Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving quality of service and resource utilization for multimedia streaming over third generation mobile networks

Les reseaux mobiles de troisieme generation ont ete concus pour offrir des services avances de communication tels que la voix sur IP et le video-streaming, et des debits relativement eleves. On assiste aujourd'hui a une evolution vers des reseaux « tout IP », plus efficaces et moins couteux pour les operateurs. De nouveaux problemes se posent comme par exemple le surcout du aux en-tetes IP ou des taux de pertes de paquets eleves sur des liens radio. De plus, la plupart des reseaux IP existants ne peuvent satisfaire les contraintes de ces applications en termes de delai, gigue ou pertes. La premiere partie de cette these porte sur un schema de compression permettant de reduire le surcout induit par les en-tetes IP. Ensuite, nous introduisons de nouvelles strategies pour le support de la qualite de service, basees sur l'ordonnancement des paquets. Enfin, nous etudions le controle de congestion pour la video, et nous proposons des mecanismes d'estimation des pertes dues a la radio et de retransmission selective, visant a ameliorer la qualite des flux video.
Supervision 2.0: e-supervision a decade later

39 super vision B U L L E T I N Greenwalt asked in 2001 if it was ethical to carry out supervision in this way. A question of whether it should be done and not whether or not it could be done. Today, virtual supervision in human and health services occurs quite often. But there is a difference between 2001 and now. Many of the limitations that existed a decade earlier have disappeared, in part because of the phenomenal advances of communication technology and the massive adoption of digital, mobile, and virtual devices. We are not limited to text only as we were a decade ago. With e-supervision today, we can even abstain from using text as a medium of communication and tap into other mediums. These additional mediums allow us to examine the ethical dilemmas posed by Greenwalt through a more general supervision and not just an e-supervision lens. There is today a clearer recognition of concerns about elements of supervision in general, such as confidentiality, autonomy, fidelity, beneficence, and nonmalficence. These elements are not so different in the contexts of e-supervision as in traditional supervision. Technology with all mediums, not just text only, provides better ways to ensure high professional and clinical standards. A third dimension of our profession should be discussed when considering e-supervision. We have become much more alert in the last few years. We as a profession still focus on the traditional components of the supervision relationship: the setting, quality of relationship, self of the therapist, theoretical model, accountability, time, evaluation, liability and ethical issues, etc. But, we are taking our awareness into new focus with the advent of the family therapy competencies and more generally the learning outcomes movement becoming core in training. Plus evidence-based clinical work is becoming a demand in clinics. Supervision as well as e-supervision will have to be measured against these criteria. If one were to measure supervision on the basis of the question of how it is making a difference in the professional development of the therapist and the resolution of the issues that bring patients to consult with the therapist, traditional supervision is as challenged with a positive response as e-supervision. What are the competencies that define good professional and ethical supervision? How are we measuring what we assume is appropriate supervision? We know that e-supervision is technically possible. It may not replace the " experience " …
Impacting Adherence to Infant Safe Sleep Practice

This paper provides a complete microsystem assessment of a pediatric unit. The assessment includes identification of a process problem with infant safe sleep practice in the hospital setting. The paper explores six different published articles regarding clinical practice guidelines, best practices, and evidence-based interventions. The literature review indicates agreement amongst various authors following infant safe sleep guidelines in the hospital setting. The literature review also indicates that caregiver role modeling while in the hospital setting is the most influential component that affects parents’ practices upon return to the home setting. The clinical project will include baseline needs assessments of both bedside caregivers in the hospital setting and parents, then coaching sessions with bedside caregivers will occur. Baseline safe sleep audit data will also be collected. Concurrently, a product analysis will take place to address the identified barrier of storage space. A cost benefit analysis will show that the crib pockets would save the health system money, and possibly save an infant’s life. A post assessment will occur to measure effectiveness of coaching sessions. Safe sleep audit data will be graphed to indicate effectiveness of the interventions.
Principal components analysis for tracking of facial features

A new method of tracking the position of important facial features in 'head-and-shoulders' sequences is presented for low bit-rate wireless communication. The initial part of the analysed sequence is decomposed into sub-images containing important facial features. Tracking of the facial features in subsequent frames is based on this set of sub-images.
Cancer-related fatigue (crf)

Cancer-related fatigue (CRF) constitutes one of the most common reported side effect of cancer and its’ treatment. Chemotherapy, radiation therapy, bone marrow transplant and biological therapy are cancer treatments commonly associated with fatigue. The majority of literature is reporting prevalence rates of CRF above 60%, whereas, other relevant studies are reporting rates of up to 80-99%.
Face Detection Based on Skin Color and Adaboost Arithmetic

Face detection is the first link and a key link in face recognition.static color image is used for detecting human face,and the primary research is skin color application in face detection.Different image background,face variability and change in light conditions have increased the difficulty of face detection.Therefore,face detection from an image is a challenge.Adaboost algorithm is used to detect human face,and a new method of face detection,which combines skin color with Adaboost is presented.Conversion of the input image from RGB to RCbCr,and then skin color is segmented,background interference is excluded,Adaboost is used to get face location from possible regional.Experiments show that this method has low rate of false detection,good robustness,and strong practicality to face detection problem.
Are older adults receiving evidence-based advice to prevent falls post-discharge from hospital?

Background: Older adults experience a high rate of falls when they transition to community-living following discharge from hospital. Objectives: To describe the proportion of older adults who could recall having discussed falls and falls prevention strategies with a health professional within 6 months following discharge from hospital. To describe the recalled content of these discussions and the strategies recommended and/or undertaken to prevent falls. Methods: Prospective cohort study of 155 older adults surveyed prior to discharge from hospital, of whom 123 were followed up at month 3 and/or month 6 in the community post-discharge. Participants were recruited from three Australian hospitals. Questionnaires captured predictive factors that may predispose to a fall and data related to the objectives being examined. Results: Of the 123 participants who had at least one follow-up, 54 reported discussing falls with a health professional (49 discussed falls with their general practitioners). Of the 54 participants who recalled having a discussion, 33 commented that they were asked whether they had fallen over. Only six discussed interventions to prevent falls. However, 44 stated that they attempted a total of 53 strategies to prevent falls post-discharge. Of these strategies, 40 had an absence of evidence of effectiveness, 11 had evidence of effectiveness, while two had either evidence of no benefit/harm or evidence of harm for the prevention of falls. In all, 53 participants reported falling post-discharge, but 42% of them did not recall discussing falls with their health professional. Conclusion: There is considerable scope for health professionals, especially general practitioners, to increase the frequency with which they discuss falls and evidence-based interventions to prevent falls in this population.
LC Classification as linked data

In 2009 and in 2011, the Library of Congress made two of its largest authority files – Subject Headings and Names – available as linked data via LC’s Linked Data Service, ID.LOC. GOV. Both are offered in MADS/RDF and SKOS. It is LC’s objective, in 2012, to publish another of its largest authority files as linked data: LC Classification. Whereas the source records for Subject Headings and Names are encoded in the MARC Authority format, from which there is a relatively straightforward mapping to MADS/RDF and SKOS, LC Classification records rely on the MARC Classification format. Mapping from LC Classification to MADS/RDF or SKOS has been a little more challenging. For example, records that represent classification ranges, which are not Concepts intended to be assigned, are not easily accommodated in SKOS. This presents additional problems when needing to accurately represent the relationships in RDF for LC Classification. With comparison to the publication of LCSH and Names at ID.LOC. GOV, this paper will examine issues encountered – and how those challenges were addressed – during the conversion of LC Classification to MADS/RDF and SKOS for release as linked data at ID.LOC. GOV.
The ICWSM 2009 Spinn3r Dataset

The dataset, provided by Spinn3r.com, is a set of 44 million blog posts made between August 1st and October 1st, 2008. The post includes the text as syndicated, as well as metadata such as the blog's homepage, timestamps, etc. The data is formatted in XML and is further arranged into tiers approximating to some degree search engine ranking. The total size of the dataset is 142 GB uncompressed, (27 GB compressed). This dataset spans a number of big news events (the Olympics; both US presidential nominating conventions; the beginnings of the financial crisis; .) as well as everything else you might expect to find posted to blogs. To get access to the Spinn3r dataset, please download and sign the usage agreement , and email it to dataset-request (at) icwsm.org. Once your form is processed (usually within 1-3 days), you will be sent a URL and password where you can download the collection. Here is a sample of blog posts from the collection. The XML format is described on the Spinn3r website.
Studying Learning Spaces: A Review of Selected Empirical Studies

The author presents a review of empirical studies of learning spaces conducted primarily in the disciplines of science education and library sciences to aid researchers in the design of future learning space assessments. The studies included a variety of perspectives, such as examinations of spaces on learning outcomes, student engagement, and pedagogy. The selections also represent varying methods, including surveys, observations, and interviews, and include both quantitative and qualitative data analysis. This review of literature suggests that learning space studies should be designed to include multiple targets and approaches, as well as innovative methods combined with traditional methods for triangulation. Learning space researchers should also strive for detailed reporting and wider dissemination of their studies for better knowledge sharing in the field.
Analysis of entrainment in face-to-face interaction using heart rate variability

The entrainment between talkers in face-to-face interaction plays an important role in the smooth exchange of information. In this paper, the physiological signal entrainment in face-to-face interaction was analyzed on the basis of heart rate and its variability as indices, based on the previous known fact that alteration of cardiac rhythm has been used as an indicator of the emotional state. The subjects consisted of two pairs of mothers and healthy infants aged 5 and 9 months as a primitive form of communication, and one pair of male students. The existence of physiological signal entrainment was demonstrated from some examples of synchronized time changes of heart rate variability in both mother-infant interaction and adult conversation. This finding suggests the entrainment is biologically essential to human communication and it could be applicable for improved human-robot interaction.
Embedding the 2D interaction metaphor in a real 3D virtual environment

Recent advances in both rendering algorithms and hardware has brought virtual reality to the threshold of being able to model realistically complex environments, e.g., the mockup of a large structure. As impressive as these advances have been there is still little that a user can do within a VR system other than look--and react. If VR is to be usable in a design setting users will need to be able to interact, to control and modify their virtual environments using virtual tools inside that environment. In this paper we describe a realistic virtual computer/personal digital assistant that we have built. To the user this virtual computer appears as a hand held flat panel display. Input can be provided to this virtual computer using a virtual finger or stylus to `touch' the screen. We migrate applications developed for a flat screen environment into the virtual environment without modifying the application code. A major strength of this approach is that we meld the naturally 3D interaction metaphor of a hand held virtual tool with the software support provided by some 2D user interface toolkits. Our approach has provided us great flexibility in both designing and implementing user interface components for VR environments, and it has enabled us to represent the familiar flat screen human computer interaction metaphor within the VR context. We will describe some applications which made use of our capability.
Learning Sparse Recurrent Neural Networks in Language Modeling

In the context of statistical language modeling, we explored the task of learning an Elman network with sparse weight matrices, as a pilot study towards learning a sparsely connected fully recurrent neural network, which would be potentially useful in many cases. We also explored how efficient and scalable it can be in practice. In particular, we explored these tasks: (1) We adapted the Iterative Hard Thresholding (IHT) algorithm into the BackPropagation Through Time (BPTT) learning. (2) To accelerate convergence of the IHT algorithm, we designed a scheme for expanding the network by replicating the existing hidden neurons. Thus we can start training from a small and dense network which is already learned. (3) We implemented this algorithm in GPU. Under small minibatch sizes and large network sizes (e.g., 2000 hidden neurons) it achieves 160 times speedup compared to the RNNLM toolkit in CPU. With larger minibatch sizes there could be another 10 times speedup, though the convergence rate becomes an issue in such cases and further effort is needed to address this problem. (4) Without theoretical convergence guarantee of the IHT algorithm in our problem setting, we did an empirical study showing that learning a sparse network does give competitive perplexity in language modeling. In particular, we showed that a sparse network learned in this way can outperform a dense network when the number of effective parameters is kept the same. (5) We gathered performance metric comparing the computational effiii ciency of the matrix operations of interest in both sparse and dense settings. The results suggest that for network sizes which we can train in reasonable time at this moment, sparse matrices do not computational advantage than dense matrices, unless we are allowed to have very sparse networks. Thus for research purposes we may want to focus on using dense matrices, while for engineering purposes a more flexible matrix design leveraging the power of dense and sparse matrices might be necessary.
Adversarial Learning for Weakly-Supervised Social Network Alignment

Nowadays, it is common for one natural person to join multiple social networks to enjoy different kinds of services. Linking identical users across multiple social networks, also known as social network alignment, is an important problem of great research challenges. Existing methods usually link social identities on the pairwise sample level, which may lead to undesirable performance when the number of available annotations is limited. Motivated by the isomorphism information, in this paper we consider all the identities in a social network as a whole and perform social network alignment from the distribution level. The insight is that we aim to learn a projection function to not only minimize the distance between the distributions of user identities in two social networks, but also incorporate the available annotations as the learning guidance. We propose three models SNNAu, SNNAb and SNNAo to learn the projection function under the weakly-supervised adversarial learning framework. Empirically, we evaluate the proposed models over multiple datasets, and the results demonstrate the superiority of our proposals.
Analysis and Synthesis of Leaky-Wave Devices in Planar Technology

Resumen de la tesis: El trabajo llevado a cabo durante la realizacion de la tesis doctoral titulada ? Analysis and Synthesis of Leaky-Wave Devices in Planar Technology? , se ha centrado en el analisis y sintesis de dispositivos de microondas en tecnologia planar. En concreto, se han estudiado diferentes tipos de antenas ? leaky-wave? (LWAs) basadas en tecnologia planar, en las cuales mediante el control del modo de fuga a lo largo de la antena se ha podido obtener una gran variedad de diagramas de radiacion. Ademas, otros dispositivos como multiplexores y sistemas de enfoque en campo cercano han sido disenados y validados mediante su posterior fabricacion. Con el objetivo de poder obtener de una manera mas eficiente las caracteristicas de propagacion de los modos de fuga ? leaky? en funcion de los principales parametros geometricos de la estructura, se han desarrollado diversas herramientas de analisis modal basadas en la tecnica de resonancia transversa de la estructura. Tambien se han estudiado las caracteristicas que presentan dichos tipos de antenas en tecnologia de guia de onda integrada en sustrato (SIW). Esta tecnologia permite integrar de una forma sencilla y de bajo coste, dispositivos con prestaciones similares a los que anteriormente se fabricaban en tecnologias clasicas de guias de onda.
Supporting intelligent terminals by cross-layer adaptation over HSDPA network

Next generation of mobile networks will support intelligent terminals having different categories and generating traffic with various qualities of service (QoS) requirements. To provide an end-to-end QoS, application terminals need to be adaptive and deal with network changing conditions. Knowledge has to be shared between network layers to obtain the highest possible adaptivity. In this context, we propose and evaluate an adaptive proportional fair algorithm with user multiplexing. Performance results show that the proposed algorithm is effective in reducing sojourn delays and in enhancing fairness among terminal users. The study investigates as well the impact of terminal categories with different levels of performance on our scheduling algorithm.
Intelligent Selection Techniques For Virtual Environments

Selection in 3D games and simulations is a well-studied problem. Many techniques have been created to address many of the typical scenarios a user could experience. For any single scenario with consistent conditions, there is likely a technique which is well suited. If there isn't, then there is an opportunity for one to be created to best suit the expected conditions of that new scenario. It is critical that the user be given an appropriate technique to interact with their environment. Without it, the entire experience is at risk of becoming burdensome and not enjoyable. With all of the different possible scenarios, it can become problematic when two or more are part of the same program. If they are put closely together, or even intertwined, then the developer is often forced to pick a single technique that works so-so in both, but is likely not optimal for either, or maybe optimal in just one of them. In this case, the user is left to perform selections with a technique that is lacking in one way or another, which can increase errors and frustration. In our research, we have outlined different selection scenarios, all of which were classified by their level of object density (number of objects in scene) and object velocity. We then performed an initial study on how it impacts performance of various selection techniques, including a new selection technique that we developed just for this test, called Expand. Our results showed, among other things, that a standard Raycast technique works well in slow moving and sparse environments, while revealing that our new Expand technique works well in denser environments. With the results from our first study, we sought to develop something that would bridge the gap in performance between those selection techniques tested. Our idea was a framework that could harvest several different selection techniques and determine which was the most optimal at any time. Each selection technique would report how effective it was, given the provided scenario conditions. The framework was responsible for activating the appropriate selection technique when the user made a selection attempt. With this framework in hand, we performed two additional user studies to determine how effective it could be in actual use, and to identify its strengths and weaknesses. Each study compared several selection techniques individually against the framework which utilized them collectively, picking the most suitable. Again, the same scenarios from our first study were reused. From these studies, we gained a deeper understanding of the many challenges associated with automatic selection technique determination. The results from these two studies showed that transitioning between techniques was potentially viable, but rife with design challenges that made its optimization quite difficult. In an effort to sidestep some of the issues surrounding the switching of discrete techniques, we sought to attack the problem from the other direction, and make a single technique act similarly to two techniques, adjusting…
Fortschrittliches Anzeige- und Interaktionskonzept für die kooperative Führung hochautomatisierter Fahrzeuge: Ausgewählte Ergebnisse mit H-Mode 2D 1.0

H-Mode ist ein auf der H(orse)-Metapher basierendes haptisch-visuelles Anzeigeund Interaktionskonzept fur die kooperative Steuerung hochautomatisierter Bewegung, insbesondere hochautomatisierter Luft- und Bodenfahrzeuge. Dabei wirken Automation und Mensch gemeinsam, aber zu wechselnden Anteilen, uber ein haptisches Stellteil und visuelle Anzeigen gekoppelt, auf die Fuhrung. Dieser Beitrag beschreibt den Stand des Konzeptes 2012 fur Bodenfahrzeuge, insbesondere eine Version des H-Modes mit aktivem Lenkrad und Gaspedal einerseits, und einem aktivem Sidestick andererseits, jeweils gekoppelt mit einer Voranzeige einer Bewegungstrajektorie. Es werden 2 Studien vorgestellt, die das Konzept in einem statischen Fahrsimulator der TU Munchen und einem dynamischen Bewegungssimulator des DLR Braunschweig untersuchen. So konnte festgestellt werden, dass durch die Anzeige einer Trajektorie in einem kontaktanalogen Headup- Display (kHuD) das Vertrauen in die Automation erhoht und die Eingriffszeiten bei Systemfehlern verkurzt werden. Die Gebrauchstauglichkeit wurde insgesamt als gut eingeschatzt. Der Artikel schliest mit einem Ausblick auf die nachste Version des H-Modes, der die Interaktion fur eine temporar vollautomatisierte Betriebsart beinhalten wird.