Miracle-dz/UniFAR-FTUs huggingface dataset:
Network Coordination Algorithm Based on Distributed Probability Matrix Factorization

Network Coordination Systems (NCS) are powerful mechanisms to efficiently predict the network latency of pairwise hosts in Internet without directly network measurement between them. Each host is embedded into a distance space where the latency between nodes is calculated according to the distant function defined by the space with assigned coordination of hosts. In terms of the properties of distant space, most popular NCS can be classified into two categories. One is based on metric space and the other is based on vector space obtained by matrix factorization. Unfortunately, the metric space such as Euclidean space based NCS is known to severely suffer from the weakness of inaccurate formulation of the Triangle Inequality Violation (TIV) and asymmetric latency frequently observed in Internet. To overcome the limitations of metric space, matrix factorization methodology is therefore proposed to represent the latency matrix with missing data by the product of two low-dimension vector matrices. In contrast to the huge amount of work on metric space type of NCS, there are fewer study of matrix factorization NCS up to now. This leads us to consider a probabilistic matrix factorization (PMF) based network distance prediction framework. In this paper we propose a model of distributed probabilistic matrix factorization (DPMF) which provides a probabilistic view of NCS with introduction of latent random variables to the incoming and outgoing vectors of hosts. Simulation on the real word data set shows that DPMF can achieve competitive prediction accuracy compared with two matrix factorization based NCS algorithms. Although the convergence rate of DPMF is relatively slow, the probabilistic viewpoint of delay matrix allows automatic regularization parameter selection in latent vector iteration process which makes the algorithm much practical for various latency data sets. Therefore, DPMF provides a promising generative process of latency value which potentially extends the usage scope of NCS.
Wrapping up a Summary: From Representation to Generation

The main focus of this work is to investigate robust ways for generating summaries from summary representations without recurring to simple sentence extraction and aiming at more human-like summaries. This is motivated by empirical evidence from TAC 2009 data showing that human summaries contain on average more and shorter sentences than the system summaries. We report encouraging preliminary results comparable to those attained by participating systems at TAC 2009.
A framework for collaborative graphical based design environments

Current electronic design automation (EDA) and computer-aided software engineering (CASE) tools typically do not support collaborative work. When designers are geographically dispersed and with different time zones, real time collaboration can be a daunting task. A collaborative environment providing a platform for designers to communicate with one other more effectively is needed to address this problem. With this, instead of depending on telephone calls or emails, designers can interact among themselves in real time through computer-based support. Several studies have been done on collaborative computing. However, there are still no standard architecture styles for such an environment. This paper examines the use of a client-server based architecture to support collaborative environment for graphical based design tools. A design overview and the salient features of such a collaborative environment or system is presented. A prototype developed using Microsoft . NET framework and Visual C# to demonstrate its viability is also discussed in this paper.
Plenoptic Modeling of 3D Scenes with a Sensor-augmented Multi-Camera Rig

We propose a system for robust modeling and visualisation of complex outdoor scenes from multi-camera image sequences and additional sensor information. A camera rig with one or more fire-wire cameras is used in conjunction with a 3-axis rotation sensor to robustly obtain a calibration of the scene with an uncalibrated structure from motion approach. Dense depth maps are estimated with multi-viewpoint stereo and the scene is visualized from a plenoptic representation of the scene.
An Improved Ontology Mapping System Based on GRA

Ontology mapping created by end-users contains class hierarchy structure knowledge of the domain, and using that knowledge could produce new domainal ontology mapping. However, current systems have the following drawbacks: insufficient consideration of class hierarchy complexity, incomplete deletion inconsistent knowledge and inefficiency. Aiming at solving those problems, this paper proposes a new method of dealing differently with "similar to" and "equal to" relations in grass-roots ontology alignment. Besides, this paper re-designed inferences on class hierarchy knowledge base. The experiment result shows that revised system is more efficient than the original one, can produce results with higher precision while maintaining high recall, and can support complex ontology mapping.
Differentiation-Dedifferentiation as a Guiding Principle for the Analysis of Lifespan Development

Differentiation-dedifferentiation as a theoretical construct in lifespan developmental research has most often been used to describe increasingly similar versus dissimilar between-person differences in the changes of multiple intellectual abilities. Based on data from the Interdis- ciplinary Longitudinal Study of Adult Development (ILSE) we argue that differentiation- dedifferentiation may be used as a general guiding principle in developmental research. We demonstrate how the principle can be extended towards generally describing multiple traits between persons that include intellectual abilities and personality, towards describing within- person longitudinal development, and towards describing micro- and macrodevelopmental changes within- and between-persons aligning goal-related activities in a way that supports leading individually meaningful lifes.
Follicular Dendritic Cell Regulation of CXCR4-Mediated Germinal Center CD4 T Cell Migration1

Follicular dendritic cells (FDCs) up-regulate the chemokine receptor CXCR4 on CD4 T cells, and a major subpopulation of germinal center (GC) T cells (CD4+CD57+), which are adjacent to FDCs in vivo, expresses high levels of CXCR4. We therefore reasoned that GC T cells would actively migrate to stromal cell-derived factor-1 (CXCL12), the CXCR4 ligand, and tested this using Transwell migration assays with GC T cells and other CD4 T cells (CD57−) that expressed much lower levels of CXCR4. Unexpectedly, GC T cells were virtually nonresponsive to CXCL12, whereas CD57−CD4 T cells migrated efficiently despite reduced CXCR4 expression. In contrast, GC T cells efficiently migrated to B cell chemoattractant-1/CXCL13 and FDC supernatant, which contained CXCL13 produced by FDCs. Importantly, GC T cell nonresponsiveness to CXCL12 correlated with high ex vivo expression of regulator of G protein signaling (RGS), RGS13 and RGS16, mRNA and expression of protein in vivo. Furthermore, FDCs up-regulated both RGS13 and RGS16 mRNA expression in non-GC T cells, resulting in their impaired migration to CXCL12. Finally, GC T cells down-regulated RGS13 and RGS16 expression in the absence of FDCs and regained migratory competence to CXCL12. Although GC T cells express high levels of CXCR4, signaling through this receptor appears to be specifically inhibited by FDC-mediated expression of RGS13 and RGS16. Thus, FDCs appear to directly affect GC T cell migration within lymphoid follicles.
The Survival and Success of Penny Stock IPOs: an Analysis of the Consequences of Low Listing Requirements

We analyze a large sample of IPOs realized in a country where the minimal listing requirements are amongst the lowest in the world. In Canada, IPOs mainly consist of microand penny stocks offered by non-venture-backed companies in the developing stage. The proportion of issuers without revenues (positive earnings) is 45% (71%) and the median issue price is CAN$0.75, less than Euro0.50. Consequently, Canada offers a very rich context to study the effect of relatively lenient requirements on the survival and success of these issues. We divide issuers into four categories, from the lowest level of requirement (no sales, earnings or history) to the highest level (major exchange listing requirements). Using this classification, we analyze the survival and success of Canadian IPOs based on an original sample of 2,373 issues from 1986 to 2003. Following the TSX Venture Exchange, we consider that a newly listed company succeeds if it graduates to a senior exchange. Using Survival functions and Cox Proportional Hazards models, we test whether the differences between the survival and success rates are linked to the class of minimum listing requirements in which the company is situated at the IPO. Lastly, we estimate the costs and benefits in terms of failure and success associated with easing the new listing requirements. Our research attempts to contribute to the debate surrounding IPO regulation, listing requirements, and the balance between investor protection and issuer financing. The situation we analyze, where a stock market plays a role usually assumed by specialized intermediaries such as venture capitalists, is also of interest for public policy makers. Cécile Carpentier, Associate Professor, Laval University and CIRANO Associate Fellow, Faculty of administrative science, School of Accountancy, Pavilion Palasis-Prince, 2325 de la Terrasse, Laval University, Québec (Québec) Canada, G1V 0A6, phone: 418 656-2131 # 6385, fax: 418 656-7746, email: Cecile.Carpentier@fsa.ulaval. ca. Jean-Marc Suret, Professor, Laval University and CIRANO Fellow, phone: 418 656-7134, fax: 418 656-7746, email: Jean-Marc.Suret@fsa.ulaval. ca. The authors thank the Fonds réservé de l’Autorité des marchés financiers du Québec (the "Autorité") and the Social Sciences and Humanities Research Council (SSHRC) of Canada for financial support. The comments and opinions expressed by the authors of this article do not necessarily reflect the opinion of the Autorité. The authors thank Serge Dumais for valuable research assistance. The authors are grateful for comments from Michel Levasseur, Eric de Bodt, and participants at the Canadian Law and Economics Association annual meeting, Toronto (September, 2007), the ESC/ESA seminar in Lille (December, 2007) and the AFFI Annual meeting in Finance in Paris (December, 2007)
Mapping peering interconnections to a facility

Annotating Internet interconnections with robust physical coordinates at the level of a building facilitates network management including interdomain troubleshooting, but also has practical value for helping to locate points of attacks, congestion, or instability on the Internet. But, like most other aspects of Internet interconnection, its geophysical locus is generally not public; the facility used for a given link must be inferred to construct a macroscopic map of peering. We develop a methodology, called constrained facility search, to infer the physical interconnection facility where an interconnection occurs among all possible candidates. We rely on publicly available data about the presence of networks at different facilities, and execute traceroute measurements from more than 8,500 available measurement servers scattered around the world to identify the technical approach used to establish an interconnection. A key insight of our method is that inference of the technical approach for an interconnection sufficiently constrains the number of candidate facilities such that it is often possible to identify the specific facility where a given interconnection occurs. Validation via private communication with operators confirms the accuracy of our method, which outperforms heuristics based on naming schemes and IP geolocation. Our study also reveals the multiple roles that routers play at interconnection facilities; in many cases the same router implements both private interconnections and public peerings, in some cases via multiple Internet exchange points. Our study also sheds light on peering engineering strategies used by different types of networks around the globe.
Altered function of monocytes/macrophages in patients with autoimmune hepatitis

The pathogenesis of autoimmune hepatitis (AIH) involves the intervention of the innate and adaptive immune responses. In the current study, the alterations in monocytes/Kupffer cells (KCs) were investigated in patients with AIH. A total of 21 patients with AIH at different stages of the disease, and 7 controls with non-alcoholic fatty liver disease were selected. The abundance of VAV1 and p21-activated kinase 1 (PAK1) in the liver and KCs was analyzed. In addition, the expression levels of HLA-DR and CD80 in the peripheral blood monocytes (PBMs) were measured, and phagocytosis of PBMs was assessed. KCs of AIH patients exhibited higher expression levels of VAV1 and PAK1. This upregulated expression was associated with disease progression. A reduced expression of HLA-DR and CD80, and reduced capacity of E. coli phagocytosis in PBMs was observed for patients with AIH. This downregulated expression was associated with disease progression. The results of the current study indicated that defective function of KCs and PBMs may be involved in the pathogenesis of AIH.
Accurate modeling of physical time in asynchronous embedded sensing networks

Cyber-physical systems (CPSs) allow user to interconnect devices that monitor and control a physical environment. Many times these devices run at different clock frequencies. Due to system complexity, simulation represents a proper way for efficient debugging and validation. In previous work we have proposed a simulation framework for CPSs. The work presented in this paper extends this framework to allow different phase shift between CPS devices for a time accurate simulation.
Non-negativity preserving numerical algorithms for stochastic differential equations

Construction of splitting-step methods and properties of related non-negativity and boundary preserving numerical algorithms for solving stochastic differential equations (SDEs) of Ito-type are discussed. We present convergence proofs for a newly designed splitting-step algorithm and simulation studies for numerous numerical examples ranging from stochastic dynamics occurring in asset pricing theory in mathematical finance (SDEs of CIR and CEV models) to measure-valued diffusion and superBrownian motion (SPDEs) as met in biology and physics.
Using Linear Dynamical Topic Model for Inferring Temporal Social Correlation in Latent Space

The abundance of online user data has led to a surge of interests in understanding the dynamics of social relationships using computational methods. Utilizing users' items adoption data, we develop a new method to compute the Granger-causal (GC) relationships among users. In order to handle the high dimensional and sparse nature of the adoption data, we propose to model the relationships among users in latent space instead of the original data space. We devise a Linear Dynamical Topic Model (LDTM) that can capture the dynamics of the users' items adoption behaviors in latent (topic) space. Using the time series of temporal topic distributions learned by LDTM, we conduct Granger causality tests to measure the social correlation relationships between pairs of users. We call the combination of our LDTM and Granger causality tests as Temporal Social Correlation. By conducting extensive experiments on bibliographic data, where authors are analogous to users, we show that the ordering of authors' name on their publications plays a statistically significant role in the interaction of research topics among the authors. We also present a case study to illustrate the correlational relationships between pairs of authors.
Maximum Size Matchings and Input Queued Switches

Simulation results suggest that a maximum size matching (MSM) algorithm will lead to 100% throughput for uniform Bernoulli i.i. d traffic. Previous analysis on the throughput of MSM algorithms enforce deterministic constraints on the joint arrival traffic. In this paper we explore MSM algorithms under Bernoulli arrivals. We show that when the arrival traffic is admissible and cells are scheduled in batches, a sub-class of MSMs called the Critical Maximum Size Matching achieves 100% throughput under (uniform and nonuniform) Bernoulli i.i. d arrivals. Further, we show that — with batch scheduling — all MSMs achieve 100% throughput under Bernoulli i.i. d. uniform load.
Interference Alignment With Asymmetric Complex Signaling—Settling the Høst-Madsen–Nosratinia Conjecture

It has been conjectured by Hø-Madsen and Nosratinia that complex Gaussian interference channels with constant channel coefficients have only one degree-of-freedom regardless of the number of users. While several examples are known of constant channels that achieve more than 1 degree-of-freedom, these special cases only span a subset of measure zero. In other words, for almost all channel coefficient values, it is not known if more than 1 degree-of-freedom is achievable. In this paper, we settle the Høst-Madsen-Nosratinia conjecture in the negative. We show that at least 1.2 degrees-of-freedom are achievable for all values of complex channel coefficients except for a subset of measure zero. For the class of linear beamforming and interference alignment schemes considered in this paper, it is also shown that 1.2 is the maximum number of degrees-of-freedom achievable on the complex Gaussian 3 user interference channel with constant channel coefficients, for almost all values of channel coefficients. To establish the achievability of 1.2 degrees-of-freedom we use the novel idea of asymmetric complex signaling - i.e., the inputs are chosen to be complex but not circularly symmetric. It is shown that unlike Gaussian point-to-point, multiple-access and broadcast channels where circularly symmetric complex Gaussian inputs are optimal, for interference channels optimal inputs are in general asymmetric. With asymmetric complex signaling, we also show that the 2 user complex Gaussian X channel with constant channel coefficients achieves the outer bound of 4/3 degrees-of-freedom, i.e., the assumption of time-variations/frequency-selectivity used in prior work to establish the same result, is not needed.
Open Government Data Portals Analysis: The Brazilian Case

Governments and public agencies are publishing data on the Web, called Open Government Data (OGD), without restrictions for its sharing and reuse. This growing interest has motivated Brazilian Government Administrations to launch Open Data initiatives. As a consequence, in the last years, several Brazilian Open Data portals have been launched. Nowadays, there is a huge number of OGD portals from different countries and a lot of effort has been made to evaluate them. Although Brazil is one of the leaders of the Open Data initiative in South American and one of the founders of the Open Government Partnership, there are no comprehensive reports about the current Brazilian OGD scenario. In this context, we evaluated 13 Brazilian OGD portals according to several criteria ranging from the volume of data available to the quality of the data. As part of the results, we found that quantity and size of datasets are very diverse, CSV is the most used data format, at least 47 different data formats have been used to publish Open Data and most of the Brazilian Open Data portals use the CKAN platform. In this paper, we present and discuss the research method and the results of our work.
Efficient Simulation and Integrated Likelihood Estimation in Non-Linear Non-Gaussian State Space Models

We propose a generic approach to inference in the non-linear, non-Gaussian state space model. This approach builds on recent developments in precision-based algorithms to estimating general state space models with multivariate observations and states. The baseline algorithm approximates the conditional distribution of the states by a multivariate t density, which is then used for integrated likelihood estimation via importance sampling or for posterior simulation using Markov chain Monte Carlo (MCMC). We build further upon this baseline approach to consider more sophisticated algorithms such as accept-reject Metropolis-Hasting and variational approximation. To illustrate the proposed approach, we estimate the risk of a liquidity trap in the US under a time-varying parameter vector autoregressive (TVP-VAR) model with stochastic volatility.
Why Do Firms Both Make and Buy? An Investigation of Concurrent Sourcing

Transaction cost economics, neoclassical economics, and the firm capabilities literatures propose theories of the firm that typically depict firm boundaries determined by a dichotomous choice: the make or buy decision. However, none of these theories presents a satisfying explanation as to why firms would concurrently source, i.e., simultaneously make and buy the same good. This study combines these organizational economics theories and compares when firms make, buy, and concurrently source through surveying small manufacturing firms. Support was shown for aspects of all three theories, with evidence indicating that concurrent sourcing is a distinctly different choice, rather existing along a make/buy continuum. Copyright © 2007 John Wiley & Sons, Ltd.
Clustering Protein Sequences with Tailored General Regression Model Technique

— Cluster analysis divides data into groups that are meaningful, useful, or both. Analysis of biological data is creating a new generation of epidemiologic, prognostic, diagnostic and treatment modalities. Clustering of protein sequences is one of the current research topics in the field of computer science. Linear relation is valuable in rule discovery for a given data, such as if value X goes up 1, value Y will go down 3”, etc. The classical linear regression models the linear relation of two sequences perfectly. However, if we need to cluster a large repository of protein sequences into groups where sequences have strong linear relationship with each other, it is prohibitively expensive to compare sequences one by one. In this paper, we propose a new technique named General Regression Model Technique Clustering Algorithm (GRMTCA) to benignly handle the problem of linear sequences clustering. GRMT gives a measure, GR * , to tell the degree of linearity of multiple sequences without having to compare each pair of them.
Eye mark pointer in immersive projection display

We developed a pointer in 3D virtual space, using an eye-tracking system as a sensor. The eye mark pointer is installed to a virtual environment system which provides stereoscopic vision with an immersive projection display. The circular-polarization stereoscopic vision enables us to use the eye-tracking system in the immersive projection display. The eye-tracking system obtains relative gaze directions with respect to the head, so the absolute position requires compensation of the user's head motion with a head tracker. We then compare the eye mark pointer with a joystick in an experiment with the virtual environment system. The experimental result indicates the pointing of the eye mark pointer is 9.8 times quicker than that of the joystick, and suggests that the eye mark pointer is available for pointing at the target in the virtual environment.