Are electronic white canes better than traditional canes? A comparative study with blind and blindfolded participants

Visually impaired individuals often rely on assistive technologies such as white canes for independent navigation. Many electronic enhancements to the traditional white cane have been proposed. However, only a few of these proof-of-concept technologies have been tested with authentic users, as most studies rely on blindfolded non-visually impaired participants or no testing with participants at all. Experiments involving blind users are usually not contrasted with the traditional white cane. This study set out to compare an ultrasound-based electronic cane with a traditional white cane. Moreover, we also compared the performance of a group of visually impaired participants (N = 10) with a group of blindfolded participants without visual impairments (N = 31). The results show that walking speed with the electronic cane is significantly slower compared to the traditional white cane. Moreover, the results show that the performance of the participants without visual impairments is significantly slower than for the visually impaired participants. No significant differences in obstacle detection rates were observed across participant groups and device types for obstacles on the ground, while 79% of the hanging obstacles were detected by the electronic cane. The results of this study thus suggest that electronic canes present only one advantage over the traditional cane, namely in its ability to detect hanging obstacles, at least without prolonged practice. Next, blindfolded participants are insufficient substitutes for blind participants who are expert cane users. The implication of this study is that research into digital white cane enhancements should include blind participants. These participants should be followed over time in longitudinal experiments to document if practice will lead to improvements that surpass the performance achieved with traditional canes.

     

Tropos: An Agent-Oriented Software Development Methodology

Our goal in this paper is to introduce and motivate a methodology, called Tropos,¹ for building agent oriented software systems. Tropos is based on two key ideas. First, the notion of agent and all related mentalistic notions (for instance goals and plans) are used in all phases of software development, from early analysis down to the actual implementation. Second, Tropos covers also the very early phases of requirements analysis, thus allowing for a deeper understanding of the environment where the software must operate, and of the kind of interactions that should occur between software and human agents. The methodology is illustrated with the help of a case study. The Tropos language for conceptual modeling is formalized in a metamodel described with a set of UML class diagrams.     

Cooperation in Games and Epistemic Readings of Independence-Friendly Sentences

In the literature on logics of imperfect information it is often stated, incorrectly, that the Game-Theoretical Semantics of Independence-Friendly (IF) quantifiers captures the idea that the players of semantical games are forced to make some moves without knowledge of the moves of other players. We survey here the alternative semantics for IF logic that have been suggested in order to enforce this “epistemic reading” of sentences. We introduce some new proposals, and a more general logical language which distinguishes between “independence from actions” and “independence from strategies”. New semantics for IF logic can be obtained by choosing embeddings of the set of IF sentences into this larger language. We compare all the semantics proposed and their purported game-theoretical justifications, and disprove a few claims that have been made in the literature.     

A metatheory of a mechanized object theory

In this paper we propose a metatheory, MT, which represents the computation which implements its object theory, OT, and, in particular, the computation which implements deduction in OT. To emphasize this fact we say that MT is a metatheory of a mechanized object theory. MT has some “unusual” properties, e.g. it explicitly represents failure in the application of inference rules, and the fact that large amounts of the code implementing OT are partial, i.e. they work only for a limited class of inputs. These properties allow us to use MT to express and prove tactics, i.e. expressions which specify how to compose possibly failing applications of inference rules, to interpret them procedurally to assert theorems in OT, to compile them into the system implementation code, and, finally, to generate MT automatically from the system code. The definition of MT is part of a larger project which aims at the implementation of self-reflective systems, i.e. systems which are able to introspect their own code, to reason about it and, possibly, to extend or modify it.     

Comparison of MCNPX-C90 and TRIPOLI-4-D for fuel depletion calculations of a Gas-cooled Fast Reactor

The Gas-cooled Fast Reactor is one of the reactor concepts selected by the Generation IV International Forum for the next generation of innovative nuclear energy systems. Several fuel design concepts are being investigated. Burnup depletion of mixed fuel of uranium and plutonium, cooled with gas in a fast neutron energy spectrum must be simulated. Various codes are being developed and/or adapted to improve the quality of the results, and also to reduce the computing time required for the simulations.     

Effects of milk high pressure homogenization on biogenic amine accumulation during ripening of ovine and bovine Italian cheeses

The aim of this work was to evaluate the biogenic amine (BA) content during the ripening of both bovine and ovine cheeses obtained using milk subjected to a homogenization treatment at 100 MPa before cheese-making. The data obtained were compared with those from cheeses produced by the same milks without any treatment or thermized. The results showed that both microbial ecology and BA concentrations of cheeses during ripening were significantly influenced by the type of milk used for cheese-making and by the treatment applied to the raw materials. In particular, the microbial counts found in Caciotta indicated that the high pressure homogenization (HPH) of milk significantly reduced the presence of the yeasts, Micrococcaceae and lactobacilli at the end of ripening. On the other hand, the HPH treatment of milk favoured the proliferation of yeasts in ovine cheese. Moreover, the ovine cheeses were characterized by a remarkably higher accumulation of BA than bovine cheeses. However, the HPH treatment of milk was able to drastically reduce the biogenic amine concentrations in both cheese typologies at the end of ripening.     

Theoretical considerations on the adsorption isotherm for ionic systems at electrode interphases

The Guggenheim model of the interphase has been used to study ionic adsorption at electrode interphases from constant ionic strength solutions. Starting with an experimental adsorption isotherm, we deduce the electric equation of state and this equation can help to know what kind of systems respond to the adsorption isotherm. Interphase electrochemical potentials are also obtianed and the stardard state guage is comented. Results can be transferred to understand some trends of ionic adsorption at varying ionic strength solutions.     

Life cycle activity analysis: logistics and environmental policies for bottled water in Portugal

An innovative mathematical programming decision support model –Life Cycle Activity Analysis (LCAA)– is presented, integrating considerations of optimal allocations of resources and impacts upon the environment during the life cycle of products. LCAA is based on the classical formulation of activity analysis and on the life cycle assessment framework. The concept of linear activities is extended to embrace mass and energy fluxes over the entire life cycle of products including their environmental impacts. Special attention is given to the presence of loops in the product chains, such as those occurring when materials/products are recovered (reused, recycled.). An application brought from the Portuguese bottled water industry is described. The model features alternative activities for production technologies and product recovery strategies and permits the joint consideration of monetary costs and environmental burdens. The results obtained under five scenarios, including distinct disposal strategies and environmental constraints, are discussed.     

Integration of polynomials over n-dimensional polyhedra

Explicit formulae and algorithms for computing integrals of polynomials over n-dimensional polyhedra are given. Two different approaches are discussed: one uses a decompositive representation, while the other one uses a boundary representation of the polyhedron. The algorithms are followed by a discussion of the complexity. In the appendix the pseudo-code and some examples of calculation are given.     

Electric load analysis using an artificial neural network

Load forecasting in the current, increasingly liberalized, electricity power market is of crucial importance as a means for producers to optimize and rationalize energy supply. A number of electric power companies are equipped to make forecasts with the aid of traditional statistical methods. This paper presents the use of an artificial neural net to an hourly based load forecasting application for a small electric grid on an Italian island (Lipari) not connected to the mainland. The aim was to examine the forecasting ability of a neural net in a situation where the electric load was subject to considerable seasonal variations over the year. The variations are affected by energy demand related to the tourism season as well as by climatic conditions, especially temperature. The network developed was a multi‐layer perceptron type built on three layers trained with a back‐propagation algorithm. The input layer receives all the most relevant information regarding: the class of day type, the hour in the daytime, the load and background temperature recorded at the indicated time for the months of March, August and October whilst the output layer provides the forecast value at the indicated time in December. The results obtained are encouraging; in the training phase the RMS error rate was around 2% and this rate settled at about 2.6% during testing. As both the margins of error recorded are acceptable, the use of a neural network for electric load forecasting applications can be considered an attractive option. Copyright © 2005 John Wiley & Sons, Ltd.