oDect: an RFID‐based object detection API to support applications development on mobile devices

The RFID technology is becoming ever more popular in the development of ubiquitous computing applications. A full exploitation of the RFID potential requires the study and implementation of human–computer interaction (HCI) modalities to be able to support wide usability by the target audience. This implies the need for programming methodologies specifically dedicated to support the easy and efficient prototyping of applications to have feedback from early tests with users. On the basis of our field‐working experience, we have designed oDect, a high‐level language and platform‐independent application programming interface (API), ad hoc designed to meet the needs of typical applications for mobile devices (smart phones and PDAs). oDect aims at allowing application developers to create their prototypes focusing on the needs of the final users, without having to care about the low‐level software that interacts with the RFID hardware. Further, in an end‐user developing (EUD) approach, oDect provides specific support for the application end‐user herself to cope with typical problems of RFID applications in detecting objects. We describe in detail the features of the API and discuss the findings of a test with four programmers, where we analyse and evaluate the use of the API in four sample applications. We also present results of an end‐user test, which investigated strengths and weaknesses of the territorial agenda (TA) concept. The TA is an RFID‐based citizen guide that aids—through time‐ and location‐based reminders—users in their daily activities in a city. The TA directly exploits EUD features of oDect, in particular concerning the possibility of linking detected objects with custom actions. Copyright © 2008 John Wiley & Sons, Ltd.     

Boosting text segmentation via progressive classification

A novel approach for reconciling tuples stored as free text into an existing attribute schema is proposed. The basic idea is to subject the available text to progressive classification, i.e., a multi-stage classification scheme where, at each intermediate stage, a classifier is learnt that analyzes the textual fragments not reconciled at the end of the previous steps. Classification is accomplished by an ad hoc exploitation of traditional association mining algorithms, and is supported by a data transformation scheme which takes advantage of domain-specific dictionaries/ontologies. A key feature is the capability of progressively enriching the available ontology with the results of the previous stages of classification, thus significantly improving the overall classification accuracy. An extensive experimental evaluation shows the effectiveness of our approach.     

Artificial institutions: a model of institutional reality for open multiagent systems

Software agents’ ability to interact within different open systems, designed by different groups, presupposes an agreement on an unambiguous definition of a set of concepts, used to describe the context of the interaction and the communication language the agents can use. Agents’ interactions ought to allow for reliable expectations on the possible evolution of the system; however, in open systems interacting agents may not conform to predefined specifications. A possible solution is to define interaction environments including a normative component, with suitable rules to regulate the behaviour of agents. To tackle this problem we propose an application-independent metamodel of artificial institutions that can be used to define open multiagent systems. In our view an artificial institution is made up by an ontology that models the social context of the interaction, a set of authorizations to act on the institutional context, a set of linguistic conventions for the performance of institutional actions and a system of norms that are necessary to constrain the agents’ actions.     

A multi-scale template method for shape detection with bio-medical applications

In this paper we present a novel methodology based on non-parametric deformable prototype templates for reconstructing the outline of a shape from a degraded image. Our method is versatile and fast and has the potential to provide an automatic procedure for classifying pathologies. We test our approach on synthetic and real data from a variety of medical and biological applications. In these studies it is important to reconstruct accurately the shape of the object under investigation from very noisy data. Here we assume that we have some prior knowledge about the object outline represented by a prototype shape. Our procedure deforms this shape by means of non-affine transformations and the contour is reconstructed by minimizing a newly developed objective function that depends on the transformation parameters. We introduce an iterative template deformation procedure in which the scale of the deformation decreases as the algorithm proceeds. We compare our results with those from a Gaussian Mixture Model segmentation and two state-of-the-art Level Set methods. This comparison shows that the proposed procedure performs consistently well on both real and simulated data. As a by-product we develop a new filter that recovers the connectivity of a shape.

Magnebike: A magnetic wheeled robot with high mobility for inspecting complex‐shaped structures

This paper describes the Magnebike robot, a compact robot with two magnetic wheels in a motorbike arrangement, which is intended for inspecting the inner casing of ferromagnetic pipes with complex‐shaped structures. The locomotion concept is based on an adapted magnetic wheel unit integrating two lateral lever arms. These arms allow for slight lifting off the wheel in order to locally decrease the magnetic attraction force when passing concave edges, as well as laterally stabilizing the wheel unit. The robot has the main advantage of being compact (180 × 130 × 220 mm) and mechanically simple: it features only five active degrees of freedom (two driven wheels each equipped with an active lifter stabilizer and one steering unit). The paper presents in detail design and implementation issues that are specific to magnetic wheeled robots. Low‐level control functionalities are addressed because they are necessary to control the active system. The paper also focuses on characterizing and analyzing the implemented robot. The high mobility is shown through experimental results: the robot not only can climb vertical walls and follow circumferential paths inside pipe structures but it is also able to pass complex combinations of 90‐deg convex and concave ferromagnetic obstacles with almost any inclination regarding gravity. It requires only limited space to maneuver because turning on the spot around the rear wheel is possible. This high mobility enables the robot to access any location in the specified environment. Finally the paper analyzes the maximum payload for different types of environment complexities because this is a key feature for climbing robots and provides a security factor about the risk of falling and slipping. © 2009 Wiley Periodicals, Inc.     

Fuzzy motion control strategy for cooperation of multiple automated vehicles with passengers comfort

This paper considers motion control for a cooperative system of automated passenger vehicles. It develops a cooperative scheme based on a decentralized planning algorithm which considers the vehicles in an initial open chain configuration. In this scheme the trajectories are intersections-free, and each trajectory is planned independently of the others. To ensure the stabilization of each vehicle in the planned trajectory, a fuzzy closed loop motion control is presented, where, based on the properties of the Fuzzy maps, the Lyapunov’s stability of the motion errors is demonstrated for all the vehicles. Based on the ISO 2631-1 standard, the saturation property of the Fuzzy maps guarantees low values of longitudinal and lateral accelerations, to ensure comfort of the human body during the motion. The validity of this control algorithm is supported by simulation experiments.     

A systematic literature review on IoT-aware business process modeling views,requirements and notations

Software and Systems Modeling - The Internet of things has been adopted in several sectors both influencing how people work and enhancing organizations’ business processes. This resulted in...     

Simplified analytical models for compressed concrete columns confined by FRP and FRCM system

In order to consider the response of concrete columns confined by FRP and FRCM system, proper models have to be formulated. In this context the present paper shows a generalized criterion for the determination of the increase in strength, in ductility and in dissipated energy for varying corner radius ratio of the cross section and fiber volumetric ratio. The procedure is based on the best fitting of several experimental data and unlike the usual empirical approaches available in the literature, the proposed technique relates the confinement effectiveness to a single parameter representative of the relative stiffness between the original concrete core and the reinforcement system. Furthermore, the proposed analytical models overcomes the limit of many empirical or semi-empirical models given in the literature that are applicable only to specific cases. A comparison with same available models confirm the reliability of the proposed procedure.