Miracle-dz/UniFAR-FTUs huggingface dataset:
Under Review as a Conference Paper at Iclr 2016 Predicting Distributions with Linearizing Belief Networks

Conditional belief networks introduce stochastic binary variables in neural networks. Contrary to a classical neural network, a belief network can predict more than the expected value of the output Y given the inputX . It can predict a distribution of outputs Y which is useful when an input can admit multiple outputs whose average is not necessarily a valid answer. Such networks are particularly relevant to inverse problem such as image prediction for denoising, or text to speech. However, traditional sigmoid belief networks are hard to train and are not suited to continuous problems. This work introduces a new family of networks called linearizing belief nets or LBNs. A LBN decomposes into a deep linear network where each linear unit can be turned on or off by non-deterministic binary latent units. It is a universal approximator of real-valued conditional distributions and can be trained using gradient descent. Moreover, the linear pathways efficiently propagate continuous information and they act as multiplicative skip-connections that help optimization by removing gradient diffusion. This yields a model which trains efficiently and improves the state-of-the-art on image denoising and facial expression generation with the Toronto faces dataset.
CVS: a compiler for the analysis of cryptographic protocols

The Security Process Algebra (SPA) is a CCS-like specification language where actions belong to two different levels of confidentiality. It has been used to define several non-interference-like security properties whose verification has been automatized by means of the tool CoSeC. In recent years, a method for analyzing security protocols using SPA and CoSeC has been developed. Even if it has been useful in analyzing small security protocols, this method has shown to be error-prone as it requires the description by hand of the protocol and of the environment in which it will execute. This problem has been solved by defining a protocol specification language more abstract than SPA, called VSP and a compiler CVS that generates in an automatic way the SPA specification for a given protocol described in VSP. The VSP/CVS technology is very powerful and its usefulness is shown with the case-study of the Woo-Lam one-way authentication protocol, for which an attack undocumented in the literature is found.
Subject Collections

strategy? their hosts: signal of climate change or pre-existing adaptive Phenological asynchrony between herbivorous insects and References (427 articles) evolution (307 articles) ecology Articles on similar topics can be found in the following collections Email alerting service here right-hand corner of the article or click Receive free email alerts when new articles cite this article-sign up in the box at the top Phenological asynchrony between herbivorous insects and their hosts: signal of climate change or pre-existing adaptive strategy? Climate change alters phenological relations between interacting species. We might expect the historical baseline, or starting-point, for such effects to be precise synchrony between the season at which a consumer most requires food and the time when its resources are most available. We synthesize evidence that synchrony was not the historical condition in two insect – plant interactions involving Edith's checkerspot butterfly (Euphydryas editha), the winter moth (Operophtera brumata) and their host plants. Initial observations of phenological mismatch in both systems were made prior to the onset of anthropogenically driven climate change. Neither species can detect the phenology of its host plants with precision. In both species, evolution of life history has involved compromise between maximizing fecundity and minimizing mortality, with the outcome being superficially maladaptive strategies in which many, or even most, individuals die of starvation through poor syn-chrony with their host plants. Where phenological asynchrony or mismatch with resources forms the starting point for effects of anthropogenic global warming, consumers are particularly vulnerable to impacts that exacerbate the mismatch. This vulnerability likely contributed to extinction of a well-studied metapopulation of Edith's checkerspot, and to the skewed geographical pattern of population extinctions underlying a northward and upward range shift in this species.
Offline Signature Verification for Authentication

verification has become a recent trend to prevent unauthorized accesses to all kinds of e-data. Signature is strongly accepted in legally and socially as identification and authentication of a person's identity. But, it is very difficult to verify the signature physically. So, it is needed to design a system that verifies the signature of a human automatically. A set of actual signatures is collected from individuals whose signatures have to be authenticated by the system. The topological and texture features are extracted from the actual signature set. The system is trained by using these features. The mean feature values of all the actual signature features are calculated. This mean features acts as the model for verification against a test signature. Euclidian distance between template signature features and claimed signature features serves as a measure of similarity between the two. If this distance is greater than a predefined threshold, then the test signature is detected as fake. The system provides the result to classify actual and forgery signature with accuracy up to 100%.
High Impact Academic Paper Prediction Using Temporal and Topological Features

Predicting promising academic papers is useful for a variety of parties, including researchers, universities, scientific councils, and policymakers. Researchers may benefit from such data to narrow down their reading list and focus on what will be important, and policymakers may use predictions to infer rising fields for a more strategic distribution of resources. This paper proposes a novel technique to predict a paper's future impact (i.e., number of citations) by using temporal and topological features derived from citation networks. We use a behavioral modeling approach in which the temporal change in the number of citations a paper gets is clustered, and new papers are evaluated accordingly. Then, within each cluster, we model the impact prediction as a regression problem where the objective is to predict the number of citations that a paper will get in the near or far future, given the early citation performance of the paper. The results of empirical evaluations on data from several well-known citation databases show that the proposed framework performs significantly better than the state of the art approaches.
Research on Wireless Sensor Network and Carrying Network Integration Based on Gateway

In this paper, we analyze the protocol architecture of Wireless Sensor Networks (WSNs) and carrying networks, and propose a connection scheme based on gateway, which is suitable to the integration of these two networks. According to the characteristics of these gateways, we put forward the concept of end-to-end connection, give the address mapping scheme to the gateway and design a simple gateway node. To realize higher connection reliability, we advance a method of backup gateway and multi-gateways selections. This work can greatly facilitate the research for connecting WSN with the carrying network, IoT (Internet of Things), which also makes contribution to the influence of this connection.
RF Capacitance Extraction Utilizing a Series Resistance Deembedding Scheme for Ultraleaky MOS Devices

An accurate extraction method for series resistance and capacitance based on RF S-parameter measurement in ultraleaky MOS devices is presented in this paper. The method is proven by using a three-element equivalent circuit model for a capacitor and a well-known microwave theory. The proposed method improves the measurement accuracy and significantly reduces the frequency-dependence of capacitance. This method is demonstrated for a 1.5 nm SiO2 dielectric NMOSFET.
Using patient data similarities to predict radiation pneumonitis via a self-organizing map

This work investigates the use of the self-organizing map (SOM) technique for predicting lung radiation pneumonitis (RP) risk. SOM is an effective method for projecting and visualizing high-dimensional data in a low-dimensional space (map). By projecting patients with similar data (dose and non-dose factors) onto the same region of the map, commonalities in their outcomes can be visualized and categorized. Once built, the SOM may be used to predict pneumonitis risk by identifying the region of the map that is most similar to a patient's characteristics. Two SOM models were developed from a database of 219 lung cancer patients treated with radiation therapy (34 clinically diagnosed with Grade 2+ pneumonitis). The models were: SOMall built from all dose and non-dose factors and, for comparison, SOMdose built from dose factors alone. Both models were tested using ten-fold cross validation and Receiver Operating Characteristics (ROC) analysis. Models SOMall and SOMdose yielded ten-fold cross-validated ROC areas of 0.73 (sensitivity/specificity = 71%/68%) and 0.67 (sensitivity/specificity = 63%/66%), respectively. The significant difference between the cross-validated ROC areas of these two models (p < 0.05) implies that non-dose features add important information toward predicting RP risk. Among the input features selected by model SOMall, the two with highest impact for increasing RP risk were: (a) higher mean lung dose and (b) chemotherapy prior to radiation therapy. The SOM model developed here may not be extrapolated to treatment techniques outside that used in our database, such as several-field lung intensity modulated radiation therapy or gated radiation therapy.
Chemorheological studies on a thermoset PU/clay nanocomposite system

Chemorheology of neat polyurethane (PU) system, composed of a diisocyanate and a polyol, and a PU/clay nanocomposite system with an organoclay 5 phr was investigated. Differential scanning calorimetry (DSC) and Fourier transform infrared spectroscopy (FTIR) were used to study the polymerization behavior of both systems. The PU/clay nanocomposite system showed a faster polymerization rate than neat PU system. The rheological property change during isothermal and dynamic polymerization of both systems was measured using a rheometer to analyze chemorheology of them. A viscosity function that can describe viscosity change of a thermoset resin system during polymerization was adopted to analyze the viscosity data obtained from the rheometer. The PU/clay nanocomposite system had shorter gelation time than neat PU system. Structural analyses of the PU/clay nanocomposite were performed by X-ray diffractometer (XRD) and transmission electronic microscope (TEM).
Collaborative Exploration in Grid Domains - Constructive Conjecture of a Polynomial Time Complexity

This work discusses the problem of exploration of an unknown environment using a collaborative group of simple agents. While this problem was known to be of a non-polynomial time complexity, it was speculated in the past that in grid domains the completion time of this problem is much lower (although analytic proofs were not available hitherto). In this work we present a preliminary result concerning a constructive analytic constraint for guaranteeing that the time complexity of this problem in grid domains is indeed polynomial.
A medication adherence monitoring system for pill bottles based on a wearable inertial sensor

This paper presents a medication adherence monitoring system for pill bottles based on a wearable inertial sensor. Signal templates corresponding to the two actions of twist-cap and hand-to-mouth are created using a camera-assisted training phase. The act of pill intake is then identified by performing a moving window dynamic time warping in real-time between signal templates and the signals acquired by the wearable inertial sensor. The outcomes of the experimentations carried out indicate that the developed medical adherence monitoring system identifies the act of pill intake with a high degree of accuracy.
Shadow Segmentation and Compensation in High Resolution Satellite Images

In high spatial resolution satellite images, shadows are usually cast by elevated objects such as buildings, bridges, and towers, especially in urban region. Shadows may cause loss of feature information, false color tone and shape distortion of objects, which seriously affect the quality of images. Hence, it is important to segment shadow regions and restore their information for image interpretation. This paper presents an effective and robust approach for shadow segmentation and compensation in color satellite images with high spatial resolution. The approach uses normalized saturation-value difference index (NSVDI) in hue-saturation-value (HSV) color space to detect shadows and exploits histogram matching to recover the information under shadows. Experimental results by applying the proposed approach in the IKONOS color images of urban area demonstrate the effectiveness and feasibility of the proposed approach.
Nutritional Status of Boarding and Non-Boarding Children in Selected Schools in the Accra Metropolis

Malnutrition is highly prevalent in developing countries. Children are at high nutritional risk of being malnourished because of their physiological demands at this age. However, the nutritional status of school age children is poorly documented in Ghana. The aim of this study was to assess and compare the nutritional status of boarding and non-boarding pupils aged 8 to 10 years in the Accra Metropolis, Ghana. A cross-sectional study was conducted among 124 children in three private schools which have boarding facilities (optional) in the Accra Metropolis, Ghana. Dietary intakes of children between the ages of 8 and 10 years were assessed using a two-day 24 hour recall. Weight and height measurements were taken. WHO Anthroplus software was used to determine WAZ, HAZ and BAZ. Ghanaian food composition tables were used to calculate the nutritional components of foods eaten by subjects. T-tests were used to analyse differences between variables. The prevalence of stunting, underweight, overweight and obesity among the children were 0.8%, 0.8%, 12.1% and 11.3% respectively. The total energy and nutrient intake of calcium among children (both boarders and non-boarders) was inadequate. There was no significant difference in the nutritional status and mean nutrient intake between boarding and non-boarding children. Nutritional status between boarders and non boarders were found to be similar. Key words: School children, boarders, non-boarders, Ghanaian, nutritional status
Fabrication of mechanical structures using macroporous silicon

In this paper, free standing beams and trench structures are successfully fabricated in both n and p-type silicon using macro-porous silicon. Electrochemical etching in hydrofluoric acid has been demonstrated to make 3-D structures in n-type silicon, in a single etch step. A set-up for n-type silicon involves a light source to generate electronic holes in silicon substrate, and the width of the pores can be controlled by the light intensity. However, the use of light makes the set-up more complicated. Using HF, p-type silicon was found only to form random micro-porous structures, and thus not the trenches achieved in n-type silicon. Recently, in order to form a macro pore in p-type silicon, a new etchant has been proposed in which the macro pores. This technique has been used to obtain macro-porous structures in p-type material. This technique has been extended to make free standing structures, as done with n-type material. This work has shown that free standing structures can be fabricated using a single etch step in both n and p-type material. P-type has the advantage that no light source is required and also thermal oxide can be used as a masking layer. However, experiments performed to date have shown that the n-type material process is easier to control and is more flexible, in terms of the structures which can be fabricated. Work is continuing to further improve these processes and this paper will examine the processes for n- and p-type material giving the relative merits.
Non-Linear Dynamic Viscoelasticity of Xanthan Gum Solutions

Xanthan gum is a high molecular-weight polysaccharide, soluble in cold water, and mainly used in the food industry as a thickener and stabiliser. The rheological properties of xanthan gum are therefore of key interest to improve their thickening and stabilising properties. Recently, large amplitude oscillatory shear (LAOS) measurements have been carried out in order to gain a deeper insight into microstructural changes in complex fluids such as xanthan gum solutions. This work has studied the influence of salt concentration on the rheological properties of xanthan gum solutions, comparing the results obtained by means of traditional small amplitude oscillatory shear (SAOS) and LAOS measurements.
Backward mimicry and forward influence in prosodic contour choice in standard American English

Entrainment is the tendency of speakers engaged in conversation to align different aspects of their communicative behavior. In this study we explore in more detail a measure of prosodic entrainment defined in previous work, which uses a discrete parametrization of intonational contours defined by the ToBI conventions for prosodic description. We divide this measure into two asymmetric variants: backward mimicry (in which a speaker uses a contour used previously by the interlocutor) and forward influence (in which a speaker’s contour appears later in the speech of the interlocutor). This distinction sheds new light on significant correlations with a number of social variables related to the level of engagement of speakers in a corpus of task-oriented dialogues in Standard American English.
Approximate Nearest Line Search in High Dimensions

We consider the Approximate Nearest Line Search (NLS) problem. Given a set L of N lines in the high dimensional Euclidean space Rd, the goal is to build a data structure that, given a query point q ∈ Rd, reports a line l ∈ L such that its distance to the query is within (1 + e) factor of the distance of the closest line to the query point q. The problem is a natural generalization of the well-studied Approximate Nearest Neighbor problem for point sets (ANN), and is a natural first step towards understanding how to build efficient nearest-neighbor data structures for objects that are more complex than points. Our main result is a data structure that, for any fixed e > 0, reports the approximate nearest line in time (d + log N + 1/e)O(1) using O(N + d)O(1/e2) space. This is the first high-dimensional data structure for this problem with poly-logarithmic query time and polynomial space. In contrast, the best previous data structure for this problem, due to Magen [16], required quasi-polynomial space. Up to polynomials, the bounds achieved by our data structure match the performance of the best algorithm for the approximate nearest neighbor problem for point sets.
Central Bank Communication and Policy Effectiveness

A notable change in central banking over the past 15 years has been a world-wide movement toward increased communication by central banks about their policy decisions, the targets that they seek to achieve through those decisions, and the central bank's view of the economy's likely future evolution. This paper considers the role of such communication in the successful conduct of monetary policy, with a particular emphasis on an issue that remains controversial: to what extent is it desirable for central banks to comment on the likely path of short-term interest rates? After reviewing general arguments for and against central-bank transparency, the paper considers two specific contexts in which central banks have been forced to consider how much they are willing to say about the future path of interest rates. The first is the experiment with policy signaling by the FOMC in the U.S., using the statement released following each Committee meeting, since August 2003. The second is the need to make some assumption about future policy when producing the projections (for future inflation and other variables) that are central to inflation-forecast targeting procedures, of the kind used by the Bank of England, the Swedish Riksbank, the Reserve Bank of New Zealand, and others. In both cases, it is argued that increased willingness to share the central bank's own assumptions about future policy with the public has increased the predictability of policy, in ways that are likely to have improved central bank's ability to achieve their stabilization objectives.
A new approximation algorithm for the planar augmentation problem

The planar augmentation problem is the problem of adding a minimum number of edges to a given planar graph such that the resulting graph is biconnected and still planar. This problem is NP-hard [15]. We present a new $approximation algorithm for the planar augmentation problem. The best approximation factor achieved so far is 2 [15]. Furthermore, we ran extensive computational experiments on ‘real world’ graphs. The outcome is surprising: The solution of our new algorithm is very often optimum and in almost all cases the solution found by our algorithm contains at most one more edge than in an optimum solution.
Comparison of measured and calculated skin doses in CT-guided interventional procedures.

OBJECTIVE The objective of our study was to compare theoretic estimations of the dose to the patient's skin during CT-guided interventional procedures with measurements performed using radiation therapy verification films. MATERIALS AND METHODS In each of the 12 interventions studied, a Kodak EDR2 film was positioned under the patient's anatomic area of concern. After processing, each film was scanned with a medical-grade scanner to produce a digital image from which the gray-scale profiles were obtained using the appropriate software. From these data and respective data from a series of calibration films, the entrance skin dose (ESD) profiles were derived. These ESD profiles were compared with the ESD profiles produced using a theoretic model and its revised version, which utilizes the DICOM data of each slice (i.e., tube potential, tube loading, slice thickness, slice location, pitch, and table height) and air-kerma output measurements from the CT tube. RESULTS In general, the ESD profiles calculated using the revised theoretic method were in better agreement with the profiles derived from the verification films than the ESD profiles derived from the original theoretic method. The deviations from the peak skin doses (PSDs) derived from the digital film images were within -3% and 27% of the PSDs derived from the verification films. The respective deviations of the ESD profiles calculated with the original theoretic method were quite larger. CONCLUSION The theoretic model provides a useful tool for estimating skin doses during CT-guided interventions with a reasonable level of accuracy. With further refinement and a little automation this method could be implemented for daily use.