Input-state-output representations of concatenated 2D convolutional codes

In this paper we investigate a novel model of concatenation of a pair of two-dimensional (2D) convolutional codes. We consider finite-support 2D convolutional codes and choose the so-called Fornasini-Marchesini input-state-output (ISO) model to represent these codes. More concretely, we interconnect in series two ISO representations of two 2D convolutional codes and derive the ISO representation of the ob- tained 2D convolutional code. We provide necessary condition for this representation to be minimal. Moreover, structural properties of modal reachability and modal observability of the resulting 2D convolutional codes are investigated.

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.

Efficient Image and Video Representations for Retrieval

Image (Video) retrieval is an interesting problem of retrieving images (videos) similar to the query. Images (Videos) are represented in an input (feature) space and similar images (videos) are obtained by finding nearest neighbors in the input representation space. Numerous input representations both in real valued and binary space have been proposed for conducting faster retrieval. In this thesis, we present techniques that obtain improved input representations for retrieval in both supervised and unsupervised settings for images and videos. Supervised retrieval is a well known problem of retrieving same class images of the query. We address the practical aspects of achieving faster retrieval with binary codes as input representations for the supervised setting in the first part, where binary codes are used as addresses into hash tables. In practice, using binary codes as addresses does not guarantee fast retrieval, as similar images are not mapped to the same binary code (address). We address this problem by presenting an efficient supervised hashing (binary encoding) method that aims to explicitly map all the images of the same class ideally to a unique binary code. We refer to the binary codes of the images as `Semantic Binary Codes' and the unique code for all same class images as `Class Binary Code'. We also propose a new class­ based Hamming metric that dramatically reduces the retrieval times for larger databases, where only hamming distance is computed to the class binary codes. We also propose a Deep semantic binary code model, by replacing the output layer of a popular convolutional Neural Network (AlexNet) with the class binary codes and show that the hashing functions learned in this way outperforms the state­ of ­the art, and at the same time provide fast retrieval times. In the second part, we also address the problem of supervised retrieval by taking into account the relationship between classes. For a given query image, we want to retrieve images that preserve the relative order i.e. we want to retrieve all same class images first and then, the related classes images before different class images. We learn such relationship aware binary codes by minimizing the similarity between inner product of the binary codes and the similarity between the classes. We calculate the similarity between classes using output embedding vectors, which are vector representations of classes. Our method deviates from the other supervised binary encoding schemes as it is the first to use output embeddings for learning hashing functions. We also introduce new performance metrics that take into account the related class retrieval results and show significant gains over the state­ of­ the art. High Dimensional descriptors like Fisher Vectors or Vector of Locally Aggregated Descriptors have shown to improve the performance of many computer vision applications including retrieval. In the third part, we will discuss an unsupervised technique for compressing high dimensional vectors into high dimensional binary codes, to reduce storage complexity. In this approach, we deviate from adopting traditional hyperplane hashing functions and instead learn hyperspherical hashing functions. The proposed method overcomes the computational challenges of directly applying the spherical hashing algorithm that is intractable for compressing high dimensional vectors. A practical hierarchical model that utilizes divide and conquer techniques using the Random Select and Adjust (RSA) procedure to compress such high dimensional vectors is presented. We show that our proposed high dimensional binary codes outperform the binary codes obtained using traditional hyperplane methods for higher compression ratios. In the last part of the thesis, we propose a retrieval based solution to the Zero shot event classification problem - a setting where no training videos are available for the event. To do this, we learn a generic set of concept detectors and represent both videos and query events in the concept space. We then compute similarity between the query event and the video in the concept space and videos similar to the query event are classified as the videos belonging to the event. We show that we significantly boost the performance using concept features from other modalities.

Aplicación de la medicina ancestral en los usuarios del Centro de Salud Carlos Elizalde. Cuenca 2015

ANTECEDENTES: En gran parte del mundo la medicina tradicional es el pilar principal de la prestación de servicios de salud, por ello en algunos países suele denominarse medicina complementaria. La medicina tradicional ha sufrido transformaciones, y los valores de este tipo de medicina están desapareciendo con rapidez a pesar que la OMS dicta estrategias para su implementación y el MSP del Ecuador reconoce su valor. OBJETIVO GENERAL: Caracterización de la aplicación de la medicina ancestral en los usuarios y usuarias del Centro de Salud “Carlos Elizalde”. METODOLOGIA: Es un estudio cuantitativo descriptivo en el que caracteriza la aplicación de la medicina ancestral en los usuarios del Centro de Salud “Carlos Elizalde”. El método utilizado fue la entrevista previo consentimiento informado realizada, según criterios de inclusión y exclusión a un universo de 110 usuarios, en la tabulación de datos se utilizó el programa SPSS Windows y Excel, y estos fueron analizados en tablas simples y gráficos. RESULTADOS: Los resultados obtenidos han servido para identificar la aplicación la Medicina Ancestral en los usuarios que acuden al Centro de Salud “Carlos Elizalde” de la Parroquia Yanuncay, identificando a las personas que más acuden al tratamiento son adultos con 71% y adultos mayores con un 16%, la mayoría son amas de casa en un 38%, con instrucción de primaria incompleta, es las enfermedades más frecuentes son espanto con un 36%, mal aire 18% y 10% caída de zhungo; para el tratamiento utilizan plantas o hiervas en un 54%

Dynamic mental representations of habitual behaviours: Food choice on a web-based environment

Aim: Rather than being rigid, habitual behaviours may be determined by dynamic mental representations that can adapt to context changes. This adaptive potential may result from particular conditions dependent on the interaction between two sources of mental constructs activation: perceived context applicability and cognitive accessibility . Method: T wo web-shopping simulations of fering the choice between habitually chosen and non-habitually chosen food products were presented to participants. This considered two choice contexts dif fering in the habitual behaviour perceived applicability (low vs. high) and a measure of habitual behaviour chronicity . Results: Study 1 demonstrated a perceived applicability ef fect, with more habitual (non-organic) than non-habitual (organic) food products chosen in a high perceived applicability (familiar) than in a low perceived applicability (new) context. The adaptive potential of habitual behaviour was evident in the habitual products choice consistency across three successive choices, despite the decrease in perceived applicability . Study 2 evidenced the adaptive potential in strong habitual behaviour participants – high chronic accessibility – who chose a habitual product (milk) more than a non-habitual product (orange juice), even when perceived applicability was reduced (new context). Conclusion: Results portray consumers as adaptive decision makers that can flexibly cope with changes in their (inner and outer) choice contexts.

Evolutionary transition to freshwater by ancestral marine palaemonids: evidence from osmoregulation in a tide pool shrimp

The transition from marine/brackish waters to freshwater habitats constitutes a severe osmotic and ionic challenge, and successful invasion has demanded the selection of morphological, physiological, biochemical and behavioral adaptations. We evaluated short-term (1 to 12 h exposure) and long-term (5 d acclimation), anisosmotic extracellular (osmolality, [Na(+), Cl(-)]) and long-term isosmotic intracellular osmoregulatory capability in Palaemon northropi, a neotropical intertidal shrimp. F northropi survives well and osmo- and ionoregulates strongly during short- and long-term exposure to 5-45 parts per thousand salinity, consistent with its rocky tide pool habitat subject to cyclic salinity fluctuations, Muscle total free amino acid (FAA) concentrations decreased by 63% in shrimp acclimated to 5%. salinity, revealing a role in hypoosmotic cell volume regulation; this decrease is mainly a consequence of diminished glycine, arginine and proline. Total FAA contributed 31% to muscle intracellular osmolality at 20 parts per thousand, an isosmotic salinity, and decreased to 13% after acclimation to 5 parts per thousand. Gill and nerve tissue FAA concentrations remained unaltered. These tissue-specific responses reflect efficient anisosmotic and anisoionic extracellular regulatory mechanisms, and reveal the dependence of muscle tissue on intracellular osmotic effectors. FAA concentration is higher in P. northropi than in diadromous and hololimnetic palaemonids, confirming muscle FAA concentration as a good parameter to evaluate the degree of adaptation to dilute media. The osmoregulatory capability of P. northropi may reflect the potential physiological capacity of ancestral marine palaemonids to penetrate into dilute media, and reveals the importance of evaluating osmoregulatory processes in endeavors to comprehend the invasion of dilute media by ancestral marine crustaceans.

Veteranness : Representations of Combat-related PTSD in U.S. Popular Visual Media

Posttraumatic stress and PTSD are becoming familiar terms to refer to what we often call the invisible wounds of war, yet these are recent additions to a popular discourse in which images of and ideas about combat-affected veterans have long circulated. A legacy of ideas about combat veterans and war trauma thus intersects with more recent clinical information about PTSD to become part of a discourse of visual media that has defined and continues to redefine veteran for popular audiences. In this dissertation I examine realist combat veteran representations in selected films and other visual media from three periods: during and after World Wars I and II (James Allen from I Am a Fugitive from a Chain Gang, Fred Derry and Al Stephenson from The Best Years of Our Lives); after the Vietnam War (Michael from The Deer Hunter, Eriksson from Casualties of War), and post 9/11 (Will James from The Hurt Locker, a collection of veterans from Wartorn: 1861-2010.) Employing a theoretical framework informed by visual media studies, Barthes’ concept of myth, and Foucault’s concept ofdiscursive unity, I analyze how these veteran representations are endowed with PTSD symptom-like behaviors and responses that seem reasonable and natural within the narrative arc. I contend that veteran myths appear through each veteran representation as the narrative develops and resolves. I argue that these veteran myths are many and varied but that they crystallize in a dominant veteran discourse, a discursive unity that I term veteranness. I further argue that veteranness entangles discrete categories such as veteran, combat veteran, and PTSD with veteran myths, often tying dominant discourse about combat-related PTSD to outdated or outmoded notions that significantly affect our attitudes about and treatment of veterans. A basic premise of my research is that unless and until we learn about the lasting effects of the trauma inherent to combat, we hinder our ability to fulfill our responsibilities to war veterans. A society that limits its understanding of posttraumatic stress, PTSD and post-war experiences of actual veterans affected by war trauma to veteranness or veteran myths risks normalizing or naturalizing an unexamined set of sociocultural expectations of all veterans, rendering them voice-less, invisible, and, ultimately disposable.

Towards flexible parsing of structured textual model representations

Existing parsers for textual model representation formats such as XMI and HUTN are unforgiving and fail upon even the smallest inconsistency between the structure and naming of metamodel elements and the contents of serialised models. In this paper, we demonstrate how a fuzzy parsing approach can transparently and automatically resolve a number of these inconsistencies, and how it can eventually turn XML into a human-readable and editable textual model representation format for particular classes of models.

Defending the 'public interest': an assessment of competing actor representations of 'solutions' to growing natural resource deficiencies.

This paper applies a SRT framework to the study of two case studies, namely the recent campaign of opposition to the legalization of hydraulic fracking in the State of New York and the more ongoing debate on land leasing in Africa. In relation to both campaigns, the analysis accounts for the arguments of a major financial institution and industry representatives who stress the safe and value-adding dimensions of these practices, as well as the views of opponents who refute the validity of industry's position and point to the unacceptable risks posed to the community, health and the environment. In spite of a number of obvious differences between these two case studies, not least differences arising from contrasting socio-economic and geo-political settings, there were also some notable similarities. First, was a tendency amongst protesters in both cases to formulate their role as contemporaries in a historically extended struggle for democratic justice. All perceived of themselves as guardians of their community's right to resist a corporate 'invasion' of their territories, like their forefathers and mothers before them. A theme of colonialism was explored in both settings through various identity and thematic anchoring devices that deliberately evoked shared understandings and historical memories of exploitation and human suffering. The evocation of powerful symbols of identity through visual narratives of protest further reinforced the cultural comprehensibility of opponents' message of protest in both contexts.

The potential of symbolic approximation. Disentangling the effects of approximation vs. calculation demands in nonsymbolic and symbolic representations.

Mathematical skills that we acquire during formal education mostly entail exact numerical processing. Besides this specifically human faculty, an additional system exists to represent and manipulate quantities in an approximate manner. We share this innate approximate number system (ANS) with other nonhuman animals and are able to use it to process large numerosities long before we can master the formal algorithms taught in school. Dehaene´s (1992) Triple Code Model (TCM) states that also after the onset of formal education, approximate processing is carried out in this analogue magnitude code no matter if the original problem was presented nonsymbolically or symbolically. Despite the wide acceptance of the model, most research only uses nonsymbolic tasks to assess ANS acuity. Due to this silent assumption that genuine approximation can only be tested with nonsymbolic presentations, up to now important implications in research domains of high practical relevance remain unclear, and existing potential is not fully exploited. For instance, it has been found that nonsymbolic approximation can predict math achievement one year later (Gilmore, McCarthy, & Spelke, 2010), that it is robust against the detrimental influence of learners´ socioeconomic status (SES), and that it is suited to foster performance in exact arithmetic in the short-term (Hyde, Khanum, & Spelke, 2014). We provided evidence that symbolic approximation might be equally and in some cases even better suited to generate predictions and foster more formal math skills independently of SES. In two longitudinal studies, we realized exact and approximate arithmetic tasks in both a nonsymbolic and a symbolic format. With first graders, we demonstrated that performance in symbolic approximation at the beginning of term was the only measure consistently not varying according to children´s SES, and among both approximate tasks it was the better predictor for math achievement at the end of first grade. In part, the strong connection seems to come about from mediation through ordinal skills. In two further experiments, we tested the suitability of both approximation formats to induce an arithmetic principle in elementary school children. We found that symbolic approximation was equally effective in making children exploit the additive law of commutativity in a subsequent formal task as a direct instruction. Nonsymbolic approximation on the other hand had no beneficial effect. The positive influence of the symbolic approximate induction was strongest in children just starting school and decreased with age. However, even third graders still profited from the induction. The results show that also symbolic problems can be processed as genuine approximation, but that beyond that they have their own specific value with regard to didactic-educational concerns. Our findings furthermore demonstrate that the two often con-founded factors ꞌformatꞌ and ꞌdemanded accuracyꞌ cannot be disentangled easily in first graders numerical understanding, but that children´s SES also influences existing interrelations between the different abilities tested here.

Quotidien et implication citoyenne : regard anthropologique sur la jeunesse kanak à Koné (Nouvelle-Calédonie)

Ce mémoire a pour but de décrire et d’analyser la diversité des expériences de jeunes Kanak et d’explorer comment ils font preuve d’agencéité en vue de prendre part au « vivre ensemble » en Nouvelle-Calédonie. Ne pouvant couvrir l’ensemble de la « jeunesse kanak », la recherche porte en particulier sur une « bande » de jeunes de Koné impliquée dans des associations régies par la loi du 1er juillet 1901 et dont les activités se déroulent autour d’une maisonnée du quartier des Cigales. L’analyse révèle qu’on ne peut réduire les expériences et pratiques des jeunes aux discours dominants qui les enferment dans une culture ancestrale immuable et qui mettent surtout l’accent sur leur inadéquation dans le monde contemporain et leurs problèmes. Les jeunes sont dotés de capacités créatives, désirent contribuer à la société, mais surtout, à y avoir un espace de parole. La recherche montre également que les expériences et initiatives des jeunes doivent être comprises en relation avec la « situation » contemporaine dans laquelle elles prennent place et qui est caractérisée par les transformations du contexte social, politique et économique de la Nouvelle-Calédonie depuis la signature de l’Accord de Nouméa (1998). Mots-clés : Kanak, Nouvelle-Calédonie, jeunes, destin commun, citoyenneté, vie quotidienne, milieu urbain, autochtone.