936 resultados para Biology, Bioinformatics|Computer Science
Resumo:
This technical report is concerned with one aspect of environmental monitoring—the detection and analysis of acoustic events in sound recordings of the environment. Sound recordings offer ecologists the advantage of cheaper and increased sampling but make available so much data that automated analysis becomes essential. The report describes a number of tools for automated analysis of recordings, including noise removal from spectrograms, acoustic event detection, event pattern recognition, spectral peak tracking, syntactic pattern recognition applied to call syllables, and oscillation detection. These algorithms are applied to a number of animal call recognition tasks, chosen because they illustrate quite different modes of analysis: (1) the detection of diffuse events caused by wind and rain, which are frequent contaminants of recordings of the terrestrial environment; (2) the detection of bird and calls; and (3) the preparation of acoustic maps for whole ecosystem analysis. This last task utilises the temporal distribution of events over a daily, monthly or yearly cycle.
Resumo:
The XML Document Mining track was launched for exploring two main ideas: (1) identifying key problems and new challenges of the emerging field of mining semi-structured documents, and (2) studying and assessing the potential of Machine Learning (ML) techniques for dealing with generic ML tasks in the structured domain, i.e., classification and clustering of semi-structured documents. This track has run for six editions during INEX 2005, 2006, 2007, 2008, 2009 and 2010. The first five editions have been summarized in previous editions and we focus here on the 2010 edition. INEX 2010 included two tasks in the XML Mining track: (1) unsupervised clustering task and (2) semi-supervised classification task where documents are organized in a graph. The clustering task requires the participants to group the documents into clusters without any knowledge of category labels using an unsupervised learning algorithm. On the other hand, the classification task requires the participants to label the documents in the dataset into known categories using a supervised learning algorithm and a training set. This report gives the details of clustering and classification tasks.
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The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.
Resumo:
Gradual authentication is a principle proposed by Meadows as a way to tackle denial-of-service attacks on network protocols by gradually increasing the confidence in clients before the server commits resources. In this paper, we propose an efficient method that allows a defending server to authenticate its clients gradually with the help of some fast-to-verify measures. Our method integrates hash-based client puzzles along with a special class of digital signatures supporting fast verification. Our hash-based client puzzle provides finer granularity of difficulty and is proven secure in the puzzle difficulty model of Chen et al. (2009). We integrate this with the fast-verification digital signature scheme proposed by Bernstein (2000, 2008). These schemes can be up to 20 times faster for client authentication compared to RSA-based schemes. Our experimental results show that, in the Secure Sockets Layer (SSL) protocol, fast verification digital signatures can provide a 7% increase in connections per second compared to RSA signatures, and our integration of client puzzles with client authentication imposes no performance penalty on the server since puzzle verification is a part of signature verification.
Resumo:
The ultimate goal of an authorisation system is to allocate each user the level of access they need to complete their job - no more and no less. This proves to be challenging in an organisational setting because on one hand employees need enough access to perform their tasks, while on the other hand more access will bring about an increasing risk of misuse - either intentionally, where an employee uses the access for personal benefit, or unintentionally through carelessness, losing the information or being socially engineered to give access to an adversary. With the goal of developing a more dynamic authorisation model, we have adopted a game theoretic framework to reason about the factors that may affect users’ likelihood to misuse a permission at the time of an access decision. Game theory provides a useful but previously ignored perspective in authorisation theory: the notion of the user as a self-interested player who selects among a range of possible actions depending on their pay-offs.
Resumo:
Stigmergy is a biological term used when discussing insect or swarm behaviour, and describes a model supporting environmental communication separately from artefacts or agents. This phenomenon is demonstrated in the behavior of ants and their food gathering process when following pheromone trails, or similarly termites and their termite mound building process. What is interesting with this mechanism is that highly organized societies are achieved with a lack of any apparent management structure. Stigmergic behavior is implicit in the Web where the volume of users provides a self-organizing and self-contextualization of content in sites which facilitate collaboration. However, the majority of content is generated by a minority of the Web participants. A significant contribution from this research would be to create a model of Web stigmergy, identifying virtual pheromones and their importance in the collaborative process. This paper explores how exploiting stigmergy has the potential of providing a valuable mechanism for identifying and analyzing online user behavior recording actionable knowledge otherwise lost in the existing web interaction dynamics. Ultimately this might assist our building better collaborative Web sites.
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Road safety is a major concern worldwide. Road safety will improve as road conditions and their effects on crashes are continually investigated. This paper proposes to use the capability of data mining to include the greater set of road variables for all available crashes with skid resistance values across the Queensland state main road network in order to understand the relationships among crash, traffic and road variables. This paper presents a data mining based methodology for the road asset management data to find out the various road properties that contribute unduly to crashes. The models demonstrate high levels of accuracy in predicting crashes in roads when various road properties are included. This paper presents the findings of these models to show the relationships among skid resistance, crashes, crash characteristics and other road characteristics such as seal type, seal age, road type, texture depth, lane count, pavement width, rutting, speed limit, traffic rates intersections, traffic signage and road design and so on.
Resumo:
Although player enjoyment is central to computer games, there is currently no accepted model of player enjoyment in games. There are many heuristics in the literature, based on elements such as the game interface, mechanics, gameplay, and narrative. However, there is a need to integrate these heuristics into a validated model that can be used to design, evaluate, and understand enjoyment in games. We have drawn together the various heuristics into a concise model of enjoyment in games that is structured by flow. Flow, a widely accepted model of enjoyment, includes eight elements that, we found, encompass the various heuristics from the literature. Our new model, GameFlow, consists of eight elements -- concentration, challenge, skills, control, clear goals, feedback, immersion, and social interaction. Each element includes a set of criteria for achieving enjoyment in games. An initial investigation and validation of the GameFlow model was carried out by conducting expert reviews of two real-time strategy games, one high-rating and one low-rating, using the GameFlow criteria. The result was a deeper understanding of enjoyment in real-time strategy games and the identification of the strengths and weaknesses of the GameFlow model as an evaluation tool. The GameFlow criteria were able to successfully distinguish between the high-rated and low-rated games and identify why one succeeded and the other failed. We concluded that the GameFlow model can be used in its current form to review games; further work will provide tools for designing and evaluating enjoyment in games.
Resumo:
This paper explores the embodiment of agency concepts in tangible user interfaces to create meaningful learning experiences. Current notions of agent-based tangible technology are extended, through the development of low-fidelity prototypes, to include additional flexibility and adaptability. A study involving these prototypes was conducted in a kindergarten environment with nine four-year-old children. Observations of children's interactions with the prototypes produced insightful results which will be used to further refine the product under development.
Resumo:
Developing safe and sustainable road systems is a common goal in all countries. Applications to assist with road asset management and crash minimization are sought universally. This paper presents a data mining methodology using decision trees for modeling the crash proneness of road segments using available road and crash attributes. The models quantify the concept of crash proneness and demonstrate that road segments with only a few crashes have more in common with non-crash roads than roads with higher crash counts. This paper also examines ways of dealing with highly unbalanced data sets encountered in the study.
Resumo:
This paper describes an ethnographic study completed within a kindergarten environment with the view of gaining insights into the development of new technology for young children. Ethnography within HCI has primarily focused on studies of work practices. This project explored the effectiveness of ethnography in supporting the design of playful technology for a constantly changing, creative, and (sometimes) messy environment. The study was effective in drawing out patterns in observations and as such provides useful suggestions for the development of technology for kindergarten settings.
Resumo:
This paper examines the issues surrounding the successful design and development of tangible technology for optimal engagement in playful activities. At present there is very little data on how, and in what contexts, tangible interactions with technology promote lasting engagement and immersion. The framework at the core of this paper has been designed to guide the effective design of tangible technology for immersive interaction. The paper investigates the relationship between tangible user interfaces (TUI) characteristics of representation and control, and immersive flow experiences produced through balancing skill and challenge in user interaction.
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In this paper we present an account of children's interactions with a mobile technology prototype within a school context. The Noise Detectives trial was conducted in a school setting with the aim of better understanding the role of mobile technology as a mediator within science learning activities. Over eighty children, aged between ten and twelve, completed an outdoor data gathering activity using a mobile learning prototype that included paper and digital components. They measured and recorded noise levels at a range of locations throughout the schools. We analyzed the activity to determine how the components of the prototype were integrated into the learning activity, and to identify differences in behavior that resulted from using these components. We present design implications that resulted from observed differences in prototype use and appropriation.
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This paper reports on the challenges faced during the design and deployment of educationally-focused cultural probes with children. The aim of the project was to use cultural probes to discover insights into children's interests and ideas within an educational context. The deployment of a cultural probe pack with children aged between 11 and 13 has demonstrated the method's effectiveness as a tool for design inspiration. Children's responses to the cultural probe have provided a valuable insight into the attributes of successful probe activities, the nature of contextual information which may be gathered and the limitations of the method.
Resumo:
The project is working towards building an understanding of the personal interests and experiences of children with the aim of designing appropriate, usable and, most importantly, inspirational educational technology. kidprobe, an adaptation of the technology probe concept, has been used as a lightweight method of gaining contextual information about children's interactions with 'fun' technology. kidprobe has produced design inspiration which focuses primarily on the social and emotional connections children made. The use of kidprobe has generated some important ideas for improving the use of probes with children. It is an important first step in understanding how to effectively adapt probing techniques to inspire the design of technology for children.