Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast two-stage estimator for clustered count data with overdispersion

ABSTRACT Clustered count data are commonly analysed by the generalized linear mixed model (GLMM). Here, the correlation due to clustering and some overdispersion is captured by the inclusion of cluster-specific normally distributed random effects. Often, the model does not capture the variability completely. Therefore, the GLMM can be extended by including a set of gamma random effects. Routinely, the GLMM is fitted by maximizing the marginal likelihood. However, this process is computationally intensive. Although feasible with medium to large data, it can be too time-consuming or computationally intractable with very large data. Therefore, a fast two-stage estimator for correlated, overdispersed count data is proposed. It is rooted in the split-sample methodology. Based on a simulation study, it shows good statistical properties. Furthermore, it is computationally much faster than the full maximum likelihood estimator. The approach is illustrated using a large dataset belonging to a network of Belgian general practices.
TDMA SLOT RESERVATION IN CLUSTER-BASED VANETS

TDMA SLOT RESERVATION IN CLUSTER-BASED VANETS Mohammad Salem Almalag Old Dominion University, 2013 Director: Dr. Michele C. Weigle Vehicular Ad Hoc Networks (VANETs) are a form of Mobile Ad Hoc Networks (MANETs) in which vehicles on the road form the nodes of the network. VANETs provide several services to enhance the safety and comfort of drivers and passengers. These services can be obtained by the wireless exchange of information among the vehicles driving on the road. In particular, the transmission of two different types of messages, safety/update and non-safety messages. The transmission of safety/update message aims to inform the nearby vehicles about the sender’s current status and/or a detected dangerous situation. This type of transmission is designed to help in accident and danger avoidance. Moreover, it requires high message generated rate and high reliability. On the other hand, the transmission of non-safety message aims to increase the comfort on vehicles by supporting several non-safety services, from notifications of traffic conditions to file sharing. Unfortunately, the transmission of non-safety message has less priority than safety messages, which may cause shutting down the comfort services. The goal of this dissertation is to design a MAC protocol in order to provide the ability of the transmission of non-safety message with little impact on the reliability of transmitting safety message even if the traffic and communication densities are high. VANET is a highly dynamic network. With lack of specialized hardware for infrastructure and the mobility to support network stability and channel utilization, a cluster-based MAC protocol is needed to solve these overcomes. This dissertation makes the following contributions: 1. A multi-channel cluster-based TDMA MAC protocol to coordinate intracluster communications (TC-MAC) 2. A CH election and cluster formation algorithm based on the traffic flow and a cluster maintenance algorithm that benefits from our cluster formation algorithm 3. A multi-channel cluster-based CDMA/TDMA hybrid MAC protocol to coordinate inter-cluster communications I will show that TC-MAC provides better performance than the current WAVE standard in terms of safety/update message reliability and non-safety message delivery. Additionally, I will show that my clustering and cluster maintenance protocol provides more stable clusters, which will reduce the overhead of clusterhead election and re-clustering and leads to an efficient hierarchical network topology.
The Google truth

Since 2008, Google Flu Trends has followed the spread of annual virus outbreaks, based on the assumption that wherever people are Googling "flu symptoms", an outbreak is imminent. Now, researchers are turning the Google lens on more difficult issues, some of which are invisible to conventional polls, says economist Seth Stephens-Davidowitz. He analyzed Google searches and voting patterns in the US to measure the extent to which racism hurt Barack Obama in the 2008 presidential election. He ranked states based on the proportion of searches that contained the word "nigger" between 2004 and 2007. The states with the highest rates of these searches were ones where Obama underperformed in the election, such as Ohio and West Virginia. He concluded that racism alone cost Obama 3%-5% of the total vote.
Study of removing striping noise in CCD image

Striping noise is the common system noise during formation of image using linear array CCD and has the character of periodicity, directivity and banding distributing. It can be caused by errors in internal calibration devices, or by slight gain/offset differences among the elements that conform the array of detectors. Striping noise covers up useful information in CCD image and brings adverse effect to image interpretation. On the basis of analyzing wavelet decomposed coefficient, the regularities of distribution about striping noise in wavelet coefficient is found, thereby the method of wavelet threshold selection which is suitable to striping noise distribution is put forward. According to Donoho's method about denoising using wavelet, the image including striping noise is processed. Comparing the power spectrum of processed image with the one of original image polluted by striping noise in frequency field, we find pulse brought by striping noise is removed and the goal which reserves image details and reduces stripes is achieved.
Asymptotic distribution theory in the analysis of covariance structures

In this paper we present a unified approach to the asymptotic distribution theory of covariance structures. Our approach is based on the differential calculus of min-max functions, which is developed in the first sections of the paper. The general theory is demonstrated by means of generalized least squares estimators. New and well-known results are obtained in the general framework. In particular, the asymptotic behavior of the estimators under an alternative hypothesis and the problem of non-identifiability are discussed. Finally, potential possibilities of the theory are illustrated by the example of minimum trace factor analysis.
Finite irreducible modules of Lie conformal algebras 𝒲(a,b) and some Schrödinger–Virasoro type Lie conformal algebras

Lie conformal algebras [Formula: see text] are the semi-direct sums of Virasoro Lie conformal algebra and its nontrivial conformal modules of rank one. In this paper, we first give a complete classification of all finite nontrivial irreducible conformal modules of [Formula: see text]. It is shown that all such modules are of rank one. Moreover, with a similar method, all finite nontrivial irreducible conformal modules of Schrödinger–Virasoro type Lie conformal algebras [Formula: see text] and [Formula: see text] are characterized.
Incremental Reconstruction of Moving Object Trajectory

This article presents a model and a prototype implementation of a technical application programming interface (API) for incremental reconstruction of the moving objects trajectories captured by closed-circuit television (CCTV) and High-definition television (HDTV) cameras. This paper proposes a unique, much simpler model-driven approach which is more efficient than other approaches for dynamic tracking such as Microsoft Kinect. The research reported here is part of a research program of the Cybersecurity Research Group of London Metropolitan University for real-time video analytics with applicability to surveillance in security, disaster recovery and safety management, and customer insight.
Secure analysis of multi-antenna cooperative networks with residual transceiver HIs and CEEs

This paper investigates the secure performance of multi-antenna decode-and-forward (DF) relaying networks where the Nakagami- m fading channel is taken into account. In practice, the joint impact of residual transceiver hardware impairments (HIs) and channel estimation errors (CEEs) on the outage probability (OP) and intercept probability (IP) are taken into account. Considering HIs and CEEs, an optimal transmit antenna selection scheme is proposed to enhance the secure performance and then a collaborative eavesdropping scheme is proposed. More specifically, they derive exact closed-form expressions for the outage and intercept probabilities. To obtain more useful insights the asymptotic behaviours for the OP are examined in the high signal-to-noise ratio (SNR) regime and the diversity orders are obtained and discussed. Simulation results confirm the analytical derivations and demonstrate that: (i) As the power distribution coefficient increases, OP decreases, while IP increases; (ii) There exist error floors for the OP at high SNRs, which is determined by CEEs; (iii) The secure performance can be improved by increasing the number of source antennas and artificial noise quantisation coefficient, while as the number of eavesdropping increases, the security of the system is reduced; (iv) There is a trade-off between the OP and IP.
Efficient Modeling of the Interaction of Mesoscale Gravity Waves with Unbalanced Large-Scale Flows: Pseudomomentum-Flux Convergence versus Direct Approach

This paper compares two different approaches for the efficient modeling of subgrid-scale inertia–gravity waves in a rotating compressible atmosphere. The first approach, denoted as the pseudomomentum scheme, exploits the fact that in a Lagrangian-mean reference frame the response of a large-scale flow can only be due to forcing momentum. Present-day gravity wave parameterizations follow this route. They do so, however, in an Eulerian-mean formulation. Transformation to that reference frame leads, under certain assumptions, to pseudomomentum-flux convergence by which the momentum is to be forced. It can be shown that this approach is justified if the large-scale flow is in geostrophic and hydrostatic balance. Otherwise, elastic and thermal effects might be lost. In the second approach, called the direct scheme and not relying on such assumptions, the large-scale flow is forced both in the momentum equation, by anelastic momentum-flux convergence and an additional elastic term, and in the entropy equation, via entropy-flux convergence. A budget analysis based on one-dimensional wave packets suggests that the comparison between the abovementioned two schemes should be sensitive to the following two parameters: 1) the intrinsic frequency and 2) the wave packet scale. The smaller the intrinsic frequency is, the greater their differences are. More importantly, with high-resolution wave-resolving simulations as a reference, this study shows conclusive evidence that the direct scheme is more reliable than the pseudomomentum scheme, regardless of whether one-dimensional or two-dimensional wave packets are considered. In addition, sensitivity experiments are performed to further investigate the relative importance of each term in the direct scheme, as well as the wave–mean flow interactions during the wave propagation.
Optimizing Hearing Aid Utilisation using Telemedicine Tools

At any given time, a proportion of the population is suffering hearing impairment to some degree, and using a hearing aid may not offer a satisfactory solution. Recognising speech is the most common concern (Arlinger, 2003). Wesendahl (2003) suggests that “Some important reasons for these circumstances are the stigma of wearing hearing aids, an unsatisfactory solution in contrast to the marketing promises of the prescribed device, the quality of fitting in artificial conditions rather than in real soundscapes, and the price”(p56). There have been instances of patient interaction over the Internet, but few holistic solutions. Finding a telemedicine business model that delivers value, makes operational sense and is economically sustainable has been reported as problematic. In this article, some operational and business issues are discussed, and one attempt at a holistic solution is using telemedicine tools is described, followed by suggested topics for further research.
Overview of deep learning

Deep learning is a new way of training multi-layer neural network.The optimization difficulty associated with the deep models can be alleviated,it has induced great attention of machine learning community.Firstly,this paper discussed the origin of deep learning,then analyzed virtue brought by deep learning.It introduced the main stream deep learning algorithm and their applications.Finally it concluded the problem remaining and development orientation.
NFV Real-time Analytics and Orchestration: Use Cases and Architectural Framework

One of the key goals of NFV is to optimize the infrastructure resource usage while driving operational simplicity. Real-time analytics providing insight into various components such as compute (e.g. dynamic CPU utilization), storage (e.g. dynamic capacity usage), network (e.g. dynamic bandwidth utilization), energy (e.g. dynamic power consumption) is key to not only providing visibility into the NFV infrastructure and thus driving operational simplicity but also optimizing resource usage for the purposes of orchestration. This draft focusses on use cases and architectural framework for real-time analytics and orchestration including Big Data predictive analytics for addressing the aforementioned requirements.
I2RS protocol strawman

This document provides a strawman proposal for the I2RS protocol covering the ephemeral data store and data flow requirements not covered by i2rs publication/subscription service or traceability. It also proposes additions to YANG for the ephemeral data store and for additional data flow requirements. It proposes additions to the NETCONF and RESTCONF for these additions. Future versions of this document will propose changes to support the I2RS protocol security requirements.
High-Performance Computing for Extreme-Scale Data Analytics.

As data sets increase in size, extreme-scale computing is needed to organize and analyze massive data. This clearly affects computing integrity and cybersecurity. One of the research recommendations in the first 2015 ASCR Cybersecurity Workshop report [4] was: “Research and develop methods to collect extreme-scale data and knowledge, and develop and apply analytics in order to understand and improve scientific computing integrity and computer security”. Since this type of data is very different from those in traditional physics-based simulations, a significant effort is needed to develop the fundamental computational tools necessary for computer security and scientific computing integrity. Our goal is to enable scalable data analytics using existing and future DOE leadership-class facilities. Supercomputing centers currently use specialized hardware platforms for data analysis and management. Examples include large shared-memory systems (e.g., PSC Blacklight and Sherlock) and/or systems with large-scale flash-based storage (e.g., TACC Wrangler). Our recent focus has been on scalable data analytics using supercomputers. We foresee a convergence in architectures in such a way that they will be equally friendly (or challenging) to both traditional scientific computations and data-intensive computations. With the large investments that organizations like DOE are making in supercomputers, it is important to leverage these investments for our data analytics needs as well. As most large data sets cannot be stored in the memory of a single compute node, there is a need for distributed-memory processing. In recent work, we show that end-to-end analytics on massive data sets can be performed using just a small fraction of a supercomputer’s resources. We analyze the largest publicly-available hyperlink graph (the 2012 Web Data Commons graph with 128 billion edges) using 256 compute nodes of the NCSA Blue Waters supercomputer [7]. We believe the following research areas will be important:
Métodos de inversión para un modelo de deformación volcánica

La correcta monitorizacion geodesica de los volcanes y su actividad es esencial para la prevencion y evaluacion de riesgos en zonas volcanicas activas. Esta consiste en el analisis e interpretacion de las deformaciones que aparecen en la superficie de zonas volcanicas activas, que tienen su origen en diferentes procesos tectonicos, magmaticos o hidrotermales producidos en el subsuelo dificiles de observar y monitorizar. El objetivo ultimo consiste en obtener informacion sobre las caracteristicas de la fuente de tensiones que esta generando las deformaciones a partir de estas. Los primeros modelos de estudio que se propusieron son modelos analiticos simplificados como el modelo de Mogi (1958). Sin embargo, el creciente desarrollo tanto de las tecnicas de medicion de las deformaciones (como estaciones GPS o InSAR) como de la capacidad de computacion de los ordenadores ha abierto el camino a la introduccion de modelos numericos basados en elementos finitos (MEF), que permiten estudiar de manera mas precisa y realista estos fenomenos. En este trabajo se presenta un estudio de diferentes metodos de inversion por elementos finitos para resolver un problema de deformacion volcanica bidimensional utilizando el programa MatLab. Se toman las siguientes hipotesis simplificadoras: El medio de la region volcanica es isotropo y homogeneo. Las deformaciones son elasticas y lineales. Las tensiones tienen su origen exclusivamente en las variaciones de presion de una camara magmatica esferica situada en el interior del medio. No existen errores en las deformaciones y desplazamientos observados. En este trabajo, en lugar de trabajar con observaciones reales, se calculan los desplazamientos resolviendo el problema directo de elasticidad lineal por elementos finitos. El problema directo consiste en hallar el campo de desplazamientos producidos por un determinado campo de tensiones. El problema inverso consiste, conocidos los desplazamientos en la superficie, en hallar las caracteristicas de la fuente de las tensiones, resolviendolo mediante metodos de optimizacion. Este trabajo trata de hallar la localizacion de la camara magmatica y su presurizacion, considerando la robustez y eficiencia de las diferentes tecnicas de optimizacion. En primer lugar, se estudian diferentes tecnicas de inversion para el caso de un area volcanica con una sola camara magmatica. En segunda instancia, se estudian dichas tecnicas para un escenario con dos camaras magmaticas en el interior del medio. Para la resolucion numerica de los problemas se utiliza el programa MatLab, que dispone de una serie de paquetes de herramientas como PDE ToolBox o Global Optimization ToolBox adecuados para esta aplicacion.
EFEKTIVITAS AKTIVITAS MENGHITUNG BERKAT (COUNTING BLESSING) TERHADAP KEPUASAN PERNIKAHAN

Kepuasan pernikahan berperan penting pada kesejahteraan mental individu yang berada dalam relasi pernikahan. Dalam ranah psikologi positif, aktivitas positif merupakan salah satu kegiatan yang dapat dilakukan untuk meningkatkan kesejahteraan mental dan juga berdampak positif pada relasi individu. Melalui penelitian ini, peneliti bertujuan melihat efektivitas dari aktivitas menghitung berkat terhadap kepuasan pernikahan. Penelitian dilakukan menggunakan metode eksperimental dengan melibatkan 58 partisipan yang terbagi menjadi dua kelompok secara acak, yaitu kelompok yang melakukan aktivitas menghitung berkat (n = 21) dan kelompok yang tidak melakukan aktivitas menghitung berkat (n = 37). Pemilihan partisipan dengan teknik convenience sampling dilakukan untuk menjaring partisipan yang sudah menikah dan berada dalam rentang usia pernikahan antara 1 sampai 13 tahun, tinggal satu rumah dengan pasangan, dan berpendidikan terakhir minimal diploma. Tingkat kepuasan pernikahan diukur menggunakan alat ukur Enrich Marital Satisfaction Scale (EMS) yang dilakukan sebelum (pre-test) dan setelah (post-test) pemberian intervensi aktivitas menghitung berkat. Hasil penelitian ini menunjukkan tidak terdapat perbedaan signifikan pada tingkat kepuasan pernikahan partisipan sebelum dan setelah melakukan aktivitas menghitung berkat t(20)= -0,39, p>0,05. Selain itu hasil penelitian ini juga melihat bahwa tidak ada perbedaan signifikan antara kelompok yang melakukan aktivitas menghitung berkat dan kelompok yang tidak melakukan aktivitas tersebut terhadap tingkat kepuasan pernikahan U = 34,10, z = -0,77, ns (p > 0,05).
An Interference Coordination Scheme for Hyper-Dense Heterogeneous Networks

Network densification is needed to meet the throughput demands likely to arise in 2020 and beyond, and small cells are expected to carry a majority of traffic. Since the number of small cells is huge, and they are always randomly deployed, the interference scenarios become much more complicated than in conventional cellular systems. In this paper, an interference coordination scheme based on graph method and clustering strategy for hyper-dense heterogeneous networks (HetNets) is presented. It is shown that the proposed scheme improves the network throughput and user satisfaction by dynamically allocating frequency sub-bands in K-tier networks.
E PluriBus Unum: High Performance Connectivity On Buses

We present PluriBus, a system that enables high-performance Internet access on-board moving vehicles. It seamlessly bonds multiple wide-area wireless links, which individually tend to be lossy and have high delays, into a reliable communication channel. PluriBus employs a novel technique called opportunistic erasure coding. It sends erasure coded packets only when there is an opening in a path’s spare capacity. Packets are coded using Evolution codes that we have developed to greedily maximize the expected number of packets recovered with each coded packet. These methods let us opportunistically use any spare resources, in a way that minimizes the impact on data traffic. We have deployed PluriBus on two buses. Our experiments show that it reduces the median flow completion time for a realistic workload by a factor of 2.5, compared to an existing method for spreading traffic across multiple paths.
Quantum Simulation of Strongly-Driven Systems Using Ultracold Lithium and Strontium

Author(s): Senaratne, Ruwan | Advisor(s): Weld, David | Abstract: Weakly-interacting atoms in a Bose-Einstein condensate coherently occupy the ground-state of their container. This phenomenon, coupled with the technical ability to produce precise, isolated and dynamically-tunable trapping potentials, makes ultracold atoms a versatile platform for simulating quantum mechanical systems. This thesis details the construction of two apparatus at the University of California, Santa Barbara for the production of Bose-Einstein condensates of lithium and strontium atoms respectively. Results of the first experiment performed on the strontium apparatus, a quantum simulation of ultrafast dynamics, are presented. In this experiment, driven cold atoms simulate ultrafast ionization dynamics in attosecond laser pulses, counter-intuitively emulating some of the fastest processes in atomic physics with some of the slowest. A sequence of experiments which demonstrate the correspondence with ultrafast science are described, including the direct observation of carrier-envelope-phase dependent sub-cycle unbinding dynamics. Preliminary results from a second experiment, studying phasonic excitations in a quasiperiodic lattice, are also discussed.
An Analogy-based Approach to Lexicon Acquisition

The Analogy-Based Lexical Acquisition System that we describe in this report belongs to a by now big family of NLP systems which are able to classify linguistic objects on the basis of instances of already acquired Knowledge (Federici and Pirrelli 1994, Montemagni et al. 1996, Pirrelli and Federici 1995, Yvon 1997). TEL:: +39 50 560481