Amir Pourabdollah

Towards an Authoritative OpenStreetMap: Conflating OSM and OS OpenData National Maps' Road Network

The quality aspects of OpenStreetMap (OSM), as the global representation of crowd-sourced mapping, have always been of priomary concern to academics. While the methodologies for checking its quality against the national maps have been implemented by a number of studies, there are minimal works on how to practically improve the quality of OSM towards being an authoritative map source. This paper presents a method for conflating road attributes, namely the name and reference code, of OSM with the Open Data provided by Ordnance Survey (the British national mapping agency). The added values in the proposed methodology include the daily updates and serving of the conflated maps via open Web Services. More importantly, the OSM crowd correction is facilitated by frequently highlighting and web-serving the individual differences. There are currently over 5,800 differences in matching road names and references between the two datasets. In addition to describing the conflation methodology, the different geographic distribution patterns of the identified differences are discussed. A negative effect of the road density on the ratio of the mismatched features between the two datasets is observable, evidenced by their different geographical distribution over the map. It is shown that the best correspondence between attributes exists in the very dense areas, followed by the very low density areas, and lastly in the middle to large sized cities.

Quality assessment of OpenStreetMap data using trajectory mining

Abstract OpenStreetMap (OSM) data are widely used but their reliability is still variable. Many contributors to OSM have not been trained in geography or surveying and consequently their contributions, including geometry and attribute data inserts, deletions, and updates, can be inaccurate, incomplete, inconsistent, or vague. There are some mechanisms and applications dedicated to discovering bugs and errors in OSM data. Such systems can remove errors through user-checks and applying predefined rules but they need an extra control process to check the real-world validity of suspected errors and bugs. This paper focuses on finding bugs and errors based on patterns and rules extracted from the tracking data of users. The underlying idea is that certain characteristics of user trajectories are directly linked to the type of feature. Using such rules, some sets of potential bugs and errors can be identified and stored for further investigations.

Which spatial data quality can be meta-propagated?

As a mid-way between the usability criteria proposed by the upcoming ISO 19157 and error propagation methods, the concept of meta-propagation allows derivation of an estimate of the propagated uncertainties using only metadata information about the quality of the datasets and processes used in a scientific workflow. The principle of meta-propagation has been illustrated using the thematic accuracy with the quantitative attribute accuracy sub-element. This paper explores other data quality elements that can be meta-propagated. Using a similar approach as for thematic accuracy, we address further the metadata quality for the processes and their links with data quality. The paper focuses on generic principles and a few specific situations where appropriate quality measures can be fully described. Basic meta-propagation, based on separability of the assessments (i.e. one input to one output), is presented but the paper also discusses the potential of using quality measures for non-separable approaches. Spatiality of the measures, i.e. taking the benefit of a spatial data quality value being a map, is also investigated. Practical considerations between the burden of deriving needed quality metadata and the will to derive useful uncertainty assessments for large scientific workflows are also expressed.

Changes under the hood - a new type of non-singleton fuzzy logic system

A major asset of fuzzy logic systems is dealing with uncertainties arising in their various applications, thus it is important to make them achieve this task as effectively and comprehensively as possible. While singleton fuzzy logic systems provide some capacity to deal with such uncertainty aspects, non-singleton fuzzy logic systems (NSFLSs) have further enhanced this capacity, particularly in handling input uncertainties. This paper proposes a novel approach to NSFLSs, which further develops this potential by changing the method of handling input fuzzy sets within the inference engine. While the standard approach is getting the maximum of the intersection between inputs and antecedents fuzzy sets (in the “pre-filtering” stage), it is proposed to employ the centroid of the intersection as the basis of each rules firing degree. The motivation is to capture the interaction of input and antecedent fuzzy sets with high fidelity, thus making NSFLSs more sensitive to the inputs uncertainty information. The testbed is the common problem of Mackey-Glass time series prediction in the presence of input noise. Analyses of the results show that the new method outperforms the standard approach (by reducing the prediction error) and has potential for a more efficient uncertainty handling in NSFLS applications.

Towards data-driven environmental planning and policy design-leveraging fuzzy logic to operationalize a planning framework

Environmental planning is complex, and requires careful consideration of a large number of factors, including quantitative ones (e.g., water balance) and qualitative ones (e.g., heterogeneous stakeholder input). To better integrate these factors, value-driven frameworks have been designed in the environmental conservation community. These frameworks are currently largely utilized manually by conservation and policy experts in order to inform policy design. In this paper, we present a fuzzy logic based system, which has been developed to operationalize the existing manual framework while preserving essential qualities, including the capture of uncertainty in the data sources and a consistent interpretability of the underlying automatic reasoning mechanisms. We provide a detailed description of the current implementation which can be applied in the operationalization of policy design and planning tasks in a range of natural resources management cases, followed by a set of concrete, practical outputs for a studied use case in Western Australia. Finally, we highlight remaining limitations and future work.

A similarity-based inference engine for non-singleton fuzzy logic systems

In non-singleton fuzzy logic systems (NSFLSs) input uncertainties are modelled with input fuzzy sets in order to capture input uncertainty such as sensor noise. The performance of NSFLSs in handling such uncertainties depends both on the actual input fuzzy sets (and their inherent model of uncertainty) and on the way that they affect the inference process. This paper proposes a novel type of NSFLS by replacing the composition-based inference method of type-1 fuzzy relations with a similarity-based inference method that makes NSFLSs more sensitive to changes in the inputs uncertainty characteristics. The proposed approach is based on using the Jaccard ratio to measure the similarity between input and antecedent fuzzy sets, then using the measured similarity to determine the firing strength of each individual fuzzy rule. The standard and novel approaches to NSFLSs are experimentally compared for the well-known problem of Mackey-Glass time series predictions, where the NSFLSs inputs have been perturbed with different levels of Gaussian noise. The experiments are repeated for system training under both noisy and noise-free conditions. Analyses of the results show that the new method outperforms the standard approach by substantially reducing the prediction errors.

On transitioning from type-1 to interval type-2 fuzzy logic systems

Capturing the uncertainty arising from system noise has been a core feature of fuzzy logic systems (FLSs) for many years. This paper builds on previous work and explores the methodological transition of type-1 (T1) to interval type-2 fuzzy sets (IT2 FSs) for given “levels” of uncertainty. Specifically, we propose to transition from T1 to IT2 FLSs through varying the size of the Footprint Of Uncertainty (FOU) of their respective FSs while maintaining the original FS shape (e.g., triangular) and keeping the size of the FOU over the FS as constant as possible. The latter is important as it enables the systematic relating of FOU size to levels of uncertainty and vice versa, while the former enables an intuitive comparison between the T1 and T2 FSs. The effectiveness of the proposed method is demonstrated through a series of experiments using the well-known Mackey-Glass (MG) time series prediction problem. The results are compared with the results of the IT2 FS creation method introduced in [1] which follows a similar methodology as the proposed approach but does not maintain the membership function (MF) shape.

UCML: Ubiquitous Control Modeling Language for Android Platform

Ubiquitous Control Modeling Language (UCML) is an XML-based language aiming at utilizing the local resources of smart handheld devices and making mobile phone users aware and involved in contributing to the technology that exists in their hands. UCML focuses on developing and executing ubiquitous control applications within smart mobile devices by typing specific predefined XML elements in UCML modules directly on the device. The module function is to acquire data from mobile phone built-in sensors, apply conditions on these data, and trigger a response when these conditions are satisfied. The user can identify which sensor, condition and response to be used. UCML application has been designed to be friendly, easy-to-use, natural-understanding language that is suitable for sensor-interested mobile phone users. Google’s Android is the chosen platform to be the underlying operating system for UCML. This paper proposes the On-Device Development approach (ODD) and discusses some technologies and tools that have influenced the development of UCML. The current UCML version represents basic prototype software with sample conditions and responses. Therefore, it has the potential to be extended and upgraded, allowing integration with other applications and to work with remote sensors and actuators to mimic a complete Ubiquitous Computing environment.

Are we talking about the same structure?: a unified approach to hypertext links, xml, rdf and zigzag

There are many different hypertext systems and paradigms, each with their apparent advantages. However the distinctions are perhaps not as significant as they seem. If we can reduce the core linking functionality to some common structure, which allows us to consider hypertext systems within a common model, we could identify what, if anything, distinguishes hypertext systems from each other. This paper offers such a common structure, showing the conceptual similarities between each of these systems and paradigms.

Towards low-cost collaborative mobile positioning

In the lack of an infrastructure-independent solution for an integrated indoor/outdoor positioning, this paper studies the challenges to realize a public and low-cost solution, based on mass users of multiple-sensor mobile phones. Having multiple location sensors in the mobile phones with different levels of accuracy, having many users in the environment which can share their absolute or relative localizations, in addition to the ability of the phones to access external data sources may lead to an integrated algorithms which are called collaborative positioning. The stakeholders of the solution (mobile phones sensors, users, fixed stations and external databases) are involved in an iterative algorithm to estimate or improve the accuracy of each nodes position based on statistical models. This paper also provides scenarios and initial solution to the problem of collaborative mobile phone positioning based on signal strength measurement. “Position broadcasting” and “Peer-to-peer correction” has been suggested as possible design approaches.