Miracle-dz/UniFAR-FTUs huggingface dataset:
Microscopic cross-sections of old artworks

Materials research of microscopic cross-sections of paintings color layers is a very useful tool. It gives the restorers better insight into the technique, reveals how the artwork was created and what kind of materials was used. The proposed approach solves the problem of the proper spatial alignment of visible light and ultraviolet light images of cross-sections for further analysis by means of multimodal geometrical image registration. Then, the application offers primary segmentation of color layers. Second part of our work deals with automatic image retrieval, as a part of designing a database of laboratory research reports for restoration purposes. The aim is to facilitate search for reports about artworks with similar characteristic, based on the cross-section images.
The Dataflow Time and Space Complexity of FFTs

Abstract In this paper we analyze the performance of a recursive and an iterative fast Fourier transform algorithm, written in Id and run on MINT, a simulator for the Monsoon dataflow machine. Our complexity measures are: the number of instructions executed, the critical path length of the dataflow graph, and the storage occupancy. Using a set of simple functions, we calibrate loop and divide-and-conquer behavior of Monsoon and compare it with the "tagged token dataflow architecture. " We discuss the issues in explicit resource management in a functional language, introduce the language features required for this, and show results of our resource managed FFT programs.
An Information Theoretic Approach to Detection of Minority Subsets in Database

Detection of rare and exceptional occurrences in large- scale databases have become an important practice in the field of knowledge discovery and information retrieval. Many databases include large amount of noise or irrelevant data, whose distribution often overlaps with the subsets of exceptional data containing useful knowledge. This paper addresses the problem of finding a small subset of "minority" data whose distribution overlaps with, but are exceptional to or inconsistent with that of the majority of the database. In such a case, conventional distance-based or density-based approaches in Outlier Detection are ineffective due to their dependence on the structure of the majority or the prerequisite of critical parameters. We formalize the task as an estimation of a model of the minority subset which provides a simple description of the subset and yet maintains divergence from that of the majority. This estimation is formalized as a minimization problem using an information theoretic framework of Rate Distortion theory. We further introduce conditions of the majority to derive an objective function which factorizes the property of the minority and dependence to the structure of the majority. The proposed method shows improvements from conventional approaches in artificial data and a promising result in document retrieval problem.
Fair anonymity for the Tor network

Current anonymizing networks have become an important tool for guaranteeing users' privacy. However, these platforms can be used to perform illegitimate actions, which sometimes makes service providers see traffic coming from these networks as a probable threat. In order to solve this problem, we propose to add support for fairness mechanisms to the Tor network. Specifically, by introducing a slight modification to the key negotiation process with the entry and exit nodes, in the shape of group signatures. By means of these signatures, we set up an access control method to prevent misbehaving users to make use of the Tor network. Additionally, we establish a predefined method for denouncing illegitimate actions, which impedes the application of the proposed fairness mechanisms as a threat eroding users' privacy. As a direct consequence, traffic coming from Tor would be considered less suspicious by service providers.
Theoretically Grounded Conversational Interfaces to Digital Information

This paper introduces a general methodology for the development and study of conversational systems. Closer coupling of linguistic and psycholinguistic theories about dialogue with the development of dialogue systems allows each to inform the other more fully. Three activities support our goals. We develop theories through the empirical investigation of dialogue in conversational settings. We use this to inform our theoretical research on dialogue and our design of advanced conversational interface systems. We then experiment with these systems to compare their behavior to human-to-human interactions. This paper discusses a study and analysis of conversations about library information, the development of a system based on this analysis, lessons learned, and future goals.
Detecting Genuine Communities from Large-Scale Social Networks: A Pattern-Based Method

Community detection is a long-standing yet very difficult task in social network analysis. It becomes more challenging as many online social networking sites are evolving into super-large scales. Numerous methods have been proposed for community detection from massive networks, but how to reconcile the partitioning efficiency and the community quality remains an open problem. In this paper, we attempt to address this challenge by introducing a COSine-pattern-based COMmunity extractionframework:COSCOM.TheCOSCOMadoptsanextractingviewofcommunitydetection. It first extracts the so-called asymptotically equivalent structures (AESs) from networks, from which the nodes are further partitioned into crisp communities using any of the existing methods. Specifically,weprovethatanAESisaverytightgroupofnodes,andisactuallyacosinepatterndefined by the extended cosine similarity.A novel cosine-pattern mining algorithm based on the ordered antimonotone of cosine similarity is thus proposed for the efficient extraction of AESs. Experiments on various real-world social networks demonstrate the advantage of the extracting view of community detection. In particular, COSCOM shows merits in detecting genuine communities by either internal or external validity.
Stochastic Differential Equation Modeling and Analysis of TCP-Windowsize Behavior

In this paper we present new modeling and analysis technique for characterizing the steady state performance of a TCP flow. We invert the loss process in our model, by treating loss events arriving at the source as a Poisson stream rather than packets going out on the network with some loss probability p. This enables us to model the window size behavior as a Poisson Counter driven Stochastic Differential Equation and perform analysis. We use the data collected in [1] to validate our modeling and analysis technique. Results indicate that our model is able to capture the behavior of TCP throughput quite accurately. Our technique enables simple fluid analysis of TCP and other TCP-like congestion control mechanism.
Working the Phones: Control and Resistance in Call Centres

to purchase vast tracts of land. Finally, he traces the uneven adoption of agricultural biotechnology, which is common in maize but rare in wheat and rice, to the relatively uncompetitive character of global feed grain markets. As noted above, Grains does not aspire to report on new research but to provide a concise introduction to the global political economy of several keystone agricultural commodities. It accomplishes this task and provides a useful framework for understanding the challenging issues of food security and sovereignty in the contemporary world. Given the complexity of the topic and the brevity of the book, it is inevitable that some readers will finish the book wishing for a deeper exploration in certain areas. For example, Winders might have extended his discussion through a more extensive consideration of how political and market forces have shaped the biological characteristics of commodity wheat, rice, and maize. The book’s discussion of genetic engineering moves in this direction, but Winders does not consider the lengthy history of seed breeding and selection that also reduced the diversity of these grain crops to just a few varieties. Close readers will also note that the book suffers from problems of copyediting, although the responsibility here lies with the press rather than the author. In all, Grains will be a helpful text for use in courses about the political economy of agriculture and may provide a useful introduction for researchers who are beginning to work in this area.
Dynamic ultrametricity in finite-dimensional spin glasses

We show results of simulations of a weakly driven four-dimensional Edwards-Anderson (EA) spin glass, which present clear signatures of dynamical ultrametricity at low temperatures. The presence of a hierarchical organization of time scales is evident from the appearance of a triangular relation between correlations at three characterisitc long times in the asymptotic limit of small drive, and also in the scaling form of stationary correlations in this regime. Recent results in the three-dimensional case have been inconclusive showing the importance of dimensionality in tackling this delicate problem.
Cell-mediated immunity to Friend virus-induced leukemia.

By employing the 125IUdR release cytotoxicity assay, we have been able to measure the primary and secondary cell-mediated cytotoxic response of C57BL/6 mice to FBL-3 cells, a syngeneic Friend virus-induced leukemia. It was found that the secondary cell-mediated cytotoxic response occurred more rapidly after challenge (within 3 days) than the primary response, and the levels of reactivity were considerably higher. As in the primary response, the secondary cytotoxic reactivity of spleen cells was T cell dependent, being eliminated by pretreatment with anti-θ antibody plus complement. However, the secondary reactivity of pertioneal exudate (PE) cells was not entirely T-cell dependent. The specificity of the secondary cytotoxic response was analyzed by primary or secondary immunization with various tumor cells and by testing of cytotoxic lymphocytes against a variety of target cells. When spleen cells were used for testing, only tumor cells induced by Friend, Moloney, or Rauscher (FMR) leukemia viruses could produce secondary cell-mediated cytotoxic responses against FBL-3 cells. This correlated well with the specificity observed in the in vivo tumor transplantation protection studies. Similarly, spleen cells immune to FBL-3 had appreciable cytotoxicity against tumor cells induced by FMR viruses. The FBL-3 immune mice also gave significant protection against the challenge of FMR leukemias. When PE cells were used for testing, they gave a broader spectrum of reactivity. These cells usually gave higher levels of cytotoxicity against tumor cells induced by FMR viruses, but also gave less, but appreciable, cytotoxicity against non-FMR tumors. The latter reactivity might be related to the antigens induced by the murine endogenous type C viruses.
Étude préliminaire d'une méthode de prise de décision adaptative pour la commande vocale dans un habitat intelligent

Dans les habitats intelligents, les predictions et decisions qui sont souvent faites a priori necessitent de la part de l'utilisateur une configuration qui peut etre complexe et fastidieuse. Ces habitats ont pourtant des capacites de perception requises pour analyser le comportement de l'utilisateur et modifier ses decisions automatiquement. Nous presentons une etude preliminaire qui teste un systeme de decision a partir d'une commande vocale et de son contexte modifie par renforcement. Le systeme experimente sur un corpus realiste montre le potentiel d'une telle adaptation.
Transplantation of syngeneic Schwann cells to the retina of the rhodopsin knockout (rho(-/-)) mouse.

PURPOSE To determine whether subretinal Schwann cell transplantation can prolong the survival of photoreceptors in the rhodopsin knockout (rho(-/-)) mouse. METHODS Schwann cells were prepared from postnatal day (PN) 5 to 7 mouse pups and grafted subretinally into the eyes of PN35 rho(-/-) mice. RT-PCR was performed on similarly prepared cells to determine growth factor production in vitro. Eyes were retrieved at PN70 for anatomic and statistical analysis. Control animals received grafts of fibroblasts or sham surgery. RESULTS RT-PCR demonstrated the presence of message for ciliary neurotrophic factor (CNTF), brain-derived neurotrophic factor (BDNF), and glia-derived neurotrophic factor (GDNF) in the cultured Schwann cells. Schwann cell grafts produced a statistically significant rescue of photoreceptors in a restricted area of retina at PN70, but the effect was lost by PN140. Preserved inner segments could be identified, but outer segments were never present. Sham surgery also resulted in photoreceptor rescue but at a reduced level. Fibroblast grafts appeared to produce little or no rescue effect. Grafts of Schwann cells or fibroblasts and sham surgery induced a reactive Müller glial response. CONCLUSIONS Schwann cells can prolong photoreceptor survival in the rhodopsin knockout mouse until at least PN70.
Neural networks and pattern recognition in human-computer interaction

This paper reports on the activities of the workshop held on Sunday 28th April at the CHI'91 conference. Participants were there to discuss different ideas, methods and approaches to using pattern recognition in human-computer interaction.The workshop aimed to bring together researchers using novel methodologies, such as neural networks, in HCI applications, as well as practitioners using alternative or more traditional methods to perform pattern recognition tasks in HCI. The intention was to explore the scope and limitations of each type of approach and its requirements, for example in terms of representation and resources. The workshop considered the relationships between the different approaches and the possibility of developing hybrid methodologies to resolve HCI problems.Researchers working with both traditional and novel pattern recognition methods that have applications to human-computer interaction, and those with strong views either way, submitted position statements outlining their interest and viewpoints. Their research results are summarised in this report; in addition, the discussions on methods, on how the work reported interrelates, and on future areas of interest are presented. Major results from the use of neural network systems and other pattern recognition systems in the interface are presented, with application areas ranging from the interpretation of gestural input to the automatic determination of user task. Fuller details of the research can be found in a book based on the proceedings[2].
Finding recurrent sources in sequences

Many genomic sequences and, more generally, (multivariate) time series display tremendous variability. However, often it is reasonable to assume that the sequence is actually generated by or assembled from a small number of sources, each of which might contribute several segments to the sequence. That is, there are h hidden sources such that the sequence can be written as a concatenation of k > h pieces, each of which stems from one of the h sources. We define this (k,h)-segmentation problem and show that it is NP-hard in the general case. We give approximation algorithms achieving approximation ratios of 3 for the L1 error measure and √5 for the L2 error measure, and generalize the results to higher dimensions. We give empirical results on real (chromosome 22) and artificial data showing that the methods work well in practice.
On-line Routing for Virtual Private Networks

Today, large telecommunications customers are increasingly using virtual private networks to link geographically dispersed sites. A virtual private network is provided by provision-ing a set of permanent (long term) virtual circuits between customer endpoints on a large backbone network. This paper considers the problem of routing a set of permanent virtual circuit requests over a backbone network. Several factors make this routing problem complicated. Routing decisions must be made on-line without any knowledge of future request sets. Furthermore, frequent rerouting to correct ineeciencies that can result from the on-line routing decisions are not possible since rerouting creates a service disruption for the customer. Finally, the forward and reverse bandwidth of a virtual circuit must be routed over the same single path. Using an extensive set of simulations, this paper evaluates several diierent strategies for on-line permanent virtual circuit routing. We nd that a strategy based on recent results in competitive analysis and ideas from combinatorial optimization consistently provides the best performance. The problem of admission control is closely related to the problem of routing. This paper also provides a theoretical lower bound which suggests that non-greedy admission control is a fundamental component of an eecient on-line permanent virtual circuit routing algorithm.
A Novel Efficient and Accurate Detection Model to Detect Emerging Attacks in Network

Over past few decades, the rapid popularity of computer networks and their related applications have increases the information security issues in rocket speed which pose challenges to develop an efficient network intrusion detection system that can detect a high rate of attacks with the acceptable reliability. In current scenario no one detached security system is capable to detect all types of attack with accuracy, day by day naive attackers launch powerful attacks which can bring down an entire network. However, in the last few decades a lot of approaches have been intensively proposed to defend the system, but complete network security still is a critical issue due to the wideness of the network system, the field lacks an integrated approach with high detection rate for minority attacks namely R2L and U2R. In this paper we have proposed a new advanced network security approach which can efficiently detect a wide variety of attacks with higher accuracy.
International Union of Pure and Applied Chemistry Physical Chemistry Division Commission on Colloid and Surface Chemistry including Catalysis* Reporting Physisorption Data for Gas/solid Systems with Special Reference to the Determination of Surface Area and Porosity Reporting Physisorption Data for 

Republication of this report is permitted without the need for formal JUPAC permission on condition that an acknowledgement, with full reference together with JUPAC copyright symbol (© 1985 JUPAC), is printed. Publication of a translation into another language is subject to the additional condition of prior approval from the relevant JUPAC National Adhering Organization. The purpose of this Manual is twofold: first to draw attention to the problems and ambiguities which have arisen in connection with the reporting of gas adsorption (physisorption) data; second to formulate proposals for the standardisation of procedures and terminology which will lead to a generally accepted code of practice. The proposals are based on, and are in general accordance with, the Manual of Symbols The first stage in the interpretation of a physisorption isotherm is to identify the isotherm type and hence the nature of the adsorption process(es): monolayer-multilayer adsorption, capillary condensation or micropore filling. The BET method is unlikely to yield a value of the actual surface area if the isotherm is either Type I or Type III; but both Type II and Type IV isotherms are, in general, amenable to the BET analysis, provided that the value of C is neither too low nor too high and that the BET plot is linear in the region of the isotherm containing Point B. The computation of mesopore size distribution is valid only if the isotherm is of Type IV, but in view of the complexity of most pore systems little is to be gained by the application of an elaborate method of computation. If a Type I isotherm exhibits a nearly constant adsorption at high relative pressure, the micropore volume is given by the amount adsorbed at the plateau. At present there is no reliable procedure available for the computation of the micropore size distribution from a single isotherm. A check list is recommended to assist authors in the measurement of adsorption isotherms and the presentation of the data in the primary literature.
Generation Grid Grid Distribution Transmission Distribution Markets Telecom Oil and Gas Smart Distribution Alstom Grid Smart Distribution Solutions for Smart Utilities

As electric distribution utilities face intense pressure to find new and innovative ways to reduce their costs, Smart Distribution offers promising solutions for enhancing grid performance and increasing customer satisfaction, while creating a more sustainable environment. As the Electric Distribution industry enters the Smart Grid era, it is deploying a variety of new technologies (including distributed energy resources) and communications infrastructure to enhance the performance of the distribution grid, improve customer satisfaction and reduce the carbon footprint. On the one hand, these new Smart Grid investments look as though they will pay off as customers begin to enthusiastically adopt photovoltaic solar systems, electric vehicles, demand response, etc. On the other hand, the challenging economic climate finds electric distribution utilities still fighting an uphill battle with state regulatory entities in order to justify the expense of their investments. These opposite forces will pose unique opportunities and challenges to electric distribution utilities. Smart Grid solutions call for enhanced operational methodologies as well as better economic models to reliably and profitably manage future distribution grids. To begin engaging in solutions that proactively meet these new challenges, the Electric Distribution industry has introduced the term Smart Distribution.
Second class particles in the rarefaction fan

On considere le processus d'exclusion simple totalement asymetrique unidimensionnel avec derive a droite. Le processus commence avec la configuration «tout un» a gauche de l'origine et «tout zero» a droite. On prouve qu'une particule de deuxieme classe placee a l'origine a l'instant zero choisit une des caracteristiques avec une loi uniforme et ensuite suit cette caracteristique a vitesse constante. Le resultat s'etend au cas d'une mesure initiale produit avec densites ρ a gauche et λ a droite de l'origine, satisfaisant p > λ. Finalement, on prouve que deux particules de deuxieme classe dans le front de rarefaction ont une probabilite positive de ne pas se rencontrer
Discriminative Training for Automatic Speech Recognition: Modeling, Criteria, Optimization, Implementation, and Performance

Discriminative training techniques have been shown to consistently outperform the maximum likelihood (ML) paradigm for acoustic model training in automatic speech recognition (ASR). Consequently, today's discriminative training methods are fundamental components of state-of-the-art systems and are a major line of research in speech recognition. This article gives a comprehensive overview of discriminative training methods for acoustic model training in the context of ASR. The article covers all related aspects of discriminative training for speech recognition, i.e., specific training criteria and their relation, statistical modeling, different parameter optimization approaches, efficient implementation of discriminative training, and a performance overview.