Analysing Police-Recorded Data

The quarterly bulletins on crime statistics in England and Wales are compiled from two sets of data: crime survey and police-recorded crime. Whilst the former is considered to give the most reliable trends, the latter has a greater level detail for a fuller spectrum of crimes types. This paper explores the advantages and problems of analysing police-recorded data for the insights they contain. This is illustrated by examples from an analysis of domestic violence

A Semantic Rule-Based Approach for Software Privacy by Design

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the URI link. Open access journalInformation system business is currently witnessing an increasing demand for system conformance with the international regime of GRC Governance, Risk and Compliance. Among different compliance approaches, data protection and privacy laws plays a key role. In this paper, we propose a compliance requirement analysis method from early stages of system modelling based on a semantically-rich model, where a mapping can be established from data protection and privacy requirements defined by laws and regulations to system business goals and contexts. The early consideration of requirements satisfies Privacy by Design, a key concept in General Data Protection Regulation 2012. The proposed semantic model consists of a number of ontologies each corresponding to a knowledge component within the developed framework of our approach. Each ontology is a thesaurus of concepts in the compliance related to system along with relationships and rules between these concepts that encompass the domain knowledge. The main contribution of the work presented in this paper is the ontology-based compliance framework that demonstrates how description-logic reasoning techniques can be used to simulate legal reasoning requirements employed by legal professions against the description of each ontology

Monitoring dynamics of urban landscape using spatial morphological indices: a case study of Thames Gateway area

Land use changes are results of interaction (over time and space) between humans and their physical environment. Cities and urban landscapes reflect the social, economic, political, environmental as well as technological processes in their changes as evident in their pattern and structures. This study tests the use of morphological indices for monitoring landscapes in a heavily modified landscape (urban). The study analyses the spatial and temporal changes in land use and land cover pattern in the area adjoining the Thames Gateway and selected parts of Greater London, UK. The investigation focuses on an examination of the temporal changes of various land use types as well as their structural properties and distribution over this period

Detecting cyber supply chain attacks on cyber physical systems using Bayesian belief network

Identifying cyberattack vectors on cyber supply chains (CSC) in the event of cyberattacks are very important in mitigating cybercrimes effectively on Cyber Physical Systems CPS. However, in the cyber security domain, the invincibility nature of cybercrimes makes it difficult and challenging to predict the threat probability and impact of cyber attacks. Although cybercrime phenomenon, risks, and treats contain a lot of unpredictability's, uncertainties and fuzziness, cyberattack detection should be practical, methodical and reasonable to be implemented. We explore Bayesian Belief Networks (BBN) as knowledge representation in artificial intelligence to be able to be formally applied probabilistic inference in the cyber security domain. The aim of this paper is to use Bayesian Belief Networks to detect cyberattacks on CSC in the CPS domain. We model cyberattacks using DAG method to determine the attack propagation. Further, we use a smart grid case study to demonstrate the applicability of attack and the cascading effects. The results show that BBN could be adapted to determine uncertainties in the event of cyberattacks in the CSC domain

Automated updating of road network databases: road segment grouping using snap-drift neural network

Presented in this paper is a major step towards an innovative solution of GIS road network databases updating which moves away from existing traditional methods where vendors of road network databases go through the time consuming and logistically challenging process of driving along roads to register changes or GIS road network update methods that are exclusively tied to remote sensing images. Our proposed road database update solution would allow users of GIS road network dependent applications (e.g. in-car navigation system) to passively collect characteristics of any “unknown route” (roads not in the database) on behalf of the provider. These data are transferred back to the provider and inputted into an artificial neural net (ANN) which decides, along with similar track data provided by other service users, whether to automatically update (add) the “unknown road” to the road database on probation allowing subsequent users to see the road on their system and use it if need be. At a later stage when there is enough certainty on road geometry and other characteristics the probationary flag could be lifted and permanently added to the road network database. Towards this novel approach we mimicked two journey scenarios covering two test sites and aimed to group the road segments from the journey into their respective road types using the snap-drift neural network (SDNN). The performance of the SDNN is presented and its potential in the proposed solution is investigated

Constructing and evaluating contextual indices using GIS: a case of primary school performance tables

School performance tables emphasising aggregate examination scores have become an enduring feature of the educational landscape. These tables are problematic, even flawed, as a guide, given the recognised broad link between pupil performance and the social and economic environment in which they live. There is continued interest in being able to contextualise school examination scores so as better to reflect relative achievement. The inherent spatiality of inequalities lends itself to analysis using geographical information systems (GIS), particularly in the task of creating context from geodemographic and lifestyle data. In this paper I explore a methodology for creating and analysing a contextual index of ambient disadvantage centred on robust normalisation of data and illustrate this by using census variables, pupil numbers, and test scores for 3687 primary schools in the north of England. Relevant census variables are interpolated using ordinary kriging with an element of smoothing so as to simulate, to some extent, the effect of school catchment areas. Key features of using robust normalisation are that variable weights can be tested and the internal level of support for an index, the weighted absolute deviation, can be calculated and mapped. This latter quantity provides a quality measure for an index. The methodology is critically assessed in relation to other recent approaches.

A Fuzzy Set Approach to Using Linguistic Hedges in Geographical Information Systems

Spatial data quality has been attracting much interest. Much of the problem lies in the degree to which current data structures are unable to model the real world and the way imperfections in the data may propagate during analyses and cast doubt on the validity of the outcomes. Much of the research has concentrated on the quantitative accuracy of spatial data, the derivation of indices and their propagation through analyses. Geographical data invariably includes an element of interpretation for which linguistic hedges of uncertainty may be generated. The paper presents a new technique of handling such expressions in a GIS through fuzzy expectation - intuitive probabilities linked to stylized fuzzy sets. By using fuzzy expectation as linguistic building blocks, many of the difficulties in using fuzzy set descriptors in GIS have been overcome. The stylized fuzzy sets can be propagated using Boolean operators to give a resultant fuzzy set which can be ‘translated’ back into a linguistic quality statement. For the first time, linguistic criteria of fitness-for-use can be derived for GIS outputs regardless of the language being used

GIS, environmental modeling and engineering

Allan Brimicombe.xv, 361 p. : ill., maps ; 25 cm