Miracle-dz/UniFAR-FTUs huggingface dataset:
" Small Sample Size " : a Methodological Problem in Bayes Plug-in Classifier for Image Recognition

New technologies in the form of improved instrumentation have made it possible to take detailed measurements over recognition patterns. This increase in the number of features or parameters for each pattern of interest not necessarily generates better classification performance. In fact, in problems where the number of training samples is less than the number of parameters, i.e. " small sample size " problems, not all parameters can be estimated and traditional classifiers often used to analyse lower dimensional data deteriorate. The Bayes plug-in classifier has been successfully applied to discriminate high dimensional data. This classifier is based on similarity measures that involve the inverse of the sample group covariance matrices. However, these matrices are singular in " small sample size " problems. Thus, several other methods of covariance estimation have been proposed where the sample group co-variance estimate is replaced by covariance matrices of various forms. In this report, some of these approaches are reviewed and a new covariance estimator is proposed. The new estimator does not require an optimisation procedure, but an eigenvector-eigenvalue ordering process to select information from the projected sample group covariance matrices whenever possible and the pooled covariance otherwise. The effectiveness of the method is shown by some experimental results.
Linking communities of practice online

Les Bibliothhquaires et professionels de l'information forment une communitie mondiale d'utilisateurs. Grace aux blogs, un type de logiciel social, les bibliothhquaires peuvent ichanger leurs idies aux travers des cultures grace ` l'Internet. Cette itude enqujte sur l'utilisation des `biblio-blogs' en tant qu'outils de communication pour les professionels de l'Information. Nous montrons que bien que les bibliothhquaires Frangais lisent, se rifhrent et commentent sur les Blogs en Anglais, leurs confrjres anglophones ne participent pas aux Blogs Frangais. Nos risultats montrent aussi que la biblioblogosphhre est plus compacte que son iquivalent anglophone.
ThumbCam: Returning to single touch interactions to explore 3D virtual environments

Three-dimensional virtual environments are present in many different applications, being used even in small handheld devices. To navigate in these environments using such devices, most of current solutions rely on multi-touch interactions. However, previous works have already stated that multi-touch gestures on smartphones are not always feasible. In this work we present ThumbCam, a novel single-touch technique for camera manipulation on 3D virtual environments. With our solution, the user is able to move and look around and circle points of interest, while interacting using only his thumb. We compare ThumbCam with other state-of-the-art techniques, showing that it can offer more operations with a single touch. A qualitative user evaluation revealed that users found our solution appealing.
Ribosome profiling reveals resemblance between long non-coding RNAs and 5′ leaders of coding RNAs

Large-scale genomics and computational approaches have identified thousands of putative long non-coding RNAs (lncRNAs). It has been controversial, however, as to what fraction of these RNAs is truly non-coding. Here, we combine ribosome profiling with a machine-learning approach to validate lncRNAs during zebrafish development in a high throughput manner. We find that dozens of proposed lncRNAs are protein-coding contaminants and that many lncRNAs have ribosome profiles that resemble the 5′ leaders of coding RNAs. Analysis of ribosome profiling data from embryonic stem cells reveals similar properties for mammalian lncRNAs. These results clarify the annotation of developmental lncRNAs and suggest a potential role for translation in lncRNA regulation. In addition, our computational pipeline and ribosome profiling data provide a powerful resource for the identification of translated open reading frames during zebrafish development.
Does the Current Account Matter?

The purpose of this paper is to investigate in detail the behavior of the current account in emerging economies, and in particular its role if any in financial crises. Models of current account behavior are reviewed, and a dynamic model of current account sustainability is developed. The empirical analysis is based on a massive data set that covers over 120 countries during more than 25 years. Important controversies related to the current account including the extent to which current account deficits help predict currency crises are also analyzed. Throughout the paper I am interested in analyzing whether there is evidence supporting the idea that there are costs involved in running 'very large' deficits. Moreover, I investigate the nature of these potential costs, including whether they are particularly high in the presence of other type of imbalances.
Advances in silicon-on-insulator optoelectronics

Recent developments in silicon based optoelectronics relevant to fiber optical communication are reviewed. Silicon-on-insulator photonic integrated circuits represent a powerful platform that is truly compatible with standard CMOS processing. Progress in epitaxial growth of silicon alloys has created the potential for silicon based devices with tailored optical response in the near infrared. The deep submicrometer CMOS process can produce gigabits-per-second low-noise lightwave electronics. These trends combined with economical incentives will ensure that silicon-based optoelectronics will be a player in future fiber optical networks and systems.
Metasearch and Federation using Query Difficulty Prediction

Fusing the results of a distributed Information Retrieval system has often been viewed as two separate problems: metasearch, where several search engines are retrieving from one document collection, and federation, where one search engine is retrieving from several document collections. In this work we present a unified framework for fusion based on predicting query diculty. We validate our approach using a rigorous, quantitative, experimental procedure, which uses Desktop Search Engines and a standard document collection. We show that the proposed algorithm performs significantly better than previously-proposed algorithms for both metasearch and federation.
Are You Talking to Me? Stakeholder Communication and the Risks and Rewards of Dialogue

This chapter critically examines emerging trends in stakeholder and communications theory in order to examine different modes of communication among stakeholder groups. We consider first the impacts of a complex understanding of stakeholder relations on one-way communication models that offer alternatives of standardizing or tailoring messages. Then, we deal with more interactive forms of communication, focusing specifically on the issue of stakeholder dialogue. We suggest that although stakeholder “dialogue” is a notion that has become popular in consulting and corporate vernaculars, in our view, its conditions and consequences have been little examined and are poorly understood. We contend that the current level of debate leaves unresolved important questions regarding the fundamental meanings of dialogue. Moreover, contrary to accepted wisdom, we argue that more involved and interactive modes of stakeholder dialogue surface important, and as yet, unexamined problems. In particular, we propose the very real possibility for stakeholder dialogue to lead to issues of cacophony, identity fragmentation, and organizational paralysis.
Projections from auditory cortex to the cochlear nucleus in rats: Synapses on granule cell dendrites

Previous work has demonstrated that layer V pyramidal cells of primary auditory cortex project directly to the cochlear nucleus. The postsynaptic targets of these centrifugal projections, however, are not known. For the present study, biotinylated dextran amine, an anterograde tracer, was injected into the auditory cortex of rats, and labeled terminals were examined with light and electron microscopy. Labeled corticobulbar axons and terminals in the cochlear nucleus are found almost exclusively in the granule cell domain, and the terminals appear as boutons (1–2 μm in diameter) or as small mossy fiber endings (2–5 μm in diameter). These cortical endings contain round synaptic vesicles and form asymmetric synapses on hairy dendritic profiles, from which thin (0.1 μm in diameter), nonsynaptic “hairs” protrude deep into the labeled endings. These postsynaptic dendrites, which are typical of granule cells, surround and receive synapses from large, unlabeled mossy fiber endings containing round synaptic vesicles and are also postsynaptic to unlabeled axon terminals containing pleomorphic synaptic vesicles. No labeled fibers were observed synapsing on profiles that did not fit the characteristics of granule cell dendrites. We describe a circuit in the auditory system by which ascending information in the cochlear nucleus can be modified directly by descending cortical influences. © 1996 Wiley‐Liss, Inc.
A SEARCH FOR X-RAY REIONIZATION SIGNATURES FROM CROSS-CORRELATION OF WMAP AND ROSAT RASS DATA

We present an observational search for the possible correlation between cosmic microwave background (CMB) polarization and soft X-ray background (SXRB) based on the ROSAT All-sky Survey (RASS) archive and WMAP five-year observations. This is motivated by the fact that some of the CMB polarization may arise from the scattering of CMB photons due to the free electrons generated by X-ray heating sources in the epoch of reionization. Detection of such a correlation allows one to study the role of X-ray heating in the process of reionization. However, the cross-angular power spectrum of the CMB polarization and SXRB maps constructed from ROSAT RASS and WMAP five-year maps is consistent with no correlation. We attribute this negative detection to both the extremely weak signals and large instrumental noises. While a future search is needed with high-sensitivity instruments for both CMB polarization and soft X-ray photons, our current results can still be used as a useful constraint on the effect of X-ray heating in the epoch of reionization.
A speed-up algorithm for Poisson Propagation

Based on the theory of electrostatic field, a novel semi-supervised learning method named Poisson Propagation has been proposed by Fei Wang. In his formulation, data are regarded as points in the field and the labels of unlabeled data points are propagated from labeled sources, which is like the field responses modeled by Poisson's equation. In this paper, we develop an efficient way for accelerating the PP algorithm, and also provide the theoretical analysis of the optimality of such acceleration approach. Our method is tested on 6 different data sets. The experiment results show the effectiveness of our acceleration algorithm.
A Network Inversion Technique for Estimating Equivalent Dipole Description of Visual Evoked Potential

Abstract: For the activation study of the brain, dipole localization from the scalp potential is one of the most promising techniques to realize a reasonable temporal resolution which cannot be realized in functional MR and PET. The goal of our study is to estimate inversely the electrical brain activity in the form of several dipoles from the scalp potential, using a network inversion technique. As a basic approach, we have inversely estimated several dipoles from the potential distribution on a spherical surface, in the homogeneous sphere model. In the training phase, by expanding the neural network input dimensions being redundant, the network can easily learn the forward mapping. In the inversion phase, the space of the expanded-network-input-vector can be narrowed by introducing a penalty term. Additionally, a consensus term was used to force several dipoles to have a similar orientation. We estimate that this is applicable to the localization of several dipoles that reflect the actual brain activity, especially in the visual evoked potentials.
AN OVERVIEW OF IMAGE SEGMENTATION ALGORITHMS

Image segmentation is a puzzled problem even after four decades of research. Research on image segmentation is currently conducted in three levels. Development of image segmentation methods, evaluation of segmentation algorithms and performance and study of these evaluation methods. Hundreds of techniques have been proposed for segmentation of natural images, noisy images, medical images etc. Currently most of the researchers are evaluating the segmentation algorithms using ground truth evaluation of (Berkeley segmentation database) BSD images. In this paper an overview of various segmentation algorithms is discussed. The discussion is mainly based on the soft computing approaches used for segmentation of images without noise and noisy images and the parameters used for evaluating these algorithms. Some of these techniques used are Markov Random Field (MRF) model, Neural Network, Clustering, Particle Swarm optimization, Fuzzy Logic approach and different combinations of these soft techniques. Keywords-Image Segmentation,BSD images,Soft Computing Techniques.
A comparison of abstract versions of deflation, balancing and additive coarse grid correction preconditioners

In this paper we consider various preconditioners for the conjugate gradient (CG) method to solve large linear systems of equations with symmetric positive definite system matrix. We continue the comparison between abstract versions of the deflation, balancing and additive coarse grid correction preconditioning techniques started in (SIAM J. Numer. Anal. 2004; 42:1631–1647; SIAM J. Sci. Comput. 2006; 27:1742–1759). There the deflation method is compared with the abstract additive coarse grid correction preconditioner and the abstract balancing preconditioner. Here, we close the triangle between these three methods. First of all, we show that a theoretical comparison of the condition numbers of the abstract additive coarse grid correction and the condition number of the system preconditioned by the abstract balancing preconditioner is not possible. We present a counter example, for which the condition number of the abstract additive coarse grid correction preconditioned system is below the condition number of the system preconditioned with the abstract balancing preconditioner. However, if the CG method is preconditioned by the abstract balancing preconditioner and is started with a special starting vector, the asymptotic convergence behavior of the CG method can be described by the so‐called effective condition number with respect to the starting vector. We prove that this effective condition number of the system preconditioned by the abstract balancing preconditioner is less than or equal to the condition number of the system preconditioned by the abstract additive coarse grid correction method. We also provide a short proof of the relationship between the effective condition number and the convergence of CG. Moreover, we compare the A‐norm of the errors of the iterates given by the different preconditioners and establish the orthogonal invariants of all three types of preconditioners. Copyright © 2008 John Wiley & Sons, Ltd.
The MICROMIXER: a highly linear variant of the Gilbert mixer using a bisymmetric Class-AB input stage

This paper outlines the basic theory of a development of the Gilbert mixer. The bipolar junction transistor (BJT) differential pair widely used as the RF input stage is replaced by a bisymmetric Class-AB topology based on translinear principles. It does not have inherent gain compression, affording a greatly extended signal capacity. The linearity of variants of the basic form is excellent, providing two-tone intermodulation intercepts as high as +30 dBm, without the expenditure of high bias currents. It can operate on supplies as low as 2.2 V, with a power consumption of under 5 mW. The input impedance of this mixer is accurately controllable (typically 50 /spl Omega/) and provides a true broadband match. The noise figure depends on design details and is generally not as low as in mixers specifically optimized for noise performance, although acceptable for many receiver applications. Inductively degenerated variants can be tuned to a narrowband match at microwave frequencies and provide full-mixing SSB noise figures as low as 6.5 dB, Practical realizations are in use in applications to 1.9 GHz.
Jumping mini-robot with bio-inspired legs

This paper presents a bio-inspired concept for an autonomous centimeter-scale robot for locomotion on un-even terrains with bionic legs. Our previous work, the jumping robot “GRILLO I” (Fig. 1A), is firstly introduced, as well as its limitations. For improving the performance of this prototype, we made biological observations on jumping insects by means of a high speed camera. It was found that the legs configuration let map muscle-like force into a constant force at feet-ground interface, which represents an optimum design for jumping. That gives us the bionic inspiration to redesign the legs that can reproduce the dynamic characteristics of insect jumping. Based on this idea, a new jumping robot prototype, GRILLO II (Fig. 1B), is then presented, as well as jumping details measured by the high speed camera and accelerometer.
Development of muscle suit for upper limb

We have been developing a "muscle suit" that provides muscular support to the paralyzed or those otherwise unable to move unaided, as well as to manual workers. The muscle suit is a garment without a metal frame and uses a McKibben actuator driven by compressed air. Because actuators are sewn into the garment, no metal frame is needed, making the muscle suit very light and cheap. With the muscle suit, the patient can willfully control his or her movement. The muscle suit is very helpful for both muscular and emotional support. We propose an armor-type muscle suit in order to overcome issues of a prototype system and then show how abduction motion, which we believe, is the most difficult motion for the upper body, is realized.
Re-evaluating the role of BCR/ABL in chronic myelogenous leukemia

Chronic myelogenous leukemia (CML) requires the BCR/ABL tyrosine kinase for disease onset and maintenance. As a result, CML can be successfully treated with tyrosine kinase inhibitors (TKIs) such as imatinib. Most patients are maintained in a disease-suppressed state on daily TKI therapy for several years and in many cases this treatment prevents progression to the blast phase. If the TKI is discontinued, CML redevelops in 95% of patients as a result of persisting leukemia initiating cells (LICs). There are several hypotheses that describe the potential mechanism(s) responsible for LIC persistence in CML, but supporting evidence is limited. Furthermore, of the few patients who discontinue TKI therapy and are “cured” (i.e., in treatment-free remission), most have residual BCR/ABL-expressing cells in their hematopoietic tissues. There are also healthy individuals without a CML diagnosis who express the BCR/ABL mutation in a fraction of their hematopoietic cells. Finally, mice that express BCR/ABL from the Bcr locus as a knockin mutation do not develop CML. These mice have lower BCR/ABL levels than retroviral or transgenic models of BCR/ABL that do develop CML. Understanding why mice with BCR/ABL expressed from the Bcr locus and some people that express BCR/ABL are not afflicted with CML will provide insights into therapies to prevent or cure this disease.
Active Integrity Constraints for Database Consistency Maintenance

This paper introduces active integrity constraints (AICs), an extension of integrity constraints for consistent database maintenance. An active integrity constraint is a special constraint whose body contains a conjunction of literals which must be false and whose head contains a disjunction of update actions representing actions (insertions and deletions of tuples) to be performed if the constraint is not satisfied (that is its body is true). The AICs work in a domino-like manner as the satisfaction of one AIC may trigger the violation and therefore the activation of another one. The paper also introduces founded repairs, which are minimal sets of update actions that make the database consistent, and are specified and ldquosupportedrdquo by active integrity constraints. The paper presents: 1) a formal declarative semantics allowing the computation of founded repairs and 2) a characterization of this semantics obtained by rewriting active integrity constraints into disjunctive logic rules, so that founded repairs can be derived from the answer sets of the derived logic program. Finally, the paper studies the computational complexity of computing founded repairs.
3D-LeukoNoC: A dynamic NoC protection

Weaknesses derived from Through-Silicon-Vias (TSV)-based physical configurations of three-dimension Multiprocessor System-on-Chip (3D-MPSoC) can be exploited by malicious software to attack the system. By means of vertical communication manipulation an attacker is able to modify, spy and even denial the TSV communication. In this paper we propose 3D-LeukoNoC, a flexible and efficient security architecture based on 3D-NoC communication structure which, as the biological immune system, is able to detect attacks, isolate sensitive vertical communication while guaranteeing the correct system behavior. We compare our approach with several 3D-protection proposals, including the simple extension of 2D security countermeasures. We show that our solution outperforms other approaches with respect to attack detection while decreasing cost and performance impact on the system.
Support Vector Regression for Rainfall-Runoff Modeling in Urban Drainage: A Comparison with the EPA’s Storm Water Management Model

Rainfall-runoff models can be classified into three types: physically based models, conceptual models, and empirical models. In this latter class of models, the catchment is considered as a black box, without any reference to the internal processes that control the transformation of rainfall to runoff. In recent years, some models derived from studies on artificial intelligence have found increasing use. Among these, particular attention should be paid to Support Vector Machines (SVMs). This paper shows a comparative study of rainfall-runoff modeling between a SVM-based approach and the EPA’s Storm Water Management Model (SWMM). The SVM is applied in the variant called Support Vector regression (SVR). Two different experimental basins located in the north of Italy have been considered as case studies. Two criteria have been chosen to assess the consistency between the recorded and predicted flow rates: the root-mean square error (RMSE) and the coefficient of determination. The two models showed comparable performance. In particular, both models can properly model the hydrograph shape, the time to peak and the total runoff. The SVR algorithm tends to underestimate the peak discharge, while SWMM tends to overestimate it. SVR shows great potential for applications in the field of urban hydrology, but currently it also has significant limitations regarding the model calibration.