Agent‐oriented activity recognition in the event calculus: An application for diabetic patients

We present a knowledge representation framework on the basis of the Event Calculus that allows an agent to recognize complex activities from low‐level observations received by multiple sensors, reason about the life cycle of such activities, and take action to support their successful completion. Activities are multivalue fluents that change according to events that occur in the environment. The parameters of an activity consist of a unique label, a set of participants involved in the performing of the activity, and a unique goal associated with the activity revealing the activity's desired outcome. Our contribution is the identification of an activity life cycle describing how activities can be started, interrupted, suspended, resumed, or completed over time, as well as how these can be represented. The framework also specifies activity goals, their associated life cycle, and their relation with the activity life cycle. We provide the complete implementation of the framework, which includes an activity generator that automatically creates synthetic sensor data in the form of event streams that represent the everyday lifestyle of a type 1 diabetic patient. Moreover, we test the framework by generating very large activity streams that we use to evaluate the performance of the recognition capability and study its relative merits.     

Organizational determinants of IT adoption in the pharmaceutical distribution sector

The aim of this paper is to propose new organizational factors that might explain the differences in the extent and the speed of IT adoption. With this in mind, we carried out an analysis of 16 cases in the pharmaceutical distribution sector in Spain. The results indicate that there are certain intangible assets that favour the introduction and development of IT. Among these are a frank and fluid communication between departments and members of the organization, low levels of conflict, the explicit support of top management towards IT adoption and learning and creative skills of IT-staff. In addition to these factors, we found others that we propose as catalysts of IT adoption. Among these we might mention the special relationship between the member-clients and the company in the case of cooperative firms.     

A simple empirical method for estimating surface water vapour pressure using MODIS near-infrared channels: applications to northern Spain's Asturias region

In this article, we present a simple methodology for obtaining algorithms to estimate surface water vapour pressure (e ₀) over cloud-free land areas using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The algorithm obtained in this case is adapted to the particular climatic characteristics of the Asturias region, but the methodology can easily be extrapolated and used to obtain algorithms for other regions around the world. The proposed method estimates e ₀ from a simple linear combination of the radiances of the MODIS near-infrared (NIR) channels more commonly applied to total precipitable water (W) estimations. Comparison between the e ₀ data measured at the ground-based meteorological stations in Asturias (daily data from 2004) versus the values predicted using the proposed algorithm gives R ² = 0.76 and residual standard error (RSE) = 2.07 hPa (16%). The algorithm was tested using the data from 2008 obtained in Asturias and in two sites outside of Asturias with similar latitudes and radiosonde observations (La Coruña and Santander). The resulting validation demonstrates that the algorithm gives good results in Asturias (root-mean-square deviation (RMSD) = 2.50 hPa (19%) and bias = 1.26 hPa, with R ² = 0.65) and when La Coruña is included (R ² = 0.61), but that its validity is decreased when Santander is also included (R ² = 0.56).

The possibility of obtaining e ₀ from three global MODIS algorithms for W retrieval was also tested and compared to our algorithm. The results show that our algorithm gives better results than the International MODIS/Atmospheric InfraRed Sounder Processing Package (IMAPP) Water Vapour Near-Infrared (WVNIR) product and the Sobrino algorithm. The MODIS Total Precipitable Water (MOD05) product is worse than that obtained with our algorithm in Asturias (R ² = 0.61 vs. R ² = 0.65), but the two values are similar if the stations in La Coruña (R ² = 0.60) and Santander (R ² = 0.56) are included in the comparison. The dominant advantage of the novel algorithm proposed in this study is that it is simpler and can be produced quickly in real time.     

Input-output stability of systems with backlash

The objective of this work is to study the stability of systems with backlash, from an input-output point of view. In the first part, an L_∞ analysis is addressed. This analysis provides not only conditions for boundedness of the loop signals, but also results on existence of solutions, based on Schauder fixed point theorem. In the second part, the system is studied using an L₂ or conic sector approach. The backlash graph is confined into certain conic sector, which is shown to be optimum or maximal. The conic inequality induces frequencial conditions on the linear part, which are further relaxed introducing dynamic multipliers. In the third part, both L_∞ and L₂ techniques are combined reaching a final criterion which results in a Popov-like stability condition.     

Transmission of population-coded information

As neural activity is transmitted through the nervous system, neuronal noise degrades the encoded information and limits performance. It is therefore important to know how information loss can be prevented. We study this question in the context of neural population codes. Using Fisher information, we show how information loss in a layered network depends on the connectivity between the layers. We introduce an algorithm, reminiscent of the water filling algorithm for Shannon information that minimizes the loss. The optimal connection profile has a center-surround structure with a spatial extent closely matching the neurons' tuning curves. In addition, we show how the optimal connectivity depends on the correlation structure of the trial-to-trial variability in the neuronal responses. Our results explain how optimal communication of population codes requires the center-surround architectures found in the nervous system and provide explicit predictions on the connectivity parameters.     

Semi-formal transformation of secure business processes into analysis class and use case models: An MDA approach

ContextModel-Driven Development (MDD) is an alternative approach for information systems development. The basic underlying concept of this approach is the definition of abstract models that can be transformed to obtain models near implementation. One fairly widespread proposal in this sphere is that of Model Driven Architecture (MDA). Business process models are abstract models which additionally contain key information about the tasks that are being carried out to achieve the company’s goals, and two notations currently exist for modelling business processes: the Unified Modelling Language (UML), through activity diagrams, and the Business Process Modelling Notation (BPMN).ObjectiveOur research is particularly focused on security requirements, in such a way that security is modelled along with the other aspects that are included in a business process. To this end, in earlier works we have defined a metamodel called secure business process (SBP), which may assist in the process of developing software as a source of highly valuable requirements (including very abstract security requirements), which are transformed into models with a lower abstraction level, such as analysis class diagrams and use case diagrams through the approach presented in this paper.MethodWe have defined all the transformation rules necessary to obtain analysis class diagrams and use case diagrams from SBP, and refined them through the characteristic iterative process of the action-research method.ResultsWe have obtained a set of rules and a checklist that make it possible to automatically obtain a set of UML analysis classes and use cases, starting from SBP models. Our approach has additionally been applied in a real environment in the area of the payment of electrical energy consumption.ConclusionsThe application of our proposal shows that our semi-automatic process can be used to obtain a set of useful artifacts for software development processes.     

Crossover and mutation operators for grammar-guided genetic programming

This paper proposes a new grammar-guided genetic programming (GGGP) system by introducing two original genetic operators: crossover and mutation, which most influence the evolution process. The first, the so-called grammar-based crossover operator, strikes a good balance between search space exploration and exploitation capabilities and, therefore, enhances GGGP system performance. And the second is a grammar-based mutation operator, based on the crossover, which has been designed to generate individuals that match the syntactical constraints of the context-free grammar that defines the programs to be handled. The use of these operators together in the same GGGP system assures a higher convergence speed and less likelihood of getting trapped in local optima than other related approaches. These features are shown throughout the comparison of the results achieved by the proposed system with other important crossover and mutation methods in two experiments: a laboratory problem and the real-world task of breast cancer prognosis.     

A Meta-analysis on Classification Model Performance in Real-World Datasets: An Exploratory View

The No Free Lunch (NFL) Theorem imposes a theoretical restriction on optimization algorithms and their equal average performance on different problems, under some particular assumptions. Nevertheless, when brought into practice, a perceived “ranking” on the performance is usually perceived by engineers developing machine learning applications. Questions that naturally arise are what kinds of biases the real world has and in which ways can we take advantage from them. Using exploratory data analysis (EDA) on classification examples, we gather insight on some traits that set apart algorithms, datasets and evaluation measures and to what extent the NFL theorem, a theoretical result, applies under typical real-world constraints.