Software Cartography: Thematic Software Visualization with Consistent Layout

Software visualizations can provide a concise overview of a complex software system. Unfortunately, as software has no physical shape, there is no `natural' mapping of software to a two-dimensional space. As a consequence most visualizations tend to use a layout in which position and distance have no meaning, and consequently layout typically diverges from one visualization to another. We propose an approach to consistent layout for software visualization, called Software Cartography, in which the position of a software artifact reflects its vocabulary, and distance corresponds to similarity of vocabulary. We use Latent Semantic Indexing (LSI) to map software artifacts to a vector space, and then use Multidimensional Scaling (MDS) to map this vector space down to two dimensions. The resulting consistent layout allows us to develop a variety of thematic software maps that express very different aspects of software while making it easy to compare them. The approach is especially suitable for comparing views of evolving software, as the vocabulary of software artifacts tends to be stable over time. We present a prototype implementation of Software Cartography, and illustrate its use with practical examples from numerous open-source case studies.

Comparison of Roadside Crash Injury Metrics using Event Data Recorders

The occupant impact velocity (OIV) and acceleration severity index (ASI) are competing measures of crash severity used to assess occupant injury risk in full-scale crash tests involving roadside safety hardware, e.g. guardrail. Delta-V, or the maximum change in vehicle velocity, is the traditional metric of crash severity for real world crashes. This study compares the ability of the OIV, ASI, and delta-V to discriminate between serious and non-serious occupant injury in real world frontal collisions. Vehicle kinematics data from event data recorders (EDRs) were matched with detailed occupant injury information for 180 real world crashes. Cumulative probability of injury risk curves were generated using binary logistic regression for belted and unbelted data subsets. By comparing the available fit statistics and performing a separate ROC curve analysis, the more computationally intensive OIV and ASI were found to offer no significant predictive advantage over the simpler delta-V.

Distinctive Convergence in Australian Floral Colours Seen Through the Eyes of Australian Birds

We used a colour-space model of avian vision to assess whether a distinctive bird pollination syndrome exists for floral colour among Australian angiosperms. We also used a novel phylogenetically based method to assess whether such a syndrome represents a significant degree of convergent evolution. About half of the 80 species in our sample that attract nectarivorous birds had floral colours in a small, isolated region of colour space characterized by an emphasis on long-wavelength reflection. The distinctiveness of this 'red arm' region was much greater when colours were modelled for violet-sensitive (VS) avian vision than for the ultraviolet-sensitive visual system. Honeyeaters (Meliphagidae) are the dominant avian nectarivores in Australia and have VS vision. Ancestral state reconstructions suggest that 31 lineages evolved into the red arm region, whereas simulations indicate that an average of five or six lineages and a maximum of 22 are likely to have entered in the absence of selection. Thus, significant evolutionary convergence on a distinctive floral colour syndrome for bird pollination has occurred in Australia, although only a subset of bird-pollinated taxa belongs to this syndrome. The visual system of honeyeaters has been the apparent driver of this convergence.

Consistent Layout for Thematic Software Maps

Software visualizations can provide a concise overview of a complex software system. Unfortunately, since software has no physical shape, there is no “natural“ mapping of software to a two-dimensional space. As a consequence most visualizations tend to use a layout in which position and distance have no meaning, and consequently layout typical diverges from one visualization to another. We propose a consistent layout for software maps in which the position of a software artifact reflects its \emph{vocabulary}, and distance corresponds to similarity of vocabulary. We use Latent Semantic Indexing (LSI) to map software artifacts to a vector space, and then use Multidimensional Scaling (MDS) to map this vector space down to two dimensions. The resulting consistent layout allows us to develop a variety of thematic software maps that express very different aspects of software while making it easy to compare them. The approach is especially suitable for comparing views of evolving software, since the vocabulary of software artifacts tends to be stable over time.

Fourier Series by Least Square Minimization

An introduction to Fourier Series based on the minimization of the least square error between an approximate series representation and the exact function.

Updated bathymetric chart of the East Aral Sea

The Aral Sea is located in an arid region with much sand and salt deposits in the surrounding barren open land. Hence, significant displacements of sediments into the lakebed by the action of wind, water, gravity, or snow are likely. The bathymetry of the lake was last observed in the 1960s, and within the last half century, the structure of the lakebed has changed. Based on satellite observations of the temporal changes of shoreline (Landsat optical remote sensing) and water level (multi-mission satellite altimetry) over more than one decade an updated bathymetric chart for the East Basin of the Aral Sea has been generated. During this time, the geometry of the shallow East Basin experienced strong fluctuations due to the occurrence of periods of drying and strong inflow. By the year 2014 the East Basin fell dry. The dynamic behavior of the basin allowed for estimating the lake's bathymetry from a series of satellite-based information. The river mouth made its impression in the present East Aral Sea, because its shrinking led to the inflow of much sediment into the lake's interior. In addition, salt deposits along the shorelines increased the corresponding elevation, a phenomenon that is more pronounced in the reduced lakebed because of increased salinity. It must be noted that height estimates from satellite altimetry were only possible down to a minimum elevation of 27 m above sea level due to a lack of reliable altimetry data over the largely reduced water surface. In order to construct a complete bathymetric chart of the lakebed of the East Aral Sea heights below 27 m were obtained solely from Landsat optical images following the SRB (Selected Region Boundary) approach as described by Singh et al. (2015).

Is South Sulawesi a Center of Growth in Eastern Indonesia? : Japanese ODA Strategy Revisited

Japanese ODA, especially that undertaken by JICA, has targeted South Sulawesi Province as a core area of development in eastern Indonesia, with hope that the economic growth of South Sulawesi will bring about spillover effects in other regions. This paper tests the validity of the strategy using a framework of Vector Autoregressive model. The results show that South Sulawesi’s economy Granger causes other regions in eastern Indonesia, but not vice versa, implying that South Sulawesi drives the development of other regions in eastern Indonesia. Further analysis shows that the development of the agricultural sector in South Sulawesi potentially has the highest spillover effects than other sectors and that the magnitude of spillover effect from South Sulawesi on eastern Indonesia is higher than other economically important regions, such as Eastern Java and Kalimantan.

Sources of fluctuations in parallel exchange rates and policy reform in Myanmar

Myanmar maintained a multiple exchange rate system, and the parallel market exchange rate was left untamed. In the last two decades, the Myanmar kyat exchange rate of the parallel market has exhibited the sharpest fluctuations among Southeast Asian currencies in real terms. Since the move to a managed float regime in April 2012, the question arises of whether exchange rate policies will be effective in stabilizing the real exchange rate. This paper investigates the sources of fluctuations in the real effective exchange rate using Blanchard and Quah’s (1989) structural vector autoregression model. As nominal shocks can be created by exchange rate policies, a persistent impact of a nominal shock implies more room for exchange rate policies. Decomposition of the fluctuations into nominal and real shocks indicates that the impact of nominal shocks is small and quickly diminishes, implying that complementary sterilization is necessary for effective foreign exchange market interventions.

Modeling of the Division Point of Different Propagation Mechanisms in the Near-Region Within Arched Tunnels

An accurate characterization of the near-region propagation of radio waves inside tunnels is of practical importance for the design and planning of advanced communication systems. However, there has been no consensus yet on the propagation mechanism in this region. Some authors claim that the propagation mechanism follows the free space model, others intend to interpret it by the multi-mode waveguide model. This paper clarifies the situation in the near-region of arched tunnels by analytical modeling of the division point between the two propagation mechanisms. The procedure is based on the combination of the propagation theory and the three-dimensional solid geometry. Three groups of measurements are employed to verify the model in different tunnels at different frequencies. Furthermore, simplified models for the division point in five specific application situations are derived to facilitate the use of the model. The results in this paper could help to deepen the insight into the propagation mechanism within tunnel environments.

Propagation Mechanism Analysis Before the Break Point Inside Tunnels

There is no unanimous consensus yet on the propagation mechanism before the break point inside tunnels. Some deem that the propagation mechanism follows the free space model, others argue that it should be described by the multimode waveguide model. Firstly, this paper analyzes the propagation loss in two mechanisms. Then, by conjunctively using the propagation theory and the three-dimensional solid geometry, a generic analytical model for the boundary between the free space mechanism and the multi-mode waveguide mechanism inside tunnels has been presented. Three measurement campaigns validate the model in different tunnels at different frequencies. Furthermore, the condition of the validity of the free space model used in tunnel environment has been discussed in some specific situations. Finally, through mathematical derivation, the seemingly conflicting viewpoints on the free space mechanism and the multi-mode waveguide mechanism have been unified in some specific situations by the presented generic model. The results in this paper can be helpful to gain deeper insight and better understanding of the propagation mechanism inside tunnels

Computational Methods for Identification of Vibrating Structures

System identification deals with the problem of building mathematical models of dynamical systems based on observed data from the system" [1]. In the context of civil engineering, the system refers to a large scale structure such as a building, bridge, or an offshore structure, and identification mostly involves the determination of modal parameters (the natural frequencies, damping ratios, and mode shapes). This paper presents some modal identification results obtained using a state-of-the-art time domain system identification method (data-driven stochastic subspace algorithms [2]) applied to the output-only data measured in a steel arch bridge. First, a three dimensional finite element model was developed for the numerical analysis of the structure using ANSYS. Modal analysis was carried out and modal parameters were extracted in the frequency range of interest, 0-10 Hz. The results obtained from the finite element modal analysis were used to determine the location of the sensors. After that, ambient vibration tests were conducted during April 23-24, 2009. The response of the structure was measured using eight accelerometers. Two stations of three sensors were formed (triaxial stations). These sensors were held stationary for reference during the test. The two remaining sensors were placed at the different measurement points along the bridge deck, in which only vertical and transversal measurements were conducted (biaxial stations). Point estimate and interval estimate have been carried out in the state space model using these ambient vibration measurements. In the case of parametric models (like state space), the dynamic behaviour of a system is described using mathematical models. Then, mathematical relationships can be established between modal parameters and estimated point parameters (thus, it is common to use experimental modal analysis as a synonym for system identification). Stable modal parameters are found using a stabilization diagram. Furthermore, this paper proposes a method for assessing the precision of estimates of the parameters of state-space models (confidence interval). This approach employs the nonparametric bootstrap procedure [3] and is applied to subspace parameter estimation algorithm. Using bootstrap results, a plot similar to a stabilization diagram is developed. These graphics differentiate system modes from spurious noise modes for a given order system. Additionally, using the modal assurance criterion, the experimental modes obtained have been compared with those evaluated from a finite element analysis. A quite good agreement between numerical and experimental results is observed.

Joint statistical analysis of multiple measurement setups for the estimation of vibrational modes

Computing the modal parameters of large structures in Operational Modal Analysis often requires to process data from multiple non simultaneously recorded setups of sensors. These setups share some sensors in common, the so-called reference sensors that are fixed for all the measurements, while the other sensors are moved from one setup to the next. One possibility is to process the setups separately what result in different modal parameter estimates for each setup. Then the reference sensors are used to merge or glue the different parts of the mode shapes to obtain global modes, while the natural frequencies and damping ratios are usually averaged. In this paper we present a state space model that can be used to process all setups at once so the global mode shapes are obtained automatically and subsequently only a value for the natural frequency and damping ratio of each mode is computed. We also present how this model can be estimated using maximum likelihood and the Expectation Maximization algorithm. We apply this technique to real data measured at a footbridge.

Metodología de Ejecución y Explotación de los Ensayos en Vuelo de Flameo

El flameo o flutter es un fenómeno vibratorio debido a la interacción de fuerzas inerciales, elásticas y aerodinámicas. Consiste en un intercambio de energía, que se puede observar en el cambio de amortiguamientos, entre dos o más modos estructurales, denominados modos críticos, cuyas frecuencias tienden a acercarse (coalescencia de frecuencias). Los ensayos en vuelo de flameo suponen un gran riesgo debido a la posibilidad de una perdida brusca de estabilidad aeroelástica (flameo explosivo) con la posibilidad de destrucción de la aeronave. Además existen otros fenómenos asociados que pueden aparecer como el LCO (Limit Cycle Oscillation) y la interacción con los mandos de vuelo. Debido a esto, se deben llevar a cabo análisis exhaustivos, que incluyen GVT (vibraciones en tierra), antes de comenzar los ensayos en vuelo, y estos últimos deben ser ejecutados con robustos procedimientos. El objetivo de los ensayos es delimitar la frontera de estabilidad sin llegar a ella, manteniéndose siempre dentro de la envolvente estable de vuelo. Para lograrlo se necesitan métodos de predicción, siendo el “Flutter Margin”, el más utilizado. Para saber cuánta estabilidad aeroelástica tiene el avión y lo lejos que está de la frontera de estabilidad (a través de métodos de predicción) los parámetros modales, en particular la frecuencia y el amortiguamiento, son de vital importancia. El ensayo en vuelo consiste en la excitación de la estructura a diferentes condiciones de vuelo, la medición de la respuesta y su análisis para obtener los dos parámetros mencionados. Un gran esfuerzo se dedica al análisis en tiempo real de las señales como un medio de reducir el riesgo de este tipo de ensayos. Existen numerosos métodos de Análisis Modal, pero pocos capaces de analizar las señales procedentes de los ensayos de flameo, debido a sus especiales características. Un método novedoso, basado en la Descomposición por Valores Singulares (SVD) y la factorización QR, ha sido desarrollado y aplicado al análisis de señales procedentes de vuelos de flameo del F-18. El método es capaz de identificar frecuencia y amortiguamiento de los modos críticos. El algoritmo se basa en la capacidad del SVD para el análisis, modelización y predicción de series de datos con características periódicas y en su capacidad de identificar el rango de una matriz, así como en la aptitud del QR para seleccionar la mejor base vectorial entre un conjunto de vectores para representar el campo vectorial que forman. El análisis de señales de flameo simuladas y reales demuestra, bajo ciertas condiciones, la efectividad, robustez, resistencia al ruido y capacidad de automatización del método propuesto. ABSTRACT Flutter involves the interaction between inertial, elastic and aerodynamic forces. It consists on an exchange of energy, identified by change in damping, between two or more structural modes, named critical modes, whose frequencies tend to get closer to each other (frequency coalescence). Flight flutter testing involves high risk because of the possibility of an abrupt lost in aeroelastic stability (hard flutter) that may lead to aircraft destruction. Moreover associated phenomena may happen during the flight as LCO (Limit Cycle Oscillation) and coupling with flight controls. Because of that, intensive analyses, including GVT (Ground Vibration Test), have to be performed before beginning the flights test and during them consistent procedures have to be followed. The test objective is to identify the stability border, maintaining the aircraft always inside the stable domain. To achieve that flutter speed prediction methods have to be used, the most employed being the “Flutter Margin”. In order to know how much aeroelastic stability remains and how far the aircraft is from the stability border (using the prediction methods), modal parameters, in particular frequency and damping are paramount. So flight test consists in exciting the structure at various flight conditions, measuring the response and identifying in real-time these two parameters. A great deal of effort is being devoted to real-time flight data analysis as an effective way to reduce the risk. Numerous Modal Analysis algorithms are available, but very few are suitable to analyze signals coming from flutter testing due to their special features. A new method, based on Singular Value Decomposition (SVD) and QR factorization, has been developed and applied to the analysis of F-18 flutter flight-test data. The method is capable of identifying the frequency and damping of the critical aircraft modes. The algorithm relies on the capability of SVD for the analysis, modelling and prediction of data series with periodic features and also on its power to identify matrix rank as well as QR competence for selecting the best basis among a set of vectors in order to represent a given vector space of such a set. The analysis of simulated and real flutter flight test data demonstrates, under specific conditions, the effectiveness, robustness, noise-immunity and the capability for automation of the method proposed.

Modelos para el análisis dinámico y la predicción a corto plazo de los precios de la electricidad en mercados liberalizados

En esta tesis se va a describir y aplicar de forma novedosa la técnica del alisado exponencial multivariante a la predicción a corto plazo, a un día vista, de los precios horarios de la electricidad, un problema que se está estudiando intensivamente en la literatura estadística y económica reciente. Se van a demostrar ciertas propiedades interesantes del alisado exponencial multivariante que permiten reducir el número de parámetros para caracterizar la serie temporal y que al mismo tiempo permiten realizar un análisis dinámico factorial de la serie de precios horarios de la electricidad. En particular, este proceso multivariante de elevada dimensión se estimará descomponiéndolo en un número reducido de procesos univariantes independientes de alisado exponencial caracterizado cada uno por un solo parámetro de suavizado que variará entre cero (proceso de ruido blanco) y uno (paseo aleatorio). Para ello, se utilizará la formulación en el espacio de los estados para la estimación del modelo, ya que ello permite conectar esa secuencia de modelos univariantes más eficientes con el modelo multivariante. De manera novedosa, las relaciones entre los dos modelos se obtienen a partir de un simple tratamiento algebraico sin requerir la aplicación del filtro de Kalman. De este modo, se podrán analizar y poner al descubierto las razones últimas de la dinámica de precios de la electricidad. Por otra parte, la vertiente práctica de esta metodología se pondrá de manifiesto con su aplicación práctica a ciertos mercados eléctricos spot, tales como Omel, Powernext y Nord Pool. En los citados mercados se caracterizará la evolución de los precios horarios y se establecerán sus predicciones comparándolas con las de otras técnicas de predicción. ABSTRACT This thesis describes and applies the multivariate exponential smoothing technique to the day-ahead forecast of the hourly prices of electricity in a whole new way. This problem is being studied intensively in recent statistics and economics literature. It will start by demonstrating some interesting properties of the multivariate exponential smoothing that reduce drastically the number of parameters to characterize the time series and that at the same time allow a dynamic factor analysis of the hourly prices of electricity series. In particular this very complex multivariate process of dimension 24 will be estimated by decomposing a very reduced number of univariate independent of exponentially smoothing processes each characterized by a single smoothing parameter that varies between zero (white noise process) and one (random walk). To this end, the formulation is used in the state space model for the estimation, since this connects the sequence of efficient univariate models to the multivariate model. Through a novel way, relations between the two models are obtained from a simple algebraic treatment without applying the Kalman filter. Thus, we will analyze and expose the ultimate reasons for the dynamics of the electricity price. Moreover, the practical aspect of this methodology will be shown by applying this new technique to certain electricity spot markets such as Omel, Powernext and Nord Pool. In those markets the behavior of prices will be characterized, their predictions will be formulated and the results will be compared with those of other forecasting techniques.

Interpretación geométrica de redes neuronales recurrentes discretas mediante grafos completos

El objetivo del presente trabajo de investigación es explorar nuevas técnicas de implementación, basadas en grafos, para las Redes de Neuronas, con el fin de simplificar y optimizar las arquitecturas y la complejidad computacional de las mismas. Hemos centrado nuestra atención en una clase de Red de Neuronas: las Redes de Neuronas Recursivas (RNR), también conocidas como redes de Hopfield. El problema de obtener la matriz sináptica asociada con una RNR imponiendo un determinado número de vectores como puntos fijos, no está en absoluto resuelto, el número de vectores prototipo que pueden ser almacenados en la red, cuando se utiliza la ley de Hebb, es bastante limitado, la red se satura rápidamente cuando se pretende almacenar nuevos prototipos. La ley de Hebb necesita, por tanto, ser revisada. Algunas aproximaciones dirigidas a solventar dicho problema, han sido ya desarrolladas. Nosotros hemos desarrollado una nueva aproximación en la forma de implementar una RNR en orden a solucionar estos problemas. La matriz sináptica es obtenida mediante la superposición de las componentes de los vectores prototipo, sobre los vértices de un Grafo, lo cual puede ser también interpretado como una coloración de dicho grafo. Cuando el periodo de entrenamiento se termina, la matriz de adyacencia del Grafo Resultante o matriz de pesos, presenta ciertas propiedades por las cuales dichas matrices serán llamadas tetraédricas. La energía asociada a cualquier estado de la red es representado por un punto (a,b) de R2. Cada uno de los puntos de energía asociados a estados que disten lo mismo del vector cero está localizado sobre la misma línea de energía de R2. El espacio de vectores de estado puede, por tanto, clasificarse en n clases correspondientes a cada una de las n diferentes distancias que puede tener cualquier vector al vector cero. La matriz (n x n) de pesos puede reducirse a un n-vector; de esta forma, tanto el tiempo de computación como el espacio de memoria requerido par almacenar los pesos, son simplificados y optimizados. En la etapa de recuperación, es introducido un vector de parámetros R2, éste es utilizado para controlar la capacidad de la red: probaremos que lo mayor es la componente a¡, lo menor es el número de puntos fijos pertenecientes a la línea de energía R¡. Una vez que la capacidad de la red ha sido controlada mediante este parámetro, introducimos otro parámetro, definido como la desviación del vector de pesos relativos, este parámetro sirve para disminuir ostensiblemente el número de parásitos. A lo largo de todo el trabajo, hemos ido desarrollando un ejemplo, el cual nos ha servido para ir corroborando los resultados teóricos, los algoritmos están escritos en un pseudocódigo, aunque a su vez han sido implamentados utilizando el paquete Mathematica 2.2., mostrándolos en un volumen suplementario al texto.---ABSTRACT---The aim of the present research is intended to explore new specifícation techniques of Neural Networks based on Graphs to be used in the optimization and simplification of Network Architectures and Computational Complexhy. We have focused our attention in a, well known, class of Neural Networks: the Recursive Neural Networks, also known as Hopfield's Neural Networks. The general problem of constructing the synaptic matrix associated with a Recursive Neural Network imposing some vectors as fixed points is fer for completery solved, the number of prototype vectors (learning patterns) which can be stored by Hebb's law is rather limited and the memory will thus quickly reach saturation if new prototypes are continuously acquired in the course of time. Hebb's law needs thus to be revised in order to allow new prototypes to be stored at the expense of the older ones. Some approaches related with this problem has been developed. We have developed a new approach of implementing a Recursive Neural Network in order to sob/e these kind of problems, the synaptic matrix is obtained superposing the components of the prototype vectors over the vértices of a Graph which may be interpreted as a coloring of the Graph. When training is finished the adjacency matrix of the Resulting Graph or matrix of weights presents certain properties for which it may be called a tetrahedral matrix The energy associated to any possible state of the net is represented as a point (a,b) in R2. Every one of the energy points associated with state-vectors having the same Hamming distance to the zero vector are located over the same energy Une in R2. The state-vector space may be then classified in n classes according to the n different possible distances firom any of the state-vectors to the zero vector The (n x n) matrix of weights may also be reduced to a n-vector of weights, in this way the computational time and the memory space required for obtaining the weights is optimized and simplified. In the recall stage, a parameter vectora is introduced, this parameter is used for controlling the capacity of the net: it may be proved that the bigger is the r, component of J, the lower is the number of fixed points located in the r¡ energy line. Once the capacity of the net has been controlled by the ex parameter, we introduced other parameter, obtained as the relative weight vector deviation parameter, in order to reduce the number of spurious states. All along the present text, we have also developed an example, which serves as a prove for the theoretical results, the algorithms are shown in a pseudocode language in the text, these algorithm so as the graphics have been developed also using the Mathematica 2.2. mathematical package which are shown in a supplementary volume of the text.