The benefits of tree-based models for stock selection

The identification of the primary drivers of stock returns has been of great interest to both financial practitioners and academics alike for many decades. Influenced by classical financial theories such as the CAPM (Sharp, 1964; Lintner, 1965) and APT (Ross, 1976), a linear relationship is conventionally assumed between company characteristics as derived from their financial accounts and forward returns. Whilst this assumption may be a fair approximation to the underlying structural relationship, it is often adopted for the purpose of convenience. It is actually quite rare that the assumptions of distributional normality and a linear relationship are explicitly assessed in advance even though this information would help to inform the appropriate choice of modelling technique. Non-linear models have nevertheless been applied successfully to the task of stock selection in the past (Sorensen et al, 2000). However, their take-up by the investment community has been limited despite the fact that researchers in other fields have found them to be a useful way to express knowledge and aid decision-making...

Comparison and modification of car following models toward a more accurate microscopic simulation parameters reproduction

Traffic safety studies demand more than what current micro-simulation models can provide as they presume that all drivers of motor vehicles exhibit safe behaviours. Several car-following models are used in various micro-simulation models. This research compares the mainstream car following models’ capabilities of emulating precise driver behaviour parameters such as headways and Time to Collisions. The comparison firstly illustrates which model is more robust in the metric reproduction. Secondly, the study conducted a series of sensitivity tests to further explore the behaviour of each model. Based on the outcome of these two steps exploration of the models, a modified structure and parameters adjustment for each car-following model is proposed to simulate more realistic vehicle movements, particularly headways and Time to Collision, below a certain critical threshold. NGSIM vehicle trajectory data is used to evaluate the modified models performance to assess critical safety events within traffic flow. The simulation tests outcomes indicate that the proposed modified models produce better frequency of critical Time to Collision than the generic models, while the improvement on the headway is not significant. The outcome of this paper facilitates traffic safety assessment using microscopic simulation.

A visual language for the collaborative visualization of integrated conceptual models in product development scenarios

In various industrial and scientific fields, conceptual models are derived from real world problem spaces to understand and communicate containing entities and coherencies. Abstracted models mirror the common understanding and information demand of engineers, who apply conceptual models for performing their daily tasks. However, most standardized models in Process Management, Product Lifecycle Management and Enterprise Resource Planning lack of a scientific foundation for their notation. In collaboration scenarios with stakeholders from several disciplines, tailored conceptual models complicate communication processes, as a common understanding is not shared or implemented in specific models. To support direct communication between experts from several disciplines, a visual language is developed which allows a common visualization of discipline-specific conceptual models. For visual discrimination and to overcome visual complexity issues, conceptual models are arranged in a three-dimensional space. The visual language introduced here follows and extends established principles of Visual Language science.

Impact fees and new housing cost: A comparative analysis of the empirical models

Developers and policy makers are consistently at odds over the debate as to whether impact fees increase house prices. This debate continues despite the extensive body of theoretical and empirical international literature that discusses the passing on to home buyers of impact fees, and the corresponding increase to housing prices. In attempting to quantify this impact, over a dozen empirical studies have been carried out in the US and Canada since the 1980’s. However the methodologies used vary greatly, as do the results. Despite similar infrastructure funding policies in numerous developed countries, no such empirical works exist outside of the US/Canada. The purpose of this research is to analyse the existing econometric models in order to identify, compare and contrast the theoretical bases, methodologies, key assumptions and findings of each. This research will assist in identifying if further model development is required and/or whether any of these models have external validity and are readily transferable outside of the US. The findings conclude that there is very little explicit rationale behind the various model selections and that significant model deficiencies appear still to exist.

Influence of Rainfall and Catchment Characteristics on Urban Stormwater Quality

The accuracy and reliability of urban stormwater quality modelling outcomes are important for stormwater management decision making. The commonly adopted approach where only a limited number of factors are used to predict urban stormwater quality may not adequately represent the complexity of the quality response to a rainfall event or site-to-site differences to support efficient treatment design. This paper discusses an investigation into the influence of rainfall and catchment characteristics on urban stormwater quality in order to investigate the potential areas for errors in current stormwater quality modelling practices. It was found that the influence of rainfall characteristics on pollutant wash-off is step-wise based on specific thresholds. This means that a modelling approach where the wash-off process is predicted as a continuous function of rainfall intensity and duration is not appropriate. Additionally, other than conventional catchment characteristics, namely, land use and impervious surface fraction, other catchment characteristics such as impervious area layout, urban form and site specific characteristics have an important influence on both, pollutant build-up and wash-off processes. Finally, the use of solids as a surrogate to estimate other pollutant species was found to be inappropriate. Individually considering build-up and wash-off processes for each pollutant species should be the preferred option.

Maximal structuring of acyclic process models

This article addresses the transformation of a process model with an arbitrary topology into an equivalent structured process model. In particular, this article studies the subclass of process models that have no equivalent well-structured representation but which, nevertheless, can be partially structured into their maximally-structured representation. The transformations are performed under a behavioral equivalence notion that preserves the observed concurrency of tasks in equivalent process models. The article gives a full characterization of the subclass of acyclic process models that have no equivalent well-structured representation, but do have an equivalent maximally-structured one, as well as proposes a complete structuring method. Together with our previous results, this article completes the solution of the process model structuring problem for the class of acyclic process models.

Slice, mine and dice : complexity-aware automated discovery of business process models

Automated process discovery techniques aim at extracting models from information system logs in order to shed light into the business processes supported by these systems. Existing techniques in this space are effective when applied to relatively small or regular logs, but otherwise generate large and spaghetti-like models. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. The result is a collection of process models -- each one representing a variant of the business process -- as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically by means of subprocess extraction. The proposed technique allows users to set a desired bound for the complexity of the produced models. Experiments on real-life logs show that the technique produces collections of models that are up to 64% smaller than those extracted under the same complexity bounds by applying existing trace clustering techniques.

Online calibration of stereo rigs for long-term autonomy

Stereo-based visual odometry algorithms are heavily dependent on an accurate calibration of the rigidly fixed stereo pair. Even small shifts in the rigid transform between the cameras can impact on feature matching and 3D scene triangulation, adversely affecting pose estimates and applications dependent on long-term autonomy. In many field-based scenarios where vibration, knocks and pressure change affect a robotic vehicle, maintaining an accurate stereo calibration cannot be guaranteed over long periods. This paper presents a novel method of recalibrating overlapping stereo camera rigs from online visual data while simultaneously providing an up-to-date and up-to-scale pose estimate. The proposed technique implements a novel form of partitioned bundle adjustment that explicitly includes the homogeneous transform between a stereo camera pair to generate an optimal calibration. Pose estimates are computed in parallel to the calibration, providing online recalibration which seamlessly integrates into a stereo visual odometry framework. We present results demonstrating accurate performance of the algorithm on both simulated scenarios and real data gathered from a wide-baseline stereo pair on a ground vehicle traversing urban roads.

Calibration of the electron volt spectrometer, a deep inelastic neutron scattering spectrometer at the ISIS pulsed neutron spallation source

The electron Volt Spectrometer (eVS) is an inverse geometry filter difference spectrometer that has been optimised to measure the single atom properties of condensed matter systems using a technique known as Neutron Compton Scattering (NCS) or Deep Inelastic Neutron Scattering (DINS). The spectrometer utilises the high flux of epithermal neutrons that are produced by the ISIS neutron spallation source enabling the direct measurement of atomic momentum distributions and ground state kinetic energies. In this paper the procedure that is used to calibrate the spectrometer is described. This includes details of the method used to determine detector positions and neutron flight path lengths as well as the determination of the instrument resolution. Examples of measurements on 3 different samples are shown, ZrH2, 4He and Sn which show the self-consistency of the calibration procedure.

Some extensions to representation and encoding of structure in models of distributional semantics

This thesis makes several contributions towards improved methods for encoding structure in computational models of word meaning. New methods are proposed and evaluated which address the requirement of being able to easily encode linguistic structural features within a computational representation while retaining the ability to scale to large volumes of textual data. Various methods are implemented and evaluated on a range of evaluation tasks to demonstrate the effectiveness of the proposed methods.

Calibration of the electron volt spectrometer, a deep inelastic neutron scattering spectrometer at the ISIS pulsed neutron spallation source

The electron Volt Spectrometer (eVS) is an inverse geometry filter difference spectrometer that has been optimised to measure the single atom properties of condensed matter systems using a technique known as Neutron Compton Scattering (NCS) or Deep Inelastic Neutron Scattering (DINS). The spectrometer utilises the high flux of epithermal neutrons that are produced by the ISIS neutron spallation source enabling the direct measurement of atomic momentum distributions and ground state kinetic energies. In this paper the procedure that is used to calibrate the spectrometer is described. This includes details of the method used to determine detector positions and neutron flight path lengths as well as the determination of the instrument resolution. Examples of measurements on 3 different samples are shown, ZrH2, 4He and Sn which show the self-consistency of the calibration procedure.

A critical analysis of crisis escalation models : understanding stages and severity in infrastructure disturbance

A range of authors from the risk management, crisis management, and crisis communications literature have proposed different models as a means of understanding components of crisis. A generic component of these sources has focused on preparedness practices before disturbance events and response practices during events. This paper provides a critical analysis of three key explanatory models of how crises escalate highlighting the strengths and limitations of each approach. The paper introduces an optimised conceptual model utilising components from the previous work under the four phases of pre-event, response, recovery, and post-event. Within these four phases, a ten step process is introduced that can enhance understanding of the progression of distinct stages of disturbance for different types of events. This crisis evolution framework is examined as a means to provide clarity and applicability to a range of infrastructure failure contexts and provide a path for further empirical investigation in this area.

Error modeling and calibration of exteroceptive sensors for accurate mapping applications

Reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. In field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. This is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. The whole system is as reliable as the weakest link in this chain. In this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as LIDAR or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. The coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. This allows the mapping accuracy to be calculated at run time. A generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. This allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. The mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. The techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. Consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. © 2009 Wiley Periodicals, Inc.

Ad hoc radiometric calibration of a thermal-infrared camera

Many applications can benefit from the accurate surface temperature estimates that can be made using a passive thermal-infrared camera. However, the process of radiometric calibration which enables this can be both expensive and time consuming. An ad hoc approach for performing radiometric calibration is proposed which does not require specialized equipment and can be completed in a fraction of the time of the conventional method. The proposed approach utilizes the mechanical properties of the camera to estimate scene temperatures automatically, and uses these target temperatures to model the effect of sensor temperature on the digital output. A comparison with a conventional approach using a blackbody radiation source shows that the accuracy of the method is sufficient for many tasks requiring temperature estimation. Furthermore, a novel visualization method is proposed for displaying the radiometrically calibrated images to human operators. The representation employs an intuitive coloring scheme and allows the viewer to perceive a large variety of temperatures accurately.