Discovering unbounded episodes in sequential data

One basic goal in the analysis of time-series data is to find frequent interesting episodes, i.e, collections of events occurring frequently together in the input sequence. Most widely-known work decide the interestingness of an episode from a fixed user-specified window width or interval, that bounds the subsequent sequential association rules. We present in this paper, a more intuitive definition that allows, in turn, interesting episodes to grow during the mining without any user-specified help. A convenient algorithm to efficiently discover the proposed unbounded episodes is also implemented. Experimental results confirm that our approach results useful and advantageous.Postprint (published version

Mining relevant and extreme patterns on climate time series with CLIPSMiner.

One of the most important challenges for the researchers in the 21st Century is related to global heating and climate change that can have as consequence the intensification of natural hazards. Another problem of changes in the Earth's climate is its impact in the agriculture production. In this scenario, application of statistical models as well as development of new methods become very important to aid in the analyses of climate from ground-based stations and outputs of forecasting models. Additionally, remote sensing images have been used to improve the monitoring of crop yields. In this context we propose a new technique to identify extreme values in climate time series and to correlate climate and remote sensing data in order to improve agricultural monitoring. Accordingly, this paper presents a new unsupervised algorithm, called CLIPSMiner (CLImate PatternS Miner) that works on multiple time series of continuous data, identifying relevant patterns or extreme ones according to a relevance factor, which can be tuned by the user. Results show that CLIPSMiner detects, as expected, patterns that are known in climatology, indicating the correctness and feasibility of the proposed algorithm. Moreover, patterns detected using the highest relevance factor is coincident with extreme phenomena. Furthermore, series correlations detected by the algorithm show a relation between agroclimatic and vegetation indices, which confirms the agrometeorologists' expectations

Solutions Network Formulation Report. Visible/Infrared Imager/Radiometer Suite and Advanced Microwave Scanning Radiometer Data Products for National Drought Monitor Decision Support

Drought effects are either direct or indirect depending on location, population, and regional economic vitality. Common direct effects of drought are reduced crop, rangeland, and forest productivity; increased fire hazard; reduced water levels; increased livestock and wildlife mortality rates; and damage to wildlife and fish habitat. Indirect impacts follow on the heels of direct impacts. For example, a reduction in crop, rangeland, and forest productivity may result in reduced income for farmers and agribusiness, increased prices for food and timber, unemployment, reduced tax revenues, increased crime, foreclosures on bank loans to farmers and businesses, migration, and disaster relief programs. In the United States alone, drought is estimated to result in annual losses of between $6 - 8 billion. Recent sustained drought in the United States has made decision-makers aware of the impacts of climate change on society and environment. The eight major droughts that occurred in the United States between 1980 and 1999 accounted for the largest percentage of weather-related monetary losses. Monitoring drought and its impact that occurs at a variety of scales is an important government activity -- not only nationally but internationally as well. The NDMC (National Drought Mitigation Center) and the USDA (U.S. Department of Agriculture) RMA (Risk Management Agency) have partnered together to develop a DM-DSS (Drought Monitoring Decision Support System). This monitoring system will be an interactive portal that will provide users the ability to visualize and assess drought at all levels. This candidate solution incorporates atmospherically corrected VIIRS data products, such as NDVI (Normalized Difference Vegetation Index) and Ocean SST (sea surface temperature), and AMSR-E soil moisture data products into two NDMC vegetation indices -- VegDRI (Vegetation Drought Response Index) and VegOUT (Vegetation Outlook) -- which are then input into the DM-DSS

Temporal data mining algorithms for metric temporal constraint networks discovery

The thesis describes algorithms for mining time-stamped sequences to discover frequent temporal patterns using the STP formalism

Design as interactions of problem framing and problem solving: a formal and empirical basis for problem framing in design

In this thesis, I present, illustrate and empirically validate a novel approach to modelling and explaining design process. The main outcome of this work is the formal definition of the problem framing, and the formulation of a recursive model of framing in design. The model (code-named RFD), represents a formalisation of a grey area in the science of design, and sees the design process as a recursive interaction of problem framing and problem solving. The proposed approach is based upon a phenomenon introduced in cognitive science and known as (reflective) solution talkback. Previously, there were no formalisations of the knowledge interactions occurring within this complex reasoning operation. The recursive model is thus an attempt to express the existing knowledge in a formal and structured manner. In spite of rather abstract, knowledge level on which the model is defined, it is a firm step in the clarification of design process. The RFD model is applied to the knowledge-level description of the conducted experimental study that is annotated and analysed in the defined terminology. Eventually, several schemas implied by the model are identified, exemplified, and elaborated to reflect the empirical results. The model features the mutual interaction of predicates ‘specifies’ and ‘satisfies’. The first asserts that a certain set of explicit statements is sufficient for expressing relevant desired states the design is aiming to achieve. The validity of predicate ‘specifies’ might not be provable directly in any problem solving theory. A particular specification can be upheld or rejected only by drawing upon the validity of a complementary predicate ‘satisfies’ and the (un-)acceptability of the considered candidate solution (e.g. technological artefact, product). It is the role of the predicate ‘satisfies’ to find and derive such a candidate solution. The predicates ‘specifies’ and ‘satisfies’ are contextually bound and can be evaluated only within a particular conceptual frame. Thus, a solution to the design problem is sound and admissible with respect to an explicit commitment to a particular specification and design frame. The role of the predicate ‘acceptable’ is to compare the admissible solutions and frames against the ‘real’ design problem. As if it answered the question: “Is this solution really what I wanted/intended?” Furthermore, I propose a set of principled schemas on the conceptual (knowledge) level with an aim to make the interactive patterns of the design process explicit. These conceptual schemas are elicited from the rigorous experiments that utilised the structured and principled approach to recording the designer’s conceptual reasoning steps and decisions. They include the refinement of an explicit problem specification within a conceptual frame; the refinement of an explicit problem specification using a re-framed reference; and the conceptual re-framing (i.e. the identification and articulation of new conceptual terms) Since the conceptual schemas reflect the sequence of the ‘typical’ decisions the designer may make during the design process, there is no single, symbol-level method for the implementation of these conceptual patterns. Thus, when one decides to follow the abstract patterns and schemas, this abstract model alone can foster a principled design on the knowledge level. It must be acknowledged that for the purpose of computer-based support, these abstract schemas need to be turned into operational models and consequently suitable methods. However, such operational perspective was beyond the time and resource constraints placed on this research

Gaelic language maintenance process(es)

Gaelic Language Maintenance Process(es) is a contemporary ethnographic study of seventeen isolated Gaelic language users. The seventeen individuals in the study, ages three to seventy-two, were selected from Ontario, Canada and Central Scotland to identify and illustrate the perceptions and processes involved in isolated Gaelic language maintenance. Each subject was interviewed, and subsequently shadowed, for a period of nine days. During the period of active observation, the subjects recorded their thoughts about and experiences of their Gaelic language maintenance within a personal journal. The interviews, observations, and personal diaries of the subjects' Gaelic lives were then collated by the researcher into seventeen individual narratives. Through close reading, each narrative illuminated the interwoven threads and constructs which provided additional insight into the 'quilt' of isolated Gaelic language maintenance. The seven, common-sense typologies and constructs drawn from the individuals' experience of the Gaelic language world revealed a shared, inner universe of meaning where some of the major categories in the (experience of) their social language world centred upon their recognition of Gaelic ability, maintenance, community roles, and "special" identity to form a tapestry for maintenance outside of the bloc. Peigi, Pàdruig, Catriona, Cairistiona, Chlair, Cormac, Colla, Tomasina, Tara, Teàrlag, Treasaididh, Tollaidh, Aileas, Artair, Aigneas, Anna, and Aonghas generously allow readers an opportunity to share in their thoughts and feelings and [the researcher's] observations about what it is like to maintain the Gaelic language in isolation from Cape Breton and the Western Isles