Winnowing ontologies based on application use

The requirements of specific applications and services are often over estimated when ontologies are reused or built. This sometimes results in many ontologies being too large for their intended purposes. It is not uncommon that when applications and services are deployed over an ontology, only a few parts of the ontology are queried and used. Identifying which parts of an ontology are being used could be helpful to winnow the ontology, i.e., simplify or shrink the ontology to smaller, more fit for purpose size. Some approaches to handle this problem have already been suggested in the literature. However, none of that work showed how ontology-based applications can be used in the ontology-resizing process, or how they might be affected by it. This paper presents a study on the use of the AKT Reference Ontology by a number of applications and services,and investigates the possibility of relying on this usage information to winnow that ontology

Social dynamics in conferences: analyses of data from the Live Social Semantics application

Popularity and spread of online social networking in recent years has given a great momentum to the study of dynamics and patterns of social interactions. However, these studies have often been confined to the online world, neglecting its interdependencies with the offline world. This is mainly due to the lack of real data that spans across this divide. The Live Social Semantics application is a novel platform that dissolves this divide, by collecting and integrating data about people from (a) their online social networks and tagging activities from popular social networking sites, (b) their publications and co-authorship networks from semantic repositories, and (c) their real-world face-to-face contacts with other attendees collected via a network of wearable active sensors. This paper investigates the data collected by this application during its deployment at three major conferences, where it was used by more than 400 people. Our analyses show the robustness of the patterns of contacts at various conferences, and the influence of various personal properties (e.g. seniority, conference attendance) on social networking patterns

Virtual Machines Embedding for Cloud PON AWGR and Server Based Data Centres

In this study, we investigate the embedding of various cloud applications in PON AWGR and Server Based Data Centres

Semantics, sensors, and the social web: The live social semantics experiments

The Live Social Semantics is an innovative application that encourages and guides social networking between researchers at conferences and similar events. The application integrates data and technologies from the Semantic Web, online social networks, and a face-to-face contact sensing platform. It helps researchers to find like-minded and influential researchers, to identify and meet people in their community of practice, and to capture and later retrace their real-world networking activities at conferences. The application was successfully deployed at two international conferences, attracting more than 300 users in total. This paper describes this application, and discusses and evaluates the results of its two deployment

Providing Enhanced Social Interaction Services for Industry Exhibitors at Large Medical Conferences

Large medical conferences offer opportunities for participants to find industry exhibitors that offer products and services relevant to their professional interests. Companies often invest significant effort in promotions that encourage participants to spend time at their stand (e.g. providing free gifts, leaflets, running competitions) and register some contact details. Attendees will use the conference to find others who also share similar professional interests, as well as keep up to date with developments on products such has pharmaceuticals and medical equipment. From both perspectives, a number of improvements can be made to enhance the overall experience by using existing active RFID technology: Vendors would be able to more closely monitor the success of their promotions with statistics on the stand's visitors, as well as find more potential customers by using real-time visualizations; Participants would be able to log their social interactions, keeping an electronic history of the people they have met. The SocioPatterns project and Live Social Semantics experiments have recently demonstrated a scalable and robust infrastructure that would support these kinds of improvements. In this paper, we propose an infrastructure that provides enhanced social interaction services for vendors and participants by using small active RFID badges worn by attendees and attached to fixed locations

Biodegradable PLGA Based Nanoparticles for Sustained Regional Lymphatic Drug Delivery

The purpose of this work is to evaluate biodegradable drug carriers with defined size, hydrophobicity, and surface charge density for preferential lymphatic uptake and retention for sustained regional drug delivery. PLGA–PMA:PLA-PEG (PP) nanoparticles of defined size and relative hydrophobicity were prepared by nanoprecipitation method. These were compared with PS particles of similar sizes and higher hydrophobicity. PLGA–PMA:PLGA-COOH (PC) particles at 80:20, 50:50, and 20:80 ratios were prepared by nanoprecipitation for the charge study. Particle size and zeta potential were characterized by dynamic light scattering and laser doppler anemometry, respectively. Particles were administered in vivo to rats subcutaneously. Systemic and lymph node uptake was evaluated by marker recovery. Lymphatic uptake and node retention of PP nanoparticles was shown to be inversely related to size. Lymphatic uptake and node retention of PP particles, as compared to PS particles, was shown to be inversely related to hydrophobicity. Lastly, lymphatic uptake and node retention of PC nanoparticles were directly related to the anionic charge on the particles. In vivo lymphatic uptake and retention in a rat model indicates that the 50 nm PP particles are ideal for sustained regional delivery into the lymphatics for prevention/treatment of oligometastases

Evaluating semantic relations by exploring ontologies on the Semantic Web

We investigate the problem of evaluating the correctness of a semantic relation and propose two methods which explore the increasing number of online ontologies as a source of evidence for predicting correctness. We obtain encouraging results, with some of our measures reaching average precision values of 75%

Simple broadband circularly polarized monopole antenna with two asymmetrically connected U-shaped parasitic strips and defective ground plane

A simple compact broadband circularly polarized monopole antenna, which comprises a simple monopole, a modified ground plane with an implementing triangular stub and two asymmetrically connected U-shaped parasitic strips, is proposed. Simulation results show that the proposed compact antenna (0.62λo×0.68λo) achieves a 10-dB impedance bandwidth (IBW) of 111% (1.7 to 5.95 GHz) and a 3-dB axial ratio bandwidth (ARBW) of 61% (3.3–6.2 GHz) with a peak gain between 2.9–4 dBi for the entire ARBW. With its broad IBW and ARBW, compact size and simple structure, the proposed antenna is suitable for different wireless communications

Prediction of sulphide build-up in filled sewer pipes

Millions of dollars are being spent worldwide on the repair and maintenance of sewer networks and wastewater treatment plants. The production and emission of hydrogen sulphide has been identified as a major cause of corrosion and odour problems in sewer networks. Accurate prediction of sulphide build-up in a sewer system helps engineers and asset managers to appropriately formulate strategies for optimal sewer management and reliability analysis. This paper presents a novel methodology to model and predict the sulphide build-up for steady state condition in filled sewer pipes. The proposed model is developed using a novel data-driven technique called evolutionary polynomial regression (EPR) and it involves the most effective parameters in the sulphide build-up problem. EPR is a hybrid technique, combining genetic algorithm and least square. It is shown that the proposed model can provide a better prediction for the sulphide build-up as compared with conventional models