Variable-number tandem repeats genotyping used to aid and inform management strategies for a bovine Johne's disease incursion in tropical and subtropical Australia

The application of variable-number tandem repeats (VNTR) genotyping of Mycobacterium avium subsp. paratuberculosis isolates to assist in investigating incidents of bovine Johne’s disease in a low-prevalence region of Australia is described in the current study. Isolates from a response to detection of bovine Johne’s disease in Queensland were compared with strains from national and international sources. The tandem application of mycobacterial interspersed repetitive unit (MIRU) and multilocus short sequence repeats (MLSSR) genotyping identified 2 strains, 1 that infected cattle on multiple properties with trace-forward histories from a common infected property, and 1 genotypically different strain recovered from a single property. The former strain showed an identical genotype to an isolate from India. Neither strain showed a genotypic link to regions of Australia with a higher prevalence of the disease. Genotyping has indicated incursions from 2 independent sources. This intelligence has informed investigations into potential routes of entry and the soundness of ongoing control measures, and supported strategy and policy decisions regarding management of Mycobacterium avium subsp. paratuberculosis incursions for Queensland.

Robust automatic face clustering in news video

Clustering identities in a video is a useful task to aid in video search, annotation and retrieval, and cast identification. However, reliably clustering faces across multiple videos is challenging task due to variations in the appearance of the faces, as videos are captured in an uncontrolled environment. A person's appearance may vary due to session variations including: lighting and background changes, occlusions, changes in expression and make up. In this paper we propose the novel Local Total Variability Modelling (Local TVM) approach to cluster faces across a news video corpus; and incorporate this into a novel two stage video clustering system. We first cluster faces within a single video using colour, spatial and temporal cues; after which we use face track modelling and hierarchical agglomerative clustering to cluster faces across the entire corpus. We compare different face recognition approaches within this framework. Experiments on a news video database show that the Local TVM technique is able effectively model the session variation observed in the data, resulting in improved clustering performance, with much greater computational efficiency than other methods.

Information Visualization in a Business Decision Support System

Information visualization is a process of constructing a visual presentation of abstract quantitative data. The characteristics of visual perception enable humans to recognize patterns, trends and anomalies inherent in the data with little effort in a visual display. Such properties of the data are likely to be missed in a purely text-based presentation. Visualizations are therefore widely used in contemporary business decision support systems. Visual user interfaces called dashboards are tools for reporting the status of a company and its business environment to facilitate business intelligence (BI) and performance management activities. In this study, we examine the research on the principles of human visual perception and information visualization as well as the application of visualization in a business decision support system. A review of current BI software products reveals that the visualizations included in them are often quite ineffective in communicating important information. Based on the principles of visual perception and information visualization, we summarize a set of design guidelines for creating effective visual reporting interfaces.

Cryptographic Software Export Controls in the EU

Certain software products employing digital techniques for encryption of data are subject to export controls in the EU Member States pursuant to Community law and relevant laws in the Member States. These controls are agreed globally in the framework of the so-called Wassenaar Arrangement. Wassenaar is an informal non-proliferation regime aimed at promoting international stability and responsibility in transfers of strategic (dual-use) products and technology. This thesis covers provisions of Wassenaar, Community export control laws and export control laws of Finland, Sweden, Germany, France and United Kingdom. This thesis consists of five chapters. The first chapter discusses the ratio of export control laws and the impact they have on global trade. The ratio is originally defence-related - in general to prevent potential adversaries of participating States from having the same tools, and in particular in the case of cryptographic software to enable signals intelligence efforts. Increasingly as the use of cryptography in a civilian context has mushroomed, export restrictions can have negative effects on civilian trade. Information security solutions may also be took weak because of export restrictions on cryptography. The second chapter covers the OECD's Cryptography Policy, which had a significant effect on its member nations' national cryptography policies and legislation. The OECD is a significant organization,because it acts as a meeting forum for most important industrialized nations. The third chapter covers the Wassenaar Arrangement. The Arrangement is covered from the viewpoint of international law and politics. The Wassenaar control list provisions affecting cryptographic software transfers are also covered in detail. Control lists in the EU and in Member States are usually directly copied from Wassenaar control lists. Controls agreed in its framework set only a minimum level for participating States. However, Wassenaar countries can adopt stricter controls. The fourth chapter covers Community export control law. Export controls are viewed in Community law as falling within the domain of Common Commercial Policy pursuant to Article 133 of the EC Treaty. Therefore the Community has exclusive competence in export matters, save where a national measure is authorized by the Community or falls under foreign or security policy derogations established in Community law. The Member States still have a considerable amount of power in the domain of Common Foreign and Security Policy. They are able to maintain national export controls because export control laws are not fully harmonized. This can also have possible detrimental effects on the functioning of internal market and common export policies. In 1995 the EU adopted Dual-Use Regulation 3381/94/EC, which sets common rules for exports in Member States. Provisions of this regulation receive detailed coverage in this chapter. The fifth chapter covers national legislation and export authorization practices in five different Member States - in Finland, Sweden, Germany, France and in United Kingdom. Export control laws of those Member States are covered when the national laws differ from the uniform approach of the Community's acquis communautaire. Keywords: export control, encryption, software, dual-use, license, foreign trade, e-commerce, Internet

Policing online fraud in Australia: The emergence of a victim‐oriented approach

Online fraud is a global problem. Millions of individuals worldwide are losing money and experiencing the devastation associated with becoming a victim of online fraud. In 2014, Australians reported losses of $82 million as a result of online fraud to the Australian Competition and Consumer Commission (ACCC). Given that the ACCC is one of many agencies that receives victim complaints, and the extent of under‐reporting of online fraud, this figure is likely to represent only a fraction of the actual monetary losses incurred. The successful policing of online fraud is hampered by its transnational nature, the prevalence of false/stolen identities used by offenders, and a lack of resources available to investigate offences. In addition, police are restricted by the geographical boundaries of their own jurisdictions which conflicts with the lack of boundaries afforded to offenders by the virtual world. In response to this, Australia is witnessing the emergence of victim‐oriented policing approaches to counter online fraud victimisation. This incorporates the use of financial intelligence as a tool to proactively notify potential victims of online fraud. Using a variety of Australian examples, this paper documents the history to this new approach and considers the significance that such a shift represents to policing in a broader context. It also details the value that this approach can have to both victims and law enforcement agencies. Overall, it is argued that a victim‐oriented approach to policing online fraud can have substantial benefits to police and victims alike.

Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Enhancing the shopping experience with ambient displays: A field study in a retail store

This paper discusses the prototypical implementation of an ambient display and the results of an empirical study in a retail store. It presents the context of shopping as an application area for Ambient Intelligence (AmI) technologies. The prototype consists of an ambient store map that enhances the awareness of customer activity. The results of our study indicate potentials and challenges for an improvement of the shopping experience with AmI technologies. Based on our findings we discuss challenges and future developments for applying AmI technologies to shopping environments.

An open source service oriented Mobile Business Intelligence Tool (MBIT)

Corporate executives require relevant and intelligent business information in real-time to take strategic decisions. They require the freedom to access this information anywhere and anytime. There is a need to extend this functionality beyond the office and on the fingertips of the decision makers. Mobile Business Intelligence Tool (MBIT) aims to provide these features in a flexible and cost-efficient manner. This paper describes the detailed architecture of MBIT to overcome the limitations of existing mobile business intelligence tools. Further, a detailed implementation framework is presented to realize the design. This research highlights the benefits of using service oriented architecture to design flexible and platform independent mobile business applications. © 2009 IEEE.

Diabetic ketoacidosis and electroencephalographic changes in newly diagnosed pediatric patients

Objective: To document electroencephalogram (EEG) changes and their correlation with clinical parameters in a newly diagnosed pediatric cohort of type 1 diabetes mellitus (T1DM) patients with and without diabetic ketoacidosis (DKA) and to define their medium term utility and significance. Research design and methods: Prospective longitudinal study of children presenting with T1DM. EEGs were performed within 24 h of diagnosis, day 5, and at 6 months post-diagnosis and reviewed by a neurologist blinded to clinical status. Severity of encephalopathy was graded from 1 to 5 using the Aoki and Lombroso encephalopathy scale. Cognitive abilities were assessed using standardized tests of attention, memory, and intelligence. Results: Eighty eight children were recruited; 34 presented with DKA. Abnormal background slowing was more often observed in the first 24 h in children with DKA (p = 0.01). Encephalopathy scores on day 1 correlated with initial pH, CO2, HCO3, base excess, respiratory rate, heart rate, diastolic blood pressure, and IV fluid intake (all parameters p < 0.05). EEG scores at day 1 did not correlate with contemporaneous mental state or cognition in the medium term. Conclusions: DKA was associated with significant clinical and neurophysiologic signs of brain dysfunction at presentation. While EEG is sensitive to the detection of encephalopathy in newly diagnosed T1DM, it has limited use in identifying children at risk of later cognitive deficits.

Using a glow graph to represent data flow and dependency in event logs

The idea of extracting knowledge in process mining is a descendant of data mining. Both mining disciplines emphasise data flow and relations among elements in the data. Unfortunately, challenges have been encountered when working with the data flow and relations. One of the challenges is that the representation of the data flow between a pair of elements or tasks is insufficiently simplified and formulated, as it considers only a one-to-one data flow relation. In this paper, we discuss how the effectiveness of knowledge representation can be extended in both disciplines. To this end, we introduce a new representation of the data flow and dependency formulation using a flow graph. The flow graph solves the issue of the insufficiency of presenting other relation types, such as many-to-one and one-to-many relations. As an experiment, a new evaluation framework is applied to the Teleclaim process in order to show how this method can provide us with more precise results when compared with other representations.

Agents Based Algorithms for Design Parameter Estimation in Contaminant Transport Inverse Problems

A considerable amount of work has been dedicated on the development of analytical solutions for flow of chemical contaminants through soils. Most of the analytical solutions for complex transport problems are closed-form series solutions. The convergence of these solutions depends on the eigen values obtained from a corresponding transcendental equation. Thus, the difficulty in obtaining exact solutions from analytical models encourages the use of numerical solutions for the parameter estimation even though, the later models are computationally expensive. In this paper a combination of two swarm intelligence based algorithms are used for accurate estimation of design transport parameters from the closed-form analytical solutions. Estimation of eigen values from a transcendental equation is treated as a multimodal discontinuous function optimization problem. The eigen values are estimated using an algorithm derived based on glowworm swarm strategy. Parameter estimation of the inverse problem is handled using standard PSO algorithm. Integration of these two algorithms enables an accurate estimation of design parameters using closed-form analytical solutions. The present solver is applied to a real world inverse problem in environmental engineering. The inverse model based on swarm intelligence techniques is validated and the accuracy in parameter estimation is shown. The proposed solver quickly estimates the design parameters with a great precision.

Application of artificial intelligence for the assessment of the status of power transformers

The Dissolved Gas Analysis (DGA) a non destructive test procedure, has been in vogue for a long time now, for assessing the status of power and related transformers in service. An early indication of likely internal faults that may exist in Transformers has been seen to be revealed, to a reasonable degree of accuracy by the DGA. The data acquisition and subsequent analysis needs an expert in the concerned area to accurately assess the condition of the equipment. Since the presence of the expert is not always guaranteed, it is incumbent on the part of the power utilities to requisition a well planned and reliable artificial expert system to replace, at least in part, an expert. This paper presents the application of Ordered Ant Mner (OAM) classifier for the prediction of involved fault. Secondly, the paper also attempts to estimate the remaining life of the power transformer as an extension to the elapsed life estimation method suggested in the literature.

Specific language impairment in pre-adolescence, adolescence, and adulthood with special emphasis on health-related quality of life

This clinical study focused on effects of childhood specific language impairment (SLI) on daily functioning in late life. SLI is a neurobiological disorder with genetic predisposition and manifests as poor language production or comprehension or both in a child with age-level non-verbal intelligence and no other known cause for deficient language development. The prevalence rate of around 7% puts it among the most prevalent developmental disorders in childhood. Negative long-term effects, such as problems in learning and behavior, are frequent. In follow-up studies the focus has seldom been on self-perception of daily functioning and participation, which are considered important in the International Classification of Functioning, Disability, and Health (ICF). To investigate the self-perceived aspects of everyday functioning in individuals with childhood receptive SLI compared with age- and gender-matched control populations, the 15D, 16D, and 17D health-related quality of life (HRQoL) questionnaires were applied. These generic questionnaires include 15, 16, and 17 dimensions, respectively, and give both a single index score and a profile with values on each dimension. Information on different life domains (rehabilitation, education, employment etc.) from each age-group was collected with separate questionnaires. The study groups comprised adults, adolescents (12-16 years), and pre-adolescents (8-11 years) who had received a diagnosis of receptive SLI and had been examined, usually before school age, at the Department of Phoniatrics of Helsinki University Central Hospital, where children with language deficits caused by various etiologies are examined and treated by a multidisciplinary team. The adult respondents included 33 subjects with a mean age of 34 years. Measured with 15D, the subjects perceived their HRQoL to be nearly as good as that of their controls, but on the dimensions of speech, usual activities, mental functioning, and distress they were significantly worse off. They significantly more often lived with their parents (19%) or were pensioned (26%) than the adult Finnish population on average. Adults with self-perceived problems in finding words and in remembering instructions, manifestations of persistent language impairment, showed inferior every day functioning to the rest of the study group. Of the adolescents and pre-adolescents, 48 and 51, respectively, responded. The majority in both groups had received special education or extra educational support at school. They all had attended speech therapy at some point; at the time of the study only one adolescent, but every third pre-adolescent still received speech therapy. The 16D score of the adolescent or the 17D score of the pre-adolescents did not differ from that of their controls. The 16D profiles differed on some dimensions; subjects were significantly worse off on the dimension of mental functioning, but better off on the dimension of vitality than controls. Of the 17D dimensions, the study group was significantly worse off on speech, whereas the control group reported significantly more problems in sleeping. Of the childhood performance measures investigated, low verbal intelligence quotient (VIQ), which is often considered to reflect receptive language impairment, was in adults subjects significantly associated with some of the self-perceived problems, such as problems in usual activities and mental functioning. The 15D, 16D, and 17D questionnaires served well in measuring self-perceived HRQoL. Such standardized measures with population values are especially important in confirming with the ICF guidelines. In the future these questionnaires could perhaps be used on a more individual level in follow-up of children in clinics, and even in special schools and classes, to detect those children at greatest risk of negative long-term effects and perhaps diminished well-being regarding daily functioning and participation.

The Effect of Intrauterine Growth Restriction on Long-Term Outcome in Very or Extremely Low Birth Weight Infants

The project consisted of two long-term follow-up studies of preterm children addressing the question whether intrauterine growth restriction affects the outcome. Assessment at 5 years of age of 203 children with a birth weight less than 1000 g born in Finland in 1996-1997 showed that 9% of the children had cognitive impairment, 14% cerebral palsy, and 4% needed a hearing aid. The intelligence quotient was lower (p<0.05) than the reference value. Thus, 20% exhibited major, 19% minor disabilities, and 61% had no functional abnormalities. Being small for gestational age (SGA) was associated with sub-optimal growth later. In children born before 27 gestational weeks, the SGA had more neuropsychological disabilities than those appropriate for gestational age (AGA). In another cohort with birth weight less than 1500 g assessed at 5 years of age, echocardiography showed a thickened interventricular septum and a decreased left ventricular end-diastolic diameter in both SGA and AGA born children. They also had a higher systolic blood pressure than the reference. Laser-Doppler flowmetry showed different endothelium-dependent and -independent vasodilation responses in the AGA children compared to those of the controls. SGA was not associated with cardio-vascular abnormalities. Auditory event-related potentials (AERPs) were recorded using an oddball paradigm with frequency deviants (standard tone 500 Hz and deviant 750-Hz with 10% probability). At term, the P350 was smaller in SGA and AGA infants than in controls. At 12 months, the automatic change detection peak (mismatch negativity, MMN) was observed in the controls. However, the pre-term infants had a difference positivity that correlated with their neurodevelopment scores. At 5 years of age, the P1-deflection, which reflects primary auditory processing, was smaller, and the MMN larger in the preterm than in the control children. Even with a challenging paradigm or a distraction paradigm, P1 was smaller in the preterm than in the control children. The SGA and AGA children showed similar AERP responses. Prematurity is a major risk factor for abnormal brain development. Preterm children showed signs of cardiovascular abnormality suggesting that prematurity per se may carry a risk for later morbidity. The small positive amplitudes in AERPs suggest persisting altered auditory processing in the preterm in-fants.

Localization of handwritten text in documents using moment invariants and Delaunay triangulation

This paper describes an approach based on Zernike moments and Delaunay triangulation for localization of hand-written text in machine printed text documents. The Zernike moments of the image are first evaluated and we classify the text as hand-written using the nearest neighbor classifier. These features are independent of size, slant, orientation, translation and other variations in handwritten text. We then use Delaunay triangulation to reclassify the misclassified text regions. When imposing Delaunay triangulation on the centroid points of the connected components, we extract features based on the triangles and reclassify the text. We remove the noise components in the document as part of the preprocessing step so this method works well on noisy documents. The success rate of the method is found to be 86%. Also for specific hand-written elements such as signatures or similar text the accuracy is found to be even higher at 93%.