Automatic Schaeffer's gestures recognition system

Schaeffer's sign language consists of a reduced set of gestures designed to help children with autism or cognitive learning disabilities to develop adequate communication skills. Our automatic recognition system for Schaeffer's gesture language uses the information provided by an RGB‐D camera to capture body motion and recognize gestures using dynamic time warping combined with k‐nearest neighbors methods. The learning process is reinforced by the interaction with the proposed system that accelerates learning itself thus helping both children and educators. To demonstrate the validity of the system, a set of qualitative experiments with children were carried out. As a result, a system which is able to recognize a subset of 11 gestures of Schaeffer's sign language online was achieved.     

PrivaKERB: A user privacy framework for Kerberos

Kerberos is one of the most well-respected and widely used authentication protocols in open and insecure networks. It is envisaged that its impact will increase as it comprises a reliable and scalable solution to support authentication and secure service acquisition in the Next Generation Networks (NGN) era. This means however that security and privacy issues related to the protocol itself must be carefully considered. This paper proposes a novel two-level privacy framework, namely PrivaKERB, to address user privacy in Kerberos. Our solution offers two privacy levels to cope with user anonymity and service access untraceability. We detail how these modes operate in preserving user privacy in both single-realm and cross-realm scenarios. By using the extensibility mechanisms already available in Kerberos, PrivaKERB does not change the semantics of messages and enables future implementations to maintain interoperability. We also evaluate our solution in terms of service time and resource utilization. The results show that PrivaKERB is a lightweight solution imposing negligible overhead in both the participating entities and network.     

The iflow address processor

The IAP takes advantage of fast, wide embedded DRAM to perform fast forwarding-table lookups and statistics collection for the next generation of fast, intelligent routers. Its lookup rate of 65.5 million lookups per second allows two lookups per packet at 10 gigabits per second into a 256 K entry table     

Highly discriminative statistical features for email classification

This paper reports on email classification and filtering, more specifically on spam versus ham and phishing versus spam classification, based on content features. We test the validity of several novel statistical feature extraction methods. The methods rely on dimensionality reduction in order to retain the most informative and discriminative features. We successfully test our methods under two schemas. The first one is a classic classification scenario using a 10-fold cross-validation technique for several corpora, including four ground truth standard corpora: Ling-Spam, SpamAssassin, PU1, and a subset of the TREC 2007 spam corpus, and one proprietary corpus. In the second schema, we test the anticipatory properties of our extracted features and classification models with two proprietary datasets, formed by phishing and spam emails sorted by date, and with the public TREC 2007 spam corpus. The contributions of our work are an exhaustive comparison of several feature selection and extraction methods in the frame of email classification on different benchmarking corpora, and the evidence that especially the technique of biased discriminant analysis offers better discriminative features for the classification, gives stable classification results notwithstanding the amount of features chosen, and robustly retains their discriminative value over time and data setups. These findings are especially useful in a commercial setting, where short profile rules are built based on a limited number of features for filtering emails.     

3D characterization of hot metallic shells during industrial forging

During industrial forging of hot metallic shells, it is necessary to regularly measure the dimensions of the parts, especially the inner and outer diameters and the thickness of the walls. A forging sequence lasts 2 h or more during which the diameter of the shell is regularly measured in order to decide when to stop the forging process. For better working conditions, for the safety of the blacksmiths, and for a faster and more accurate measurement, we have developed a novel system based on two commercially available time of flight laser scanners for the measurement of the diameters of hot cylindrical metallic shells during the forging process. The advantages of using laser scanners are that they can be placed very far from the hot shell, more than 15 m, while at the same time giving an accurate point cloud from which three-dimensional views of the shell can be reconstructed and diameter measurements done. Moreover, more accurate measurement is achieved in less time with the laser system than with the conventional method using a large ruler. The system has been successfully used to measure the diameters of hot cylindrical metallic shells.     

Modeling of the relative humidity via functional networks and control of the temperature via classic controls for a bird incubator

The control of the relative humidity and the temperature is important for the birds to be born. It is not easy to control the relative humidity, but it is possible to obtain the measure of the relative humidity as a consequence of the control of the temperature in a bird incubator. In this article, (1) the mathematical model for the control of temperature in the bird incubator is presented, (2) a functional network to approximate the relative humidity behavior in the bird incubator is proposed, (3) a control for the temperature in the bird incubator is proposed, the error of the proportional control applied to the mathematical model of the temperature of the bird incubator is assured to be uniformly stable, (4) the comparison results of four classic control laws for the control of the temperature considering the proposed mathematical model of the temperature and the functional network to approximate the relative humidity behavior in the bird incubator are presented.     

Positive N-periodic descriptor control systems

A small-gain theorem is presented for almost global stability of monotone control systems which are open-loop almost globally stable, when constant inputs are applied. The theorem assumes “negative feedback” interconnections. This typically destroys the monotonicity of the original flow and potentially destabilizes the resulting closed-loop system.     

Super‐resolution of the undersampled and subpixel shifted image sequence by a neural network

Numerous approaches to super‐resolution (SR) of sequentially observed images (image sequence) of low resolution (LR) have been presented in the past two decades. However, neural network methods are almost ignored for solving SR problems. This is because the SR problem traditionally has been regarded as the optimization of an ill‐posed large set of linear equations. A designed neural network based on this has a large number of neurons, thereby requiring a long learning time. Also, the deduced cost function is overly complex. These defects limit applications of a neural network to an SR problem. We think that the underlying meaning of the SR problem should refer to super‐resolving an imaging system by image sequence observation, instead of merely improving the image sequence itself. SR can be regarded as a pattern mapping from LR to SR images. The parameters of the pattern mapping can be learned from the imaging process of the image sequence. This article presents a neural network for SR based on learning from the imaging process of the image sequence. In order to speed up the convergence, we employ vector mapping to train the neural network. A mapping vector is composed of some neighbor subpixels. Such a well‐trained neural network has powerful generalization ability so that it can be used directly to estimate the SR image of the other image sequences without learning again. Our simulations show the effectiveness of the proposed neural network. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 8–15, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20001     

A Diffusion Model Analysis of the Effects of Aging in the Lexical-Decision Task.

The effects of aging on response time (RT) are examined in 2 lexical-decision experiments with young and older subjects (age 60-75). The results show that the older subjects were slower than the young subjects, but more accurate. R. Ratcliff s (1978) diffusion model provided a good account of RTs, their distributions, and response accuracy. The fits show an 80-100-ms slowing of the nondecision components of RT for older subjects relative to young subjects and more conservative decision criterion settings for older subjects than for young subjects. The rates of accumulation of evidence were not significantly different for older compared with young subjects (less than 2% and 5% higher for older subjects relative to young subjects in the 2 experiments). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Neurotrophic control of ovarian development

Substantial evidence now exists indicating that the neurotrophins, a family of growth factors required for the survival, development, and differentiation of various neuronal populations of the nervous system, are also important for the development of nonneuronal tissues. Such a function was first suggested by studies showing the presence of high-affinity neurotrophin receptors in a variety of nonneuronal tissues including those of the cardiovascular, endocrine, immune, and reproductive systems. Within the latter, the gonads appear to be a preferential site of neurotrophin action as suggested by the presence in the mammalian ovary of at least four of the five known neurotrophins and all of the neurotrophin receptors thus far identified. While the various functions that the neurotrophins may have in the ovary are still being elucidated, it is now clear that in addition to recruiting the ovarian innervation, they play a direct role in the regulation of two different maturational periods that are critical for the acquisition of female reproductive function: early follicular development and ovulation. Neurotrophins facilitate the development of newly formed follicles by promoting the initial differentiation and the subsequent growth of primordial follicles. These actions appear to be related to the ability of neurotrophins to sustain the proliferation of both mesenchymal and granulosa cells, and to induce the synthesis of follicle stimulating hormone (FSH) receptors. At the time of the first ovulation, neurotrophins contribute to the ovulatory cascade by increasing prostaglandin E(2) release, reducing gap junction communication, and inducing cell proliferation within the thecal compartment of preovulatory follicles.