Mobile P2Ping: A Super-Peer based Structured P2P System Using a Fleet of City Buses

Recently, researchers have introduced the notion of super-peers to improve signaling efficiency as well as lookup performance of peer-to-peer (P2P) systems. In a separate development, recent works on applications of mobile ad hoc networks (MANET) have seen several proposals on utilizing mobile fleets such as city buses to deploy a mobile backbone infrastructure for communication and Internet access in a metropolitan environment. This paper further explores the possibility of deploying P2P applications such as content sharing and distributed computing, over this mobile backbone infrastructure. Specifically, we study how city buses may be deployed as a mobile system of super-peers. We discuss the main motivations behind our proposal, and outline in detail the design of a super-peer based structured P2P system using a fleet of city buses.

Designing context-aware adaptive units of learning based on IMS-LD standard

Learning contents adaptation has been a subject of interest in the research area of the adaptive hypermedia systems. Defining which variables and which standards can be considered to model adaptive content delivery processes is one of the main challenges in pedagogical design over e-learning environments. In this paper some specifications, architectures and technologies that can be used in contents adaptation processes considering characteristics of the context are described and a proposal to integrate some of these characteristics in the design of units of learning using adaptation conditions in a structure of IMS-Learning Design (IMS-LD) is presented. The key contribution of this work is the generation of instructional designs considering the context, which can be used in Learning Management Systems (LMSs) and diverse mobile devices

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

COMP6218 Web Architecture - Web Content Formats

Plain Text - ASCII, Unicode, UTF-8 Content Formats - XML-based formats (RSS, MathML, SVG, Office) + PDF Text based data formats: CSV, JSON

Creating a Table of Contents to cover only part of a file's content using MS Word 2011 for Apple computers

A Table of Contents can be tweaked so that it picks up the content from only part of a file (such as an Appendix). This video shows you how to make such a change to a Table of Contents that is based upon Heading Styles. For best viewing Download the video.

"Thematically Analysing Social Network Content During Disasters Through the Lens of the Disaster Management Lifecycle" & "Investigating Similarity Between Privacy Policies of Social Networking Sites as a Precursor for Standardization"

Abstract 1: Social Networks such as Twitter are often used for disseminating and collecting information during natural disasters. The potential for its use in Disaster Management has been acknowledged. However, more nuanced understanding of the communications that take place on social networks are required to more effectively integrate this information into the processes within disaster management. The type and value of information shared should be assessed, determining the benefits and issues, with credibility and reliability as known concerns. Mapping the tweets in relation to the modelled stages of a disaster can be a useful evaluation for determining the benefits/drawbacks of using data from social networks, such as Twitter, in disaster management.A thematic analysis of tweets’ content, language and tone during the UK Storms and Floods 2013/14 was conducted. Manual scripting was used to determine the official sequence of events, and classify the stages of the disaster into the phases of the Disaster Management Lifecycle, to produce a timeline. Twenty- five topics discussed on Twitter emerged, and three key types of tweets, based on the language and tone, were identified. The timeline represents the events of the disaster, according to the Met Office reports, classed into B. Faulkner’s Disaster Management Lifecycle framework. Context is provided when observing the analysed tweets against the timeline. This illustrates a potential basis and benefit for mapping tweets into the Disaster Management Lifecycle phases. Comparing the number of tweets submitted in each month with the timeline, suggests users tweet more as an event heightens and persists. Furthermore, users generally express greater emotion and urgency in their tweets.This paper concludes that the thematic analysis of content on social networks, such as Twitter, can be useful in gaining additional perspectives for disaster management. It demonstrates that mapping tweets into the phases of a Disaster Management Lifecycle model can have benefits in the recovery phase, not just in the response phase, to potentially improve future policies and activities. Abstract2: The current execution of privacy policies, as a mode of communicating information to users, is unsatisfactory. Social networking sites (SNS) exemplify this issue, attracting growing concerns regarding their use of personal data and its effect on user privacy. This demonstrates the need for more informative policies. However, SNS lack the incentives required to improve policies, which is exacerbated by the difficulties of creating a policy that is both concise and compliant. Standardization addresses many of these issues, providing benefits for users and SNS, although it is only possible if policies share attributes which can be standardized. This investigation used thematic analysis and cross- document structure theory, to assess the similarity of attributes between the privacy policies (as available in August 2014), of the six most frequently visited SNS globally. Using the Jaccard similarity coefficient, two types of attribute were measured; the clauses used by SNS and the coverage of forty recommendations made by the UK Information Commissioner’s Office. Analysis showed that whilst similarity in the clauses used was low, similarity in the recommendations covered was high, indicating that SNS use different clauses, but to convey similar information. The analysis also showed that low similarity in the clauses was largely due to differences in semantics, elaboration and functionality between SNS. Therefore, this paper proposes that the policies of SNS already share attributes, indicating the feasibility of standardization and five recommendations are made to begin facilitating this, based on the findings of the investigation.

Application of agent-based modeling to the study of gender stereotypes

Gender stereotypes are sets of characteristics that people believe to be typically true of a man or woman. We report an agent-based model (ABM) that simulates how stereotypes disseminate in a group through associative mechanisms. The model consists of agents that carry one of several different versions of a stereotype, which share part of their conceptual content. When an agent acts according to his/her stereotype, and that stereotype is shared by an observer, then the latter’s stereotype strengthens. Contrarily, if the agent does not act according to his/ her stereotype, then the observer’s stereotype weakens. In successive interactions, agents develop preferences, such that there will be a higher probability of interaction with agents that confirm their stereotypes. Depending on the proportion of shared conceptual content in the stereotype’s different versions, three dynamics emerge: all stereotypes in the population strengthen, all weaken, or a bifurcation occurs, i.e., some strengthen and some weaken. Additionally, we discuss the use of agent-based modeling to study social phenomena and the practical consequences that the model’s results might have on stereotype research and their effects on a community

Face and content validity of smoking-related and matched control pictures

Smoking-related pictures and matched controls are useful tools in experimental tasks of attentional bias. Noteworthy the procedures used to produce and validate these pairs of pictures are poorly reported. This study aimed to describe the production and evidence of validity of a set of smoking-related pictures and their matched controls. Two studies were conducted to assess validity. An online internet-based survey was used to assess face validity of 12 pictures related to smoking behavior and 12 matched controls. All pictures were colored and were 95mm length x 130mm width. Participants were asked if the pictures were related or not to the smoking behavior and also rated how much each picture was related to smoking behavior. The second study investigated attentional bias in smokers (n = 47) and non-smokers (n = 50), and examined how they assessed all pictures in terms of pleasantness and the 12 smoking-related pictures in terms of relevance to their own smoking behavior. Craving was assessed before and after the experiment. Results indicate that this set of pictures are valid since smoking-related pictures were considered more related to smoking behavior compared to their matched controls. Moreover, smokers showed greater attentional bias for smoking-related pictures than non-smokers. Craving and relevance of the smoking-related pictures were higher in smokers than in non-smokers. Smokers considered smoking-related pictures them less unpleasant than non-smokers. These findings provide evidence of face and content validity of this set of pictures, which will be available to researchers, contributing to maximize the standardization of future investigations.

Cartoons and economics: general analysis based on colombian economic cartoons

May cartoons be considered as a viable and credible source for the study of economics? There is hardly any research on the subject, even though there is a quite significant amount of cartoons with economic content. This suggests that economics (and economists) have not paid enough attention and do not incorporate in their analysis a relevant primary source. The present paper aims to explore the value of using cartoons as a complementary primary source in economic analysis. We present a way of analyzing economic history through cartoons; first, reviewing cartoons which describe particular historical circumstances and second, examining cartoons that represent generic economic situations and are not necessarily linked to a historical period. We choose 17 cartoons, from different cartoonist, especially Colombian cartoonists that may give us an idea of economic matters and economic history.

Using problem-based learning for introducing producer theory and market structure in intermediate microeconomics

This paper shows how instructors can use the problem‐based learning method to introduce producer theory and market structure in intermediate microeconomics courses. The paper proposes a framework where different decision problems are presented to students, who are asked to imagine that they are the managers of a firm who need to solve a problem in a particular business setting. In this setting, the instructors’ role is to provide both guidance to facilitate student learning and content knowledge on a just‐in‐time basis

Analytical methodologies based on X-Ray Fluorescence Spectrometry (XRF) and Inductively Couple Plasma Spectroscopy (ICP) for the assessment of metal dispersal around mining environments

La investigació que es presenta en aquesta tesi es centra en l'aplicació i millora de metodologies analítiques existents i el desenvolupament de nous procediments que poden ser utilitzats per a l'estudi dels efectes ambientals de la dispersió dels metalls entorn a les zones mineres abandonades. En primer lloc, es van aplicar diferents procediments d'extracció simple i seqüencial per a estudiar la mobilitat, perillositat i bio-disponibilitat dels metalls continguts en residus miners de característiques diferents. Per altra banda, per a estudiar les fonts potencials de Pb en la vegetació de les zones mineres d'estudi, una metodologia basada en la utilització de les relacions isotòpiques de Pb determinades mitjançant ICP-MS va ser avaluada. Finalment, tenint en compte l'elevat nombre de mostres analitzades per a avaluar l'impacte de les activitats mineres, es va considerar apropiat el desenvolupament de mètodes analítics d'elevada productivitat. En aquest sentit la implementació d'estratègies quantitatives així com l'aplicació de les millores instrumentals en els equips de XRF han estat avaluades per a aconseguir resultats analítics fiables en l'anàlisi de plantes. A més, alguns paràmetres de qualitat com la precisió, l'exactitud i els límits de detecció han estat curosament determinats en les diverses configuracions de espectròmetres de XRF utilitzats en el decurs d'aquest treball (EDXRF, WDXRF i EDPXRF) per a establir la capacitat de la tècnica de XRF com a tècnica alternativa a les clàssiques comunament aplicades en la determinació d'elements en mostres vegetals.

Semantic-level Visual Content Descriptor combining visual and textual cues as collaterals

In this paper, we introduce a novel high-level visual content descriptor which is devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt to bridge the so called “semantic gap”. The proposed image feature vector model is fundamentally underpinned by the image labelling framework, called Collaterally Confirmed Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts of the images with the state-of-the-art low-level image processing and visual feature extraction techniques for automatically assigning linguistic keywords to image regions. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicates that our proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models.

Case-based analysis in user requirements modelling for knowledge construction

Context: Learning can be regarded as knowledge construction in which prior knowledge and experience serve as basis for the learners to expand their knowledge base. Such a process of knowledge construction has to take place continuously in order to enhance the learners’ competence in a competitive working environment. As the information consumers, the individual users demand personalised information provision which meets their own specific purposes, goals, and expectations. Objectives: The current methods in requirements engineering are capable of modelling the common user’s behaviour in the domain of knowledge construction. The users’ requirements can be represented as a case in the defined structure which can be reasoned to enable the requirements analysis. Such analysis needs to be enhanced so that personalised information provision can be tackled and modelled. However, there is a lack of suitable modelling methods to achieve this end. This paper presents a new ontological method for capturing individual user’s requirements and transforming the requirements onto personalised information provision specifications. Hence the right information can be provided to the right user for the right purpose. Method: An experiment was conducted based on the qualitative method. A medium size of group of users participated to validate the method and its techniques, i.e. articulates, maps, configures, and learning content. The results were used as the feedback for the improvement. Result: The research work has produced an ontology model with a set of techniques which support the functions for profiling user’s requirements, reasoning requirements patterns, generating workflow from norms, and formulating information provision specifications. Conclusion: The current requirements engineering approaches provide the methodical capability for developing solutions. Our research outcome, i.e. the ontology model with the techniques, can further enhance the RE approaches for modelling the individual user’s needs and discovering the user’s requirements.

Temperature-responsive properties and drug solubilization capacity of amphiphilic copolymers based on N-vinylpyrrolidone and vinyl propyl ether

A series of amphiphilic copolymers were synthesized by free-radical copolymerization of N-vinylpyrrolidone (NVP) with vinyl propyl ether (VPE), and the structure of the copolymers was characterized by elemental analysis and gel permeation chromatography. The reactivity of VPE in copolymerization was found to be significantly lower than the reactivity of NVP, which resulted in a decrease of copolymers’ yields and molecular weights with higher content of VPE in the feed mixture. An investigation of the behavior of the copolymers in aqueous solutions at different temperatures by dynamic light scattering revealed the presence of lower critical solution temperature, which depending on the content of VPE ranged within 23−38 °C. Aqueous solutions of these copolymers were studied by fluorescent spectroscopy with pyrene as a polarity probe to reveal the formation of hydrophobic domains. The copolymers were found to be useful for enhancing the solubility of riboflavin in water.