Uma análise das diferenças em termos da cultura e dos interesses profissionais a partir do projeto de substituiçao das IAS 39: Financial Instruments - Recognition and Measurement

Mestrado em Contabilidade

The recognition of work

The following article argues that recognition structures in work relations differ significantly in the sphere of paid work in contrast to unpaid work in private spheres. According to the systematic approach on recognition of Axel Honneth three different levels of recognition are identified: the interpersonal recognition, organisational recognition and societal recognition. Based on this framework it can be stated that recognition structures in the sphere of paid work and in private spheres differ very much. Whereas recognition in private spheres depends very much on personal relations, thus on the interpersonal level, recognition in employment relationships can be moreover built on organisational structures. Comparing recognition structures in both fields it becomes apparent, that recognition in field of employment can be characterised as much more concrete, comparable and measurable. Therefore, it can be concluded that the structural differences of recognition contribute to the high societal and individual importance of employment in contrast to unpaid work in private spheres.

ECG Biometrics: A Template Selection Approach

Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.

Human biomonitoring: biomarkers, susceptibility, and nutrigenetics

The methods of molecular biology applied in epidemiological research lead us to the realm of molecular epidemiology, where there is immense potential for the establishment of associations between cancer and exposure to risk factors in lifestyle, profession, or pollution. Human biomonitoring consists, on the one hand, in research and identification of hazardous environmental conditions and, on the other hand, in the assessment of cancer risk following exposure to such conditions. Since carcinogenesis is a lengthy process, the biomarkers used to recognize biological abnormalities are selected and developed in the realm of molecular epidemiology. Such biomarkers are quantifiable and allow for the recognition of progression from normal to abnormal biological conditions at the molecular level. They can be categorized in biomarkers of exposure, effect, and genetic susceptibility. Genotoxicity biomarkers are a particular subset of effect biomarkers and are used to assess genomic instability caused by environmental or occupational exposure, being considered useful carcinogenesis predictors.

Logarithmically proportional objective function for planar surfaces recognition in 3D point cloud

3D laser scanning is becoming a standard technology to generate building models of a facility's as-is condition. Since most constructions are constructed upon planar surfaces, recognition of them paves the way for automation of generating building models. This paper introduces a new logarithmically proportional objective function that can be used in both heuristic and metaheuristic (MH) algorithms to discover planar surfaces in a point cloud without exploiting any prior knowledge about those surfaces. It can also adopt itself to the structural density of a scanned construction. In this paper, a metaheuristic method, genetic algorithm (GA), is used to test this introduced objective function on a synthetic point cloud. The results obtained show the proposed method is capable to find all plane configurations of planar surfaces (with a wide variety of sizes) in the point cloud with a minor distance to the actual configurations. © 2014 IEEE.

Chiroptical and emissive properties of a calix[4]arene-containing chiral poly (P-phenylene ethynylene) with enantioselective recognition ability

Supramolecular chirality was achieved in solutions and thin films of a calixarene-containing chiral aryleneethynylene copolymer. The observed chiroptical activity, which is primarily allied with the formation of aggregates of high molecular weight polymer chains, is the result of a combination of intrachain and interchain effects. The former arises by the adoption of an induced helix-sense by the polymer main-chain while the latter comes from the exciton coupling of aromatic backbone transitions. The co-existence of bulky bis-calixKlarene units and chiral side-chains on the polymer skeleton prevents efficient pi-stacking of neighbouring chains, keeping the chiral assembly highly emissive. In contrast, for a model polymer lacking calixarene moieties, the chiroptical activity is dominated by strong interchain exciton couplings as a result of more favourable packing of polymer chains, leading to a marked decrease of photoluminescence in the aggregate state. The enantiomeric recognition abilities of both polymers towards (R)- and (S)-alpha-methylbenzylamine were examined. It was found that a significant enantiodiscrimination is exhibited by the calixarene-based polymer in the aggregate state.

Analysis and recognition of similar environmental sounds

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

Imparidades e os valores contabilísticos de Gray: estudo empírico de empresas não cotadas em Portugal

v. 1, n. 1 Floriano-PI, Jan-Jun. 2014

ECG-based biometrics: A real time classification approach

Behavioral biometrics is one of the areas with growing interest within the biosignal research community. A recent trend in the field is ECG-based biometrics, where electrocardiographic (ECG) signals are used as input to the biometric system. Previous work has shown this to be a promising trait, with the potential to serve as a good complement to other existing, and already more established modalities, due to its intrinsic characteristics. In this paper, we propose a system for ECG biometrics centered on signals acquired at the subject's hand. Our work is based on a previously developed custom, non-intrusive sensing apparatus for data acquisition at the hands, and involved the pre-processing of the ECG signals, and evaluation of two classification approaches targeted at real-time or near real-time applications. Preliminary results show that this system leads to competitive results both for authentication and identification, and further validate the potential of ECG signals as a complementary modality in the toolbox of the biometric system designer.

TRAILER project overview: tagging, recognition and acknowledgment of informal learning experiences

The evolution of new technology and its increasing use, have for some years been making the existence of informal learning more and more transparent, especially among young and older adults in both Higher Education and workplace contexts. However, the nature of formal and non-formal, course-based, approaches to learning has made it hard to accommodate these informal processes satisfactorily, and although technology bring us near to the solution, it has not yet achieved. TRAILER project aims to address this problem by developing a tool for the management of competences and skills acquired through informal learning experiences, both from the perspective of the user and the institution or company. This paper describes the research and development main lines of this project.

Interface caligráfica de escrita no ar

Na atualidade, está a emergir um novo paradigma de interação, designado por Natural User Interface (NUI) para reconhecimento de gestos produzidos com o corpo do utilizador. O dispositivo de interação Microsoft Kinect foi inicialmente concebido para controlo de videojogos, para a consola Xbox360. Este dispositivo demonstra ser uma aposta viável para explorar outras áreas, como a do apoio ao processo de ensino e de aprendizagem para crianças do ensino básico. O protótipo desenvolvido visa definir um modo de interação baseado no desenho de letras no ar, e realizar a interpretação dos símbolos desenhados, usando os reconhecedores de padrões Kernel Discriminant Analysis (KDA), Support Vector Machines (SVM) e $N. O desenvolvimento deste projeto baseou-se no estudo dos diferentes dispositivos NUI disponíveis no mercado, bibliotecas de desenvolvimento NUI para este tipo de dispositivos e algoritmos de reconhecimento de padrões. Com base nos dois elementos iniciais, foi possível obter uma visão mais concreta de qual o hardware e software disponíveis indicados à persecução do objetivo pretendido. O reconhecimento de padrões constitui um tema bastante extenso e complexo, de modo que foi necessária a seleção de um conjunto limitado deste tipo de algoritmos, realizando os respetivos testes por forma a determinar qual o que melhor se adequava ao objetivo pretendido. Aplicando as mesmas condições aos três algoritmos de reconhecimento de padrões permitiu avaliar as suas capacidades e determinar o $N como o que apresentou maior eficácia no reconhecimento. Por último, tentou-se averiguar a viabilidade do protótipo desenvolvido, tendo sido testado num universo de elementos de duas faixas etárias para determinar a capacidade de adaptação e aprendizagem destes dois grupos. Neste estudo, constatou-se um melhor desempenho inicial ao modo de interação do grupo de idade mais avançada. Contudo, o grupo mais jovem foi revelando uma evolutiva capacidade de adaptação a este modo de interação melhorando progressivamente os resultados.

Enhancing informal learning recognition through TRAILER project

International Workshop on solutions that Enhance Informal LEarning Recognition – WEILER 2013

Reliable and Fast Hand-Offs in Low-Power Wireless Networks

Hand-off (or hand-over), the process where mobile nodes select the best access point available to transfer data, has been well studied in wireless networks. The performance of a hand-off process depends on the specific characteristics of the wireless links. In the case of low-power wireless networks, hand-off decisions must be carefully taken by considering the unique properties of inexpensive low-power radios. This paper addresses the design, implementation and evaluation of smart-HOP, a hand-off mechanism tailored for low-power wireless networks. This work has three main contributions. First, it formulates the hard hand-off process for low-power networks (such as typical wireless sensor networks - WSNs) with a probabilistic model, to investigate the impact of the most relevant channel parameters through an analytical approach. Second, it confirms the probabilistic model through simulation and further elaborates on the impact of several hand-off parameters. Third, it fine-tunes the most relevant hand-off parameters via an extended set of experiments, in a realistic experimental scenario. The evaluation shows that smart-HOP performs well in the transitional region while achieving more than 98 percent relative delivery ratio and hand-off delays in the order of a few tens of a milliseconds.

Exploiting the bin-class histograms for feature selection on discrete data

In machine learning and pattern recognition tasks, the use of feature discretization techniques may have several advantages. The discretized features may hold enough information for the learning task at hand, while ignoring minor fluctuations that are irrelevant or harmful for that task. The discretized features have more compact representations that may yield both better accuracy and lower training time, as compared to the use of the original features. However, in many cases, mainly with medium and high-dimensional data, the large number of features usually implies that there is some redundancy among them. Thus, we may further apply feature selection (FS) techniques on the discrete data, keeping the most relevant features, while discarding the irrelevant and redundant ones. In this paper, we propose relevance and redundancy criteria for supervised feature selection techniques on discrete data. These criteria are applied to the bin-class histograms of the discrete features. The experimental results, on public benchmark data, show that the proposed criteria can achieve better accuracy than widely used relevance and redundancy criteria, such as mutual information and the Fisher ratio.

Embedded system for individual recognition based on ECG biometrics

Biometric recognition is emerging has an alternative solution for applications where the privacy of the information is crucial. This paper presents an embedded biometric recognition system based on the Electrocardiographic signals (ECG) for individual identification and authentication. The proposed system implements a real-time state-of-the-art recognition algorithm, which extracts information from the frequency domain. The system is based on a ARM Cortex 4. Preliminary results show that embedded platforms are a promising path for the implementation of ECG-based applications in real-world scenario.