Miracle-dz/UniFAR-FTUs huggingface dataset:
4 Wavelets and Face Recognition

Face recognition has recently received significant attention (Zhao et al. 2003 and Jain et al. 2004). It plays an important role in many application areas, such as human-machine interaction, authentication and surveillance. However, the wide-range variations of human face, due to pose, illumination, and expression, result in a highly complex distribution and deteriorate the recognition performance. In addition, the problem of machine recognition of human faces continues to attract researchers from disciplines such as image processing, pattern recognition, neural networks, computer vision, computer graphics, and psychology. A general statement of the problem of machine recognition of faces can be formulated as follows: Given still or video images of a scene, identify or verify one or more persons in the scene using a stored database of faces. In identification problems, the input to the system is an unknown face, and the system reports back the determined identity from a database of known individuals, whereas in verification problems, the system needs to confirm or reject the claimed identity of the input face. The solution to the problem involves segmentation of faces (face detection) from cluttered scenes, feature extraction from the face regions, recognition or verification. Robust and reliable face representation is crucial for the effective performance of face recognition system and still a challenging problem. Feature extraction is realized through some linear or nonlinear transform of the data with subsequent feature selection for reducing the dimensionality of facial image so that the extracted feature is as representative as possible. Wavelets have been successfully used in image processing. Its ability to capture localized time-frequency information of image motivates its use for feature extraction. The decomposition of the data into different frequency ranges allows us to isolate the frequency components introduced by intrinsic deformations due to expression or extrinsic factors (like illumination) into certain subbands. Wavelet-based methods prune away these variable subbands, and focus on the subbands that contain the most relevant information to better represent the data. In this paper we give an overview of wavelet, multiresolution representation and wavelet packet for their use in face recognition technology.
Squall: Scalable Real-time Analytics

Squall is a scalable online query engine that runs complex analytics in a cluster using skew-resilient, adaptive operators. Squall builds on state-of-the-art partitioning schemes and local algorithms, including some of our own. This paper presents the overview of Squall, including some novel join operators. The paper also presents lessons learned over the five years of working on this system, and outlines the plan for the proposed system demonstration.
Transactivation of Trk Neurotrophin Receptors by G-Protein-Coupled Receptor Ligands Occurs on Intracellular Membranes

Neurotrophins, such as NGF and BDNF, activate Trk receptor tyrosine kinases through receptor dimerization at the cell surface followed by autophosphorylation and intracellular signaling. It has been shown that activation of Trk receptor tyrosine kinases can also occur via a G-protein-coupled receptor (GPCR) mechanism, without involvement of neurotrophins. Two GPCR ligands, adenosine and pituitary adenylate cyclase-activating polypeptide (PACAP), can activate Trk receptor activity to increase the survival of neural cells through stimulation of Akt activity. To investigate the mechanism of Trk receptor transactivation, we have examined the localization of Trk receptors in PC12 cells and primary neurons after treatment with adenosine agonists and PACAP. In contrast to neurotrophin treatment, Trk receptors were sensitive to transcriptional and translational inhibitors, and they were found predominantly in intracellular locations particularly associated with Golgi membranes. Biotinylation and immunostaining experiments confirm that most of the transactivated Trk receptors are found in intracellular membranes. These results indicate that there are alternative modes of activating Trk receptor tyrosine kinases in the absence of neurotrophin binding at the cell surface and that receptor signaling may occur and persist inside of neuronal cells.
Genetic rescue persists beyond first-generation outbreeding in small populations of a rare plant

Habitat fragmentation commonly causes genetic problems and reduced fitness when populations become small. Stocking small populations with individuals from other populations may enrich genetic variation and alleviate inbreeding, but such artificial gene flow is not commonly used in conservation owing to potential outbreeding depression. We addressed the role of long-term population size, genetic distance between populations and test environment for the performance of two generations of offspring from between-population crosses of the locally rare plant Ranunculus reptans L. Interpopulation outbreeding positively affected an aggregate measure of fitness, and the fitness superiority of interpopulation hybrids was maintained in the second offspring (F2) generation. Small populations benefited more strongly from interpopulation outbreeding. Genetic distance between crossed populations in neutral markers or quantitative characters was not important. These results were consistent under near-natural competition-free and competitive conditions. We conclude that the benefits of interpopulation outbreeding are likely to outweigh potential drawbacks, especially for populations that suffer from inbreeding.
Using affective avatars and rich multimedia content for education of children with autism

Autism is a communication disorder that mandates early and continuous educational interventions on various levels like the everyday social, communication and reasoning skills. Computer-aided education has recently been considered as a likely intervention method for such cases, and therefore different systems have been proposed and developed worldwide. In more recent years, affective computing applications for the aforementioned interventions have also been proposed to shed light on this problem. In this paper, we examine the technological and educational needs of affective interventions for autistic persons. Enabling affective technologies are visited and a number of possible exploitation scenarios are illustrated. Emphasis is placed in covering the continuous and long term needs of those persons by unobtrusive and ubiquitous technologies with the engagement of an affective speaking avatar. A personalised prototype system facilitating these scenaria is described. Last but not least, we examine the feedback educators for autistic persons provide for the system in terms of its usefulness, efficiency and the envisaged reaction of the autistic persons, which has been collected by means of an anonymous questionnaire. Results illustrate the clear potential of this effort in facilitating a very promising autism intervention.
Les pactes sociaux en Europe dans les années 1990

Depuis le debut des annees 1990, des pactes sociaux ont ete negocies dans differents pays europeens. Cet article s'interroge sur les raisons et la signification de l'apparition deformes de negociation nationale qui avaient disparu dans la decennie precedente. L'hypothese de cet article est que la perspective de l'UEM a modifie le contexte des relations professionnelles en particulier dans les pays ne faisant pas partie structurellement de la zone mark tels que le Portugal, l'Italie, l'Espagne, la Finlande et l'Irlande, mais aussi la Belgique. Les acteurs sociaux y sont amenes a anticiper les implications de l'UEM surtout en matiere d'inflation et de salaire. Cela a favorise la centralisation des negociations sur ce theme. Une internalisation des variables macroeconomiques ainsi qu'un reagencement des niveaux de la negociation ont eu lieu. Le caractere durable ou non de ces pactes reste cependant une question largement ouverte.
Supercritical Fluid Impregnation of Essential Bark Oil in Copolymers of L-Lactide with 7-Membered Cyclic Compounds

In order to develop a novel controlled-release material, we previously attempted to impregnate poly(L-lactide) (poly(L-LA)), poly(L-LA-ran-CL) (CL: e-caprolactone) or poly(L-LA-ran-TEMC) (TEMC: tetramethylene carbonate) with low boiling point, organic useful compounds using supercritical carbon dioxide (scCO2) as the solvent. In this work, the factors influencing impregnation of poly (L-LA) random copolymers with useful compounds were investigated under scCO2 using the copolymers previously used. The influence of temperature, pressure, and time on the impregnation contents of the useful compounds on the copolymers was evaluated. The polymer used, which is a base of this material, was poly(L-LA-ran-CL), poly(L-LA-ran-TEMC), or poly(L-LA-ran-DXO) (DXO: 1,5-dioxepan-2-one). Statistical random copolymers of L-LA with CL, TEMC, or DXO were synthesized using Sn(oct)2 as a catalyst at 150°C for 24 h without solvent. Preparation of the controlled-release materials was carried out using essential bark oil from Thujopsis dolabrata var. hondae and synthetic L-LA random copolymers as a base material under scCO2. The impregnation experiment, which investigated the influence of pressure, was conducted in the range of 10 to 20 MPa. The influence of temperature on impregnation was carried out at 40°C to 100°C. Impregnation time was varied from 1 to 5 h. The pressure of essential oil impregnated into poly(L-LA) random copolymers was the highest at 14 MPa. In the influence of temperature on impregnation, the amount of essential oil increased with increasing temperature.
The Intergenerational Transmission of Employers

We find that about 40% of a cohort of young Canadian men have been employed at some time with an employer for which their father also worked, and 6%–9% have the same employer in adulthood. The intergenerational transmission of employers is positively related to paternal earnings, particularly at the very top of the earnings distribution, and to the presence of self-employment income and the number of employers with which the father has had direct contact. It has an important influence on nonlinear patterns in the intergenerational elasticity of earnings.
Performance analysis of downlink Two — Tier networks

In this paper, we analyze downlink coverage probability and mean achievable rate of two - tier networks (macrocell and femtocell) where femtocells are assumed to be grouped and majority of these groups are located in the annular region of macrocell coverage area. To analyze this model, we use high-order cluster point process. Finally, the performance is discussed numerically.
Analysis of sequence to sequence neural networks on grapheme to phoneme conversion task

In this paper, we analyze the performance of various sequence to sequence neural networks on the task of grapheme to phoneme (G2P) conversion. G2P is a very important component in applications like text-to-speech, automatic speech recognition etc,. Because the number of graphemes that a word consists of and the corresponding number of phonemes are different, they are first aligned and then mapped. With the recent advent of sequence to sequence neural networks, the alignment step can be skipped allowing us to directly map the input and output sequences. Although the sequence to sequence neural nets have been applied for this task very recently, there are some questions concerning the architecture that need to be addressed. We show in this paper that, complex recurrent neural network units (like long-short term memory cells) may not be required to achieve good performance on this task. Instead simple recurrent neural networks (RNN) will suffice. We also show that the encoder can be a uni-directional RNN as opposed to the usually preferred bi-directional RNN. Further, our experiments reveal that encoder-decoder models with soft-alignment outperforms fixed vector context counterpart. The results demonstrate that with very few parameters we can indeed achieve comparable performance to much more complicated architectures.
A survey on congestion control techniques in Wireless Sensor Networks

Wireless Sensor Networks are event based systems that consists of a collection of autonomous sensor nodes that are spatially distributed and cooperatively monitor physical and environmental conditions. When an event has been detected these sensor nodes become active in transmitting the information and the load becomes heavy, increasing the data traffic and this might lead to congestion that results in packet drops, throughput reduction and degradation of channel quality which in turn decrease network performance. A congestion control scheme is necessary to monitor and regulate the traffic levels at an acceptable value. This paper review various existing works used for detecting and controlling congestion. Different performance metrics that are used for measuring congestion was also surveyed. Finally a comparison of various performance measures was presented.
Evidence of Endemic Hendra Virus Infection in Flying-Foxes (Pteropus conspicillatus)—Implications for Disease Risk Management

This study investigated the seroepidemiology of Hendra virus in a spectacled flying-fox (Pteropus conspicillatus) population in northern Australia, near the location of an equine and associated human Hendra virus infection in late 2004. The pattern of infection in the population was investigated using a serial cross-sectional serological study over a 25-month period, with blood sampled from 521 individuals over six sampling sessions. Antibody titres to the virus were determined by virus neutralisation test. In contrast to the expected episodic infection pattern, we observed that seroprevalence gradually increased over the two years suggesting infection was endemic in the population over the study period. Our results suggested age, pregnancy and lactation were significant risk factors for a detectable neutralizing antibody response. Antibody titres were significantly higher in females than males, with the highest titres occurring in pregnant animals. Temporal variation in antibody titres suggests that herd immunity to the virus may wax and wane on a seasonal basis. These findings support an endemic infection pattern of henipaviruses in bat populations suggesting their infection dynamics may differ significantly from the acute, self limiting episodic pattern observed with related viruses (e.g. measles virus, phocine distemper virus, rinderpest virus) hence requiring a much smaller critical host population size to sustain the virus. These findings help inform predictive modelling of henipavirus infection in bat populations, and indicate that the life cycle of the reservoir species should be taken into account when developing risk management strategies for henipaviruses.
The Effects of Posted Feedback on Littering: Another Look

This study investigated the effectiveness of posted feedback as a litter control strategy in a university cafeteria. Patronage and litter rates were monitored daily throughout the second term of the academic year. Posted feedback was effective in reducing litter rates relative to baseline. Reductions in litter rates were maintained following intervention and continued to be evident 2 weeks after the completion of the study. Results support previous findings that posted feedback is a simple and effective method of litter control.
JSON-based Interoperability Applying the Pull-parser Programming Model

: The JSON format is been applied in a variety of applications: it is established as the de-facto standard for representing document stores; it is widely used to achieve interoperability and as the exchange format in RE-STful web APIs. For these reasons, it is necessary to provide interoperability between JSON and other NoSQL formats. There are several approaches that aims to translate between different NoSQL formats, however, most of them attempt to be generic and do not focus on JSON. They aim on providing an abstract and generic representation capturing all the data models constructs and to provide wrapper-like structures, or to develop pairs of translators. In this paper, we present an approach that uses the JSON data model as driving format for interoperability with distinct NoSQL data models. We take advantage of its nested textual structure to apply the pull-parser programming model to process it and to develop translators between JSON and a set of representative NoSQL formats. We focus on the JSON extraction and on the development and application of the data transformations. We validate our approach through an implementation handling a large number of data representation strategies.
Visualizing data with motion

This paper describes an experimental study of three perceptual properties of motion: flicker, direction, and velocity. Our goal is to understand how to apply these properties to represent data in a visualization environment. Results from our experiments show that all three properties can encode multiple data values, but that minimum visual differences are needed to ensure rapid and accurate target detection: flicker must be coherent and must have a cycle length of 120 milliseconds or greater, direction must differ by at least 20/spl deg/, and velocity must differ by at least 0.43/spl deg/ of subtended visual angle. We conclude with an overview of how we are applying our results to real-world data, and then discuss future work we plan to pursue.
Designing application-specific neural networks using the structured genetic algorithm

Presents a different type of genetic algorithm called the structured genetic algorithm (SGA) for the design of application-specific neural networks. The novelty of this new genetic approach is that it can determine the network structures and their weights solely by an evolutionary process. This is made possible for the SGA primarily due to its redundant genetic material and a gene activation mechanism which in combination provide a multi-layered structure to the chromosome. The authors focus on the use of this learning algorithm for automatic generation of a complete application specific neural network. With this approach, no a priori assumptions about topology are needed and the only information required is the input and output characteristics of the task. The empirical studies show that the SGA can efficiently determine the network size and topology along with the optimal set of connection weights appropriate for desired tasks, without using backpropagation or any other learning algorithm. <<ETX>>
Recent Developments in Micro-Structured Fiber Optic Sensors

Recent developments in fiber-optic sensing have involved booming research in the design and manufacturing of novel micro-structured optical fiber devices. From the conventional tapered fiber architectures to the novel micro-machined devices by advanced laser systems, thousands of micro-structured fiber-optic sensors have been proposed and fabricated for applications in measuring temperature, strain, refractive index (RI), electric current, displacement, bending, acceleration, force, rotation, acoustic, and magnetic field. The renowned and unparalleled merits of sensors-based micro-machined optical fibers including small footprint, light weight, immunity to electromagnetic interferences, durability to harsh environment, capability of remote control, and flexibility of directly embedding into the structured system have placed them in highly demand for practical use in diverse industries. With the rapid advancement in micro-technology, micro-structured fiber sensors have benefitted from the trends of possessing high performance, versatilities and spatial miniaturization. Here, we comprehensively review the recent progress in the micro-structured fiber-optic sensors with a variety of architectures regarding their fabrications, waveguide properties and sensing applications.
Tsunami hazard assessment in the Ionian Sea due to potential tsunamogenic sources – results from numerical simulations

Abstract. In spite of the fact that the great majority of seismic tsunami is generated in ocean domains, smaller basins like the Ionian Sea sometimes experience this phenomenon. In this investigation, we study the tsunami hazard associated with the Ionian Sea fault system. A scenario-based method is used to provide an estimation of the tsunami hazard in this region for the first time. Realistic faulting parameters related to four probable seismic sources, with tsunami potential, are used to model expected coseismic deformation, which is translated directly to the water surface and used as an initial condition for the tsunami propagation. We calculate tsunami propagation snapshots and mareograms for the four seismic sources in order to estimate the expected values of tsunami maximum amplitudes and arrival times at eleven tourist resorts along the Ionian shorelines. The results indicate that, from the four examined sources, only one possesses a seismic threat causing wave amplitudes up to 4 m at some tourist resorts along the Ionian shoreline.
A Fast Method for Iris Localization

Iris localization is an important step in iris recognition system and performance of the recognition system depends on the accuracy of the localization. In this paper, we have proposed an iris localization method. Here, we identify both outer and inner circular boundary of the iris. The present method has two basic steps: edge points detection and circular Hough transform. Before applying these steps, we define the bounding boxes for iris region and pupil area. Bounding box reduces the searching complexity of the Hough transform and results to a fast localization method.
New Alternating-Direction-Implicit Finite-Difference-Time-Domain Method for Photonic Crystal Devices

In this paper, a new alternating direction implicit finite difference time domain (ADI-FDTD) method has been presented. The method relies on a more stable formulation of the perfectly matched layer (PML) absorbing boundary condition making it suitable for the simulation of photonic crystals (PhCs) based devices. Its accuracy and efficiency are demonstrated by numerical examples which are shown to be in excellent agreement with those reported in literature.
Secure Group Communication in Grid Environment

A Grid is a collection of resources that are available for an application to perform tasks. Grid resources are heterogeneous, geographically distributed and belong to different administrative domains. Hence security is a major concern in a grid system. Authentication, message integrity and confidentiality are the major concerns in grid security. Our proposed approach uses a authentication protocol in order to improve the authentication service in grid environment. Secure group communication is brought about by effective key distribution to authenticated users of the channels serviced by resources. The proposed approach facilitates reduced computation and efficient group communication. It also ensures efficient rekeying for each communication session. The security protocol has been implemented and tested using Globus middleware.
Digital Calibration and Correction Methods for CMOS Analog-to-Digital Converters

SUMMARY Along with the miniaturization of CMOS-LSIs, control methods for LSIs have been extensively developed. The most predominant method is to digitize observed values as early as possible and to use digital control. Thus, many types of analog-to-digital converters (ADCs) have been developed such as temperature, time, delay, and frequency converters. ADCs are the easiest circuits into which digital correction methods can be introduced because their outputs are digital. Various types of calibration method have been developed, which has markedly improved the figure of merits by alleviating margins for device variations. The above calibration and correction methods not only overcome a circuit’s weak points but also give us the chance to develop quite new circuit topologies and systems. In this paper, several digital calibration and correction methods for major analog-to-digital converters are described, such as pipelined ADCs, deltasigma ADCs, and successive approximation ADCs.