Poly-bagging predictors for classification modelling for credit scoring

Credit scoring modelling comprises one of the leading formal tools for supporting the granting of credit. Its core objective consists of the generation of a score by means of which potential clients can be listed in the order of the probability of default. A critical factor is whether a credit scoring model is accurate enough in order to provide correct classification of the client as a good or bad payer. In this context the concept of bootstraping aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the fitted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper we propose a new bagging-type variant procedure, which we call poly-bagging, consisting of combining predictors over a succession of resamplings. The study is derived by credit scoring modelling. The proposed poly-bagging procedure was applied to some different artificial datasets and to a real granting of credit dataset up to three successions of resamplings. We observed better classification accuracy for the two-bagged and the three-bagged models for all considered setups. These results lead to a strong indication that the poly-bagging approach may promote improvement on the modelling performance measures, while keeping a flexible and straightforward bagging-type structure easy to implement.     

Input-output properties of the Page-Hinkley detector

We consider the stochastic input-output properties of a simple non-linear dynamical system, the so-called Page-Hinkley detector, playing a key role in change detection, and also in queuing theory. We show that for L-mixing inputs with negative expectation the output process of this system is L-mixing. The result is applied to get an upper bound for the false alarm rate. The proof is then adapted to get a similar result for the case of random i.i.d. inputs. Possible extensions and open problems are given in the discussion.     

A platform for the development of patient applications in the domain of personalized health

Personalized health (p-health) systems can contribute significantly to the sustainability of healthcare systems, though their feasibility is yet to be proven. One of the problems related to their development is the lack of well-established development tools for this domain. As the p-health paradigm is focused on patient self-management, big challenges arise around the design and implementation of patient systems. This paper presents a reference platform created for the development of these applications, and shows the advantages of its adoption in a complex project dealing with cardio-vascular diseases.     

GODDESS: A Goal-Directed Decision Structuring System

This paper describes an operational version of a computerized, domain-independent, decision support system which is based on a novel, goal-directed structure for representing decision problems. The structure allows the user to state relations among aspects, effects, conditions, and goals, in addition to actions and states which are the basic components of the traditional decision tree approach. The program interacts with the user in a stylized English-like dialogue, starting with the stated objectives and proceeding to unravel the more detailed means by which these objectives can be realized. At any point in time, the program focuses the user's attention on the issues which are most crucial to the problem at hand. The structure used is more compatible with the way people encode knowledge about problems and actions, and therefore promises to offer the following advantages: 1) judgments and beliefs issued by the user constitute a more valid representation of the user's experience; and 2) the user may be guided toward the discovery of action alternatives he otherwise would not have identified.     

The effect of ionising radiation on photosynthetic oxygenic microorganisms for survival in space flight revealed by automatic photosystem II-based biosensors

Photosynthetic microorganisms are expected to be useful to maintain an oxygenic atmosphere and to provide biomass for astronauts in the International Space Station as well as in future long-term space flights. However, fluxes of complex ionizing radiation of various intensities and energies make space an extreme environment for the microorganisms, affecting their photosynthetic efficiency. To automatically monitor the photosynthetic Photosystem II (PSII) activity of microorganisms under space conditions an optical biosensor, which utilizes chlorophyll fluorescence as biological transduction system, was built; the PSII activity was monitored by the biosensor during balloon flights at stratospheric altitudes of about 40 km. The effect of space stress on quantum yield of PSII varied among the tested species depending on the growth light conditions at which they were exposed during the flights.     

Recognition of shapes by attributed skeletal graphs

In this paper, we propose a framework to address the problem of generic 2-D shape recognition. The aim is mainly on using the potential strength of skeleton of discrete objects in computer vision and pattern recognition where features of objects are needed for classification. We propose to represent the medial axis characteristic points as an attributed skeletal graph to model the shape. The information about the object shape and its topology is totally embedded in them and this allows the comparison of different objects by graph matching algorithms. The experimental results demonstrate the correctness in detecting its characteristic points and in computing a more regular and effective representation for a perceptual indexing. The matching process, based on a revised graduated assignment algorithm, has produced encouraging results, showing the potential of the developed method in a variety of computer vision and pattern recognition domains. The results demonstrate its robustness in the presence of scale, reflection and rotation transformations and prove the ability to handle noise and occlusions.     

Typing artifacts in megamodeling

Model management is essential for coping with the complexity introduced by the increasing number and varied nature of artifacts involved in model-driven engineering-based projects. Global model management (GMM) addresses this issue by enabling the representation of artifacts, particularly transformation composition and execution, within a model called a megamodel. Type information about artifacts can be used for preventing type errors during execution. Built on our previous work, in this paper we present the core elements of a type system for GMM that improves its original typing approach and enables both typechecking and type inference on artifacts within a megamodel. This type system is able to deal with non-trivial situations such as the use of higher order transformations. We also present a prototypical implementation of such a type system.     

ADSA Foundation Scholar Award: New frontiers in calf and heifer nutrition—From conception to puberty

Dairy calf nutrition is traditionally one of the most overlooked aspects of dairy management, despite its large effect on the efficiency and profitability of dairy operations. Unfortunately, among all animals on the dairy farm, calves suffer from the highest rates of morbidity and mortality. These challenges have catalyzed calf nutrition research over the past decade to mitigate high incidences of disease and death, and improve animal health, growth, welfare, and industry sustainability. However, major knowledge gaps remain in several crucial stages of development. The purpose of this review is to summarize the key concepts of nutritional physiology and programming from conception to puberty and their subsequent effects on development of the calf, and ultimately, future performance. During fetal development, developmental plasticity is highest. At this time, maternal energy and protein consumption can influence fetal development, likely playing a critical role in calf and heifer development and, importantly, future production. After birth, the calf's first meal of colostrum is crucial for the transfer of immunoglobulin to support calf health and survival. However, colostrum also contains numerous bioactive proteins, lipids, and carbohydrates that may play key roles in calf growth and health. Extending the delivery of these bioactive compounds to the calf through a gradual transition from colostrum to milk (i.e., extended colostrum or transition milk feeding) may confer benefits in the first days and weeks of life to prepare the calf for the preweaning period. Similarly, optimal nutrition during the preweaning period is vital. Preweaning calves are highly susceptible to health challenges, and improved calf growth and health can positively influence future milk production. Throughout the world, the majority of dairy calves rely on milk replacer to supply adequate nutrition. Recent research has started to re-evaluate traditional formulations of milk replacers, which can differ significantly in composition compared with whole milk. Transitioning from a milk-based diet to solid feed is critical in the development of mature ruminants. Delaying weaning age and providing long and gradual step-down protocols have become common to avoid production and health challenges. Yet, determining how to appropriately balance the amount of energy and protein supplied in both liquid and solid feeds based on preweaning milk allowances, and further acknowledging their interactions, shows great promise in improving growth and health during weaning. After weaning and during the onset of puberty, heifers are traditionally offered high-forage diets. However, recent work suggests that an early switch to a high-forage diet will depress intake and development during the time when solid feed efficiency is greatest. It has become increasingly clear that there are great opportunities to advance our knowledge of calf nutrition; yet, a more concentrated and rigorous approach to research that encompasses the long-term consequences of nutritional regimens at each stage of life is required to ensure the sustainability and efficiency of the global dairy industry.