Financial time series: market analysis techniques based on matrix profiles

The Matrix Profile (MP) algorithm has the potential to revolutionise many areas of data analysis. In this article, several applications to financial time series are examined. Several approaches for the identification of similar behaviour patterns (or motifs) are proposed, illustrated, and the results discussed. While the MP is primarily designed for single series analysis, it can also be applied to multi-variate financial series. It still permits the initial identification of time periods with indicatively similar behaviour across individual market sectors and indexes, together with the assessment of wider applications, such as general market behaviour in times of financial crisis. In short, the MP algorithm offers considerable potential for detailed analysis, not only in terms of motif identification in financial time series, but also in terms of exploring the nature of underlying events

COPE: Interactive Exploration of Co-occurrence Patterns in Spatial Time Series.

Spatial time series is a common type of data dealt with in many domains, such as economic statistics and environmental science. There have been many studies focusing on finding and analyzing various kinds of events in time series; the term 'event' refers to significant changes or occurrences of particular patterns formed by consecutive attribute values. We focus on a further step in event analysis: finding and exploring events that frequently co-occurred with a target class of similar events having occurred repeatedly over a period of time. This type of analysis can provide important clues for understanding the formation and spreading mechanisms of events and interdependencies among spatial locations. We propose a visual exploration framework COPE (Co-Occurrence Pattern Exploration), which allows users to extract events of interest from data and detect various co-occurrence patterns among them. Case studies and expert reviews were conducted to verify the effectiveness and scalability of COPE using two real-world datasets

Towards a Plug-and-Play and Holistic Data Mining Framework for Understanding and Facilitating Operations in Smart Buildings

Nowadays, a significant portion of the total energy consumption is attributed to the buildings sector. In order to save energy and protect the environment, energy consumption in buildings must be more efficient. At the same time, buildings should offer the same (if not more) comfort to their occupants. Consequently, modern buildings have been equipped with various sensors and actuators and interconnected control systems to meet occupants’ requirements. Unfortunately, so far, Building Automation Systems data have not been well-exploited due to technical and cost limitations. Yet, it can be exceptionally beneficial to take full advantage of the data flowing inside buildings in order to diagnose issues, explore solutions and improve occupant-building interactions. This paper presents a plug-and-play and holistic data mining framework named PHoliData for smart buildings to collect, store, visualize and mine useful information and domain knowledge from data in smart buildings. PHoliData allows non technical experts to easily explore and understand their buildings with minimum IT support. An architecture of this framework has been introduced and a prototype has been implemented and tested against real-world settings. Discussions with industry experts have suggested the system to be extremely helpful for understanding buildings, since it can provide hints about energy efficiency improvements. Finally, extensive experiments have demonstrated the feasibility of such a framework in practice and its advantage and potential for buildings operators

The Humoral Response against <i>Salmonella</i> Typhi Protein Antigens During Acute, Convalescent, and Chronic Typhoid Fever

Enteric (typhoid) fever is a life-threatening disease caused by the Salmonella enterica subspecies enterica serovars Typhi (S. Typhi) and Paratyphi A, B, and C (S. Paratyphi A, B, and C). The disease still causes major public health problems in low- and middle-income countries, principally in Asia and Africa. The increasing frequency of multi-drug resistant (MDR) and extended-drug resistant isolates (XDR) of S. Typhi and an increasing incidence of S. Paratyphi A mean that the international dynamics of enteric fever are changing. These changes add urgency to the demand for more efficient enteric fever control campaigns. The aim of this thesis was to assess control measures for enteric fever in Vietnam and to develop techniques that can be used as further control methods. I firstly systemically reviewed retrospective information regarding enteric fever in Vietnam and combined these data with data on economic development. This investigation revealed that national economic growth, the provision of improved quality drinking water, and better sanitation were likely the greatest contributors to the decline and ultimate elimination of enteric fever in Vietnam. My work then evaluated the serodiagnostic potential of a panel of novel S. Typhi protein antigens and the Vi capsular polysaccharide (Vi) in a group of patients with febrile diseases in Bangladesh. These data demonstrated the utility of serology for typhoid diagnostics when exploiting a combination of Vi and at least one protein antigen. I then assessed the acquisition of antibody against typhoid toxin during natural S. Typhi and S. Paratyphi A infections and measured the capability of these antibodies to neutralise the toxin. The data provided supporting evidence for generating an antitoxin treatment for enteric fever (caused by both S. Typhi and S. Paratyphi A), and potentially encourages the use of typhoid toxin in vaccine formulations. Within the scope of searching for vaccine novel candidates, my work further identified a panel of immunogenic antigens shared between S. Typhi and S. Paratyphi A that can stimulate an antibody response which can instigate bactericidal killing during natural infection. Finally, by exploiting the unique immunological profiles of S. Typhi carriers (cytokines and antibody), I developed a method of identifying S. Typhi carriers and estimating the prevalence of S. Typhi carriage in a typhoid endemic population. My findings will potentially lead to the development of novel enteric fever control strategies. I conclude that improved case detection and widespread vaccination campaigns using polyvalent Salmonella vaccines should be initiated for reducing the burden of enteric fever in endemic areas