Semantic linking through spaces for cyber-physical-socio intelligence:a methodology

Humans consciously and subconsciously establish various links, emerge semantic images and reason in mind, learn linking effect and rules, select linked individuals to interact, and form closed loops through links while co-experiencing in multiple spaces in lifetime. Machines are limited in these abilities although various graph-based models have been used to link resources in the cyber space. The following are fundamental limitations of machine intelligence: (1) machines know few links and rules in the physical space, physiological space, psychological space, socio space and mental space, so it is not realistic to expect machines to discover laws and solve problems in these spaces; and, (2) machines can only process pre-designed algorithms and data structures in the cyber space. They are limited in ability to go beyond the cyber space, to learn linking rules, to know the effect of linking, and to explain computing results according to physical, physiological, psychological and socio laws. Linking various spaces will create a complex space — the Cyber-Physical-Physiological-Psychological-Socio-Mental Environment CP3SME. Diverse spaces will emerge, evolve, compete and cooperate with each other to extend machine intelligence and human intelligence. From multi-disciplinary perspective, this paper reviews previous ideas on various links, introduces the concept of cyber-physical society, proposes the ideal of the CP3SME including its definition, characteristics, and multi-disciplinary revolution, and explores the methodology of linking through spaces for cyber-physical-socio intelligence. The methodology includes new models, principles, mechanisms, scientific issues, and philosophical explanation. The CP3SME aims at an ideal environment for humans to live and work. Exploration will go beyond previous ideals on intelligence and computing.

Experiences in using a contingency factor-based validation methodology for spreadsheet DSS

The use of spreadsheets has become routine in all aspects of business with usage growing across a range of functional areas and a continuing trend towards end user spreadsheet development. However, several studies have raised concerns about the accuracy of spreadsheet models in general, and of end user developed applications in particular, raising the risk element for users. High error rates have been discovered, even though the users/developers were confident that their spreadsheets were correct. The lack of an easy to use, context-sensitive validation methodology has been highlighted as a significant contributor to the problems of accuracy. This paper describes experiences in using a practical, contingency factor-based methodology for validation of spreadsheet-based DSS. Because the end user is often both the system developer and a stakeholder, the contingency factor-based validation methodology may need to be used in more than one way. The methodology can also be extended to encompass other DSS.

An examination of the development of LTL hub-and-spoke freight distribution systems

Over recent years, hub-and-spoke distribution techniques have attracted widespread research attention. Despite there being a growing body of literature in this area there is less focus on the spoke-terminal element of the hub-and-spoke system as being a key component in the overall service received by the end-user. Current literature is highly geared towards discussing bulk optimization of freight units rather than to the more discrete and individualistic profile characteristics of shared-user Less-than-truckload (LTL) freight. In this paper, a literature review is presented to review the role hub-and-spoke systems play in meeting multi-profile customer demands, particularly in developing sectors with more sophisticated needs, such as retail. The paper also looks at the use of simulation technology as a suitable tool for analyzing spoke-terminal operations within developing hub-and spoke systems.

Scaling up question-answering to linked data

Linked Data semantic sources, in particular DBpedia, can be used to answer many user queries. PowerAqua is an open multi-ontology Question Answering (QA) system for the Semantic Web (SW). However, the emergence of Linked Data, characterized by its openness, heterogeneity and scale, introduces a new dimension to the Semantic Web scenario, in which exploiting the relevant information to extract answers for Natural Language (NL) user queries is a major challenge. In this paper we discuss the issues and lessons learned from our experience of integrating PowerAqua as a front-end for DBpedia and a subset of Linked Data sources. As such, we go one step beyond the state of the art on end-users interfaces for Linked Data by introducing mapping and fusion techniques needed to translate a user query by means of multiple sources. Our first informal experiments probe whether, in fact, it is feasible to obtain answers to user queries by composing information across semantic sources and Linked Data, even in its current form, where the strength of Linked Data is more a by-product of its size than its quality. We believe our experiences can be extrapolated to a variety of end-user applications that wish to scale, open up, exploit and re-use what possibly is the greatest wealth of data about everything in the history of Artificial Intelligence. © 2010 Springer-Verlag.

Investigating local delivery by road to retail and non-retail customers in the UK logistics sector

Over recent years, hub-and-spoke distribution techniques have attracted widespread research attention. Despite there being a growing body of literature in this area there is less focus on the spoke-terminal element of the hub-and-spoke system as being a key component in the overall service received by the end-user. Current literature is highly geared towards discussing bulk optimization of freight units rather than to the more discrete and individualistic profile characteristics of shared-user Less-than-truckload (LTL) freight. In this paper, a literature review is presented to review the role hub-and-spoke systems play in meeting multi-profile customer demands, particularly in developing sectors with more sophisticated needs, such as retail. The paper also looks at the use of simulation technology as a suitable tool for analyzing spoke-terminal operations within developing hub-and spoke systems.

Real-time detection, tracking, and monitoring of automatically discovered events in social media

We introduce ReDites, a system for realtime event detection, tracking, monitoring and visualisation. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. Events are automatically detected from the Twitter stream. Then those that are categorised as being security-relevant are tracked, geolocated, summarised and visualised for the end-user. Furthermore, the system tracks changes in emotions over events, signalling possible flashpoints or abatement. We demonstrate the capabilities of ReDites using an extended use case from the September 2013 Westgate shooting incident. Through an evaluation of system latencies, we also show that enriched events are made available for users to explore within seconds of that event occurring.

Conceptual Model and Security Requirements for DRM Techniques Used for e-Learning Objects Protection

This paper deals with the security problems of DRM protected e-learning content. After a short review of the main DRM systems and methods used in e-learning, an examination is made of participators in DRM schemes (e-learning object author, content creator, content publisher, license creator and end user). Then a conceptual model of security related processes of DRM implementation is proposed which is improved afterwards to reflect some particularities in DRM protection of e-learning objects. A methodical way is used to describe the security related motives, responsibilities and goals of the main participators involved in the DRM system. Taken together with the process model, these security properties are used to establish a list of requirements to fulfill and a possibility for formal verification of real DRM systems compliance with these requirements.

Message from the UCAWSN 2014 program Chairs

Published in the Front Matter

HI!MVC: Hierarchical MVC Framework for WEB Applications

This paper presents Hi!MVC, a framework for developing high interactive web applications with a MVC Architecture. Nowadays, to manage, extend and correct web applications can be difficult due to the navigational paradigm they are based on. Hi!MVC framework helps to make these tasks easier. This framework allows building a web based interface, generating each page from the objects that represent its state. Every class to be showed in the interface is associated with two entities: its html representation (view) and its interactions in the view manager (controller). The whole html page is generated by composition of views according to the composition relationship of objects. Interactions between user and application are managed by the controller associated to the view which shows interaction elements (links or forms). Hi!MVC allows building web interface in a hierarchical and distributed way. There are other frameworks and APIs offering MVC architectures to web applications, but we think that they are not applying exactly the same concepts. While they keep on basing their architectures on the navigational paradigm we are offering a new point of view based on an innovator hierarchical model. First, we present the main ideas of our proposal. Next, we expose how to implement it using different Java technologies. Finally, we make a first approach to our hierarchical MVC model. We also compare shortly our proposal with the previously cited technologies.

Defining Interestigness for Association Rules

Interestingness in Association Rules has been a major topic of research in the past decade. The reason is that the strength of association rules, i.e. its ability to discover ALL patterns given some thresholds on support and confidence, is also its weakness. Indeed, a typical association rules analysis on real data often results in hundreds or thousands of patterns creating a data mining problem of the second order. In other words, it is not straightforward to determine which of those rules are interesting for the end-user. This paper provides an overview of some existing measures of interestingness and we will comment on their properties. In general, interestingness measures can be divided into objective and subjective measures. Objective measures tend to express interestingness by means of statistical or mathematical criteria, whereas subjective measures of interestingness aim at capturing more practical criteria that should be taken into account, such as unexpectedness or actionability of rules. This paper only focusses on objective measures of interestingness.

Representing human expertise by the OWL web ontology language to support knowledge engineering in decision support systems

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

Preserving Linked Data

PRELIDA (PREserving LInked DAta) is an FP7 Coordination Action funded by the European Commission under the Digital Preservation Theme. PRELIDA targets the particular stakeholders of the Linked Data community, including data providers, service providers, technology providers and end user communities. These stakeholders have not been traditionally targeted by the Digital Preservation community, and are typically not aware of the digital preservation solutions already available. So an important task of PRELIDA is to raise awareness of existing preservation solutions and to facilitate their uptake. At the same time, the Linked Data cloud has specific characteristics in terms of structuring, interlinkage, dynamicity and distribution that pose new challenges to the preservation community. PRELIDA organises in-depth discussions among the two communities to identify which of these characteristics require novel solutions, and to develop road maps for addressing the new challenges. PRELIDA will complete its lifecycle at the end of this year, and the talk will report about the major findings.

Assessing the motivation of MDs to use computer-based support at the point-of-care in the emergency department

A significant body of research investigates the acceptance of computer-based support (including devices and applications ranging from e-mail to specialized clinical systems, like PACS) among clinicians. Much of this research has focused on measuring the usability of systems using characteristics related to the clarity of interactions and ease of use. We propose that an important attribute of any clinical computer-based support tool is the intrinsic motivation of the end-user (i.e. a clinician) to use the system in practice. In this paper we present the results of a study that investigated factors motivating medical doctors (MDs) to use computer-based support. Our results demonstrate that MDs value computer-based support, find it useful and easy to use, however, uptake is hindered by perceived incompetence, and pressure and tension associated with using technology.

Enhanced connectivity and QoE through LTE-WiFi interworking in Smart Cities

Mobile communication and networking infrastructures play an important role in the development of smart cities, to support real-time information exchange and management required in modern urbanization. Mobile WiFi devices that help offloading data traffic from the macro-cell base station and serve the end users within a closer range can significantly improve the connectivity of wireless communications between essential components including infrastructural and human devices in a city. However, this offloading function through interworking between LTE and WiFi systems will change the pattern of resource distributions operated by the base station. In this paper, a resource allocation scheme is proposed to ensure stable service coverage and end-user quality of experience (QoE) when offloading takes place in a macro-cell environment. In this scheme, a rate redistribution algorithm is derived to form a parametric scheduler to meet the required levels of efficiency and fairness, guided by a no-reference quality assessment metric. We show that the performance of resource allocation can be regulated by this scheduler without affecting the service coverage offered by the WLAN access point. The performances of different interworking scenarios and macro-cell scheduling policies are also compared.

Uncertainty propagation in the model web:a case study with e-Habitat

eHabitat is a Web Processing Service (WPS) designed to compute the likelihood of finding ecosystems with equal properties. Inputs to the WPS, typically thematic geospatial "layers", can be discovered using standardised catalogues, and the outputs tailored to specific end user needs. Because these layers can range from geophysical data captured through remote sensing to socio-economical indicators, eHabitat is exposed to a broad range of different types and levels of uncertainties. Potentially chained to other services to perform ecological forecasting, for example, eHabitat would be an additional component further propagating uncertainties from a potentially long chain of model services. This integration of complex resources increases the challenges in dealing with uncertainty. For such a system, as envisaged by initiatives such as the "Model Web" from the Group on Earth Observations, to be used for policy or decision making, users must be provided with information on the quality of the outputs since all system components will be subject to uncertainty. UncertWeb will create the Uncertainty-Enabled Model Web by promoting interoperability between data and models with quantified uncertainty, building on existing open, international standards. It is the objective of this paper to illustrate a few key ideas behind UncertWeb using eHabitat to discuss the main types of uncertainties the WPS has to deal with and to present the benefits of the use of the UncertWeb framework.