Miracle-dz/UniFAR-FTUs huggingface dataset:
Fusion Based Approach for Distributed Alarm Correlation in Computer Networks

We propose a new distributed alarm correlation and fault identification in computer networks. The managed network is divided into a disjoint management domains and each management domain is assigned a dedicated intelligent agent. The intelligent agent is responsible for collecting, analyzing, and correlating alarms emitted form emitted from its constituent entities in its domain. In the framework of Dempster-Shafer evidence theory, each agent perceives each alarm as a piece of evidence in the occurrence of a certain fault hypothesis and correlates the received alarms into a single alarm called local composite alarm, which encapsulates the agent’s partial view of the current status of the managed system. While the alarm correlation process is performed locally, each intelligent agent is able to correlate its alarms globally. These local composite alarms are, in turn, sent to a higher agent whose task is to fuse these alarms and form a global view of operation status of the running network. Extensive experimentations have demonstrated that the proposed approach is more alarm loss tolerant than the codebook based approaches and hence shown its effectiveness in a usually noisy network environment.
Cumulative Contextual Facilitation in Word Activation and Processing: Evidence from Distributional Modelling

Information provided by the linguistic context has been shown to have a strong facilitatory effect on the activation and processing of upcoming words. The studies described in this paper aim to model the relation between context and target words using a distributional semantic model. We report three modelling studies in which we show that this model can successfully capture context effects in human-generated data (reading times and association scores).
Spectral domain optical coherence tomography for glaucoma (an AOS thesis).

PURPOSE Optical coherence tomography (OCT) is a rapidly evolving, robust technology that has profoundly changed the practice of ophthalmology. Spectral domain OCT (SD-OCT) increases axial resolution 2- to 3-fold and scan speed 60- to 110-fold vs time domain OCT (TD-OCT). SD-OCT enables novel scanning, denser sampling, and 3-dimensional imaging. This thesis tests my hypothesis that SD-OCT improves reproducibility, sensitivity, and specificity for glaucoma detection. METHODS OCT progress is reviewed from invention onward, and future development is discussed. To test the hypothesis, TD-OCT and SD-OCT reproducibility and glaucoma discrimination are evaluated. Forty-one eyes of 21 subjects (SD-OCT) and 21 eyes of 21 subjects (TD-OCT) are studied to test retinal nerve fiber layer (RNFL) thickness measurement reproducibility. Forty eyes of 20 subjects (SD-OCT) and 21 eyes of 21 subjects (TD-OCT) are investigated to test macular parameter reproducibility. For both TD-OCT and SD-OCT, 83 eyes of 83 subjects are assessed to evaluate RNFL thickness and 74 eyes of 74 subjects to evaluate macular glaucoma discrimination. RESULTS Compared to conventional TD-OCT, SD-OCT had statistically significantly better reproducibility in most sectoral macular thickness and peripapillary RNFL sectoral measurements. There was no statistically significant difference in overall mean macular or RNFL reproducibility, or between TD-OCT and SD-OCT glaucoma discrimination. Surprisingly, TD-OCT macular RNFL thickness showed glaucoma discrimination superior to SD-OCT. CONCLUSIONS At its current development state, SD-OCT shows better reproducibility than TD-OCT, but glaucoma discrimination is similar for TD-OCT and SD-OCT. Technological improvements are likely to enhance SD-OCT reproducibility, sensitivity, specificity, and utility, but these will require additional development.
CEP Discussion Paper No 986 June 2010 Currency Unions in Prospect and Retrospect

We critically review the recent literature on currency unions, and discuss the methodological challenges posed by the empirical assessment of their costs and benefits. In the process, we provide evidence on the economic effects of the euro. In particular, and in contrast with estimates of the trade effect of other currency unions, we find that the impact of the euro on trade has been close to zero. After reviewing the costs and benefits, we conclude with some open questions on normative and positive aspects of the theory of currency unions, emphasizing the need for a unified welfare-based framework to weigh their costs and gains.
Charge as the Stereographic Projection of Geometric Precession on Pseudospheres

In this paper geometric phases (Berry and Aharonov-Bohm) are generalized to nonlinear topological phase fields on pseudospheres, where the coordinate vector field is parallel transported along the signal/soliton vector field with Levi--Civita connection. Projective PSL(2,R} symmetry describes the relativistic self-interacting bosonic sine-Gordon field. A Coulomb potential can be induced as the stereographic projection of a harmonic oscillator potential mapping angles or phases to distances and vice versa resulting in mutual coupling with a generalized coupling constant given by a nonlinear iteration. With single-valuedness requirement in 137-gonal symmetry it fits within a few ppb uncertainty to the Sommerfeld fine structure constant.
Burst-Packet-Loss Concealment for MPEG-2 Video

In this paper, we propose an object-based error-concealment technique for MPEG-2 video transmitted in a burst-packet-loss environment. A burst packet loss typically impairs consecutive slices for the reconstructed picture. The proposed object-based error concealment proceeds in two stages, by intra-picture and inter-picture estimation respectively. In the first stage, regions of the missing area are estimated by using the motion vectors adjacent to the missing area. In the second stage, the singular objects with respect to uniformly moving background within the missing area are identified and compensated from the prediction pictures. As compared with conventional concealment approaches, the proposed method achieves better PSNR performance and relieves the visual discontinuity over the compensated region.
Economic Issues Are Moral Issues: The Moral Underpinnings of the Desire to Reduce Wealth Inequality

Economic inequality is a pervasive and growing source of social problems such as poor health, crime, psychological disorders, and lack of trust in others. U.S. citizens across the political spectrum both underperceive the extent of economic inequality and would prefer to live in a society with much less inequality than both exist in reality and in their subjective estimations. Across multiple studies, we examined the ability of “moral foundations” to predict people’s desire to reduce economic inequality (while also replicating research showing widespread desire for a more equal society). Moral foundations endorsements consistently predicted desire to reduce inequality even when controlling for other relevant factors (e.g., political orientation). In addition, requests for donations to an organization focused on reducing economic inequality were able to elicit more money when the requests largely appealed to the type of moral foundations endorsed by participants.
SQL-IDS: a specification-based approach for SQL-injection detection

Vulnerabilities in web applications allow malicious users to obtain unrestricted access to private and confidential information. SQL injection attacks rank at the top of the list of threats directed at any database-driven application written for the Web. An attacker can take advantages of web application programming security flaws and pass unexpected malicious SQL statements through a web application for execution by the back-end database. This paper proposes a novel specification-based methodology for the detection of exploitations of SQL injection vulnerabilities. The new approach on the one hand utilizes specifications that define the intended syntactic structure of SQL queries that are produced and executed by the web application and on the other hand monitors the application for executing queries that are in violation of the specification. The three most important advantages of the new approach against existing analogous mechanisms are that, first, it prevents all forms of SQL injection attacks; second, its effectiveness is independent of any particular target system, application environment, or DBMS; and, third, there is no need to modify the source code of existing web applications to apply the new protection scheme to them. We developed a prototype SQL injection detection system (SQL-IDS) that implements the proposed algorithm. The system monitors Java-based applications and detects SQL injection attacks in real time. We report some preliminary experimental results over several SQL injection attacks that show that the proposed query-specific detection allows the system to perform focused analysis at negligible computational overhead without producing false positives or false negatives. Therefore, the new approach is very efficient in practice.
A MULTI-HOP AD HOC NETWORK ROUTING ALGORITHM BASED ON PERFORMANCE MAXIMIZATION

The criteria of ideal ad hoc routing protocols for selecting paths should consider and analyze the important performance parameters such as transmission reliability and network throughput. The optimal choice for a route would be a path with small number of hops and high transmission rates. In this paper, a theoretical model of performance maximization is proposed for a routing algorithm. A routing protocol using this model is proposed. A great increase on performance is shown compared with other methods. Finally, suggestions on the evaluation of different routing protocols are proposed too.
Perturbation theory for bright spinor Bose-Einstein condensate solitons

We develop a perturbation theory for bright solitons of the F = 1 integrable spinor Bose-Einstein condensates BEC model. The formalism is based on using the Riemann-Hilbert problem and provides the means to analytically calculate evolution of the soliton parameters. Both rank-one and rank-two soliton solutions of the model are obtained. We prove equivalence of the rank-one soliton and the ferromagnetic rank-two soliton. Taking into account a splitting of a perturbed polar rank-two soliton into two ferromagnetic solitons, it is sufficient to elaborate a perturbation theory for the rank-one solitons only. Treating a small deviation from the integrability condition as a perturbation, we describe the spinor BEC soliton dynamics in the adiabatic approximation. It is shown that the soliton is quite robust against such a perturbation and preserves its velocity, amplitude, and population of different spin components, only the soliton frequency acquires a small shift. Results of numerical simulations agree well with the analytical predictions, demonstrating only slight soliton profile deformation.
Theobroxide Treatment Inhibits Wild Fire Disease Occurrence in Nicotiana benthamiana by the Overexpression of Defense-related Genes

Theobroxide, a novel compound isolated from a fungus Lasiodiplodia theobromae, stimulates potato tuber formation and induces flowering of morning glory by initiating the jasmonic acid synthesis pathway. To elucidate the effect of theobroxide on pathogen resistance in plants, Nicotiana benthamiana plants treated with theobroxide were immediately infiltrated with Pseudomonas syringae pv. tabaci. Exogenous application of theobroxide inhibited development of lesion symptoms, and growth of the bacterial cells was significantly retarded. Semi-quantitative RT-PCRs using the primers of 18 defense-related genes were performed to investigate the molecular mechanisms of resistance. Among the genes, the theobroxide treatment increased the expression of pathogenesis-related protein 1a (PR1a), pathogenesis-related protein 1b (PR1b), glutathione S-transferase (GST), allen oxide cyclase (AOC), and lipoxyganase (LOX). All these data strongly indicate that theobroxide treatment inhibits disease development by faster induction of defense responses, which can be possible by the induction of defense-related genes including PR1a, PR1b, and GST triggered by the elevated jasmonic acid.
Mining order-preserving submatrices from probabilistic matrices

Order-preserving submatrices (OPSMs) capture consensus trends over columns shared by rows in a data matrix. Mining OPSM patterns discovers important and interesting local correlations in many real applications, such as those involving biological data or sensor data. The prevalence of uncertain data in various applications, however, poses new challenges for OPSM mining, since data uncertainty must be incorporated into OPSM modeling and the algorithmic aspects. In this article, we define new probabilistic matrix representations to model uncertain data with continuous distributions. A novel probabilistic order-preserving submatrix (POPSM) model is formalized in order to capture similar local correlations in probabilistic matrices. The POPSM model adopts a new probabilistic support measure that evaluates the extent to which a row belongs to a POPSM pattern. Due to the intrinsic high computational complexity of the POPSM mining problem, we utilize the anti-monotonic property of the probabilistic support measure and propose an efficient Apriori-based mining framework called ProbApri to mine POPSM patterns. The framework consists of two mining methods, UniApri and NormApri, which are developed for mining POPSM patterns, respectively, from two representative types of probabilistic matrices, the UniDist matrix (assuming uniform data distributions) and the NormDist matrix (assuming normal data distributions). We show that the NormApri method is practical enough for mining POPSM patterns from probabilistic matrices that model more general data distributions. We demonstrate the superiority of our approach by two applications. First, we use two biological datasets to illustrate that the POPSM model better captures the characteristics of the expression levels of biologically correlated genes and greatly promotes the discovery of patterns with high biological significance. Our result is significantly better than the counterpart OPSMRM (OPSM with repeated measurement) model which adopts a set-valued matrix representation to capture data uncertainty. Second, we run the experiments on an RFID trace dataset and show that our POPSM model is effective and efficient in capturing the common visiting subroutes among users.
Signal integrity modeling and measurement of TSV in 3D IC

In order to guarantee signal integrity of a TSV-based channel in 3D IC design, the modeling and measurements are conducted for electrical characterization of the TSV-based channel including TSVs and RDLs with various performance metrics such as insertion loss, noise coupling and eye diagrams. Based on the modeling and measurements of the fabricated TSV channels, design guide for the signal integrity of the channel is proposed.
Distributed power control with limited message passing for nonconcave utility maximization

Transmit power control in wireless networks has long been recognized as an effective mechanism to mitigate co-channel interference. The optimal transmit power control problem is typically non-convex if a system utility is to be maximized. In our recent work [1], we proposed a distributed algorithm, referred to as GLAD, that obtains the global optimal solution to the non-convex power control problem. Same as other existing distributed power control algorithms, GLAD requires extensive message passing among all users in the network, which leads to high signaling overhead and high processing complexity. To reduce the message passing, this paper proposes a variant of the GLAD algorithm, referred to as I-GLAD, where the prefix "I" stands for infrequent message passing. The convergence of I-GLAD can be proved regardless of the reduction in the message passing rate. To further reduce the processing complexity at each transmitter, we develop an enhanced version of I-GLAD, referred to as NI-GLAD, where only the control messages from the neighboring links are processed. Our simulation results show that I-GLAD approximately converges to the global optimal solution regardless of the type of the system utility function. Meanwhile, the optimality of the solution obtained by NI-GLAD depends on the selection of the neighborhood size.
An Energy-PerformanceMetric for Mobile Ad hoc Networks

We discussa joint energy-performancemetric for mobilead hocnetworks.Previouswork in ad hoc networkshasconcentratedonevaluatingroutingprotocolsfor eitherhighperformancemetricsor low energymetrics.Thework in thispaper evaluatesroutingprotocolsbasedon a metric that accountsfor bothenergy andperformance. We presenta family of joint energy-performancemetricsfor ad hoc networksand showsimulationresultsevaluatingmultiple protocolswith various applicationsandnetworksizes.
A Parallel Ring Ordering Algorithm for Efficient One-Sided Jacobi SVD Computations

In this paper we give evidence to show that in one-sided Jacobi SVD computation the sorting of column norms in each sweep is very important. An efficient parallel ring Jacobi ordering for computing singular value decomposition is described. This ordering can generaten(n? 1)/2 different index pairs and sort column norms at the same time. The one-sided Jacobi SVD algorithm using this parallel ordering converges in about the same number of sweeps as the sequential cyclic Jacobi algorithm. The issue of equivalence of orderings for one-sided Jacobi is also discussed. We show how an ordering which does not sort column norms into order may still perform efficiently as long as it can generate the same index pairs at the same step as one which does sorting. Some experimental results on a Fujitsu AP1000 are presented.
PolymiRTS Database 2.0: linking polymorphisms in microRNA target sites with human diseases and complex traits

The polymorphism in microRNA target site (PolymiRTS) database aims to identify single-nucleotide polymorphisms (SNPs) that affect miRNA targeting in human and mouse. These polymorphisms can disrupt the regulation of gene expression by miRNAs and are candidate genetic variants responsible for transcriptional and phenotypic variation. The database is therefore organized to provide links between SNPs in miRNA target sites, cis-acting expression quantitative trait loci (eQTLs), and the results of genome-wide association studies (GWAS) of human diseases. Here, we describe new features that have been integrated in the PolymiRTS database, including: (i) polymiRTSs in genes associated with human diseases and traits in GWAS, (ii) polymorphisms in target sites that have been supported by a variety of experimental methods and (iii) polymorphisms in miRNA seed regions. A large number of newly identified microRNAs and SNPs, recently published mouse phenotypes, and human and mouse eQTLs have also been integrated into the database. The PolymiRTS database is available at http://compbio.uthsc. edu/miRSNP/.
Placement of digital microfluidic biochips using the T-tree formulation

Droplet-based microfluidic biochips have recently gained much attention and are expected to revolutionize the biological laboratory procedure. As biochips are adopted for the complex procedures in molecular biology, its complexity is expected to increase due to the need of multiple and concurrent assays on a chip. In this paper, we formulate the placement problem of digital microfluidic biochips with a tree-based topological representation, called T-tree. To the best knowledge of the authors, this is the first work that adopts a topological representation to solve the placement problem of digital microfluidic biochips. Experimental results demonstrate that our approach is much more efficient and effective, compared with the previous unified synthesis and placement framework
On signal denoising by EMD in the frequency domain

In this work a new denoising scheme based on the empirical mode decomposition associated with a frequency analysis is introduced. Compared to classical approaches where the extracted modes are thresholded in time domain, in the proposed strategy the thresholding is done in the frequency domain. Each mode is divided into blocks of equal length where the frequency content of each one is analyzed. Relevant modes are identified using an energy and a frequency thresholds obtained by training. The denoised signal is obtained by the superposition of the thresholded modes. The effectiveness of the proposed scheme is illustrated on synthetic and real signals and the results compared to those of methods reported recently.
A haptic toolkit for the development of immersive and web-enabled games

The creation of applications of Virtual Reality enabled with Haptic interaction and dynamic simulation requires usually to cover many implementation details that increase the development time and the effectiveness of the application itself. This work presents one game application that has been developed using a Haptic toolkit for the rapid application development, that integrates 3D graphics,haptic feedback and dynamic simulation.The resulting application can be easily deployed on the Web directly to the final user.
Evaluation of Four Designed Virtual Agent Personalities

Convincing conversational agents require a coherent set of behavioral responses that can be interpreted by a human observer as indicative of a personality. This paper discusses the continued development and subsequent evaluation of virtual agents based on sound psychological principles. We use Eysenck's theoretical basis to explain aspects of the characterization of our agents, and we describe an architecture where personality affects the agent's global behavior quality as well as their back-channel productions. Drawing on psychological research, we evaluate perception of our agents' personalities and credibility by human viewers (N = 187). Our results suggest that we succeeded in validating theoretically grounded indicators of personality in our virtual agents, and that it is feasible to place our characters on Eysenck's scales. A key finding is that the presence of behavioral characteristics reinforces the prescribed personality profiles that are already emerging from the still images. Our long-term goal is to enhance agents' ability to sustain realistic interaction with human users, and we discuss how this preliminary work may be further developed to include more systematic variation of Eysenck's personality scales.
Predictive Value of Biological Markers for Hepatocellular Carcinoma Patients Treated with Orthotopic Liver Transplantation

Purpose: To help stratify candidates with hepatocellular carcinoma (HCC) for orthotopic liver transplantation (OLT), biomarkers are needed that are capable of predicting recurrence of disease (ROD). We investigated the prognostic role in this setting of immunohistochemical markers reported previously to predict poor prognosis in HCC patients treated with resection. Experimental Design: Eighty-three patients with HCC who underwent OLT between 1987 and 2001 with a minimum clinical follow up of 12 months were included in this retrospective study. We analyzed immunohistochemical expression of the adhesion molecules E-cadherin and β-catenin (membrane/nuclear localization), MIB-1 proliferative index and the cyclin-dependent kinase inhibitor p27, alongside the main clinical-pathological variables. Results: At univariate analysis, vascular thrombosis, high MIB-1 index, lower membrane expression of E-cadherin and β-catenin, and nuclear β-catenin localization were associated with ROD. At multivariate analysis, only MIB-1 index, low equal E-cadherin (with respect to non-neoplastic surrounding tissue), and nuclear β-catenin appeared as independent predictors of ROD. The logistic regression analysis model indicated that detection of any one parameter was associated with at least 88% estimated risk of ROD (up to 99% for all three). Conclusions: We propose these three molecular parameters as an additional tool for rational selection of OLT candidates among HCC patients (stratification according to the risk of ROD might help provide a similar life expectancy for cirrhotic candidates with and without HCC).