Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic max rate control algorithm for available bit rate service in ATM networks

The ATM Forum has adopted rate-based congestion control as the standard for available bit rate (ABR) services. In order to achieve fairness, it is necessary that the rate-based control schemes use intelligent marking, i.e., notify congestion only to selected connections. For these schemes to perform well, the central issue is to guarantee that the marking threshold is a good estimate of the fair share of the available bandwidth to which each connection is supposed to converge. In the existing schemes, such as the enhanced proportional rate control algorithm (EPRCA), this approximation does not always hold, for example due to bottlenecked connections, transient behaviors, safety parameters in the algorithms, or incorrect rate information from the sources. In this paper, we propose a new algorithm for the switch behavior, called the dynamic max rate control algorithm (DMRCA), which distinguishes itself from the existing schemes in that it uses a marking threshold which is a function of the degree of congestion at the switch and the maximum rate of all active connections. We show that this threshold is always an accurate estimate of the fair share, and thus the new algorithm outperforms the existing schemes, achieving fairness in all situations. The new scheme can be implemented with low complexity, and is fully compatible with the existing ATM standard.
Proceedings of the Joint Workshop on Language Technology for Closely Related Languages, Varieties and Dialects

We present the results of the 2nd edition of the Discriminating between Similar Languages (DSL) shared task, which was organized as part of the LT4VarDial’2015 workshop and focused on the identification of very similar languages and language varieties. Unlike in the 2014 edition, in 2015 we had an Others category with languages that were not seen on training. Moreover, we had two test datasets: one using the original texts (test set A), and one with named entities replaced by placeholders (test set B). Ten teams participated in the task, and the best-performing system achieved 95.54% average accuracy on test set A, and 94.01% on test set B.
Variations in micropropagated bananas and plantains : literature survey

Les donnees de la litterature concernant les variations chez les bananiers et les plantains multiplies in vitro ont ete analysees en incluant des resultats non publies du CIRAD-FLHOR. Les points discutes dans cette synthese sont les suivants : caracteristiques des variants, interet pour l'amelioration genetique et probleme pose pour la micropropagation de masse, origines, pourcentage et frequence d'apparition, facteurs influencant les variations, methodes de caracterisation, strategie possible pour limiter les risques de variation en propagation de masse. (Resume d'auteur)
Dominant Infiltration of TH 1-type CD4+ T Cells at the Retrobulbar Space of Patients with Thyroid-Associated Ophthalmopathy

Lymphocyte infiltration in the retrobulbar space is a prominent histological feature of thyroid-associated ophthalmopathy (TAO). We have characterized phenotypic and functional features of T cells derived from retrobulbar infiltrates of 3 TAO patients to better understand their roles in the disease. One hundred four T-cell clones (TCC) were directly established from cells of retrobulbar tissues using a highly efficient cloning procedure. Phenotypic analysis of TCC showed approximately 70% to 80% were CD3+ CD4+ CD8- T cells, and approximately 20% to 30% were CD3+ CD8+ CD4- T cells. None of the TCC were CD3+ CD4- CD8- T cells. Analysis of the cytokine profile of TCC, as documented by the ability to express interferon-gamma, interleukin (IL)-2, IL-4, and IL-10 demonstrated that the majority of TCC expressed T helper (T(H))1-like profile in both the mRNA and protein levels. A few TCC showed T(H)0-like profile, but no TCC showed T(H)2-like profile. These results suggest that T(H)1-type CD4+ T cells play important roles in the pathogenesis of TAO.
Protocolo de tratamento da sepse grave - HUPE contra a sepse

Brazilian National Health Institute initiated the project “Brazil against sepsis” in April 2012. In August of the same year a multiprofessional team was organized to take care of this project in Pedro Ernesto University Hospital. In September this team initiated medicine and nursing professionals, residents and graduation students training in order to obtain the best treatment protocol adhesion. The main objective of this protocol is the reduction of severe sepsis mortality. The treatment protocol is based on the Surviving Sepsis Campaign six hour package. It includes: quick severe sepsis recognition; laboratory exams collection, including arterial lactate and blood cultures, and also hemogram, glucose, urea, creatinine, total bilirubin, prothrombintime (INR) and partially activated thromboplastin time; antibiotic therapy initiated within the first hour of diagnosis; for patients with hypotension, with signs of inadequate tissue perfusion, including arterial lactate > 4 mmol/l, blood volume expansion with 0,9% saline, 20 to 30 ml/kg in the first hour, and evaluation of vasopressor amines indication. The hemodynamic targets are: central venous pressure – 8 to12 mmHg; mean arterial pressure > 65 mmHg; central venous oxygen saturation > 70%; lactate clearance > 10% in 6 hours; diuresis > 0,5 mL/kg/h. In order to achieve these goals some arrangements were provided: form of diagnosis and initial management of patients with severe sepsis; request form to obtain tray with material for deep venous puncture, central venous pressure measurement and blood cultures bottles; flowchart for quickly obtaining the first dose of antibiotic, flowchart for rapid achievement of the first laboratory tests; expediting the release of the results of cultures.
Effect of radio wave obstruction by obstacles on performance of IEEE 802.16j wireless multi-hop relay networks

In IEEE 802.16j networks, radio wave interference between wireless links must be taken into account when radio resources are assigned to network links. The protocol model, which defines the transmission and interference ranges as circles, is well-known as one of the major radio interference models. Although a lot of related studies on IEEE 802.16j networks use the protocol model, they do not consider the presence of obstacles. In this paper, we first investigate the performance of IEEE 802.16j networks considering the effect of obstacles. For that purpose, we define an obstacle model and extended protocol model for accommodating obstacles, where radio waves propagation is obstructed by obstacles. Next, the performance of IEEE 802.16j networks is evaluated through simulation experiments using the obstacle model and the extended protocol model. Additionally, we present a method for estimating the performance of IEEE 802.16j networks with obstacles. Then, we use multiple regression analysis based on simulation results and construct regression equations for network service ratio and power-to-throughput ratio. By evaluating the accuracy of the developed equations based on real-world environment, we confirm that the service ratio can be estimated with a high degree of accuracy when the distribution density of obstacle is small. Keywords-IEEE 802.16j, wireless multi-hop networks, relay network, obstacles, radio wave blocking
CLINICAL EPIDEMIOLOGICAL RESEARCH METHODS: THE BASICS AND POTENTIAL PITFALLS

Research is defined as a quest for knowledge through diligent investigation aimed at the discovery and interpretation of new knowledge using the scientific method. In the clinical setting, epidemiological methods are used to make a prediction about exposure to and/or health outcome for an individual based on scientific studies of groups of similar patients. Inadequacies in clinical epidemiological research methodologies constitute a challenge to generating and publishing sound, scientific clinical evidence. Flaws in methodology constitute the major reasons for this and indeed, for rejection of manuscripts submitted to health journals in general. Use of research methods not rigorous enough to answer a proposed research question and/or lack of adequate details on the research methods in the manuscripts submitted for publication are commonly observed features. These, not only compromise the quality of evidence generated and disseminated, but also contribute substantially to delays in the publication of manuscripts. This article describes the basic concepts of clinical epidemiological research and highlights common pitfalls and errors to be avoided.
HyPar: Towards Hybrid Parallelism for Deep Learning Accelerator Array

With the rise of artificial intelligence in recent years, Deep Neural Networks (DNNs) have been widely used in many domains. To achieve high performance and energy efficiency, hardware acceleration (especially inference) of DNNs is intensively studied both in academia and industry. However, we still face two challenges: large DNN models and datasets, which incur frequent off-chip memory accesses; and the training of DNNs, which is not well-explored in recent accelerator designs. To truly provide high throughput and energy efficient acceleration for the training of deep and large models, we inevitably need to use multiple accelerators to explore the coarse-grain parallelism, compared to the fine-grain parallelism inside a layer considered in most of the existing architectures. It poses the key research question to seek the best organization of computation and dataflow among accelerators. In this paper, inspired by recent work in machine learning systems, we propose a solution HyPar to determine layer-wise parallelism for deep neural network training with an array of DNN accelerators. HyPar partitions the feature map tensors (input and output), the kernel tensors, the gradient tensors, and the error tensors for the DNN accelerators. A partition constitutes the choice of parallelism for weighted layers. The optimization target is to search a partition that minimizes the total communication during training a complete DNN. To solve this problem, we propose a communication model to explain the source and amount of communications. Then, we use a hierarchical layer-wise dynamic programming method to search for the partition for each layer.
Specification Patterns for Robotic Missions

Mobile and general-purpose robots increasingly support everyday life, requiring dependable robotics control software. Creating such software mainly amounts to implementing complex behaviors known as missions. Recognizing this need, a large number of domain-specific specification languages has been proposed. These, in addition to traditional logical languages, allow the use of formally specified missions for synthesis, verification, simulation or guiding implementation. For instance, the logical language LTL is commonly used by experts to specify missions as an input for planners, which synthesize a robot's required behavior. Unfortunately, domain-specific languages are usually tied to specific robot models, while logical languages such as LTL are difficult to use by non-experts. We present a catalog of 22 mission specification patterns for mobile robots, together with tooling for instantiating, composing, and compiling the patterns to create mission specifications. The patterns provide solutions for recurrent specification problems; each pattern details the usage intent, known uses, relationships to other patterns, and—most importantly—a template mission specification in temporal logic. Our tooling produces specifications expressed in the temporal logics LTL and CTL to be used by planners, simulators or model checkers. The patterns originate from 245 mission requirements extracted from the robotics literature, and they are evaluated upon a total of 441 real-world mission requirements and 1251 mission specifications. Five of these reflect scenarios defined with two well-known industrial partners developing human-size robots. We further validate our patterns’ correctness with simulators and two different types of real robots.
SMILK, trait d'union entre langue naturelle et données sur le web

Le laboratoire commun SMILK avait pour double sujet d'etude l'utilisation du traitement automatique du langage naturel pour aider a la construction et au liage de donnees sur le web et, a l'inverse, l'utilisation de ces donnees liees du web semantique pour aider a l'analyse des textes et venir en appui de l'extraction de connaissances et l'annotation de contenus textuels. L'evaluation de nos travaux s'est focalisee sur la recherche d'informations portant sur des marques, plus particulierement dans le domaine de la cosmetique. Cet article decrit chaque etape de notre approche : la conception de ProVoc, une ontologie pour decrire les produits et marques ; le peuplement automatique d'une base de connaissances reposant notamment sur ProVoc a partir de ressources textuelles heterogenes; et l'evaluation d'une application prenant la forme d'un plugin de navigateur proposant des connaissances supplementaires aux utilisateurs naviguant sur le web.
Towards a Decentralized, Autonomous Multiagent Framework for Mitigating Crop Loss

We propose a generalized decision-theoretic system for a heterogeneous team of autonomous agents who are tasked with online identification of phenotypically expressed stress in crop fields. This system employs four distinct types of agents, specific to four available sensor modalities: satellites (Layer 3), uninhabited aerial vehicles (L2), uninhabited ground vehicles (L1), and static ground-level sensors (L0). Layers 3, 2, and 1 are tasked with performing image processing at the available resolution of the sensor modality and, along with data generated by layer 0 sensors, identify erroneous differences that arise over time. Our goal is to limit the use of the more computationally and temporally expensive subsequent layers. Therefore, from layer 3 to 1, each layer only investigates areas that previous layers have identified as potentially afflicted by stress. We introduce a reinforcement learning technique based on Perkins' Monte Carlo Exploring Starts for a generalized Markovian model for each layer's decision problem, and label the system the Agricultural Distributed Decision Framework (ADDF). As our domain is real-world and online, we illustrate implementations of the two major components of our system: a clustering-based image processing methodology and a two-layer POMDP implementation.
Compressive-sensing data reconstruction for structural health monitoring: a machine-learning approach

Compressive sensing has been studied and applied in structural health monitoring for data acquisition and reconstruction, wireless data transmission, structural modal identification, and spare damage identification. The key issue in compressive sensing is finding the optimal solution for sparse optimization. In the past several years, many algorithms have been proposed in the field of applied mathematics. In this article, we propose a machine learning–based approach to solve the compressive-sensing data-reconstruction problem. By treating a computation process as a data flow, the solving process of compressive sensing–based data reconstruction is formalized into a standard supervised-learning task. The prior knowledge, i.e. the basis matrix and the compressive sensing–sampled signals, is used as the input and the target of the network; the basis coefficient matrix is embedded as the parameters of a certain layer; and the objective function of conventional compressive sensing is set as the loss function of the network. Regularized by l1-norm, these basis coefficients are optimized to reduce the error between the original compressive sensing–sampled signals and the masked reconstructed signals with a common optimization algorithm. In addition, the proposed network is able to handle complex bases, such as a Fourier basis. Benefiting from the nature of a multi-neuron layer, multiple signal channels can be reconstructed simultaneously. Meanwhile, the disassembled use of a large-scale basis makes the method memory-efficient. A numerical example of multiple sinusoidal waves and an example of field-test wireless data from a suspension bridge are carried out to illustrate the data-reconstruction ability of the proposed approach. The results show that high reconstruction accuracy can be obtained by the machine learning–based approach. In addition, the parameters of the network have clear meanings; the inference of the mapping between input and output is fully transparent, making the compressive-sensing data-reconstruction neural network interpretable.
Crossbow: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers

Deep learning models are trained on servers with many GPUs, and training must scale with the number of GPUs. Systems such as TensorFlow and Caffe2 train models with parallel synchronous stochastic gradient descent: they process a batch of training data at a time, partitioned across GPUs, and average the resulting partial gradients to obtain an updated global model. To fully utilise all GPUs, systems must increase the batch size, which hinders statistical efficiency. Users tune hyper-parameters such as the learning rate to compensate for this, which is complex and model-specific. We describe Crossbow, a new single-server multi-GPU system for training deep learning models that enables users to freely choose their preferred batch size---however small---while scaling to multiple GPUs. Crossbow uses many parallel model replicas and avoids reduced statistical efficiency through a new synchronous training method. We introduce SMA, a synchronous variant of model averaging in which replicas independently explore the solution space with gradient descent, but adjust their search synchronously based on the trajectory of a globally-consistent average model. Crossbow achieves high hardware efficiency with small batch sizes by potentially training multiple model replicas per GPU, automatically tuning the number of replicas to maximise throughput. our experiments show that Crossbow improves the training time of deep learning models on an 8-GPU server by 1.3--4X compared to TensorFlow.
The Effect of MPI Collective Operations and MPI Collective Offloads on LS-DYNA® Performance

From concept to engineering, and from design to tes t and manufacturing, the automotive industry relies on powerful virtual development solutions. CFD and crash simula tions are performed in an effort to secure quality and accelerate the development process. The recent tren ds in cluster environments, such as multi-core CPUs , GPUs, cluster file systems and new interconnect speeds an d offloading capabilities are changing the dynamics of clusteredbased simulations. Software applications are being reshaped for higher parallelism and hardware config uration for solving the new emerging bottlenecks, in order to m aintain high scalability and efficiency. In this paper we cover new hardware based accelerations and offloads for M PI collectives communications and how is affect LS- DYNA performance and productivity.
Instructional Uses of Computers in Higher Education: A Survey of Higher Education in Massachusetts.

Deab, Ada Barbara Instructional Uses of CompAters in Higher Education: A Survey of Higher Education in Massachusetts. Harvard Univ., Cambridge, Mass. Oct 74 14p. ; Paper presented at the EDUCOM Fall Conference (Toronto, Ontario, October 16-18, 1974) Proceedings of the EDUCOM Fall Conference, EDOCON, Rosedale Road, P. 0. Von 364, Princeton, New Jersey 08540 (Estimated price, $6.00 for member institutions; 812.00 for others).
Uterine disease; understanding the underlying causes and envisioning solutions

36 Introduction.37 Materials and Methods.38 Results.43 Discussion.54 CHAPTER FOUR: ASSOCIATION BETWEEN UTERINE DISEASE AND INDICATORS OF NEUTROPHIL AND SYSTEMIC ENERGY STATUS IN LACTATING HOLSTEIN COWS.59 Interpretive summary.59 Abstract.60 Introduction.61 Materials and Methods.62 Results.68 Discussion.84 CHAPTER FIVE: ASSOCIATION BETWEEN CXCR1 POLYMORPHISM AND UTERINE DISEASE IN HOLSTEIN COWS.90 Interpretive summary.90 Abstract.9
Overview of the Sign3D Project High-fidelity 3D recording, indexing and editing of French Sign Language content

The Sign3D project aims at creating a range of innovative tools to allow the recording and the processing of motion captured French Sign Language (LSF) content. The challenge is to design a complete workﬂow from the movement capture (including all upper body part articulations, facial expression and gaze direction) to their restitution using a 3D virtual signer. We present the main innovation challenges at each step of the project. As accessibility for Deaf people through Sign Language is one goal of this project, a project overview of the project in SL is accessible at the following address : http://sign3d.websourd. org/sltat
Inorganics in Nuclear Medicine

More than 130 radionuclides are being used worldwide for therapeutic, diagnostic, and preventative purposes in the medical field. Using radionuclides, different organs can be imaged, and malfunction revealed. The most commonly used radionuclide in diagnosis by SPECT is technetium-99m (Tc), with some 40 million procedures yearly, almost 80% of all nuclear medicine procedures in the world. The Positron Emission Tomography (PET) is sophisticated and more precise technique using isotopes, like F produced in a cyclotron. The synthesis and use of organic molecules and their labeling with radionuclides are currently dominating in new radiopharmaceutical development. On the other hand inorganics (Co, I and Ir) are still playing unique role in nuclear medicine. In this article more commonly used radionuclides and their inorganic forms in nuclear medicine are described.
The Military Posts of Ramesses II on the Coastal Road and the Western Part of the Delta

Principales decouvertes: un temple forteresse a Zawjet Umm El-Rakham| El-Alamein, lieux avec monuments eriges par Ramses II dans la region occidentale du delta. Ramses II a ete le premier avise du danger que constituaient les Peuples de la Mer et a fait construire le long des terres cultivees et sur le littoral occidental une ligne de forteresses pour defendre le pays ou pour juguler le danger venant de la mer. Les Libyens ont tente a plusieurs reprises d'attaquer l'Egypte, mais ils ont toujours ete defaits.