Miracle-dz/UniFAR-FTUs huggingface dataset:
Applying device discovery methods for home network management

Currently there are still many devices that do not support the standards like UPnP, WSD etc. in home networks, thus, we should incorporate some standard methods with the other methods in order to get the information about the devices. In other words, a detector should complete the information by gathering the peripheral information, e.g. host name, OS version, the valid ports etc. Even if it can get the precise information from UPnP devices, the information is not always sufficient for the remote support service. The detection methods of device discovery are classified into two groups by their characteristics: the active detection and the passive detection. We present a practical method of device discovery, which combines the active detection and the passive detection, and described their characteristics by showing some experimental results.
Design and Simulation of a Car Soft Top

This paper addresses the problem of predicting the in-service behaviour of deformable product, i.e., the simulation of product functionalities under operating conditions within a Digital Mock-up. We have considered the design of a car soft-top; while today, with the aid of common computer-based tools, it is rather simple to design and simulate the kinematic mechanism of opening/closure, it is not so easy to understand how the covering material influences it. Moreover, the way the deformable material behaves may lead to malfunctions and damages of the overall structure. To this end we have used a tool, named SoftWorld that permits to model and simulate the behaviour of non-rigid materials, in our case the sunroof fabric, taking into account material properties. SoftWorld adopts a particle-based model by which an object can be represented by a set of particles connected by forces describing the objects mechanical behaviour. We describe the approach adopted to perform the simulation of the sunroof fabric. First results of experimentation are presented as well as work in progress related to the integrated co-simulation with the commercial system DADS for kinematic analysis.
Exact sampling and counting for fixed-margin matrices

The uniform distribution on matrices with specified row and column sums is often a natural choice of null model when testing for structure in two-way tables (binary or nonnegative integer). Due to the difficulty of sampling from this distribution, many approximate methods have been developed. We will show that by exploiting certain symmetries, exact sampling and counting is in fact possible in many nontrivial real-world cases. We illustrate with real datasets including ecological co-occurrence matrices and contingency tables.
Cracking Passwords using Keyboard Acoustics and Language Modeling

This project looks at how user input can be reconstructed from an audio recording of a user typing. The keyboard acoustic attack outlined in [35] is fully reimplemented and a number of extensions to their methods are developed. A novel keystroke error function is demonstrated which allows for optimal thresholds to be found when extracting keystrokes and a bagging technique is applied to previous clustering methods which increases the text recovery accuracy and removes the necessity for hand-labelled data. The properties of keystroke audio recordings are also examined and some of the limiting factors which impact on keystroke recognition are explored.
An error formula for Monte Carlo based portfolio optimization

One–period utility based portfolio optimization is a classic method in financial economics [13]. The theory is extremely well developed, and extends in many directions, for example to dynamic portfolio optimization in continuous time [12]. Nonetheless, the solutions to these problems, characterized theoretically, often remain dismayingly difficult to compute in practise. Very often, finance practitioners retreat from the economically sound methods of utility based optimization to a computationally simple but economically unjustified mean– variance method. This paper will examine a straightforward Monte Carlo method for computing utilityoptimal portfolios for problems of investing in M assets over a single period. After reviewing the basics of portfolio theory in sections 2 and 3, in section 4 we propose a formula for the error between the true solution and the Monte Carlo estimate and give a theoretical justification for it (but not a proof). As is typical in Monte Carlo methods, the error term is difficult to estimate accurately. In this paper we give rough estimates of the theoretical error in two ways: first by using the Monte Carlo simulation itself, and second by using an approximate formula derived under a Gaussian assumption. We find these two approaches to be mutually consistent, and consistent with the observed convergence of the Monte Carlo estimates. ∗Research supported by the Natural Sciences and Engineering Research Council of Canada and Mathematics of Information Technology and Complex Systems, Canada
Characterization of MODIS and SeaWiFS solar diffuser on-orbit degradation

MODIS has 20 reflective solar bands (RSB), covering the VIS, NIR, and SWIR spectral regions. They are calibrated on-orbit using a solar diffuser (SD) panel, made of space-grade Spectralon. The SD bi-directional reflectance factor (BRF) was characterized pre-launch by the instrument vendor with reference to the NIST reflectance standard. Its on-orbit degradation is tracked by an on-board solar diffuser stability monitor (SDSM). The SeaWiFS on-orbit calibration strategy uses monthly lunar observations to monitor the long-term radiometric stability of the instrument and applies daily observations of its solar diffuser (an aluminum plate coated with YB71 paint) to track the short-term changes in the instrument response. This paper provides an overview of MODIS and SeaWiFS SD observations, applications, and approaches used to track their on-orbit degradations. Results from both sensors are presented with emphasis on the spectral dependence and temporal trends of the SD degradation. Lessons and challenges from the use of SD for sensor on-orbit calibration are also discussed.
Decentralized algorithms for evaluating centrality in complex networks

Abstract— Centrality indices are often used to analyze the functionality of nodes in a communication network. Up to date most analyses are done on static networks where some entity has global knowledge of the networks properties. To expand the scope of these analyzing methods to decentral networks we will propose here a general framework for decentral algorithms that calculate centrality indices. We will describe variants of the general algorithm to calculate four different centralities, with emphasis on the algorithm of the betweenness centrality. The betweenness centrality is the most complex measure and best suited for describing network communication based on shortest paths and predicting the congestion sensitivity of a network. The communication complexity of this latter algorithm is asymptotically optimal and the time complexity scales with the diameter of the network. The calculated centrality index can be used to adapt the communication network to given constraints and changing demands such that the relevant properties like the diameter of the network or uniform distribution of energy consumption is optimized.
XMM-Newton observation of the Tycho supernova remnant

We present the observation of the Tycho supernova remnant obtained with the EPIC and RGS in- struments onboard the XMM-Newton satellite. We compare images and azimuthally averaged radial proles in emission lines from dierent elements (silicon and iron) and dierent transition lines of iron (Fe L and Fe K). While the Fe xvii L line and Si xiii K line images are globally spatially coincident, the Fe K emission clearly peaks at a smaller radius, indicating a higher temperature toward the reverse shock. This is qualitatively the prole expected when the reverse shock, after travelling through the outer power{law density prole, has entered the central plateau of the ejecta. The high energy continuum map has an overall smooth distribution, with a similar extent to the radio emission. Its radial prole peaks further out than the lines emission. Brighter and harder continuum regions are observed with a rough bipolar symmetry in the eastern and western edges. The spectral analysis of the southeastern knots supports spatial variations of the relative abundance of silicon and iron, which implies an incomplete mixing of the silicon and iron layers.
Ultrasonographic Findings of Superficial Radial Nerve and Cephalic Vein

Objective To investigate the anatomic relationship between the superficial radial nerve (SRN) and the cephalic vein (CV) through ultrasonography due to the possibility of SRN injury during cephalic venipuncture. Methods Both forearms of 51 healthy volunteers with no history of trauma or surgery were examined in proximal to distal direction using ultrasonography. We measured the distance between the radial styloid process (RSP) and the point where the SRN begins contact with the CV, and measured the distance between the RSP and the point where the SRN is separated from the CV. The point where the SRN penetrates the brachioradialis fascia was also evaluated. Results The SRN came in contact with the CV at a mean of 9.35±1.05 cm from the RSP and separated from the CV at a mean of 6.29±1.17 cm from the RSP. The SRN pierced the brachioradialis fascia at a mean of 10.31±0.89 cm from the RSP and horizontally 1.35±0.36 cm medial to the radius margin. All parameters had no significant differences in gender or direction. Conclusion The SRN had close approximation to the CV in the distal second quarter of the forearm. We recommend for cephalic venipuncture to be avoided in this area, and, if needed, it should be carried out with care not to cause injury to the SRN.
Energy-Efficient Flow Scheduling and Routing with Hard Deadlines in Data Center Networks

The power consumption of enormous network devices in data centers has emerged as a big concern to data center operators. Despite many traffic-engineering-based solutions, very little attention has been paid on performance-guaranteed energy saving schemes. In this paper, we propose a novel energy-saving model for data center networks by scheduling and routing "deadline-constrained flows" where the transmission of every flow has to be accomplished before a rigorous deadline, being the most critical requirement in production data center networks. Based on speed scaling and power-down energy saving strategies for network devices, we aim to explore the most energy efficient way of scheduling and routing flows on the network, as well as determining the transmission speed for every flow. We consider two general versions of the problem. For the version of only flow scheduling where routes of flows are pre-given, we show that it can be solved polynomially and we develop an optimal combinatorial algorithm for it. For the version of joint flow scheduling and routing, we prove that it is strongly NP-hard and cannot have a Fully Polynomial-Time Approximation Scheme (FPTAS) unless P=NP. Based on a relaxation and randomized rounding technique, we provide an efficient approximation algorithm which can guarantee a provable performance ratio with respect to a polynomial of the total number of flows.
PD1-Expressing T Cell Subsets Modify the Rejection Risk in Renal Transplant Patients

We tested whether multi-parameter immune phenotyping before or after renal transplantation can predict the risk of rejection episodes. Blood samples collected before and weekly for 3 months after transplantation were analyzed by multi-parameter flow cytometry to define 52 T cell and 13 innate lymphocyte subsets in each sample, producing more than 11,000 data points that defined the immune status of the 28 patients included in this study. Principle component analysis suggested that the patients with histologically confirmed rejection episodes segregated from those without rejection. Protein death 1 (PD-1)-expressing subpopulations of regulatory and conventional T cells had the greatest influence on the principal component segregation. We constructed a statistical tool to predict rejection using a support vector machine algorithm. The algorithm correctly identified 7 out of 9 patients with rejection, and 14 out of 17 patients without rejection. The immune profile before transplantation was most accurate in determining the risk of rejection, while changes of immune parameters after transplantation were less accurate in discriminating rejection from non-rejection. The data indicate that pretransplant immune subset analysis has the potential to identify patients at risk of developing rejection episodes, and suggests that the proportion of PD1-expressing T cell subsets may be a key indicator of rejection risk.
Using an SMT solver and Craig interpolation to detect and remove redundant linear constraints in representations of non-convex polyhedra

We present a method which computes optimized representations for non-convex polyhedra. Our method detects so-called redundant linear constraints in these representations by using an incremental SMT solver and then removes the redundant constraints based on Craig interpolation. The approach is evaluated both for formulas from the model checking context including boolean combinations of linear constraints and boolean variables and for random trees composed of quantifiers, AND-, OR-, NOT-operators, and linear constraints produced by a generator. The results clearly show the advantages of our approach in comparison to state-of-the-art solvers.
Trusting a library: A study of the latency to adopt the latest Maven release

With the popularity of open source library (re)use in both industrial and open source settings, `trust' plays vital role in third-party library adoption. Trust involves the assumption of both functional and non-functional correctness. Even with the aid of dependency management build tools such as Maven and Gradle, research have still found a latency to trust the latest release of a library. In this paper, we investigate the trust of OSS libraries. Our study of 6,374 systems in Maven Super Repository suggests that 82% of systems are more trusting of adopting the latest library release to existing systems. We uncover the impact of maven on latent and trusted library adoptions.
GNAT-Like Strategy for Polyketide Chain Initiation

An unexpected biochemical strategy for chain initiation is described for the loading module of the polyketide synthase of curacin A, an anticancer lead derived from the marine cyanobacterium Lyngbya majuscula. A central GCN5-related N-acetyltransferase (GNAT) domain bears bifunctional decarboxylase/S-acetyltransferase activity, both unprecedented for the GNAT superfamily. A CurA loading tridomain, consisting of an adaptor domain, the GNAT domain, and an acyl carrier protein, was assessed biochemically, revealing that a domain showing homology to GNAT (GNATL) catalyzes (i) decarboxylation of malonyl-coenzyme A (malonyl-CoA) to acetyl-CoA and (ii) direct S-acetyl transfer from acetyl-CoA to load an adjacent acyl carrier protein domain (ACPL). Moreover, the N-terminal adapter domain was shown to facilitate acetyl-group transfer. Crystal structures of GNATL were solved at 1.95 angstroms (ligand-free form) and 2.75 angstroms (acyl-CoA complex), showing distinct substrate tunnels for acyl-CoA and holo-ACPL binding. Modeling and site-directed mutagenesis experiments demonstrated that histidine-389 and threonine-355, at the convergence of the CoA and ACP tunnels, participate in malonyl-CoA decarboxylation but not in acetyl-group transfer. Decarboxylation precedes acetyl-group transfer, leading to acetyl-ACPL as the key curacin A starter unit.
Impact of non-quasi-static effects on 1/f3 phase noise in a 1.9-to-2.6 GHz oscillator

This work provides a comprehensive discussion of flicker noise up-conversion in current-biased oscillators. It is shown that the excess phase noise mostly arises from an AM-to-PM conversion due to the presence of a large capacitance at the tail node. During the study, a significant discrepancy has also emerged between measurements and simulations. A first attempt to explain this discrepancy is proposed, which takes into account the distributed nature of the flicker-noise source in the switching transistor pair.
Title of dissertation : NEUROMORPHIC MODEL FOR SOUND SOURCE SEGREGATION

Title of dissertation: NEUROMORPHIC MODEL FOR SOUND SOURCE SEGREGATION Lakshmi Krishnan, Doctor of Philosophy, 2015 Dissertation directed by: Professor Shihab Shamma Department of Electrical and Computer Engineering While humans can easily segregate and track a speaker’s voice in a loud noisy environment, most modern speech recognition systems still perform poorly in loud background noise. The computational principles behind auditory source segregation in humans is not yet fully understood. In this dissertation, we develop a computational model for source segregation inspired by auditory processing in the brain. To support the key principles behind the computational model, we conduct a series of electro-encephalography experiments using both simple tone-based stimuli and more natural speech stimulus. Most source segregation algorithms utilize some form of prior information about the target speaker or use more than one simultaneous recording of the noisy speech mixtures. Other methods develop models on the noise characteristics. Source segregation of simultaneous speech mixtures with a single microphone recording and no knowledge of the target speaker is still a challenge. Using the principle of temporal coherence, we develop a novel computational model that exploits the difference in the temporal evolution of features that belong to different sources to perform unsupervised monaural source segregation. While using no prior information about the target speaker, this method can gracefully incorporate knowledge about the target speaker to further enhance the segregation.Through a series of EEG experiments we collect neurological evidence to support the principle behind the model. Aside from its unusual structure and computational innovations, the proposed model provides testable hypotheses of the physiological mechanisms of the remarkable perceptual ability of humans to segregate acoustic sources, and of its psychophysical manifestations in navigating complex sensory environments. Results from EEG experiments provide further insights into the assumptions behind the model and provide motivation for future single unit studies that can provide more direct evidence for the principle of temporal coherence. NEUROMORPHIC MODEL FOR SOUND SOURCE SEGREGATION
Controlling the Bias: Inhibitory Attentional Control Moderates the Association between Social Anxiety and Selective Attentional Responding to Negative Social Information in Children and Adolescents

Previous findings suggest that some children and adolescents characterised by elevated social anxiety vulnerability attempt to regulate its debilitating consequences through attentional avoidance of negative social information. To date, however, the dimension of cognitive variability that enables the effective execution of this emotionally beneficial attentional strategy remains unknown. In the current study, we tested the hypothesis that the capacity to effectively attentionally avoid negative social information will be more evident in children and adolescents who exhibit higher levels of inhibitory attentional control, relative to those who display lower levels of inhibitory attentional control. Specifically, we recruited 115 children (aged 11 – 14 years old) from two public schools in Cluj-Napoca, Romania, who varied widely in terms of their social anxiety vulnerability, as assessed by the Social Phobia subscale of the Revised Child Anxiety and Depression Scale. These children completed a novel attentional assessment task designed to provide measures of both inhibitory attentional control, and attentional bias to negative social information. In keeping with the hypothesis under test, our present findings show that the association between social anxiety vulnerability and attentional avoidance of negative social information was indeed more evident in socially anxious children and adolescents with higher levels of inhibitory attentional control. We discuss ways in which future investigators could build upon the present findings to further shed light on the cognitive factors that contribute to vulnerability and resistance to developing social anxiety.
Managing motivation in the contact center: The employment relationship of outsourcing and temporary agency workers

Grounded in self-determination theory (SDT), this research builds a motivation profile typology of contingent workers in the contact center industry, compares outsourcer (OW) and temporary agency workers’ (TAW) profiles, and differentiates their human resources practices (HRP) perceptions and affective commitment. The hypotheses were tested in a sample of 2078 Portuguese contingent workers, through several statistical procedures, including latent profile analysis. Six profiles were identified. As expected, OW were mostly in the more intrinsic profiles, whereas TAW were in the more extrinsic ones. However, the contingent employment format did not moderate the relationship between motivation, HRP perceptions, and affective commitment.
Measures of conflict and power in strategic settings 1

In non-cooperative games, if coordination is allowed, then coalitions can take group actions, and thus become players themselves, each opposed to its complement. There is conflict when for every outcome there is at least one player who strictly prefers another outcome. In this paper, an index measuring conflict is provided. It obtains through a general procedure for turning any non-cooperative game into a [0,1]-ranged coalitional one. This latter quantifies the normalized worth of coordination within coalitions, whose group actions maximize the sum of members’ normalized utilities under the assumption that their complement chooses retaliation among best responses. That is, the max-min criterion is sophisticated by minimizing over best responses only. Taking into account retaliation possibilities enables to measure players’ power in any non-cooperative game through the Shapley value of the induced coalitional game; in fact, both transferable and non-transferable utilities are covered. But perhaps the ideal tools for analyzing power are game forms, where utilities are not specified at all, so that the only available information concerns how action profiles are mapped onto outcomes. These situations are treated by means of blockings (i.e. the dual of effectivity functions), specifying what outcomes each coalition may block. The chosen cardinality-based approach yields that power attains its maximum on Maskin blockings, and here again coalitions’ power may be used to define a coalitional game which, in turn, allows to quantify the power share of each player. 1. Some ideas contained in this paper were firstly presented at Logic, Game Theory and Social Choice 4 (22-24 June 2005, Université de Caen, France), where the participants provided interesting comments. I thank Antonio Bove and Giorgio Nicoletti for very helpful conversations. The usual disclaimer applies. 2. Department of Computer Science, University of Bologna, Mura Anteo Zamboni 7, 40126 Bologna, Italy; e-mail: giorossi@cs.unibo.it, url: www.cs.unibo.it/giorossi.
Sovereign Risk , Uncertainty and Policy

We study the effects of the ECB monetary policy and the European crises resolution policy decisions on the yields of the 10-year sovereign bonds of seven European countries. We find that some of the decisions have had significant impact on sovereign bond yields and have succeeded in increasing stability. However, the impact of the same policy decision might have been positive for some countries while negative for others, hinting about the importance of contagion channels. Economically most significant effects on the bond yields have been due to the announcement of ECB’s SMP program.