NCube/papyrus huggingface dataset:
Enseignement de la traduction technique anglais-français : portrait de la situation

Technical translation (practice-oriented in technological and industrial fields such as mechanics and metal working) has not generated many recent papers, especially when it comes to teaching. How does one specialize in technical translation? Is it necessary to acquire a prior field expertise (subject matter approach) or can a generalist become specialized by translating technical documents (textual approach)? Which training curriculum is the best, if any? How does technical translation currently stand in Quebec’s university programs and Canada’s French university programs? With this research we wanted to get a better idea of the status of technical translation in the higher education curriculum. To do so, we went through related major works and university programs. We also looked at the context within which professional translators work. Translation market is affected by major commercial and technological disruptions. The ever-shorter delays, the stagnant or decreasing rates and the huge volume of demands combined with new telecommunication and computer-assisted translation (CAT) technologies have brought advantages as well as constraints. Although these technologies increase translators’ productivity and facilitate documentary and terminological researches, they also create worldwide competition and transform translation into an industrialized process. Based on our observations, we argue that language professionals should aim for a specialized area of work on the high quality market as opposed to the mass market where a significant amount of work is submitted to automatic translation and post-editing, hence the relevance of specialized translation teaching, more precisely the under-exploited market niche of technical translation.

Keyphrases: teaching, technical translation, mechanics, metal working, subject matter approach, textual approach
Latent variable language models

There has been a renewed interest in generative modeling/unsupervised learning for language for downstream natural language understanding tasks. In this thesis, we explore the augmentation of standard language models with latent variables. In the first chapter, we provide a brief introduction of language models, the classical n-gram treatment and the more common Neural Language Models in use today. We also briefly introduce variational autoencoders and the recent work improving upon them. In Chapter 2, we review work that explores the space where latent variable models and language models intersect. We then empirically analyse the effectiveness of a couple of these methods. In particular, we re-implement the models from Bowman et al. (2015) and Yang et al. (2017), and benchmark them against the Penn Treebank dataset with some experiments of our own. In Chapter 3, we discuss an ICML submission: Generating Contradictions, Entailments and Neutral Sentences. In this work, we encode source sentences to a latent distribution space and attempt to manipulate it from there to generate sentences corresponding to the given logical entailment. While our efforts are unsuccessful, we believe that enabling controllable latent variable distributions is an interesting direction to pursue. In Chapter 4, we conclude with a review of the content covered in the thesis, and a higher-level discussion of what possible avenues of future work could resemble.

Keyphrases: language models, probabilistic models, deep learning, neural networks, latent variables
Load sequencing for double-stack trains

Double-stack trains are an important component of the railroad transport network for containerized cargo in specific markets such as the North American one. The load sequencing is an operational problem commonly faced in rail terminals by crane operators when tasked with loading containers on the railcars of a train. The load sequencing problem aims to find an efficient sequence of container retrievals in the storage yard, where containers are stored in piles while awaiting departure by train. Load sequencing is interrelated with load planning, the assignment of containers to specific locations on the train, forming a load plan which guides the load sequencing. The work in this thesis is centered around a scientific paper on the optimization of load sequencing for double-stack trains. This paper proposes algorithms based on dynamic programming and a strategy leveraging the load plans, and assesses their performance in terms of computing time, tractability and solution quality on realistic instance sizes. The results show that the heuristics suggested to solve the load sequencing scale well for realistic instance size, managing to achieve a significantly reduced computing time with a small loss in solution quality compared to exact methods, which would often falter for larger instances. The analysis also illustrates how using a flexible load plan in the load sequencing significantly improves solution quality at the cost of greater computing requirements and lack of guaranteed solution for the heuristics. Finally, the paper compares the performance resulting from the successive application of load planning and sequencing with jointly performing the load planning and sequencing.

Keyphrases: Intermodal Rail Terminals, Containers, Load Planning, Load Sequencing, Dynamic Programming, Heuristics, Double-Stack, Trains, Train, Terminal intermodal
Analyzing the benefits of communication channels between deep learning models

As artificial intelligence systems spread to more diverse and larger tasks in many domains, the machine learning algorithms, and in particular the deep learning models and the databases required to train them are getting bigger themselves. Some algorithms do allow for some scaling of large computations by leveraging data parallelism. However, they often require a large amount of data to be exchanged in order to ensure the shared knowledge throughout the compute nodes is accurate. In this work, the effect of different levels of communications between deep learning models is studied, in particular how it affects performance. The first approach studied looks at decentralizing the numerous computations that are done in parallel in training procedures such as synchronous and asynchronous stochastic gradient descent. In this setting, a simplified communication that consists of exchanging low bandwidth outputs between compute nodes can be beneficial. In the following chapter, the communication protocol is slightly modified to further include training instructions. Indeed, this is studied in a simplified setup where a pre-trained model, analogous to a teacher, can customize a randomly initialized model’s training procedure to accelerate learning. Finally, a communication channel where two deep learning models can exchange a purposefully crafted language is explored while allowing for different ways of optimizing that language.

Keyphrases: Communication, Gradient, Machine learning, Deep learning, Communication, Language, Teacher, Student, Optimization
Détection et contrôle de l’indice d’intérêt dans support publicitaire

Measuring the level of consumer interest is an important measure in marketing. Conven- tional methods of measuring interest include group or individual interviews and surveys. These methods have several weaknesses that neuromarketing methods try to avoid. Indeed, by taking measurements directly on the brain of the participants, several bias can be avoided such as verbalization of ideas. In this work, a model has been created to predict the level of interest of participants using electroencephalogram (EEG) measurements. Tests on the model show that the level of interest can be predicted with an average accuracy of 66 %, an average sensitivity of 45 % and an average F-measure of 51 %. In addition, four conviction strategies were tested to observe their effect on participant interest (discount, comparison, position and wrong choice). The results show that none of these strategies had a significant effect on the level of interest. In addition, the research demonstrates that the interest showed for a video advertisement is mainly gain by its content. In fact, the interest demonstrated for a certain brand or its competitors is less important than the advertising itself.

Keyphrases: Interest, EEG, RV, AI
Scanner 3D à lumière non structurée non synchronisé

This thesis is in the field of computer vision and specifically focuses on active reconstruction methods. Firstly, it proposes a new approach to structured light correspondence which alleviates the camera-projector synchronization problem. This allows the creation of a dense correspondence map between the camera and projector which can further be used to obtain 3D models. This high-speed approach is ideal for scanning human faces, which are notoriously difficult because of involuntary motions of the subjects. Secondly, it proposes an improvement to the matching accuracy by aligning, to high subpixel precision, the respective neighborhood patches of each pixel. Thirdly, an example of an application of the method is proposed.  Until now, great care was required to make sure that each camera image was captured exactly when the correct pattern was projected. This was difficult to achieve with low-cost hardware or large size installations. In our method, the projector sends a video loop of a selected number of unstructured light patterns at a high frame rate (30 to 60 fps for common hardware), which are captured by a camera without any form of synchronization. The only constraint to satisfy is that the camera and projector frame rates are known. The matching process not only recovers the correct pattern sequence, but is robust to partial exposures of consecutive patterns as well as rolling shutter effects. Through these steps, the crucial camera-projector synchronization problem is entirely taken care of.   Subpixel matching accuracy is obtained by relying on image interpolation to refine the original correspondences. These results are highly accurate and comparable to other state-of-the-art subpixel methods but with better robustness. The obtained results illustrate 3D models reconstructed with very high precision in difficult conditions such as indirect illumination, scene discontinuities, and use of low quality hardware.  The last part of this thesis is devoted to the description of the design and manufacturing of a customized virtual reality headset which snuggly matches a user’s face, thanks to 3d models constructed from the matching method proposed in the thesis, where high quality is obtained on low-cost hardware.

Keyphrases: Scanner 3D, Computer vision, Active reconstruction, Unstructured light, Unsynchronized camera-projector systems, Subpixel accuracy, 3D scanning
Prédiction et génération de données structurées à l'aide de réseaux de neurones et de décisions discrètes

Deep learning, a subdiscipline of machine learning, is used throughout multiple domains, including natural language processing. However, in the field multiple problems remain open, notably the prediction of long sequences and the generation of natural languages. In the following thesis, we present two models that work toward solving both of these problems. In chapter 1, we add a planning mechanism to sequence-to-sequence models. The mech- anism consists of establishing ahead of time the alignment between the input and output sequence. We show that this improves the alignment, help the model to converge faster, and necessitate fewer parameters. We also show performance gain in neural machine translation, questions generation, and the algorithmic task of finding Eulerian circuits in graphs. In chapter 2, we tackle the language generation task using generative adversarial net- works. A non-trivial problem considering the discrete nature of the output space. The model is trained using only an adversarial loss and without any gradient estimation. We show results on language modeling, context-free grammar generation, and conditional sen- tence generation.

Keyphrases: Artificial intelligence, Machine learning, Deep learning, Recurrent neural networks, Convolutional neural networks, Generative Adversarial networks, Discrete decisions
Programmes de branchement catalytiques : algorithmes et applications

The present master’s thesis studies the computational model of k-catalytic branching programs. A k-catalytic branching program is used to carry out the computation of k boolean functions on the same input and represents the nonuniform counterpart to the notion of catalytic Turing machine introduced by Buhrman et al. (STOC, 2014). It is shown that for any boolean symmetric function f there exists a k-catalytic branching program which computes f an exponential number of times and which has size O(nlgn) per copy. We show a similar result linking the complexity of any boolean function f on n bits expressible as f(x) = h(g(x)) to the complexity of g and h, where g is a function from {0,1}^n to G, h a function from G to {0,1} and G is a group. Furthermore, we introduce a set of notions such as gadgets, analyzers and programs over groups allowing us to show how nonuniform catalytic computation can go beyond transparent computation. Lastly, the new formalism introduced reveals the link until now unexplored between catalytic computation and communication complexity.

Keyphrases: gadget, dag-like communication, communication complexity, catalytic branching program, tranparent computation, function composition, analyzer, program over a group, symmetric function, scalar product
TELEQ : Création et validation d'un outil québécois d'évaluation de l'orthographe

Most available tools for clinical assessment of spelling disorder (dysorthographia) are from Europe and cannot correctly assess spelling skills of French-speaking Quebecer children because of their cultural and linguistic biases. Consequently, we created a new tool adapted for French-speaking Quebecers, called Test d’évaluation du langage écrit québécois (TELEQ). The objective of this study is to describe the performance of elementary school aged children from Quebec at the spelling tasks of TELEQ and to examine the psychometric properties (reliability and validity) of the test. The sample used for this study consisted of 117 French-speaking Quebecer children from 2nd to 6th grade without difficulties in written language. TELEQ was administrated twice to the participants at 2 to 5 weeks interval. Other tests assessing spelling skills were also administered in order to verify criterion and construct validity of TELEQ. The results show excellent test-retest reliability and internal consistency for this tool. Also, the correlations between TELEQ and the other tests reveal excellent criterion and construct validity. Overall, TELEQ displays excellent psychometric properties and it correctly estimates spelling skills of Quebecer children. This tool thus allows a more accurate evaluation of spelling abilities of young Quebecers than the available tools.

Keyphrases: Validation, Assessment tool, Spelling, Dysorthographia, Childhood, Clinical neuropsychology
Les insécurités d’attachement et l’engagement conjugal au sein de couples vivant de la détresse relationnelle

The present study examined the dyadic associations between attachment insecurities (avoidance and anxiety) and relationship commitment (optimal, over, and under) in a sample of 154 relationally distressed couples. Path analyses using the Actor-Partner Interdependence Model revealed that anxiety was positively associated with over-commitment (actor effect) and under-commitment (partner effect), whereas avoidance was positively associated with undercommitment and negatively associated with optimal commitment (actor effects). The associations between individuals’ attachment insecurities and their own optimal commitment were also moderated by their partners’ attachment insecurities. Results are discussed in light of attachment theory and their implications for couple therapy are specified.

Keyphrases: Attachment insecurities, Relationship commitment, Couple therapy
Profils de santé mentale des jeunes Québécois agressés sexuellement : comorbidité et trauma complexe

Sexually abused youth are a heterogeneous group in terms of mental health. The few studies profiling these youth often use transversal designs and self-reported measures, and aren’t specifically focused on comorbidity of mental health diagnoses. The current study’s objectives were to determine 1) if sexually abused youth under child protective agencies (CPA) we given more unique and comorbid mental health diagnoses than youth from the general population, 2) the comorbidity profiles of sexually abused youth over 10 years medical consultations and hospitalizations. Among the sexually abused group, the impact of cumulative maltreatment was also explored. The mental health diagnoses of 882 youth with a substantiated sexual abuse report between 2001 and 2010 at a participating CPA were compared to 882 matched controls (N=1764). Results of generalized linear mixed models showed that sexually abused youth presented higher rates of all types of mental health diagnoses and were up to four times more likely to present comorbid diagnoses. Latent class analyses among abused youth revealed four different comorbidity profiles; two more severe groups named complex post-traumatic stress disorder (CPTSD; 11%) and dissociation (14%); and two less severe groups named depression (10%) and low or no comorbidity (65%). Youth with more cumulative maltreatment and greater number of years of data following CSA report were more at risk of presenting a comorbidity profile. Mental health profiles of youth in the highest comorbidity class were similar to what is defined as CPTSD.

Keyphrases: TSPT complexe, Child maltreatment, Child sexual abuse, Complex PTSD, Comorbidity (cooccurence), Clinical psychology
Développement d’un cours francophone en ligne sur les politiques publiques en santé : une collaboration internationale

Objective: To present the process and challenges of developing an online competency-based course on public health policy using a collaborative international approach. methods: Five public health experts, supported by an expert in educational technology, adopted a rigorous approach to the development of the course: a needs analysis, identification of objectives and competencies, development of a pedagogical scenario for each module and target, choice of teaching methods and learning activities, materialto be identified or developed, and the responsibilities and tasks involved. results: The 2-credit (90-hour) graduate course consists of six modules including an integration module. The modules start with a variety of case studies: tobacco law (neutral packaging), supervised injection sites, housing, integrated servicesfor the frail elderly, a prevention programme for mothersfrom disadvantaged backgrounds, and the obligatory use of bicycle helmets. In modules 1, 3, 4 and 5, students learn about different stages of the public policy development process: emergence, formulation and adoption, implementation and evaluation. Module 2 focuses on the importance of values and ideologies in public policy. The integration module allows the students to apply the knowledge learned and addresses the role of experts in public policy and ethical considerations. Conclusion: The course has been integrated into the graduate programmes of the participating universities and allows students to follow, at a distance, an innovative training programme.

Keyphrases: Public policy, Education, Competency-based approach, Distance education, Public health, Curriculum, E-learning
Enjeux éthiques et psychosociaux soulevés par le pancréas artificiel

The artificial pancreas, a wearable medical technology, is being developed to simplify and improve type 1 diabetes management and control. It includes two medical devices that are already available on the market, notably the insulin pump and the continuous glucose monitor. Its innovative component is a software that automatically adjusts the insulin pump’s infusions to the continuous glucose monitor’s glycaemic readings. As with any other medical technology, the artificial pancreas likely raises psychosocial and ethical issues that could impact its clinical success among people with type 1 diabetes, but these issues have not been extensively studied. Consequently, the objective of this research project is to identify and characterize the psychosocial and ethical issues that could be raised by the artificial pancreas. To this end, we conducted an ethical analysis of the biomedical literature followed by a qualitative study of the perspectives of people with type 1 diabetes on this technology. The psychosocial and ethical issues identified through the ethical analysis and the qualitative study are grouped under five categories: (1) shared control of type 1 diabetes with the artificial pancreas, (2) body image and embodiment, (3) optimal support and realistic expectations, (4) access to the artificial pancreas, and (5) confidentiality, security, and safety. As these issues may influence the success of the artificial pancreas, they are relevant to healthcare professionals, technology developers, and policymakers.

Keyphrases: Recherche qualitative, Psychosocial, Artificial pancreas, Type 1 diabetes, Qualitative research, Medical devices, Ethics, Psychosocial
The risk of cancer in statin users : a clinical and genetic approach

Statins, 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase inhibitors, are efficient and widely used drugs in the treatment of lipid disorders, especially hypercholesterolemia. In several large randomized-controlled trials, statins significantly reduced the risk of cardiovascular events both in terms of morbidity and mortality. Nonetheless, a significant body of literature affirming the association between statin use and cancer has continued to progress in the last decade, with no consensus on whether this relationship truly exists, and if it does, whether it’s a positive or negative relationship.   Based on the lack of consensus, we sought to investigate the effect of high-dose vs. low-dose statin on incident cancer and cancer mortality from a clinical and genetic perspective. From the clinical perspective, we relied on data obtained from the TNT and IDEAL cohorts, two randomized-controlled studies that were originally intended to examine the effect of high-dose statin vs. low or usual-dose statin on the risk of cardiovascular disease for secondary prevention after myocardial infarction. We performed post-hoc analysis and evaluated the risk of cancer or cancer mortality between high and low-dose statin users. Additional sub-analyses were performed focusing exclusively on those aged ≥55 years old, men, and women. From the genetic perspective, we performed a genome-wide association study (GWAS) using the TNT cohort with available genetic data on cancer incidence.   Overall, our study failed to find any significant association between higher dose statin and cancer incidence or cancer mortality using clinical data. Furthermore, findings from the GWAS were not able to identify a reliable genetic variant associated with the tested endpoints. We conclude that the use of higher dose statins was not associated with a higher or lower risk of cancer diagnosis or cancer mortality.

Keyphrases: Cancer, Cardio-oncologie, Statins, Cardiology, Pharmacogenomics, Cardio-oncology