Novel evaluation metrics for sparse spatio-temporal point process hotspot predictions - a crime case study

Many physical and sociological processes are represented as discrete events in time and space. These spatio-temporal point processes are often sparse, meaning that they cannot be aggregated and treated with conventional regression models. Models based on the point process framework may be employed instead for prediction purposes. Evaluating the predictive performance of these models poses a unique challenge, as the same sparseness prevents the use of popular measures such as the root mean squared error. Statistical likelihood is a valid alternative, but this does not measure absolute performance and is therefore difficult for practitioners and researchers to interpret. Motivated by this limitation, we develop a practical toolkit of evaluation metrics for spatio-temporal point process predictions. The metrics are based around the concept of hotspots, which represent areas of high point density. In addition to measuring predictive accuracy, our evaluation toolkit considers broader aspects of predictive performance, including a characterisation of the spatial and temporal distributions of predicted hotspots and a comparison of the complementarity of different prediction methods. We demonstrate the application of our evaluation metrics using a case study of crime prediction, comparing four varied prediction methods using crime data from two different locations and multiple crime types. The results highlight a previously unseen interplay between predictive accuracy and spatio-temporal dispersion of predicted hotspots. The new evaluation framework may be applied to compare multiple prediction methods in a variety of scenarios, yielding valuable new insight into the predictive performance of point process-based prediction

Determining the optimal spatial and temporal thresholds that maximise the predictive accuracy of the Prospective Space-Time Scan Statistic (PSTSS) hotspot method

The spatial and temporal thresholds (K and T) are two key parameters that control the performance of the prospective space-time scan statistical (PSTSS) hotspot method. This study proposes an objective function approach, in which the optimal values of K and T that maximize the mean hit rate (a measure of predictive accuracy), are determined. The proposed approach involves sweeping through a range of values defined for each parameter and monitors their impacts on the mean hit rate. A case study of the crime data sets of the South Chicago area is presented in which 100 one-day consecutive predictions are carried out. Two aspects of the derived results are significant. First, is that there is a trade-off between the predictive accuracy obtainable from the use of PSTSS and the level of hotspot coverage. Second, is that K is found to have more influence on the accuracy than T. As K increases in size, the accuracy level decreases, whereas there is no notable impact of T on the accuracy, particularly when T _ 30 days. This study also demonstrated the distinctiveness of PSTSS as a hotspot method as compared to other conventional hotspot methods. Lastly, it is argued that the approach demonstrated in this study is not only applicable to crime hotspot prediction, but could also be used in many other domains where the PSTSS technique is used

Microbiological Quality of Kunnu-Zaki Drinks Sold in Some selected Towns in Osun State, Nigeria

The microbiological quality of freshly processed and hawked kunnu-zaki drinks, a common Nigerian non-alcoholic beverage was investigated in some selected towns in Osun State, South Western Nigeria. A total of nine (9) towns were assessed. Kunnu-zaki drinks were purchased from these towns on twelve different occasions for a period of six month. The samples were microbiologically analyzed using standard methods. pH values ranged from 3.09 - 4.21 in East and West senatorial district. The TTA of the samples ranged from 0.32 - 0.49 in Central and East senatorial district. All the screened drink samples had varying levels of bacterial contamination ranging from 4.2 x 103 to 15.0 x 103 CFU/ml, 4.1 x 104 to 9.6 x 104 CFU/ml and 3.5 x 105 to 9.0 x 105 CFU/ml for total bacteria, coliform and E. coli count respectively. Total coliform count on MPN ranged from 3 MPN/ml to 93 MPN/ml. 77.78% of the total sampled drinks (n=108) that is (84/108) had bacteria and fungi count. While all the drinks sampled had total coliform count on MPN exceeding the recommended safe level of zero organisms detectable per 100ml. Seven (7) bacteria species were isolated from the kunnu-zaki drink sampled. The bacteria isolated were Escherichia coli, Bacillus species, Staphylococcus species, Pseudomonas species, Streptococcus specie, Enterobacter species, and Klebsiella species. Fungal count ranged from 3.3 x 106 to 8.0 x 106 CFU/ml respectively. Four (4) fungi were also isolated which include Aspergillus fumigatus, Penicilium italicum, Aspergillus Niger and Aspergillus flavus. It can therefore be concluded that the presence of these isolated organisms in kunnu-zaki samples analyzed in Osun State could serve as indicator for the need to promote awareness about the possible health hazards that could arise due to the unhygienic ways of handling and processing of the beverage

Knowledge audit as an important tool in organizational management:A review of literature

The purpose of this paper is to review current literature on knowledge management and highlight the importance of knowledge audit in bringing about a holistic knowledge solution to knowledge management. Based on the review of literature on knowledge management, this study points out the role of knowledge audit in solving the challenges in organizations’ tacit and explicit knowledge. Specifically, the paper concentrates on knowledge audit, knowledge risk and international and national standards on knowledge audit processes. The contribution of this study to literature are the suggestions that knowledge risk and international standards procedures could be applied to knowledge audit. The important conclusion of this paper is that knowledge risk management has not been fully explored in the study of knowledge audit. The paper addresses the research question of what organizations must embark on in the process of knowledge audit. The paper attempts to provide answer to the question by highlighting the importance of knowledge audit and the reasons why organizations carry out knowledge audit, and also the existing knowledge audit frameworks and methodologies

CPC: Crime, Policing and Citizenship - Intelligent Policing and Big Data

Crime, Policing and Citizenship (CPC) – Space-Time Interactions of Dynamic Networks has been a major UK EPSRC-funded research project. It has been a multidisciplinary collaboration of geoinformatics, crime science, computer science and geography within University College London (UCL), in partnership with the Metropolitan Police Service (MPS). The aim of the project has been to develop new methods and applications in space-time analytics and emergent network complexity, in order to uncover patterning and interactions in crime, policing and citizen perceptions. The work carried out throughout the project will help inform policing at a range of scales, from the local to the city-wide, with the goal of reducing both crime and the fear of crime. The CPC project is timely given the tremendous challenging facing policing in big cities nationally and globally, as consequences of changes in society, population structure and economic well-being. It addresses these issues through an intelligent approach to data-driven policing, using daily reported crime statistics, GPS traces of foot and vehicular patrols, surveys of public attitudes and geo-temporal demographic data of changing community structure. The analytic focus takes a spatio-temporal perspective, reflecting the strong spatial and temporal integration of criminal, policing and citizen activities. Street networks are used throughout as a basis for analysis, reflecting their role as a key determinant of urban structure and the substrate on which crime and policing take place. The project has presented a manifesto for ‘intelligent policing’ which embodies the key issues arising in the transition from Big Data into actionable insights. Police intelligence should go beyond current practice, incorporating not only the prediction of events, but also how to respond to them, and how to evaluate the actions taken. Cutting-edge network-based crime prediction methods have been developed to accurately predict crime risks at street segment level, helping police forces to focus resources in the right places at the right times. Methods and tools have been implemented to support senior offices in strategic planning, and to provide guidance to frontline officers in daily patrolling. To evaluate police performance, models and tools have been developed to aid identification of areas requiring greater attention, and to analyse the patrolling behaviours of officers. Methods to understand and model confidence in policing have also been explored, suggesting strategies by which confidence in the police can be improved in different population segments and neighbourhood areas. A number of tools have been developed during the course of the project include data-driven methods for crime prediction and for performance evaluation. We anticipate that these will ultimately be adopted in daily policing practice and will play an important role in the modernisation of policing. Furthermore, we believe that the approaches to the building of public trust and confidence that we suggest will contribute to the transformation and improvement of the relationship between the public and police

Influence of binder type and process parameters on the compression properties and microbial survival in diclofenac tablet formulations

The influence of binder type and process parameters on the compression properties and microbial survival in diclofenac tablet formulations were studied using a novel gum from Albizia zygia. Tablets were produced from diclofenac formulations containing corn starch, lactose and dicalcium phosphate. Formulations were analyzed using the Heckel and Kawakita plots. Determination of microbial viability in the formulations was done on the compressed tablets of both contaminated and uncontaminated tablets prepared from formulations. Direct compression imparted a higher plasticity on the materials than the wet granulation method. Tablets produced by wet granulation presented with a higher crushing strength than those produced by the direct compression method. Significantly higher microbial survival (pA influência do tipo de ligante e os parâmetros do processo de propriedades de compressão e sobrevivência microbiana em comprimidos de diclofenaco foram estudados utilizando uma nova goma de Albizia zygia. Os comprimidos foram produzidos a partir de formulações de diclofenaco contendo amido de milho, lactose e fosfato bicálcico. As formulações foram analisadas usando os gráficos de Heckel e Kawakita. A determinação da viabilidade microbiana nas formulações foi feita nos comprimidos contaminados e não contaminados preparados a partir de formulações. A compressão direta confere maior plasticidade dos materiais do que o método de granulação úmida. Comprimidos produzidos por granulação úmida apresentaram maior força de esmagamento do que aqueles produzidos pelo método de compressão direta. Observou-se sobrevivência significativamente maior (p<0,05) em formulações preparadas por compressão direta. A sobrevivência percentual dos esporos de Bacillus subtilis diminuiu com o aumento da concentração do agregante. O estudo mostrou que a goma de Albizia é capaz de conferir maior plasticidade aos materiais e apresentou maior redução da contaminação microbiana nas formulações. O método de compressão direta produziu comprimidos com viabilidade reduzida de contaminantes microbianos

Evaluation of Antibacterial Utilization in Olabisi Onabanjo University Teaching Hospital, Sagamu, Ogun State

BACKGROUND: Inappropriate prescription and use of antibacterial agents is widely reported at various levels of practice. These agents are also becoming decreasingly useful due to resistance, which partly resulted from misuse and abuse. Their role in continuity of healthy life is highly crucial to fight our “competitors”. More so, they share a good proportion of total drug budget in every country including a comatose economy like ours. OBJECTIVE: The objective is to evaluate the use of antibacterial agents in order to assess how rational they are being used and if necessary to make recommendations on its improvement. This is particularly important as most hospitals in the country if not all have neglected the Drug Utilization Review aspects of Drug and Therapeutic Committee roles. It can also form basis for intervention be it educational, managerial or regulatory. METHODS: It is a retrospective drug utilization review studies, in addition a cost perspective was added. Sampled Case notes were examined for prescriptions. Interview with pharmacists about some issues such as cost of drugs and formulary list was also carried out and cost minimization analysis for branded and generics as well. RESULTS: The agents were used fairly rationally. However, the degree of poly pharmacy still remains high with an average number of drugs per encounter of 4.2. The most frequently used agent was metronidazole (17.72%), followed by gentamicin (16.88%) and ampiclox (14.07%). Out of stock items were not many. No copy of drug formulary list could be seen despite claims for its availability. CONCLUSION: Antibacterial policy need to be formulated inform of regular updated list and standard treatment guidelines. All the stakeholders must be carried along right from formulation stage to make enforcement and monitoring participative and full implementation successful. NQJHM Vol. 15 (1) 2005: pp. 42-4

Estimating cycling potential on route networks in Accra and Kathmandu

The benefits of active travel for individual and urban health, the environment, and society are becoming increasingly apparent (Celis-Morales et al. 2017), and many cities are preparing ambitious walking and cycling plans. However many transport authorities lack strong and actionable evidence to support this investment for a number of reasons, including: transport models have tended to focus on motor vehicles (Boyce and Williams 2015), data on active travel tends to be sparse and inaccessible (Kuzmyak et al. 2014), data and models are often not accessible for many potential stakeholders (e.g. civil society groups), or in formats that are difficult to understand and use (Naess et al. 2014). This project aims to tackle these problems by assessing the feasibility of tools to provide actionable, publicly accessible, and geographically detailed evidence to prioritise investment in cycling for the case study cities of Accra, Ghana and Kathmandu, Nepal

Estimating the effects of crime maps on house prices using an (un)natural experiment: a study protocol

Street-level crime maps are publicly available online in England and Wales. However, there was initial resistance to the publication of such fine-grained crime statistics, which can lower house prices and increase insurance premiums in high crime neighbourhoods. Identifying the causal effect of public crime statistics is difficult since crime statistics generally mirror actual crime. To address this question empirically, we would ideally experiment and introduce a source of random variation in the crime statistics. For instance, we could randomly increase or decrease the number of offences displayed in crime statistics and measure their effects on local house prices. For obvious reasons, we cannot pursue this research design. However, street-level crime maps contain intentional errors, which are the product of a geomasking algorithm designed to mask the location of crimes and protect the identity of victims. This project leverages features associated with the geomasking algorithm to estimate the effect of public crime statistics on house prices

Comparison of samplers collecting airborne influenza viruses: 1. Primarily impingers and cyclones.

Researchers must be able to measure concentrations, sizes, and infectivity of virus-containing particles in animal agriculture facilities to know how far infectious virus-containing particles may travel through air, where they may deposit in the human or animal respiratory tract, and the most effective ways to limit exposures to them. The objective of this study was to evaluate a variety of impinger and cyclone aerosol or bioaerosol samplers to determine approaches most suitable for detecting and measuring concentrations of virus-containing particles in air. Six impinger/cyclone air samplers, a filter-based sampler, and a cascade impactor were used in separate tests to collect artificially generated aerosols of MS2 bacteriophage and swine and avian influenza viruses. Quantification of infectious MS2 coliphage was carried out using a double agar layer procedure. The influenza viruses were titrated in cell cultures to determine quantities of infectious virus. Viral RNA was extracted and used for quantitative real time RT-PCR, to provide total virus concentrations for all three viruses. The amounts of virus recovered and the measured airborne virus concentrations were calculated and compared among the samplers. Not surprisingly, high flow rate samplers generally collected greater quantities of virus than low flow samplers. However, low flow rate samplers generally measured higher, and likely more accurate, airborne concentrations of Infectious virus and viral RNA than high flow samplers. To assess airborne viruses in the field, a two-sampler approach may work well. A suitable high flow sampler may provide low limits of detection to determine if any virus is present in the air. If virus is detected, a suitable lower flow sampler may measure airborne virus concentrations accurately