Normdaten im Semantic Web - Konzept für eine Ontologie der Personennamendatei (PND)

Das Ziel dieser Arbeit ist es, ein Konzept für eine Darstellung der Personennamendatei(PND) in den Sprachen Resource Description Framework (RDF), Resource DescriptionFramework Schema Language (RDFS) und Web Ontology Language (OWL) zu entwickeln. Der Prämisse des Semantic Web folgend, Daten sowohl in menschenverständlicher als auch in maschinell verarbeitbarer Form darzustellen und abzulegen, wird eine Struktur für Personendaten geschaffen. Dabei wird von der bestehenden Daten- und Struktursituation im Pica-Format ausgegangen. Die Erweiterbarkeit und Anpassbarkeit des Modells im Hinblick auf zukünftige, im Moment gegebenenfalls noch nicht absehbare Anwendungen und Strukurveränderungen, muss aber darüber hinaus gewährleistet sein. Die Modellierung orientiert sich an bestehenden Standards wie Dublin Core, Friend Of A Friend (FOAF), Functional Requirements for Bibliographic Records (FRBR), Functional Requirements for Authority Data (FRAD) und Resource Description and Access (RDA).

A utilização do Resource Description and Access (RDA) na criação de registros de autoridade para pessoas, famílias e entidades coletivas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bias na Representação de Assunto: Uma Discussão de Oposições Binárias nos Functional Requirements for Subject Authority Data (FRSAD)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

In-vehicle technology functional requirements for older drivers

Older drivers represent the fastest growing segment of the road user population. Cognitive and physiological capabilities diminishes with ages. The design of future in-vehicle interfaces have to take into account older drivers' needs and capabilities. Older drivers have different capabilities which impact on their driving patterns and subsequently on road crash patterns. New in-vehicle technology could improve safety, comfort and maintain elderly people's mobility for longer. Existing research has focused on the ergonomic and Human Machine Interface (HMI) aspects of in-vehicle technology to assist the elderly. However there is a lack of comprehensive research on identifying the most relevant technology and associated functionalities that could improve older drivers' road safety. To identify future research priorities for older drivers, this paper presents: (i) a review of age related functional impairments, (ii) a brief description of some key characteristics of older driver crashes and (iii) a conceptualisation of the most relevant technology interventions based on traffic psychology theory and crash data.

Data requirements and graph data structures for a multi-modal, multi-objective trip planner

Traffic congestion has a significant impact on the economy and environment. Encouraging the use of multimodal transport (public transport, bicycle, park’n’ride, etc.) has been identified by traffic operators as a good strategy to tackle congestion issues and its detrimental environmental impacts. A multi-modal and multi-objective trip planner provides users with various multi-modal options optimised on objectives that they prefer (cheapest, fastest, safest, etc) and has a potential to reduce congestion on both a temporal and spatial scale. The computation of multi-modal and multi-objective trips is a complicated mathematical problem, as it must integrate and utilize a diverse range of large data sets, including both road network information and public transport schedules, as well as optimising for a number of competing objectives, where fully optimising for one objective, such as travel time, can adversely affect other objectives, such as cost. The relationship between these objectives can also be quite subjective, as their priorities will vary from user to user. This paper will first outline the various data requirements and formats that are needed for the multi-modal multi-objective trip planner to operate, including static information about the physical infrastructure within Brisbane as well as real-time and historical data to predict traffic flow on the road network and the status of public transport. It will then present information on the graph data structures representing the road and public transport networks within Brisbane that are used in the trip planner to calculate optimal routes. This will allow for an investigation into the various shortest path algorithms that have been researched over the last few decades, and provide a foundation for the construction of the Multi-modal Multi-objective Trip Planner by the development of innovative new algorithms that can operate the large diverse data sets and competing objectives.

Describing and validating functional requirements as use cases

Requirements engineering is an important phase in software development where customer's needs and expectations are transformed into a software requirements specification. The requirements specification can be considered as an agreement between the customer and the developer where both parties agree on the expected system features and behaviour. However, requirements engineers must deal with a variety of issues that complicate the requirements process. The communication gap between the customer and the developers is among typical reasons for unsatisfactory requirements. In this thesis we study how the use case technique could be used in requirements engineering in bridging the communication gap between the customer and development team. We also discuss how a use case description can be use cases can be used as a basis for acceptance test cases.

Functional requirements for reward-modulated spike-timing-dependent plasticity.

Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.

Machine learning of functional class from phenotype data

Clare, A. and King R.D. (2002) Machine learning of functional class from phenotype data. Bioinformatics 18(1) 160-166

Towards a model-based integration of co-registered electroencephalography/functional magnetic resonance imaging data with realistic neural population meshes

Brain activity can be measured with several non-invasive neuroimaging modalities, but each modality has inherent limitations with respect to resolution, contrast and interpretability. It is hoped that multimodal integration will address these limitations by using the complementary features of already available data. However, purely statistical integration can prove problematic owing to the disparate signal sources. As an alternative, we propose here an advanced neural population model implemented on an anatomically sound cortical mesh with freely adjustable connectivity, which features proper signal expression through a realistic head model for the electroencephalogram (EEG), as well as a haemodynamic model for functional magnetic resonance imaging based on blood oxygen level dependent contrast (fMRI BOLD). It hence allows simultaneous and realistic predictions of EEG and fMRI BOLD from the same underlying model of neural activity. As proof of principle, we investigate here the influence on simulated brain activity of strengthening visual connectivity. In the future we plan to fit multimodal data with this neural population model. This promises novel, model-based insights into the brain's activity in sleep, rest and task conditions.

Support Tool to the Validation Process of Functional Requirements

The activity of validating identified requirements for an information system helps to improve the quality of a requirements specification document and, consequently, the success of a project. Although various different support tools to requirements engineering exist in the market, there is still a lack of automated support for validation activity. In this context, the purpose of this paper is to make up for that deficiency, with the use of an automated tool, to provide the resources for the execution of an adequate validation activity. The contribution of this study is to enable an agile and effective follow-up of the scope established for the requirements, so as to lead the development to a solution which would satisfy the real necessities of the users, as well as to supply project managers with relevant information about the maturity of the analysts involved in requirements specification.

Functional Magnetic Resonance Imaging Data Analysis by Autoregressive Estimator

The autoregressive (AR) estimator, a non-parametric method, is used to analyze functional magnetic resonance imaging (fMRI) data. The same method has been used, with success, in several other time series data analysis. It uses exclusively the available experimental data points to estimate the most plausible power spectra compatible with the experimental data and there is no need to make any assumption about non-measured points. The time series, obtained from fMRI block paradigm data, is analyzed by the AR method to determine the brain active regions involved in the processing of a given stimulus. This method is considerably more reliable than the fast Fourier transform or the parametric methods. The time series corresponding to each image pixel is analyzed using the AR estimator and the corresponding poles are obtained. The pole distribution gives the shape of power spectra, and the pixels with poles at the stimulation frequency are considered as the active regions. The method was applied in simulated and real data, its superiority is shown by the receiver operating characteristic curves which were obtained using the simulated data.

Functional requirements of histone deacetylases in Tup1-Ssn6 repression

The corepressor complex Tup1-Ssn6 regulates many classes of genes in yeast including cell type specific, glucose repressible, and DNA damage inducible. Tup1 and Ssn6 are recruited to target promoters through their interactions with specific DNA binding proteins such as α2, Mig1, and Crt1. Most promoters that are repressed by this corepressor complex exhibit a high degree of nucleosomal organization. This chromatin domain occludes transcription factor access to the promoter element resulting in gene repression. Previous work indicated that Tup1 interacts with underacetylated isoforms of H3 and H4, and that mutation of these histones synergistically compromises repression. These studies predict that Tup1-hypoacetyalted histone interaction is important to the repression mechanism, and in vivo hyperacetylation might compromise the corepressors ability to repress target genes. ^ One way to alter histone acetylation levels in vivo is to alter the balance between histone acetyltransferases and histone deacetylases. To date five histone deacetylases (HDACs) have been identified in yeast Rpd3, Hos1, Hos2, Hos3 and Hda1. Deletion of single or double HDAC genes had little to no effect on Tup1-Ssn6 repression, but simultaneous deletion of three specific activities Rpd3, Hos1, and Hos2 abolished repression in vivo. Promoter regions of Tup1-Ssn6 target genes in these triple deacetylase mutant cells are dramatically hyperacetylated in both H3 and H4. Examination of bulk histone acetylation levels showed that this specific HDAC triple mutant combination (rpd3 hos1 hos2) caused a dramatic and concomitant hyperacetylation of both H3 and H4. The loss of repression in the rpd3 hos1 hos2 cells, but not in other mutants, is consistent with previous observations, which indicate that histones provide redundant functions in the repression mechanism and that high levels of acetylation are required to prevent Tup1 binding. Investigation into a potential direct interaction between the Tup1-Ssn6 corepressor complex and one or more HDAC activities showed that both Rpd3 and Hos2 interact with the corepressor complex in vivo. These findings indicate that Tup1-Ssn6 repression involves the recruitment of histone deacetylase activities to target promoters, where they locally deacetylate histone residues promoting Tup1-histone tail interaction to initiate and/or maintain the repressed state. ^

Improved commercial vehicle conspicuity and signalling systems. Task I: accident analysis and functional requirements. Interim report.

National Highway Traffic Safety Administration, Washington, D.C.

Functional requirements for aircraft weapon system trainer instructor station display and recording systems

Cover title.

An examination of standards of functional requirements, performance and finish in housing

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