Useful ideas for exploiting time to engineer representations

Commentary on target article "From simple associations to systematic reasoning: a connectionist representation of rules, variables, and dynamic bindings using temporal synchrony", by L. Shastri and V. Ajjangadde, pp. 417-494

Combining data driven programming with component based software development:with applications in geovisualisation and dynamic data driven application systems

Software development methodologies are becoming increasingly abstract, progressing from low level assembly and implementation languages such as C and Ada, to component based approaches that can be used to assemble applications using technologies such as JavaBeans and the .NET framework. Meanwhile, model driven approaches emphasise the role of higher level models and notations, and embody a process of automatically deriving lower level representations and concrete software implementations. The relationship between data and software is also evolving. Modern data formats are becoming increasingly standardised, open and empowered in order to support a growing need to share data in both academia and industry. Many contemporary data formats, most notably those based on XML, are self-describing, able to specify valid data structure and content, and can also describe data manipulations and transformations. Furthermore, while applications of the past have made extensive use of data, the runtime behaviour of future applications may be driven by data, as demonstrated by the field of dynamic data driven application systems. The combination of empowered data formats and high level software development methodologies forms the basis of modern game development technologies, which drive software capabilities and runtime behaviour using empowered data formats describing game content. While low level libraries provide optimised runtime execution, content data is used to drive a wide variety of interactive and immersive experiences. This thesis describes the Fluid project, which combines component based software development and game development technologies in order to define novel component technologies for the description of data driven component based applications. The thesis makes explicit contributions to the fields of component based software development and visualisation of spatiotemporal scenes, and also describes potential implications for game development technologies. The thesis also proposes a number of developments in dynamic data driven application systems in order to further empower the role of data in this field.

Automobile friction materials: a test instrument and technique for determining dynamic mechanical properties in relation to brake squeal

This study is primarily concerned with the problem of break-squeal in disc brakes, using moulded organic disc pads. Moulded organic friction materials are complex composites and due to this complexity it was thought that they are unlikely to be of uniform composition. Variation in composition would under certain conditions of the braking system, cause slight changes in its vibrational characteristics thus causing resonance in the high audio-frequency range. Dynamic mechanical propertes appear the most likely parameters to be related to a given composition's tendency to promote squeal. Since it was necessary to test under service conditions a review was made of all the available commercial test instruments but as none were suitable it was necessary to design and develop a new instrument. The final instrument design, based on longitudinal resonance, enabled modulus and damping to be determined over a wide range of temperatures and frequencies. This apparatus has commercial value since it is not restricted to friction material testing. Both used and unused pads were tested and although the cause of brake squeal was not definitely established, the results enabled formulation of a tentative theory of the possible conditions for brake squeal. The presence of a temperature of minimum damping was indicated which may be of use to braking design engineers. Some auxilIary testing was also performed to establish the effect of water, oil and brake fluid and also to determine the effect of the various components of friction materials.

Normal ECG Recognition for Express-Diagnostics Based on Scale-Space Representation and Dynamic Matching

A novel approach of normal ECG recognition based on scale-space signal representation is proposed. The approach utilizes curvature scale-space signal representation used to match visual objects shapes previously and dynamic programming algorithm for matching CSS representations of ECG signals. Extraction and matching processes are fast and experimental results show that the approach is quite robust for preliminary normal ECG recognition.

Abstractions to support dynamic adaptation of communication frameworks for user-centric communication

The convergence of data, audio and video on IP networks is changing the way individuals, groups and organizations communicate. This diversity of communication media presents opportunities for creating synergistic collaborative communications. This form of collaborative communication is however not without its challenges. The increasing number of communication service providers coupled with a combinatorial mix of offered services, varying Quality-of-Service and oscillating pricing of services increases the complexity for the user to manage and maintain ‘always best’ priced or performance services. Consumers have to manually manage and adapt their communication in line with differences in services across devices, networks and media while ensuring that the usage remain consistent with their intended goals. This dissertation proposes a novel user-centric approach to address this problem. The proposed approach aims to reduce the aforementioned complexity to the user by (1) providing high-level abstractions and a policy based methodology for automated selection of the communication services guided by high-level user policies and (2) providing services through the seamless integration of multiple communication service providers and providing an extensible framework to support the integration of multiple communication service providers. The approach was implemented in the Communication Virtual Machine (CVM), a model-driven technology for realizing communication applications. The CVM includes the Network Communication Broker, the layer responsible for providing a network-independent API to the upper layers of CVM. The initial prototype for the NCB supported only a single communication framework which limited the number, quality and types of services available. Experimental evaluation of the approach show the additional overhead of the approach is minimal compared to the individual communication services frameworks. Additionally the automated approach proposed out performed the individual communication services frameworks for cross framework switching.

A Comparison of Audio Recordings and Therapist's Process Notes in Child and Adolescent Psychoanalytic Psychotherapy

Therapistsʼ process notes - written descriptions of a session produced shortly afterwards from memory - hold a significant role in child and adolescent psychoanalytic psychotherapy. They are central in training, in supervision, and in developing oneʼs understanding through selfsupervision and forms of psychotherapy research. This thesis examines such process notes through a comparison with audio recordings of the same sessions. In so doing, it aims to generate theory that might illuminate the causes of significantly patterned discrepancies between the notes and recordings, in order to understand more about the processes at work in psychoanalytic psychotherapy and to explore the nature of process notes, their values and limitations. The literature searches conducted revealed limited relevant studies. All identified studies that compare process notes with recordings of sessions seek to quantify the differences between the two forms of recording. Unlike these, this thesis explores the meaning of the differences between process notes and recordings through qualitative data analysis. Using psychoanalytically informed grounded theory, in total nine sets of process notes and recordings from three different psychoanalytic psychotherapists are analysed. The analysis identifies eight core categories of findings. Initial theories are developed from these categories, most significantly concerning the role and influence of a ʻcore transference dynamicʼ between therapist and patient. Further theory is developed on the nature and function of process notes as a means for the therapistʼs conscious and unconscious processing of the session, as well as on the nature of the influence of the relationships – both internal and external – within which they are written. In the light of the findings, a proposal is made for a new approach for learning about the patient and clinical work, ʻthe comparison methodʼ (supervision involving a comparison of process notes and recordings), and, in particular, for its inclusion within the training of psychoanalytic psychotherapists. Further recommendations for research are also made.

A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies

A simple but efficient voice activity detector based on the Hilbert transform and a dynamic threshold is presented to be used on the pre-processing of audio signals -- The algorithm to define the dynamic threshold is a modification of a convex combination found in literature -- This scheme allows the detection of prosodic and silence segments on a speech in presence of non-ideal conditions like a spectral overlapped noise -- The present work shows preliminary results over a database built with some political speech -- The tests were performed adding artificial noise to natural noises over the audio signals, and some algorithms are compared -- Results will be extrapolated to the field of adaptive filtering on monophonic signals and the analysis of speech pathologies on futures works

Interação didática em língua estrangeira: contributos de um estudo baseado na dimensão sócio-afetiva da aprendizagem colaborativa

Pretendeu-se com este projecto de investigação estudar a interação didática co-construída por alunos do ensino superior em moldes de aprendizagem colaborativa na aula de Inglês língua estrangeira, com enfoque na dimensão sócio-afetiva da aprendizagem. Na base do quadro teórico encontra-se o pressuposto de que o conhecimento é algo dinâmico e construído colaborativamente, e que é na interação didática que emergem os comportamentos verbais reveladores do Saber―Ser/Estar/Aprender dos sujeitos, nomeadamente através da coconstrução e negociação de sentidos. Subjacente portanto ao estudo está a convicção de que “o trabalho crítico sobre a interação permite entender os modos relacionais entre os sujeitos pedagógicos, as relações interpessoais que se estabelecem e articular o desenvolvimento linguístico-comunicativo com o desenvolvimento pessoal e social dos alunos” (Araújo e Sá & Andrade, 2002, p. 82). Esta investigação centra-se exclusivamente nos aprendentes, na sequência de indicações provenientes da revisão de literatura, as quais apontam para uma lacuna nas investigações efetuadas até à data, referente ao número insuficiente de estudos dedicado à interação didática interpares, já que a grande maioria dos estudos se dirige para a relação professor-aluno (cf. Baker & Clark, 2010; Hellermann, 2008; O'Donnell & King, 2014). Por outro lado, o estado da arte relativo às investigações focalizadas na interacção entre aprendentes permite concluir que a melhor forma de exponenciar esta interação será através da aprendizagem colaborativa (cf. Johnson, Johnson, & Stanne, 2000; Slavin, 2014; Smith, Sheppard, Johnson, & Johnson, 2005). Circunscrevemos o nosso estudo à dimensão sócio-afetiva das estratégias de aprendizagem que ocorrem nessas interações, já que a revisão da literatura fez evidenciar a correlação positiva da aprendizagem colaborativa com as dimensões social e afetiva da interação (cf. Byun et al., 2012): por um lado, a dinâmica de grupo numa aula de língua estrangeira contribui grandemente para uma perceção afetiva favorável do processo de aprendizagem, incrementando igualmente a quantidade e a qualidade da interação (cf. Felder & Brent, 2007); por outro lado, a existência, na aprendizagem colaborativa, dos fenómenos de correção dos pares e de negociação de sentidos estimula a emergência da dimensão sócio-afetiva da aprendizagem de uma língua estrangeira (cf. Campbell & Kryszewska,1992; Hadfield, 1992; Macaro, 2005). É neste enquadramento teórico que se situam as nossas questões e objetivos de investigação. Em primeiro lugar procurámos saber como é que um grupo de aprendentes de Inglês língua estrangeira do ensino superior perceciona as estratégias de aprendizagem sócio-afetivas que utiliza em contexto de sala de aula, no âmbito da aprendizagem colaborativa e nãocolaborativa. Procurámos igualmente indagar quais as estratégias de aprendizagem sócio-afetivas passíveis de serem identificadas neste grupo de aprendentes, em situação de interação didática, em contexto de aprendizagem colaborativa. Finalmente, questionámo-nos sobre a relação entre a perceção que estes alunos possuem das estratégias de aprendizagem sócio-afetivas que empregam nas aulas de Inglês língua estrangeira e as estratégias sócio-afetivas identificadas em situação de interação didática, em contexto de aprendizagem colaborativa. No que respeita à componente empírica do nosso projecto, norteámo-nos pelo paradigma qualitativo, no contexto do qual efetuámos um estudo de caso, a partir de uma abordagem tendencialmente etnográfica, por tal nos parecer mais consentâneo, quer com a nossa problemática, quer com a natureza complexa dos processos interativos em sala de aula. A metodologia quantitativa está igualmente presente, pretendendo-se que tenha adicionado mais dimensionalidade à investigação, contribuindo para a triangulação dos resultados. A investigação, que se desenvolveu ao longo de 18 semanas, teve a sala de aula como local privilegiado para obter grande parte da informação. Os participantes do estudo de caso foram 24 alunos do primeiro ano de uma turma de Inglês Língua Estrangeira de um Instituto Politécnico, sendo a investigadora a docente da disciplina. A informação proveio primordialmente de um corpus de interações didáticas colaborativas audiogravadas e posteriormente transcritas, constituído por 8 sessões com uma duração aproximada de uma hora, e das respostas a um inquérito por questionário − construído a partir da taxonomia de Oxford (1990) − relativo à dimensão sócio-afetiva das estratégias de aprendizagem do Inglês língua estrangeira. O corpus gravado e transcrito foi analisado através da categorização por indicadores, com o objetivo de se detetarem as marcas sócio-afetivas das estratégias de aprendizagem mobilizadas pelos alunos. As respostas ao questionário foram tratadas quantitativamente numa primeira fase, e os resultados foram posteriormente triangulados com os provenientes da análise do corpus de interações. Este estudo permitiu: i) elencar as estratégias de aprendizagem que os aprendentes referem utilizar em situação de aprendizagem colaborativa e não colaborativa, ii) detetar quais destas estratégias são efetivamente utilizadas na aprendizagem colaborativa, iii) e concluir que existe, na maioria dos casos, um desfasamento entre o autoconceito do aluno relativamente ao seu perfil de aprendente de línguas estrangeiras, mais concretamente às dimensões afetiva e social das estratégias de aprendizagem que mobiliza, e a forma como este aprendente recorre a estas mesma estratégias na sala de aula. Concluímos igualmente que, em termos globais, existem diferenças, por vezes significativas, entre as representações que os sujeitos possuem da aprendizagem colaborativa e aquelas que detêm acerca da aprendizagem não colaborativa.

Which way is up? Grounded mental representations of space

Processing language is postulated to involve a mental simulation, or re-enactment of perceptual, motor, and introspective states that were acquired experientially (Barsalou, 1999, 2008). One such aspect that is mentally simulated during processing of certain concepts is spatial location. For example, upon processing the word “moon” the prominent spatial location of the concept (e.g. ‘upward’) is mentally simulated. In six eye-tracking experiments, we investigate how mental simulations of spatial location affect processing. We first address a conflict in previous literature whereby processing is shown to be impacted in both a facilitatory and inhibitory way. Two of our experiments showed that mental simulations of spatial association facilitate saccades launched toward compatible locations; however, a third experiment showed an inhibitory effect on saccades launched towards incompatible locations. We investigated these differences with further experiments, which led us to conclude that the nature of the effect (facilitatory or inhibitory) is dependent on the demands of the task and, in fitting with the theory of Grounded Cognition (Barsalou, 2008), that mental simulations impact processing in a dynamic way. Three further experiments explored the nature of verticality – specifically, whether ‘up’ is perceived as away from gravity, or above our head. Using similar eye-tracking methods, and by manipulating the position of participants, we were able to dissociate these two possible standpoints. The results showed that mental simulations of spatial location facilitated saccades to compatible locations, but only when verticality was dissociated from gravity (i.e. ‘up’ was above the participant’s head). We conclude that this is not due to an ‘embodied’ mental simulation, but rather a result of heavily ingrained visuo-motor association between vertical space and eye movements.

Movement Sonification: Effects on Motor Learning beyond Rhythmic Adjustments

Motor learning is based on motor perception and emergent perceptual-motor representations. A lot of behavioral research is related to single perceptual modalities but during last two decades the contribution of multimodal perception on motor behavior was discovered more and more. A growing number of studies indicates an enhanced impact of multimodal stimuli on motor perception, motor control and motor learning in terms of better precision and higher reliability of the related actions. Behavioral research is supported by neurophysiological data, revealing that multisensory integration supports motor control and learning. But the overwhelming part of both research lines is dedicated to basic research. Besides research in the domains of music, dance and motor rehabilitation, there is almost no evidence for enhanced effectiveness of multisensory information on learning of gross motor skills. To reduce this gap, movement sonification is used here in applied research on motor learning in sports. Based on the current knowledge on the multimodal organization of the perceptual system, we generate additional real-time movement information being suitable for integration with perceptual feedback streams of visual and proprioceptive modality. With ongoing training, synchronously processed auditory information should be initially integrated into the emerging internal models, enhancing the efficacy of motor learning. This is achieved by a direct mapping of kinematic and dynamic motion parameters to electronic sounds, resulting in continuous auditory and convergent audiovisual or audio-proprioceptive stimulus arrays. In sharp contrast to other approaches using acoustic information as error-feedback in motor learning settings, we try to generate additional movement information suitable for acceleration and enhancement of adequate sensorimotor representations and processible below the level of consciousness. In the experimental setting, participants were asked to learn a closed motor skill (technique acquisition of indoor rowing). One group was treated with visual information and two groups with audiovisual information (sonification vs. natural sounds). For all three groups learning became evident and remained stable. Participants treated with additional movement sonification showed better performance compared to both other groups. Results indicate that movement sonification enhances motor learning of a complex gross motor skill-even exceeding usually expected acoustic rhythmic effects on motor learning.

Learning Binary Code Representations for Effective and Efficient Image Retrieval

The size of online image datasets is constantly increasing. Considering an image dataset with millions of images, image retrieval becomes a seemingly intractable problem for exhaustive similarity search algorithms. Hashing methods, which encodes high-dimensional descriptors into compact binary strings, have become very popular because of their high efficiency in search and storage capacity. In the first part, we propose a multimodal retrieval method based on latent feature models. The procedure consists of a nonparametric Bayesian framework for learning underlying semantically meaningful abstract features in a multimodal dataset, a probabilistic retrieval model that allows cross-modal queries and an extension model for relevance feedback. In the second part, we focus on supervised hashing with kernels. We describe a flexible hashing procedure that treats binary codes and pairwise semantic similarity as latent and observed variables, respectively, in a probabilistic model based on Gaussian processes for binary classification. We present a scalable inference algorithm with the sparse pseudo-input Gaussian process (SPGP) model and distributed computing. In the last part, we define an incremental hashing strategy for dynamic databases where new images are added to the databases frequently. The method is based on a two-stage classification framework using binary and multi-class SVMs. The proposed method also enforces balance in binary codes by an imbalance penalty to obtain higher quality binary codes. We learn hash functions by an efficient algorithm where the NP-hard problem of finding optimal binary codes is solved via cyclic coordinate descent and SVMs are trained in a parallelized incremental manner. For modifications like adding images from an unseen class, we propose an incremental procedure for effective and efficient updates to the previous hash functions. Experiments on three large-scale image datasets demonstrate that the incremental strategy is capable of efficiently updating hash functions to the same retrieval performance as hashing from scratch.

Audio-Visual Information Processing across different age groups

People possess different sensory modalities to detect, interpret, and efficiently act upon various events in a complex and dynamic environment (Fetsch, DeAngelis, & Angelaki, 2013). Much empirical work has been done to understand the interplay of modalities (e.g. audio-visual interactions, see Calvert, Spence, & Stein, 2004). On the one hand, integration of multimodal input as a functional principle of the brain enables the versatile and coherent perception of the environment (Lewkowicz & Ghazanfar, 2009). On the other hand, sensory integration does not necessarily mean that input from modalities is always weighted equally (Ernst, 2008). Rather, when two or more modalities are stimulated concurrently, one often finds one modality dominating over another. Study 1 and 2 of the dissertation addressed the developmental trajectory of sensory dominance. In both studies, 6-year-olds, 9-year-olds, and adults were tested in order to examine sensory (audio-visual) dominance across different age groups. In Study 3, sensory dominance was put into an applied context by examining verbal and visual overshadowing effects among 4- to 6-year olds performing a face recognition task. The results of Study 1 and Study 2 support default auditory dominance in young children as proposed by Napolitano and Sloutsky (2004) that persists up to 6 years of age. For 9-year-olds, results on privileged modality processing were inconsistent. Whereas visual dominance was revealed in Study 1, privileged auditory processing was revealed in Study 2. Among adults, a visual dominance was observed in Study 1, which has also been demonstrated in preceding studies (see Spence, Parise, & Chen, 2012). No sensory dominance was revealed in Study 2 for adults. Potential explanations are discussed. Study 3 referred to verbal and visual overshadowing effects in 4- to 6-year-olds. The aim was to examine whether verbalization (i.e., verbally describing a previously seen face), or visualization (i.e., drawing the seen face) might affect later face recognition. No effect of visualization on recognition accuracy was revealed. As opposed to a verbal overshadowing effect, a verbal facilitation effect occurred. Moreover, verbal intelligence was a significant predictor for recognition accuracy in the verbalization group but not in the control group. This suggests that strengthening verbal intelligence in children can pay off in non-verbal domains as well, which might have educational implications.

Deploying and processing neural representations of signals

Neural representations (NR) have emerged in the last few years as a powerful tool to represent signals from several domains, such as images, 3D shapes, or audio. Indeed, deep neural networks have been shown capable of approximating continuous functions that describe a given signal with theoretical infinite resolution. This finding allows obtaining representations whose memory footprint is fixed and decoupled from the resolution at which the underlying signal can be sampled, something that is not possible with traditional discrete representations, e.g., grids of pixels for images or voxels for 3D shapes. During the last two years, many techniques have been proposed to improve the capability of NR to approximate high-frequency details and to make the optimization procedures required to obtain NR less demanding both in terms of time and data requirements, motivating many researchers to deploy NR as the main form of data representation for complex pipelines. Following this line of research, we first show that NR can approximate precisely Unsigned Distance Functions, providing an effective way to represent garments that feature open 3D surfaces and unknown topology. Then, we present a pipeline to obtain in a few minutes a compact Neural Twin® for a given object, by exploiting the recent advances in modeling neural radiance fields. Furthermore, we move a step in the direction of adopting NR as a standalone representation, by considering the possibility of performing downstream tasks by processing directly the NR weights. We first show that deep neural networks can be compressed into compact latent codes. Then, we show how this technique can be exploited to perform deep learning on implicit neural representations (INR) of 3D shapes, by only looking at the weights of the networks.

Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

Reference Values For High-density Lipoprotein Particle Size And Volume By Dynamic Light Scattering In A Brazilian Population Sample And Their Relationships With Metabolic Parameters.

Current data indicate that the size of high-density lipoprotein (HDL) may be considered an important marker for cardiovascular disease risk. We established reference values of mean HDL size and volume in an asymptomatic representative Brazilian population sample (n=590) and their associations with metabolic parameters by gender. Size and volume were determined in HDL isolated from plasma by polyethyleneglycol precipitation of apoB-containing lipoproteins and measured using the dynamic light scattering (DLS) technique. Although the gender and age distributions agreed with other studies, the mean HDL size reference value was slightly lower than in some other populations. Both HDL size and volume were influenced by gender and varied according to age. HDL size was associated with age and HDL-C (total population); non- white ethnicity and CETP inversely (females); HDL-C and PLTP mass (males). On the other hand, HDL volume was determined only by HDL-C (total population and in both genders) and by PLTP mass (males). The reference values for mean HDL size and volume using the DLS technique were established in an asymptomatic and representative Brazilian population sample, as well as their related metabolic factors. HDL-C was a major determinant of HDL size and volume, which were differently modulated in females and in males.