32,435 research outputs found
Attribute Exploration of Discrete Temporal Transitions
Discrete temporal transitions occur in a variety of domains, but this work is
mainly motivated by applications in molecular biology: explaining and analyzing
observed transcriptome and proteome time series by literature and database
knowledge. The starting point of a formal concept analysis model is presented.
The objects of a formal context are states of the interesting entities, and the
attributes are the variable properties defining the current state (e.g.
observed presence or absence of proteins). Temporal transitions assign a
relation to the objects, defined by deterministic or non-deterministic
transition rules between sets of pre- and postconditions. This relation can be
generalized to its transitive closure, i.e. states are related if one results
from the other by a transition sequence of arbitrary length. The focus of the
work is the adaptation of the attribute exploration algorithm to such a
relational context, so that questions concerning temporal dependencies can be
asked during the exploration process and be answered from the computed stem
base. Results are given for the abstract example of a game and a small gene
regulatory network relevant to a biomedical question.Comment: Only the email address and reference have been replace
Concept discovery innovations in law enforcement: a perspective.
In the past decades, the amount of information available to law enforcement agencies has increased significantly. Most of this information is in textual form, however analyses have mainly focused on the structured data. In this paper, we give an overview of the concept discovery projects at the Amsterdam-Amstelland police where Formal Concept Analysis (FCA) is being used as text mining instrument. FCA is combined with statistical techniques such as Hidden Markov Models (HMM) and Emergent Self Organizing Maps (ESOM). The combination of this concept discovery and refinement technique with statistical techniques for analyzing high-dimensional data not only resulted in new insights but often in actual improvements of the investigation procedures.Formal concept analysis; Intelligence led policing; Knowledge discovery;
Terrorist threat assessment with formal concept analysis.
The National Police Service Agency of the Netherlands developed a model to classify (potential) jihadists in four sequential phases of radicalism. The goal of the model is to signal the potential jihadist as early as possible to prevent him or her to enter the next phase. This model has up till now, never been used to actively find new subjects. In this paper, we use Formal Concept Analysis to extract and visualize potential jihadists in the different phases of radicalism from a large set of reports describing police observations. We employ Temporal Concept Analysis to visualize how a possible jihadist radicalizes over time. The combination of these instruments allows for easy decisionmaking on where and when to act.Formal concept analysis; Temporal concept analysis; Contextual attribute logic; Text mining; Terrorist threat assesment;
How theories of practice can inform transition to a decarbonised transport system
In this article, I explore the potential of theories of practice to inform the socio-technical transition required to adequately decarbonise the UK transport system. To do so I push existing applications of practice theories by articulating a ‘systems of practice’ approach, which articulates theories of practice with socio-technical systems approaches. After sketching out a theory of practice, I explore the potential of a practice theory approach to illuminate systemic change in transport. I do this by confronting two key criticisms of practice theories; first of their difficulty in accounting for change; second in their limited ability to move beyond a micro-level focus on doing. The counter I offer to these criticisms leads directly into recognising how theories of practice can articulate with socio-technical systems approaches. From this basis, I go on to consider the implications of a practice theory approach for informing interventions to effect a system transition towards decarbonised transport
Human Motion Trajectory Prediction: A Survey
With growing numbers of intelligent autonomous systems in human environments,
the ability of such systems to perceive, understand and anticipate human
behavior becomes increasingly important. Specifically, predicting future
positions of dynamic agents and planning considering such predictions are key
tasks for self-driving vehicles, service robots and advanced surveillance
systems. This paper provides a survey of human motion trajectory prediction. We
review, analyze and structure a large selection of work from different
communities and propose a taxonomy that categorizes existing methods based on
the motion modeling approach and level of contextual information used. We
provide an overview of the existing datasets and performance metrics. We
discuss limitations of the state of the art and outline directions for further
research.Comment: Submitted to the International Journal of Robotics Research (IJRR),
37 page
Time indeterminacy and spatio-temporal building transformations: an approach for architectural heritage understanding
Nowadays most digital reconstructions in architecture and archeology describe buildings heritage as awhole of static and unchangeable entities. However, historical sites can have a rich and complex history, sometimes full of evolutions, sometimes only partially known by means of documentary sources. Various aspects condition the analysis and the interpretation of cultural heritage. First of all, buildings are not inexorably constant in time: creation, destruction, union, division, annexation, partial demolition and change of function are the transformations that buildings can undergo over time. Moreover, other factors sometimes contradictory can condition the knowledge about an historical site, such as historical sources and uncertainty. On one hand, historical documentation concerning past states can be heterogeneous, dubious, incomplete and even contradictory. On the other hand, uncertainty is prevalent in cultural heritage in various forms: sometimes it is impossible to define the dating period, sometimes the building original shape or yet its spatial position. This paper proposes amodeling approach of the geometrical representation of buildings, taking into account the kind of transformations and the notion of temporal indetermination
Sensing motion using spectral and spatial analysis of WLAN RSSI
In this paper we present how motion sensing can be obtained just by observing the WLAN radio signal strength and its fluctuations. The temporal, spectral and spatial characteristics of WLAN signal are analyzed. Our analysis
confirms our claim that ’signal strength from access points appear to jump around more vigorously when the device is moving compared to when it is still and the number of detectable access points vary considerably while the user is on the move’. Using this observation, we present a novel motion detection algorithm, Spectrally Spread Motion Detection (SpecSMD) based on the spectral analysis of
WLAN signal’s RSSI. To benchmark the proposed algorithm, we used Spatially Spread Motion Detection (SpatSMD), which is inspired by the recent work of Sohn et al. Both algorithms were evaluated by carrying out extensive measurements
in a diverse set of conditions (indoors in different buildings and outdoors - city center, parking lot, university campus etc.,) and tested against the same
data sets. The 94% average classification accuracy of the proposed SpecSMD is outperforming the accuracy of SpatSMD (accuracy 87%). The motion detection algorithms presented in this paper provide ubiquitous methods for deriving the
state of the user. The algorithms can be implemented and run on a commodity device with WLAN capability without the need of any additional hardware support
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