In recent decades, people, especially the older ones, try to live at home in autonomous way. For this purpose it is useful to monitor their vital signs and the home environment to activate suitable environment regulation and to send alarms to family members, medical, or hospitals, according to the criticality of the subject. The paper aims at proposing a flexible and reliable monitoring system based on embedded systems and wearable devices. The system main feature is that it allows the doctor and family members to monitor the patients at distance using their mobiles. A suitable communication with the first aid center is foreseen for a fast rescue of the patients in case of critical situations. A user model ontology is adopted so that patient and context data may be used by any diagnostic and first aid software, thus envisaging an open and interoperable health monitoring system for elderly people living at home. A diagnostic system based on fuzzy rules is proposed to support the choice of the best course of actions in case of critical health conditions.

Aim of the paper is to illustrate the methodology used to implement an ubiquitous city platform called Wi-City-Plus provided with mobile and centralized Decision Support Systems (DSSs) taking advantage of all the data of city interest, including social data, and those sensed by networked ambient Cyber-Physical-Systems (CPSs). The paper proposes to model such data by a suitable RDF ontology specifically designed to support the main user scenarios in smart cities and to implement both the technical and the service interoperability envisaged by the CPS ideal model. This ontology is obtained by reusing existing ontologies and allows the DSSs to access by SPARQL queries all the relevant data independent of the proprietary technology of the CPSs and of the DBMS adopted by the data owners. Examples derived from the pilot version of the proposed platform allows us to point out advantages and perspectives of our approach.

Aim of the paper is to give a demonstration of the main Cyber-Physical-Systems (CPSs) and social networking facilities used to implement an ubiquitous city platform called Wi-City-Plus provided with mobile and centralized decision support systems (DSSs) taking advantage of all the data of city interest, including social data, and those sensed by networked monitoring devices. In particular, the paper adopts a semantic web approach that allow us to model such data by a suitable ontology specifically designed to support the main user scenarios in smart cities and to implement both the technical interoperability and the service integration envisaged by the CPS ideal model.

SUMMARY In this paper, we present a bioinformatics knowledge discovery tool for extracting and validating associations between biological entities. By mining specialized scientific literature, the tool not only generates biological hypotheses in the form of associations between genes, proteins, miRNA and diseases but also validates the plausibility of such associations against high‐throughput biological data (e.g. microarray) and annotated databases (e.g. Gene Ontology). Both the knowledge discovery system and its validation are carried out by exploiting the advantages and the potentialities of the Cloud, which allowed us to derive and check the validity of thousands of biological associations in a reasonable amount of time. The system was tested on a dataset containing more than 1000 gene–disease associations achieving an average recall of about 71%, outperforming existing approaches. The results also showed that porting a data‐intensive application in an Infrastructure as a Service cloud environment boosts significantly the application's efficiency. Copyright © 2013 John Wiley & Sons, Ltd.

Mobile navigation assistance is effective if the paths to destination are chosen taking into account the current traffic flows. Also, personal and social data dealing with the current user status/task and citizen preferences should be taken into account to suggest the most appropriate services. To this aim, the paper proposes a mobile recommending system able to suggest minimum travel time paths to destination taking into account the current traffic conditions and to recommend the services most suitable to the user needs. Such recommending system works using logic rules instead of procedural algorithms, whereas the traffic monitoring system is obtained by means of the GPS signals received from the mobiles of the users. Also, the proposal provides a way to compute the Origin Destination Matrix and to optimize the parameters of the adopted traffic simulation model to increase the model reliability in predicting if novel traffic infrastructures and policies are able to decrease the time spent in the vehicles and the gasoline consumption.

A huge amount of important biomedical information is hidden in the bulk of research articles in biomedical fields. At the same time, the publication of databases of biological information and of experimental datasets generated by high-throughput methods is in great expansion, and a wealth of annotated gene databases, chemical, genomic (including microarray datasets), clinical and other types of data repositories are now available on the Web. Thus a current challenge of bioinformatics is to develop targeted methods and tools that integrate scientific literature, biological databases and experimental data for reducing the time of database curation and for accessing evidence, either in the literature or in the datasets, useful for the analysis at hand. Under this scenario, this article reviews the knowledge discovery systems that fuse information from the literature, gathered by text mining, with microarray data for enriching the lists of down and upregulated genes with elements for biological understanding and for generating and validating new biological hypothesis. Finally, an easy to use and freely accessible tool, GeneWizard, that exploits text mining and microarray data fusion for supporting researchers in discovering gene-disease relationships is described.

The assessment of skeletal bone age is an important step both in diagnostic and in therapeutic investigations of en-docrinological problems and growth disorders of children. Currently, there are two main approaches for skeletal bone age estimation that use X-Ray images: 1) the Greulich and Pyle (G&P) method and 2) the Tanner and Whitehouse (TW2 or TW3) methods. Although the G&P method is the most widely used for its simplicity, the TW2/TW3 method is the most accurate one, but it requires intensive training, especially for novice radiologists. The method is complex since it involves the simultaneous assessment of shapes and relative distances among several bones of the hand and with the further complication of the interaction between sex, age and race. In this paper we propose a computer-based system for assisting radiologists in the training with the Tan-ner&Whitehouse method; the system is based on an engine for automated assessment of skeletal bone age from X-Rays. In detail, after evaluating the user level, the system automatically proposes personalized training sessions by drawing from a wide repository of hand X-rays, and it suggests remedial sessions upon identification the features of the cases where the users demonstrated misconceptions. Finally, all the X-Rays that show combinations of features provenly difficult, are treated as teaching cases and are converted into Medical Imaging Resource Center (MIRC) format to ease their integration into more comprehensive digital educational resources.

This paper presents a novel vehicle detection and tracking system with stationary camera that relies on a recursive background-modeling approach, i.e., the adaptive Poisson mixture model, which is integrated with a hardware module consisting of luminosity sensors. The luminosity information side channel allows the system to effectively handle rapid changes in illumination, which is typical of outdoor applications and bottleneck of the existing background pixel classification methods. A novel algorithm for detecting and removing partial and full occlusions among blobs is also proposed. Partial occlusions are detected by evaluating the ratio between the area of the vehicle and the area of the vehicle's convex hull and are suppressed by identifying a cutting line using curvature analysis. A predictive model of the shape and motion features of the vehicles over consecutive frames instead corrects the error of the previous levels when full occlusions or background-vehicle occlusions occur in the scene. Quantitative evaluation and comparisons on some real-world scenarios demonstrate that the proposed approach outperforms state-of-the-art methods in terms of both vehicle detection and processing time, particularly due to the robustness and the efficiency of the background-modeling algorithm.

In this paper we propose an implicit relevance feedback method with the aim to improve the performance of known Content Based Image Retrieval (CBIR) systems by re-ranking the retrieved images according to users' eye gaze data. This represents a new mechanism for implicit relevance feedback, in fact usually the sources taken into account for image retrieval are based on the natural behavior of the user in his/her environment estimated by analyzing mouse and keyboard interactions. In detail, after the retrieval of the images by querying CBIRs with a keyword, our system computes the most salient regions (where users look with a greater interest) of the retrieved images by gathering data from an unobtrusive eye tracker, such as Tobii T60. According to the features, in terms of color, texture, of these relevant regions our system is able to re-rank the images, initially, retrieved by the CBIR. Performance evaluation, carried out on a set of 30 users by using Google Images and "pyramid" like keyword, shows that about the 87% of the users is more satisfied of the output images when the re-raking is applied.

A challenging goal today is the use of computer networking and advanced monitoring technologies to extend human intellectual capabilities in medical decision making. Modern commercial eye trackers are used in many of research fields, but the improvement of eye tracking technology, in terms of precision on the eye movements capture, has led to consider the eye tracker as a tool for vision analysis, so that its application in medical research, e.g. in ophthalmology, cognitive psychology and in neuroscience has grown considerably. The improvements of the human eye tracker interface become more and more important to allow medical doctors to increase their diagnosis capacity, especially if the interface allows them to remotely administer the clinical tests more appropriate for the problem at hand. In this paper, we propose a client/server eye tracking system that provides an interactive system for monitoring patients eye movements depending on the clinical test administered by the medical doctors. The system supports the retrieval of the gaze information and provides statistics to both medical research and disease diagnosis.

This paper proposes a novel method for text mining on the Grid, aimed at pointing out hidden relationships for hypothesis generation and suitable for semi-interactive querying. The method is based on unsupervised clustering and the outputs are visualized with contextual information. Grid implementation is crucial for feasibility. We demonstrate it with a mining run for discovering genes-diseases associations from bibliographic sources and annotated databases. The proposed methodology is in view of a Grid architecture specialized in bioinformatics mining tasks. Some performance considerations are provided.

This paper proposes a traffic monitoring architecture based on a high-speed communication network whose nodes are equipped with fuzzy processors and cellular neural network (CNN) embedded systems. It implements a real-time mobility information system where visual human perceptions sent by people working on the territory and video-sequences of traffic taken from webcams are jointly processed to evaluate the fundamental traffic parameters for every street of a metropolitan area. This paper presents the whole methodology for data collection and analysis and compares the accuracy and the processing time of the proposed soft computing techniques with other existing algorithms. Moreover, this paper discusses when and why it is recommended to fuse the visual perceptions of the traffic with the automated measurements taken from the webcams to compute the maximum traveling time that is likely needed to reach any destination in the traffic network.

A knowledge base consisting of design cases has been structured into an organizational memory, which has been supporting a community of novices to learn information system (IS) for six years. The paper discusses why the organizational learning process, which is taking place, can be described as a genetic system that evolves towards the best quality attainable, and by means of a simulation examines the role of some components of this socio-technical system (i.e. features of the organizational memory, teacher ability and memetic processes in the community) in steering this evolution. Some indications for the design of socio-technical systems supported by design memories are pointed out.

Aim of the paper is to illustrate an ontology based approach to the design of mobility information systems which, through multiple distribution channels, provide companies and individual consumers with the information that facilitate their mobility in a metropolitan area. Main advantages of the proposed approach are user queries whose semantics is independent of the system implementation, and the possibility of delegating user tasks to mobile software agents by means of either PCs or PDAs. The ontology framework also facilitates data collection and control of remote devices such as semaphores and signs. The outlined architecture is under experimentation for managing mobility in the Catania metropolitan area.

Scenario-based design is a significant informal approach to systems specification and verification, but it does not ensure correct user-centered systems. This paper shows how scenario-based design can be augmented with a theory of interactions and scenes that allows the designer to elicit user requirements within a formal framework that does not excessively constrain the user narration, and to derive a system implementation satisfying the basic software engineering requisites. The paper discusses also how the approach facilitates the formal proof of the safety and liveness properties of interactive systems.

An issue of current interest in the Open Systems Interconnection (OSI) field is the choice of a language well suited to specification and verification. For this purpose, two languages based on Milner's communication calculi are proposed, respectively intended for the specification of asynchronous and synchronous OSI systems. A formal verification method, relying upon the algebraic foundations of the two languages, is introduced and illustrated by means of examples based on nontrivial protocols and services.

The Language for temporal ordering specification (LOTOS) is a formal description technique whose development is under way within ISO, the International Organization for standardization, mainly for application to open systems interconnection (OSI) standards. The paper presents a LOTOS specification of the PROWAY interface for process control applicatioins, defined by IEC, the International Electrotechnical Commision. LOTOS is shown to be tailored for the specification of asynchronous systems. In particular, it proves suitable for the specification both of the services which define an interface and of the protocols which implement it. The paper shows how LOTOS supports formal reasoning aimed at establishing consistency between service and protocol specifications. Two examples of such a verification are developed that are related to the PROWAY interface. Finally, advantages and limitations of this approach are outlined.

The aim of this paper is to present some measurements on the performance of a X.25 packet switching subnetwork and of a typical X.25 DTE-DCE interface. The communication parameters considered are the window size of the link layer flow control, the length and contents of the packets and the internode distance. The collected measurements on the X.25 subnetwork are compared with others obtained through different versions of DTE connected to the same subnetwork. Some considerations are presented about the time spent by the packets inside the DTE and consequently about the efficiency of the DTE version used in these experiments.