Verificación de Sistemas Basada en Teoría de Tipos. System verification in type theory

Este proyecto se enmarca en la utlización de métodos formales (más precisamente, en la utilización de teoría de tipos) para garantizar la ausencia de errores en programas. Por un lado se plantea el diseño de nuevos algoritmos de chequeo de tipos. Para ello, se proponen nuevos algoritmos basados en la idea de normalización por evaluación que sean extensibles a otros sistemas de tipos. En el futuro próximo extenderemos resultados que hemos conseguido recientemente [16,17] para obtener: una simplificación de los trabajos realizados para sistemas sin regla eta (acá se estudiarán dos sistemas: a la Martin Löf y a la PTS), la formulación de estos chequeadores para sistemas con variables, generalizar la noción de categoría con familia utilizada para dar semántica a teoría de tipos, obtener una formulación categórica de la noción de normalización por evaluación y finalmente, aplicar estos algoritmos a sistemas con reescrituras. Para los primeros resultados esperados mencionados, nos proponemos como método adaptar las pruebas de [16,17] a los nuevos sistemas. La importancia radica en que permitirán tornar más automatizables (y por ello, más fácilmente utilizables) los asistentes de demostración basados en teoría de tipos. Por otro lado, se utilizará la teoría de tipos para certificar compiladores, intentando llevar adelante la propuesta nunca explorada de [22] de utilizar un enfoque abstracto basado en categorías funtoriales. El método consistirá en certificar el lenguaje "Peal" [29] y luego agregar sucesivamente funcionalidad hasta obtener Forsythe [23]. En este período esperamos poder agregar varias extensiones. La importancia de este proyecto radica en que sólo un compilador certificado garantiza que un programa fuente correcto se compile a un programa objeto correcto. Es por ello, crucial para todo proceso de verificación que se base en verificar código fuente. Finalmente, se abordará la formalización de sistemas con session types. Los mismos han demostrado tener fallas en sus formulaciones [30], por lo que parece conveniente su formalización. Durante la marcha de este proyecto, esperamos tener alguna formalización que dé lugar a un algoritmo de chequeo de tipos y a demostrar las propiedades usuales de los sistemas. La contribución es arrojar un poco de luz sobre estas formulaciones cuyos errores revelan que el tema no ha adquirido aún suficiente madurez o comprensión por parte de la comunidad. This project is about using type theory to garantee program correctness. It follows three different directions: 1) Finding new type-checking algorithms based on normalization by evaluation. First, we would show that recent results like [16,17] extend to other type systems like: Martin-Löf´s type theory without eta rule, PTSs, type systems with variables (in addition to systems in [16,17] which are a la de Bruijn), systems with rewrite rules. This will be done by adjusting the proofs in [16,17] so that they apply to such systems as well. We will also try to obtain a more general definition of categories with families and normalization by evaluation, formulated in categorical terms. We expect this may turn proof-assistants more automatic and useful. 2) Exploring the proposal in [22] to compiler construction for Algol-like languages using functorial categories. According to [22] such approach is suitable for verifying compiler correctness, claim which was never explored. First, the language Peal [29] will be certified in type theory and we will gradually add funtionality to it until a correct compiler for the language Forsythe [23] is obtained. 3) Formilizing systems for session types. Several proposals have shown to be faulty [30]. This means that a formalization of it may contribute to the general understanding of session types.

Instrumental leadership: Measurement and extension of transformational-transactional leadership theory.

Leaders must scan the internal and external environment, chart strategic and task objectives, and provide performance feedback. These instrumental leadership (IL) functions go beyond the motivational and quid-pro quo leader behaviors that comprise the full-range-transformational, transactional, and laissez faire-leadership model. In four studies we examined the construct validity of IL. We found evidence for a four-factor IL model that was highly prototypical of good leadership. IL predicted top-level leader emergence controlling for the full-range factors, initiating structure, and consideration. It also explained unique variance in outcomes beyond the full-range factors; the effects of transformational leadership were vastly overstated when IL was omitted from the model. We discuss the importance of a "fuller full-range" leadership theory for theory and practice. We also showcase our methodological contributions regarding corrections for common method variance (i.e., endogeneity) bias using two-stage least squares (2SLS) regression and Monte Carlo split-sample designs.

Endoleak and in-stent thrombus detection with CT angiography in a thoracic aortic aneurysm phantom at different tube energies using filtered back projection and iterative algorithms.

PURPOSE: To determine the lower limit of dose reduction with hybrid and fully iterative reconstruction algorithms in detection of endoleaks and in-stent thrombus of thoracic aorta with computed tomographic (CT) angiography by applying protocols with different tube energies and automated tube current modulation. MATERIALS AND METHODS: The calcification insert of an anthropomorphic cardiac phantom was replaced with an aortic aneurysm model containing a stent, simulated endoleaks, and an intraluminal thrombus. CT was performed at tube energies of 120, 100, and 80 kVp with incrementally increasing noise indexes (NIs) of 16, 25, 34, 43, 52, 61, and 70 and a 2.5-mm section thickness. NI directly controls radiation exposure; a higher NI allows for greater image noise and decreases radiation. Images were reconstructed with filtered back projection (FBP) and hybrid and fully iterative algorithms. Five radiologists independently analyzed lesion conspicuity to assess sensitivity and specificity. Mean attenuation (in Hounsfield units) and standard deviation were measured in the aorta to calculate signal-to-noise ratio (SNR). Attenuation and SNR of different protocols and algorithms were analyzed with analysis of variance or Welch test depending on data distribution. RESULTS: Both sensitivity and specificity were 100% for simulated lesions on images with 2.5-mm section thickness and an NI of 25 (3.45 mGy), 34 (1.83 mGy), or 43 (1.16 mGy) at 120 kVp; an NI of 34 (1.98 mGy), 43 (1.23 mGy), or 61 (0.61 mGy) at 100 kVp; and an NI of 43 (1.46 mGy) or 70 (0.54 mGy) at 80 kVp. SNR values showed similar results. With the fully iterative algorithm, mean attenuation of the aorta decreased significantly in reduced-dose protocols in comparison with control protocols at 100 kVp (311 HU at 16 NI vs 290 HU at 70 NI, P ≤ .0011) and 80 kVp (400 HU at 16 NI vs 369 HU at 70 NI, P ≤ .0007). CONCLUSION: Endoleaks and in-stent thrombus of thoracic aorta were detectable to 1.46 mGy (80 kVp) with FBP, 1.23 mGy (100 kVp) with the hybrid algorithm, and 0.54 mGy (80 kVp) with the fully iterative algorithm.

Social ventures : the development of the theory of sustainable contributive advantage and initial empirical tests

This thesis attempts to fill gaps in both a theoretical basis and an operational and strategic understanding in the areas of social ventures, social entrepreneurship and nonprofit business models. This study also attempts to bridge the gap in strategic and economic theory between social and commercial ventures. More specifically, this thesis explores sustainable competitive advantage from a resource-based theory perspective and explores how it may be applied to the nonmarket situation of nonprofit organizations and social ventures. It is proposed that a social value-orientation of sustainable competitive advantage, called sustainable contributive advantage, provides a more realistic depiction of what is necessary in order for a social venture to perform better than its competitors over time. In addition to providing this realistic depiction, this research provides a substantial theoretical contribution in the area of economics, social ventures, and strategy research, specifically in regards to resource-based theory. The proposed model for sustainable contributive advantage uses resource-based theory and competitive advantage in order to be applicable to social ventures. This model proposes an explanation of a social venture’s ability to demonstrate consistently superior performance. In order to determine whether sustainable competitive advantage is in fact, appropriate to apply to both social and economic environments, quantitative analyses are conducted on a large sample of nonprofit organizations in a single industry and then compared to similar quantitative analyses conducted on commercial ventures. In comparing the trends and strategies between the two types of entities from a quantitative perspective, propositions are developed regarding a social venture’s resource utilization strategies and their possible impact on performance. Evidence is found to support the necessity of adjusting existing models in resource-based theory in order to apply them to social ventures. Additionally supported is the proposed theory of sustainable contributive advantage. The thesis concludes with recommendations for practitioners, researchers and policy makers as well as suggestions for future research paths.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Advances in scaling deep learning algorithms

Les algorithmes d'apprentissage profond forment un nouvel ensemble de méthodes puissantes pour l'apprentissage automatique. L'idée est de combiner des couches de facteurs latents en hierarchies. Cela requiert souvent un coût computationel plus elevé et augmente aussi le nombre de paramètres du modèle. Ainsi, l'utilisation de ces méthodes sur des problèmes à plus grande échelle demande de réduire leur coût et aussi d'améliorer leur régularisation et leur optimization. Cette thèse adresse cette question sur ces trois perspectives. Nous étudions tout d'abord le problème de réduire le coût de certains algorithmes profonds. Nous proposons deux méthodes pour entrainer des machines de Boltzmann restreintes et des auto-encodeurs débruitants sur des distributions sparses à haute dimension. Ceci est important pour l'application de ces algorithmes pour le traitement de langues naturelles. Ces deux méthodes (Dauphin et al., 2011; Dauphin and Bengio, 2013) utilisent l'échantillonage par importance pour échantilloner l'objectif de ces modèles. Nous observons que cela réduit significativement le temps d'entrainement. L'accéleration atteint 2 ordres de magnitude sur plusieurs bancs d'essai. Deuxièmement, nous introduisont un puissant régularisateur pour les méthodes profondes. Les résultats expérimentaux démontrent qu'un bon régularisateur est crucial pour obtenir de bonnes performances avec des gros réseaux (Hinton et al., 2012). Dans Rifai et al. (2011), nous proposons un nouveau régularisateur qui combine l'apprentissage non-supervisé et la propagation de tangente (Simard et al., 1992). Cette méthode exploite des principes géometriques et permit au moment de la publication d'atteindre des résultats à l'état de l'art. Finalement, nous considérons le problème d'optimiser des surfaces non-convexes à haute dimensionalité comme celle des réseaux de neurones. Tradionellement, l'abondance de minimum locaux était considéré comme la principale difficulté dans ces problèmes. Dans Dauphin et al. (2014a) nous argumentons à partir de résultats en statistique physique, de la théorie des matrices aléatoires, de la théorie des réseaux de neurones et à partir de résultats expérimentaux qu'une difficulté plus profonde provient de la prolifération de points-selle. Dans ce papier nous proposons aussi une nouvelle méthode pour l'optimisation non-convexe.

Photoionization of Kr near the 4s threshold: I. Experiment and LS coupling theory

Absolute cross sections for the transitions of the Kr atom into the 4s^1 and 4p^4nl states of the Kr^+ ion were measured in the 4s-electron threshold region by photon-induced fluorescence spectroscopy (PIFS). The cross sections for the transitions of the Kr atom into the 4s^1 and 4p^4nl states were also calculated, as well as the 4p^4nln'l' doubly excited states, in the frame of LS-coupling many-body technique. The cross sections of the doubly-excited atomic states were used to illustrate the pronounced contributions of the latter to the photoionization process, evident from the measurements. The comparison of theory and experiment led to conclusions about the origin of the main features observed in the experiment.

Entanglement analysis of atomic processes and quantum registers

During recent years, quantum information processing and the study of N−qubit quantum systems have attracted a lot of interest, both in theory and experiment. Apart from the promise of performing efficient quantum information protocols, such as quantum key distribution, teleportation or quantum computation, however, these investigations also revealed a great deal of difficulties which still need to be resolved in practise. Quantum information protocols rely on the application of unitary and non–unitary quantum operations that act on a given set of quantum mechanical two-state systems (qubits) to form (entangled) states, in which the information is encoded. The overall system of qubits is often referred to as a quantum register. Today the entanglement in a quantum register is known as the key resource for many protocols of quantum computation and quantum information theory. However, despite the successful demonstration of several protocols, such as teleportation or quantum key distribution, there are still many open questions of how entanglement affects the efficiency of quantum algorithms or how it can be protected against noisy environments. To facilitate the simulation of such N−qubit quantum systems and the analysis of their entanglement properties, we have developed the Feynman program. The program package provides all necessary tools in order to define and to deal with quantum registers, quantum gates and quantum operations. Using an interactive and easily extendible design within the framework of the computer algebra system Maple, the Feynman program is a powerful toolbox not only for teaching the basic and more advanced concepts of quantum information but also for studying their physical realization in the future. To this end, the Feynman program implements a selection of algebraic separability criteria for bipartite and multipartite mixed states as well as the most frequently used entanglement measures from the literature. Additionally, the program supports the work with quantum operations and their associated (Jamiolkowski) dual states. Based on the implementation of several popular decoherence models, we provide tools especially for the quantitative analysis of quantum operations. As an application of the developed tools we further present two case studies in which the entanglement of two atomic processes is investigated. In particular, we have studied the change of the electron-ion spin entanglement in atomic photoionization and the photon-photon polarization entanglement in the two-photon decay of hydrogen. The results show that both processes are, in principle, suitable for the creation and control of entanglement. Apart from process-specific parameters like initial atom polarization, it is mainly the process geometry which offers a simple and effective instrument to adjust the final state entanglement. Finally, for the case of the two-photon decay of hydrogenlike systems, we study the difference between nonlocal quantum correlations, as given by the violation of the Bell inequality and the concurrence as a true entanglement measure.

Verification and FPGA circuits of a block-2 fast path-based predictor

This paper formally derives a new path-based neural branch prediction algorithm (FPP) into blocks of size two for a lower hardware solution while maintaining similar input-output characteristic to the algorithm. The blocked solution, here referred to as B2P algorithm, is obtained using graph theory and retiming methods. Verification approaches were exercised to show that prediction performances obtained from the FPP and B2P algorithms differ within one mis-prediction per thousand instructions using a known framework for branch prediction evaluation. For a chosen FPGA device, circuits generated from the B2P algorithm showed average area savings of over 25% against circuits for the FPP algorithm with similar time performances thus making the proposed blocked predictor superior from a practical viewpoint.

Infrared absorption spectra, radiative efficiencies, and global warming potentials of perfluorocarbons: Comparison between experiment and theory

Experimentally and theoretically determined infrared spectra are reported for a series of straight-chain perfluorocarbons: C2F6, C3F8, C4F10, C5F12, C6F14, and C8F18. Theoretical spectra were determined using both density functional (DFT) and ab initio methods. Radiative efficiencies (REs) were determined using the method of Pinnock et al. (1995) and combined with atmospheric lifetimes from the literature to determine global warming potentials (GWPs). Theoretically determined absorption cross sections were within 10% of experimentally determined values. Despite being much less computationally expensive, DFT calculations were generally found to perform better than ab initio methods. There is a strong wavenumber dependence of radiative forcing in the region of the fundamental C-F vibration, and small differences in wavelength between band positions determined by theory and experiment have a significant impact on the REs. We apply an empirical correction to the theoretical spectra and then test this correction on a number of branched chain and cyclic perfluoroalkanes. We then compute absorption cross sections, REs, and GWPs for an additional set of perfluoroalkenes.

Neurofuzzy design and model construction of nonlinear dynamical processes from data

A common problem in many data based modelling algorithms such as associative memory networks is the problem of the curse of dimensionality. In this paper, a new two-stage neurofuzzy system design and construction algorithm (NeuDeC) for nonlinear dynamical processes is introduced to effectively tackle this problem. A new simple preprocessing method is initially derived and applied to reduce the rule base, followed by a fine model detection process based on the reduced rule set by using forward orthogonal least squares model structure detection. In both stages, new A-optimality experimental design-based criteria we used. In the preprocessing stage, a lower bound of the A-optimality design criterion is derived and applied as a subset selection metric, but in the later stage, the A-optimality design criterion is incorporated into a new composite cost function that minimises model prediction error as well as penalises the model parameter variance. The utilisation of NeuDeC leads to unbiased model parameters with low parameter variance and the additional benefit of a parsimonious model structure. Numerical examples are included to demonstrate the effectiveness of this new modelling approach for high dimensional inputs.

Development and application of a novel algorithm for steady-state optimising control using dynamic information

A novel optimising controller is designed that leads a slow process from a sub-optimal operational condition to the steady-state optimum in a continuous way based on dynamic information. Using standard results from optimisation theory and discrete optimal control, the solution of a steady-state optimisation problem is achieved by solving a receding-horizon optimal control problem which uses derivative and state information from the plant via a shadow model and a state-space identifier. The paper analyzes the steady-state optimality of the procedure, develops algorithms with and without control rate constraints and applies the procedure to a high fidelity simulation study of a distillation column optimisation.

Curriculum theory, curriculum policy and the problem of ill-disciplined thinking

This paper examines the implications of policy fracture and arms length governance within the decision making processes currently shaping curriculum design within the English education system. In particular it argues that an unresolved ‘ideological fracture’ at government level has been passed down to school leaders whose response to the dilemma is distorted by the target-driven agenda of arms length agencies. Drawing upon the findings of a large scale on-line survey of history teaching in English secondary schools, this paper illustrates the problems that occur when policy making is divorced from curriculum theory, and in particular from any consideration of the nature of knowledge. Drawing on the social realist theory of knowledge elaborated by Young (2008), we argue that the rapid spread of alternative curricular arrangements, implemented in the absence of an understanding of curriculum theory, undermines the value of disciplined thinking to the detriment of many young people, particularly those in areas of social and economic deprivation.