Thesis (M.A.)--University of Hong Kong, 1974. / Also available in print.

Thesis (M.Soc.Sc.)--University of Hong Kong, 1984. / Also available in print.

Thesis (Ph. D.)--University of Pennsylvania, 1996. / Includes bibliographical references (leaves 331-338).

The popularity of location empowered devices such as GPS enabled smart-phones has immensely amplified the use of location-based services in social networks. This happened by allowing users to share Geo-tagged contents such as current locations/check-ins with their social network friends. These location-aware social networks are called Location-based Social Networks (LBSN), and examples include Foursquare and Gowalla. The data of LBSNs are being used for providing different kinds of services such as the recommendation of locations, friends, activities, and media contents, and the prediction of user's locations. To provide such services, different queries are utilized that exploit activity/check-in data of users. Usually, LBSN data is divided into two parts, a social graph that encapsulates the friendships of users and an activity graph that maintains the visit history of users at locations. Such a data separation is scalable enough for processing queries that directly utilize friendship information and visit history of users. These queries are called user and activity analytic queries. The visits of users at locations create relationships between those locations. Such relationships can be built on different features such as common visitors, geographical distance, and mutual location categories between them. The process of analysing such relationships for optimizing location-based services is termed Location Analytics. In location analytics, we expose the subjective nature of locations that can further be used for applications in the domain of prediction of visitors, traffic management, route planning, and targeted marketing.In this thesis, we provide a general LBSN data model which can support storage and processing of queries required for different applications, called location analytics queries. The LBSN data model we introduce, segregates the LBSN data into three graphs: the social graph, the activity graph, and the location graph. The location graph maintains the interactions of locations among each other. We define primitive queries for each of these graphs. In order to process an advanced query, we express it as a combination of these primitive queries and process them on corresponding graphs in parallel. We further provide a distributed data processing framework called GeoSocial-GraphX (GSG). GSG implements the aforementioned LBSN data model for efficient and scalable processing of the queries. We further exploit the location graph for providing novel location analytics queries in the domain of influence maximization and visitor prediction. We introduce a notion of location influence. Such influence can capture the interactions of locations based on their visitors and can be used for propagation of information between them. The applications of such a query lie in the domain of outdoor marketing, and simulation of virus and news propagation. We also provide a unified system IMaxer that can evaluate and compare different information propagation mechanisms. We further exploit the subjective nature of locations by analysing the mobility behaviour of their visitors. We use such information to predict the individual visitors as well as the groups of visitors (cohorts) in future for those locations. The prediction of visitors can be used for better event planning, traffic management, targeted marketing, and ride-sharing services.In order to evaluate the proposed frameworks and approaches, we utilize data from four real-life LBSNs: Foursquare, Brightkite, Gowalla, and Wee Places. The detailed LBSN data mining and statistically significant experimental evaluation results show the effectiveness, efficiency, and scalability of our proposed methods. Our proposed approaches can be employed in real systems for providing life-care services. / Doctorat en Sciences de l'ingénieur et technologie / The portal is not showing my complete name. The name (my complete name), I want to have on the diploma is "Muhammad Aamir Saleem". Please correct this issue. / info:eu-repo/semantics/nonPublished

Since August 2010, Facebook has entered the self-reported positioning world by providing the check-in service to its users. This service allows users to share their physical location using the GPS receiver in their mobile devices such as a smart-phone, tablet, or smart-watch. Over the years, big datasets of recorded check-ins have been collected with increasing popularity of social networks. Analyzing the check-in datasets reveals valuable information and patterns in users’ check-in behavior as well as places check-in history. The analysis results can be used in several areas including business planning and financial decisions, for instance providing location-based deals. In this thesis, we leverage novel data mining methodology to learn from big check-in data and predict the next check-in place based on only places’ history and with no reference to individual users. To this end, we study a large Facebook check-in dataset. This dataset has a high level of noise in location coordinates due to multiple collection sources, which are users’ mobile devices. The research question is how we can leverage a noise impact reduction technique to enhance performance of prediction model. We design our own noise handling mechanism to deal with feature noise. The predictive model is generated by Random Forest classification algorithm in a shared-memory parallel environment. We represent how the performance of predictors is enhanced by minimizing noise impacts. The solution is a preprocessing feature noise cleansing approach implemented in R and works fast for big check-in datasets.

M.A. / The accessibility of a region or a country is important for maintaining a strong development rate. Its necessity in research has often been pointed out and especially in research on transportation geography overseas as well as in the Republic of South Africa. This study investigates the spatial variation in the road network link development patterns in Development Region G in order to establish which districts are adequately accessible and which are not, and to establish the relation between the existing accessibility and level of development in the study area. Due to the extent of the problem which had to be investigated, it was not possible to analyse the transport and communication system in the Republic of South-Africa as a whole ...

No description available.

No description available.

While significant research effort has been dedicated to wireless position location over the past decades, most location security aspects have been overlooked. Recently, with the proliferation of diverse wireless devices and the desire to determine their position, there is an increasing concern about the security of location information which can be spoofed or disrupted by adversaries or unreliable signal sources. This dissertation addresses the problem of securing a radio location system against location spoofing, specifically the characterization, analysis, detection, and localization of location spoofing attacks by focusing on fundamental location estimation issues. The objective of this dissertation is four-fold. First, it provides an overview of fundamental security issues for position location, particularly associated with range-based localization. Of particular interest are security risks and vulnerabilities in location estimation, types of localization attacks, and their impact. The second objective is to characterize the effects of signal strength and beamforming attacks on range estimates and the resulting position estimate. The characterization can be generalized to a variety of location spoofing attacks and provides insight into the anomalous behavior of range and location estimators when under attack. Through this effort we can also identify effective attacks that are of particular interest to attack detection and localization. The third objective is to develop an effective technique for attack detection which requires neither prior environmental nor statistical knowledge. This is accomplished by exploiting the bilateral behavior of a hybrid framework using two received signal strength (RSS) based location estimators. We show that the resulting approach is effective at detecting attacks with the detection rate increasing with the severity of the induced location error. The last objective of this dissertation is to develop a localization method resilient to attacks and other adverse effects. Since the detection and localization approach relies solely on RSS measurements in order to be applicable to a wide range of wireless systems and scenarios, this dissertation focuses on RSS-based position location. Nevertheless, many of the basic concepts and results can be applied to any range-based positioning system. / Ph. D.

This research presents an analysis of the improvement in the performance of a class of fault tolerant multistage interconnection networks. In the network discussed here, fault tolerance is achieved by providing multiple redundant paths between the source and destination. The extra paths are obtained by providing redundant links between switching elements within a stave (intra-stage links), thereby increasing the switching element complexity. The techniques used in the construction of this network, its properties, advantages, and disadvantages are discussed. While early studies focused their effort in analyzing the fault tolerant characteristics of the network and the performance in a circuit switched environment, this investigation complements the previous work by examining fie performance of a packet switched network. The reasons for the choice of the architecture that include factors like hardware complexity, cost and simplicity of control algorithm are analyzed. The study concentrates on improving the run-time performance of the fault tolerant network. by using these multiple paths not only in the presence of a fault, but also in a fault-free environment. The throughput of the packet switched network in the presence of a fault, congestion and when fault free are analyzed. A description of the investigation, assumptions and factors used for the study, a cost analysis, and the results of the simulation analyses is included. / Master of Science