Barriers Survey: A Tool to Support Data Collection for Inclusive Mobility
In this paper we describe the potential for using the Volunteered Geographic Information VGI, and large crowd-sourced survey, in disable people mobility computing applications The challenge is to make these two concepts talking together exploiting the technologies in order to increase the public participation, and to move towards sustainable development. Our goal is to investigate how participative and people-centric data collection can be used to create a low-cost, open platform to survey, annotate and localise pedestrian mobility features and architectural barriers as it is perceived by the citizen themselves. The core of the project consists into the development and deployment of a mobile application and a web platform, which allow the users to collect and manage the information surveyed.
Smart Objects: An Evaluation of the Present State Based on User Needs
In the last years, some attempts have been made to explore the use of smart objects, with the purpose of monitoring well-being and supporting people’s independent living. However an inventory of characteristics of smart products currently available on the market is still lacking. The aim of this study is to provide an overview of such products in order to: (1) understand if their features really match users’ needs, answering to the definition of assistive technology and, consequently, (2) understand if an environment embedded with SOs can be considered as assistive too, taking into consideration the attributes given by the definition of the SOs, of being embedded in familiar objects and immerse in the users’ surround.
Automatic Extraction of Logical Web Lists
Recently, there has been increased interest in the extraction of structured data from the web (both “Surface” Web and“Hidden” Web). In particular, in this paper we focus on the automatic extraction of Web Lists. Although this task has been studied extensively, existing approaches are based on the assumption that lists are wholly contained in a Web page.They do not consider that many websites span their listing on several Web Pages and show for each of these only a partial view. Similar to databases, where a view can represent a subset of the data contained in a table, they split a logical list in multiple views (view lists). Automatic extraction of logical lists is an open problem. To tackle this issue we propose an unsupervised and domain-independent algorithm for logical list extraction. Experimental results on real-life and data-intensive Web sites confirm the effectiveness of our approach.
Approximating the Revenue Maximization Problem with Sharp Demands
We consider the revenue maximization problem with sharp multi-demand, in which m indivisible items have to be sold to n potential buyers. Each buyer i is interested in getting exactly d i items, and each item j gives a benefit v ij to buyer i. We distinguish between unrelated and related valuations. In the former case, the benefit v ij is completely arbitrary, while, in the latter, each item j has a quality q j , each buyer i has a value v i and the benefit v ij is defined as the product v i q j . The problem asks to determine a price for each item and an allocation of bundles of items to buyers with the aim of maximizing the total revenue, that is, the sum of the prices of all the sold items. The allocation must be envy-free, that is, each buyer must be happy with her assigned bundle and cannot improve her utility. We first prove that, for related valuations, the problem cannot be approximated to a factor O(m 1 − e ), for any e u003e 0, unless P = NP and that such result is asymptotically tight. In fact we provide a simple m-approximation algorithm even for unrelated valuations. We then focus on an interesting subclass of “proper” instances, that do not contain buyers a priori known not being able to receive any item. For such instances, we design an interesting 2-approximation algorithm and show that no (2 − e)-approximation is possible for any 0 u003c e ≤ 1, unless P = NP. We observe that it is possible to efficiently check if an instance is proper, and if discarding useless buyers is allowed, an instance can be made proper in polynomial time, without worsening the value of its optimal solution.
The nuXmv Symbolic Model Checker
This paper describes the nuXmv symbolic model checker for finite- and infinite-state synchronous transition systems. nuXmv is the evolution of the nuXmv open source model checker. It builds on and extends nuXmv along two main directions. For finite-state systems it complements the basic verification techniques of nuXmv with state-of-the-art verification algorithms. For infinite-state systems, it extends the nuXmv language with new data types, namely Integers and Reals, and it provides advanced SMT-based model checking techniques. Besides extended functionalities, nuXmv has been optimized in terms of performance to be competitive with the state of the art. nuXmv has been used in several industrial projects as verification back-end, and it is the basis for several extensions to cope with requirements analysis, contract based design, model checking of hybrid systems, safety assessment, and software model checking.
Body Posture Recognition as a Discovery Problem: A Semantic-Based Framework
The automatic detection of human activities requires large computational resources to increase recognition performances and sophisticated capturing devices to produce accurate results. Anyway, often innovative analysis methods applied to data extracted by off-the-shelf detection peripherals can return acceptable outcomes. In this paper a framework is proposed for automated posture recognition, exploiting depth data provided by a commercial tracking device. The detection problem is handled as a semantic-based resource discovery. A simple yet general data model and a corresponding ontology create the needed terminological substratum for an automatic posture annotation via standard Semantic Web languages. Hence, a logic-based matchmaking allows to compare retrieved annotations with standard posture descriptions stored as individuals in a proper Knowledge Base. Finally, non-standard inferences and a similarity-based ranking support the discovery of the best matching posture. This framework has been implemented in a prototypical tool and preliminary experimental tests have been carried out w.r.t. a reference dataset.
A Multi-model Optimization Framework for the Model Driven Design of Cloud Applications
The rise and adoption of the Cloud computing paradigm had a strong impact on the ICT world in the last few years; this technology has now reached maturity and Cloud providers offer a variety of solutions and services to their customers. However, beside the advantages, Cloud computing introduced new issues and challenges. In particular, the heterogeneity of the Cloud services offered and their relative pricing models makes the identification of a deployment solution that minimizes costs and guarantees QoS very complex. Performance assessment of Cloud based application needs for new models and tools to take into consideration the dynamism and multi-tenancy intrinsic of the Cloud environment. The aim of this work is to provide a novel mixed integer linear program (MILP) approach to find a minimum cost feasible cloud configuration for a given cloud based application. The feasibility of the solution is considered with respect to some non-functional requirements that are analyzed through multiple performance models with different levels of accuracy. The initial solution is further improved by a local search based procedure. The quality of the initial feasible solution is compared against first principle heuristics currently adopted by practitioners and Cloud providers.
Advanced Technologies for Intelligent Transportation Systems
This book focuses on emerging technologies in the field of Intelligent Transportation Systems (ITSs) namely efficient information dissemination between vehicles, infrastructures, pedestrians and public transportation systems. It covers the state-of-the-art of Vehicular Ad-hoc Networks (VANETs), with centralized and decentralized (Peer-to-Peer) communication architectures, considering several application scenarios. With a detailed treatment of emerging communication paradigms, including cross networking and distributed algorithms. Unlike most of the existing books, this book presents a multi-layer overview of information dissemination systems, from lower layers (MAC) to high layers (applications). All those aspects are investigated considering the use of mobile devices, such as smartphones/tablets and embedded systems, i.e. technologies that during last years completely changed the current market, the user expectations, and communication networks. The presented networking paradigms are supported and validated by means of extensive simulative analysis and real field deployments in different application scenarios. This book represents a reference for professional technologist, postgraduates and researchers in the area of Intelligent Transportation Systems (ITSs), wireless communication and distributed systems.