Investigating the use of semantic technologies in spatial mapping applications

Semantic Web Technologies are ideally suited to build context-aware information retrieval applications. However, the geospatial aspect of context awareness presents unique challenges such as the semantic modelling of geographical references for efficient handling of spatial queries, the reconciliation of the heterogeneity at the semantic and geo-representation levels, maintaining the quality of service and scalability of communicating, and the efficient rendering of the spatial queries' results. In this paper, we describe the modelling decisions taken to solve these challenges by analysing our implementation of an intelligent planning and recommendation tool that provides location-aware advice for a specific application domain. This paper contributes to the methodology of integrating heterogeneous geo-referenced data into semantic knowledgebases, and also proposes mechanisms for efficient spatial interrogation of the semantic knowledgebase and optimising the rendering of the dynamically retrieved context-relevant information on a web frontend

A Simulation-Based Performance Evaluation of AODV and DSR in Mobile Ad-Hoc Networks (MANETs)

This work evaluates and compares the performance of two reactive routing protocols for mobile ad-hoc networks: Ad hoc On-demand Distance Vector (AODV) and Dynamic Source Routing (DSR). The study focuses on the design and evaluation of routing protocols in mobile ad-hoc networks. Study and implementation of these protocols are been carried out using network simulator (ns2) and metrics such as Packet Delivery Fraction, Average end-to-end Delay, Routing overhead and Normalized Routing are used for performance analysis. Results are presented as a function of these metrics and the graphs generated show that DSR performs better than AODV when fewer nodes are been used

Descriptive epidemiology of salivary gland neoplasms in Nigeria: An AOPRC multicenter tertiary hospital study

Objectives: Accurate diagnosis of salivary gland neoplasms (SGN) in many centers in Africa is limited by poor diagnostic resources and ancillary services. Hence, we have carried out a multicenter epidemiological study to understand the true burden of SGN in Nigeria. Method: In this descriptive cross‐sectional study, we have deployed resources available to members of the African Oral Pathology Consortium (AOPRC) to examine the burden of salivary gland lesions in Nigeria, using a multicenter approach. Data from seven major tertiary health institutions in northern, western, and southern Nigeria were generated using a standardized data extraction format and analyzed using the Epi‐info software (Version 7.0, Atlanta, USA). Result: Of the 497 cases examined across the seven centers, we observed that SGN occurred more in females than males. Overall, pleomorphic salivary adenoma (PA) was found to be the most common. PA was found to be the commonest benign SGN while adenocystic carcinoma (ADCC) was the commonest malignant SGN. Regional variations were observed for age group, diagnosis, and gender distribution. Significant statistical differences were found between males and females for malignant SGNs (p‐value=0.037). Conclusion: We found regional variation in the pattern of distribution of SGN in Nigeria. This is the largest multicenter study of SGN in Nigeria, and our findings are robust and representative of the epidemiology of this neoplasm in Nigeria

Consolidating Heterogeneous Enterprise Data for Named Entity Linking and Web Intelligence

Linking named entities to structured knowledge sources paves the way for state-of-the-art Web intelligence applications which assign sentiment to the correct entities, identify trends, and reveal relations between organizations, persons and products. For this purpose this paper introduces Recognyze, a named entity linking component that uses background knowledge obtained from linked data repositories, and outlines the process of transforming heterogeneous data silos within an organization into a linked enterprise data repository which draws upon popular linked open data vocabularies to foster interoperability with public data sets. The presented examples use comprehensive real-world data sets from Orell Füssli Business Information, Switzerland's largest business information provider. The linked data repository created from these data sets comprises more than nine million triples on companies, the companies' contact information, key people, products and brands. We identify the major challenges of tapping into such sources for named entity linking, and describe required data pre-processing techniques to use and integrate such data sets, with a special focus on disambiguation and ranking algorithms. Finally, we conduct a comprehensive evaluation based on business news from the New Journal of Zurich and AWP Financial News to illustrate how these techniques improve the performance of the Recognyze named entity linking component