple-output (MIMO), cognitive radio, and spatial-multiplexing MIMO. Of these, spatial-multiplexing MIMO has the largest near-term potential as it has already been adopted in the WiFi, WiMAX, and LTE standards. Although transmitting independent MIMO streams is cheap and easy, with a mere linear increase in cost with streams, receiving MIMO is difficult since the optimal methods have exponentially increasing cost and power consumption. Suboptimal MIMO detectors such as K-Best have a drastically reduced complexity compared to optimal methods but still have an undesirable exponentially increasing cost with data-rate. The Markov Chain Monte Carlo (MCMC) detector has been proposed as a near-optimal method with polynomial cost, but it has a history of unusual performance issues which have hindered its adoption. In this dissertation, we introduce a revised derivation of the bitwise MCMC MIMO detector. The new approach resolves the previously reported high SNR stalling problem of MCMC without the need for hybridization with another detector method or adding heuristic temperature scaling terms. Another common problem with MCMC algorithms is an unknown convergence time making predictable fixed-length implementations problematic. When an insufficient number of iterations is used on a slowly converging example, the output LLRs can be unstable and overconfident, therefore, we develop a method to identify rare, slowly converging runs and mitigate their degrading effects on the soft-output information. This improves forward-error-correcting code performance and removes a symptomatic error floor in bit-error-rates. Next, pseudo-convergence is identified with a novel way to visualize the internal behavior of the Gibbs sampler. An effective and efficient pseudo-convergence detection and escape strategy is suggested. Finally, the new excited MCMC (X-MCMC) detector is shown to have near maximum-a-posteriori (MAP) performance even with challenging, realistic, highly-correlated channels at the maximum MIMO sizes and modulation rates supported by the 802.11ac WiFi specification, 8x8 256 QAM. Further, the new excited MCMC (X-MCMC) detector is demonstrated on an 8-antenna MIMO testbed with the 802.11ac WiFi protocol, confirming its high performance. Finally, a VLSI implementation of the X-MCMC detector is presented which retains the near-optimal performance of the floating-point algorithm while having one of the lowest complexities found in the near-optimal MIMO detector literature