981 resultados para Code Translation Framework
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The life cycle of software applications in general is very short and with extreme volatile requirements. Within these conditions programmers need development tools and techniques with an extreme level of productivity. We consider the code reuse as the most prominent approach to solve that problem. Our proposal uses the advantages provided by the Aspect-Oriented Programming in order to build a reusable framework capable to turn both programmer and application oblivious as far as data persistence is concerned, thus avoiding the need to write any line of code about that concern. Besides the benefits to productivity, the software quality increases. This paper describes the actual state of the art, identifying the main challenge to build a complete and reusable framework for Orthogonal Persistence in concurrent environments with support for transactions. The present work also includes a successfully developed prototype of that framework, capable of freeing the programmer of implementing any read or write data operations. This prototype is supported by an object oriented database and, in the future, will also use a relational database and have support for transactions.
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The purpose of this paper is twofold. Firstly it presents a preliminary and ethnomethodologically-informed analysis of the way in which the growing structure of a particular program's code was ongoingly derived from its earliest stages. This was motivated by an interest in how the detailed structure of completed program `emerged from nothing' as a product of the concrete practices of the programmer within the framework afforded by the language. The analysis is broken down into three sections that discuss: the beginnings of the program's structure; the incremental development of structure; and finally the code productions that constitute the structure and the importance of the programmer's stock of knowledge. The discussion attempts to understand and describe the emerging structure of code rather than focus on generating `requirements' for supporting the production of that structure. Due to time and space constraints, however, only a relatively cursory examination of these features was possible. Secondly the paper presents some thoughts on the difficulties associated with the analytic---in particular ethnographic---study of code, drawing on general problems as well as issues arising from the difficulties and failings encountered as part of the analysis presented in the first section.
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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.
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Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing unique opportunities. This thesis describes an emerging microfluidics-based toolkit for single cell functional proteomics, focusing on the development of the single cell barcode chips (SCBCs) with applications in fundamental and translational cancer research.
The microchip designed to simultaneously quantify a panel of secreted, cytoplasmic and membrane proteins from single cells will be discussed at the beginning, which is the prototype for subsequent proteomic microchips with more sophisticated design in preclinical cancer research or clinical applications. The SCBCs are a highly versatile and information rich tool for single-cell functional proteomics. They are based upon isolating individual cells, or defined number of cells, within microchambers, each of which is equipped with a large antibody microarray (the barcode), with between a few hundred to ten thousand microchambers included within a single microchip. Functional proteomics assays at single-cell resolution yield unique pieces of information that significantly shape the way of thinking on cancer research. An in-depth discussion about analysis and interpretation of the unique information such as functional protein fluctuations and protein-protein correlative interactions will follow.
The SCBC is a powerful tool to resolve the functional heterogeneity of cancer cells. It has the capacity to extract a comprehensive picture of the signal transduction network from single tumor cells and thus provides insight into the effect of targeted therapies on protein signaling networks. We will demonstrate this point through applying the SCBCs to investigate three isogenic cell lines of glioblastoma multiforme (GBM).
The cancer cell population is highly heterogeneous with high-amplitude fluctuation at the single cell level, which in turn grants the robustness of the entire population. The concept that a stable population existing in the presence of random fluctuations is reminiscent of many physical systems that are successfully understood using statistical physics. Thus, tools derived from that field can probably be applied to using fluctuations to determine the nature of signaling networks. In the second part of the thesis, we will focus on such a case to use thermodynamics-motivated principles to understand cancer cell hypoxia, where single cell proteomics assays coupled with a quantitative version of Le Chatelier's principle derived from statistical mechanics yield detailed and surprising predictions, which were found to be correct in both cell line and primary tumor model.
The third part of the thesis demonstrates the application of this technology in the preclinical cancer research to study the GBM cancer cell resistance to molecular targeted therapy. Physical approaches to anticipate therapy resistance and to identify effective therapy combinations will be discussed in detail. Our approach is based upon elucidating the signaling coordination within the phosphoprotein signaling pathways that are hyperactivated in human GBMs, and interrogating how that coordination responds to the perturbation of targeted inhibitor. Strongly coupled protein-protein interactions constitute most signaling cascades. A physical analogy of such a system is the strongly coupled atom-atom interactions in a crystal lattice. Similar to decomposing the atomic interactions into a series of independent normal vibrational modes, a simplified picture of signaling network coordination can also be achieved by diagonalizing protein-protein correlation or covariance matrices to decompose the pairwise correlative interactions into a set of distinct linear combinations of signaling proteins (i.e. independent signaling modes). By doing so, two independent signaling modes – one associated with mTOR signaling and a second associated with ERK/Src signaling have been resolved, which in turn allow us to anticipate resistance, and to design combination therapies that are effective, as well as identify those therapies and therapy combinations that will be ineffective. We validated our predictions in mouse tumor models and all predictions were borne out.
In the last part, some preliminary results about the clinical translation of single-cell proteomics chips will be presented. The successful demonstration of our work on human-derived xenografts provides the rationale to extend our current work into the clinic. It will enable us to interrogate GBM tumor samples in a way that could potentially yield a straightforward, rapid interpretation so that we can give therapeutic guidance to the attending physicians within a clinical relevant time scale. The technical challenges of the clinical translation will be presented and our solutions to address the challenges will be discussed as well. A clinical case study will then follow, where some preliminary data collected from a pediatric GBM patient bearing an EGFR amplified tumor will be presented to demonstrate the general protocol and the workflow of the proposed clinical studies.
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The present work aims to allow developers to implement small features on a certain Android application in a fast and easy manner, as well as provide their users to install them ondemand, i.e., they can install the ones they are interested in. These small packages of features are called plugins, and the chosen development language to develop these in was JavaScript. In order to achieve that, an Android framework was developed that enables the host application to install, manage and run these plugins at runtime. This framework was designed to have a very clean and almost readable API, which allowed for better code organization and maintainability. The implementation used the Google’s engine “V8” to interpret the JavaScript code and through a set of JNI calls made that code call certain Android methods previously registered in the runtime. In order to test the framework, it was integrated with the client’s communication application RCS+ using two plugins developed alongside the framework. Although these plugins had only the more common requirements, they were proven to work successfully as intended. Concluding, the framework although successful made it clear that this kind of development through a non-native API has its set of difficulties especially regarding the implementation of complex features.
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Nesta dissertação descreve-se uma proposta de implementação de uma plataforma de desenvolvimento de Sistemas de Comunicação Aumentativa e Alternativa para programadores, com o objectivo de melhorar a produtividade e diminuir os tempos despendidos na implementação deste tipo de soluções. Esta proposta assenta numa estrutura composta por widgets configuráveis por código e integráveis em novas aplicações, numa filosofia de reaproveitamento de objectos e funcionalidades, permitindo ainda a uniformização da estrutura do código no desenvolvimento de softwares deste tipo. Esta plataforma pretende ainda dar flexibilidade aos programadores, através da possibilidade de introdução de novas funcionalidades e widgets, permitindo também que se testem novas abordagens ao software durante a investigação. A implementação em tecnologias open source independentes da plataforma, permitirá ainda utilizar os objectos deste toolkit em vários sistemas operativos. ABSTRACT: ln this master thesis we describe an implementation proposal for an Augmentative and Alternative Communication Framework for developers, with the objective of improves the productivity and reduces the implementation times for these types of solutions. This proposal is based on a customized widgets structure that can be integrated in new applications, with the purpose of reuse common features of these applications, also allowing standardize the code structure in this kind of software development. This framework intends to provide flexibility to programmers giving them the possibility of introduce new functionalities and widgets, allowing them to test new approaches during research. The implementation based on open-source technologies, platform independent, allows the use of this toolkit in several different operating systems.
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One of the main process features under study in Cognitive Translation & Interpreting Studies (CTIS) is the chronological unfolding of the tasks. The analyses of time spans in translation have been conceived in two ways: (1) studying those falling between text units of different sizes: words, phrases, sentences, and paragraphs; (2) setting arbitrary time span thresholds to explore where do they fall in the text, whether between text units or not. Writing disfluencies may lead to comprehensive insights into the cognitive activities involved in typing while translating. Indeed, long time spans are often taken as hints that cognitive resources have been subtracted from typing and devoted to other activities, such as planning, evaluating, etc. This exploratory, pilot study combined both approaches to seek potential general tendencies and contrasts in informants’ inferred mental processes when performing different writing tasks, through the analysis of their behaviors, as keylogged. The study tasks were retyping, monolingual free writing, translation, revision and a multimodal task—namely, monolingual text production based on an infographic leaflet. Task logs were chunked, and shorter time spans, including those within words, were analyzed following the Task Segment Framework (Muñoz & Apfelthaler, in press). Finally, time span analysis was combined with the analysis of the texts as to their lexical density, type-token ratio and word frequency. Several previous results were confirmed, and some others were surprising. Time spans in free writing were longer between paragraphs and sentences, possibly hinting at planning and, in translation, between clauses and words, suggesting more cognitive activities at these levels. On the other hand, the infographic was expected to facilitate the writing process, but most time spans were longer than in both free writing and translation. Results of the multimodal task and some other results suggest venues for further research.
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Recently, massive open online courses (MOOCs) have been offering a new online approach in the field of distance learning and online education. A typical MOOC course consists of video lectures, reading material and easily accessible tests for students. For a computer programming course, it is important to provide interactive, dynamic, online coding exercises and more complex programming assignments for learners. It is expedient for the students to receive prompt feedback on their coding submissions. Although MOOC automated programme evaluation subsystem is capable of assessing source programme files that are in learning management systems, in MOOC systems there is a grader that is responsible for evaluating students’ assignments with the result that course staff would be required to assess thousands of programmes submitted by the participants of the course without the benefit of an automatic grader. This paper presents a new concept for grading programming submissions of students and improved techniques based on the Java unit testing framework that enables automatic grading of code chunks. Some examples are also given such as the creation of unique exercises by dynamically generating the parameters of the assignment in a MOOC programming course combined with the kind of coding style recognition to teach coding standards.
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Resource specialisation, although a fundamental component of ecological theory, is employed in disparate ways. Most definitions derive from simple counts of resource species. We build on recent advances in ecophylogenetics and null model analysis to propose a concept of specialisation that comprises affinities among resources as well as their co-occurrence with consumers. In the distance-based specialisation index (DSI), specialisation is measured as relatedness (phylogenetic or otherwise) of resources, scaled by the null expectation of random use of locally available resources. Thus, specialists use significantly clustered sets of resources, whereas generalists use over-dispersed resources. Intermediate species are classed as indiscriminate consumers. The effectiveness of this approach was assessed with differentially restricted null models, applied to a data set of 168 herbivorous insect species and their hosts. Incorporation of plant relatedness and relative abundance greatly improved specialisation measures compared to taxon counts or simpler null models, which overestimate the fraction of specialists, a problem compounded by insufficient sampling effort. This framework disambiguates the concept of specialisation with an explicit measure applicable to any mode of affinity among resource classes, and is also linked to ecological and evolutionary processes. This will enable a more rigorous deployment of ecological specialisation in empirical and theoretical studies.
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas. Faculdade de Educação Física
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Universidade Estadual de Campinas. Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física