Miracle-dz/UniFAR-FTUs huggingface dataset:
Small sample scene categorization from perceptual relations

This paper addresses the problem of scene categorization while arguing that better and more accurate results can be obtained by endowing the computational process with perceptual relations between scene categories. We first describe a psychophysical paradigm that probes human scene categorization, extracts perceptual relations between scene categories, and suggests that these perceptual relations do not always conform the semantic structure between categories. We then incorporate the obtained perceptual findings into a computational classification scheme, which takes inter-class relationships into account to obtain better scene categorization regardless of the particular descriptors with which scenes are represented. We present such improved classification results using several popular descriptors, we discuss why the contribution of inter-class perceptual relations is particularly pronounced for under-sampled training sets, and we argue that this mechanism may explain the ability of the human visual system to perform well under similar conditions. Finally, we introduce an online experimental system for obtaining perceptual relations for large collections of scene categories.
Discovery of the Optimal Trust Inference Path for Online Social Networks

Analysis of the trust network proves beneficial to the users in Online Social Networks (OSNs) for decision-making. Since the construction of trust propagation paths connecting unfamiliar users is the preceding work of trust inference, it is vital to find appropriate trust propagation paths. Most of existing trust network discovery algorithms apply the classical exhausted searching approaches with low efficiency and/or just take into account the factors relating to trust without regard to the role of distrust relationships. To solve the issues, we first analyze the trust discounting operators with structure balance theory and validate the distribution characteristics of balanced transitive triads. Then, Maximum Indirect Referral Belief Search (MIRBS) and Minimum Indirect Functional Uncertainty Search (MIFUS) strategies are proposed and followed by the Optimal Trust Inference Path Search (OTIPS) algorithms accordingly on the basis of the bidirectional versions of Dijkstra’s algorithm. The comparative experiments of path search, trust inference and edge sign prediction are performed on the Epinions data set. The experimental results show that the proposed algorithm can find the trust inference path with better efficiency and the found paths have better applicability to trust inference. key words: structural balance, subjective logic, trust inference, pathfinding algorithm, edge sign prediction, online social network
Distributed multi-sensor multi-target tracking with feedback

An algorithm that incorporates feedback in distributed fusion architectures for maintaining target tracks in cluttered environments is proposed. The decorrelated feedback sequences are constructed by compensating global updated estimates with track information due to global predicted estimates and local track estimates. Due to its orthogonal properties, these feedback sequences are then used in the filtering process to update local estimates before local processors acquire new sets of measurements. The process of constructing these feedback sequences is presented and implemented on a proposed distributed fusion system where each local processor receives measurements from multiple sensors.
Unsplit complex frequency-shifted PML implementation using auxiliary differential equations for seismic wave modeling

The complex-frequency-shifted perfectly matched layer (CFS-PML) technique can efficiently absorb near-grazing incident waves. In seismic wave modeling, CFS-PML has been implemented by the first-order-accuracy convolutional PML technique or second-order-accuracy recursive convolution PML technique. Both use different algorithms than the numerical scheme for the interior domain to update auxiliary memory variables in the PML and thus cannot be used directly with higher-order time-marching schemes. We work with an unsplit-field CFS-PML implementation using auxiliary differential equations (ADEs) to update the auxiliary memory variables. This ADE CFS-PML results in complete first-order differential equations. Thus, the numerical scheme for the interior domain can be used to solve ADE CFS-PML equations. We have implemented ADE CFS-PML in the finite-difference time-domain method and in anonstaggered-grid finite-difference method with the fourth-order Runge-Kutta scheme, demonstrating its straightforward impleme.
Prosody-based search features in information retrieval

Massive amounts of digital audio material are stored in databases to be accessed via digital networks. A major challenge is how to organise and index this material to best support retrieval applications. Not enough manpower will ever be available to index the terabytes of digital material by hand. Methods for interpreting the complex data automatically or at least semi-automatically must therefore be found. Valuable information in the form of prosodic features can be automatically extracted from the speech signal; computation of these features significantly enhances the automatic interpretation of especially the emotional content of the recording/audio file. In this paper, ways of utilizing prosodic or acoustic features of speech to develop retrieval applications are discussed. Also, the MediaTeam Emotional Speech Corpus is introduced.
Outage performance analysis of all-optical amplify-and-forward relaying over dual-hop optical inter-satellite link

In this paper, outage performance of dual-hop optical inter-satellite link (OISL) employing all-optical amplify-and-forward (AOAF) relaying is analyzed. Take into account the combined source-to-relay (S-R) and relay-to-destination (R-D) channel attenuation induced by geometric spread and pointing error within outer space environment, a series of closed-form expressions for outage performance are derived. Numerical results indicate that the performance of AOAF relaying dual-hop systems is low-complexity and has better performance than that of the non-relay systems under the same total power consumption.
Multimodal Biometrics -- Sources, Architecture and Fusion Techniques: An Overview

Biometrics is the science and technology of measuring and analyzing biological data of human body, extracting a feature set from the acquired data, and comparing this set against to the template set in the database. The increasing demand of enhanced security systems has led to an unprecedented interest in biometric based person authentication system. Biometric systems based on single source of information are called Unimodal systems. Although some Unimodal systems have got considerable improvement in reliability and accuracy, they often suffer from enrollment problems due to non-universal biometrics traits, susceptibility to biometric spoofing or insufficient accuracy caused by noisy data. Hence, single biometric may not be able to achieve the desired performance requirement in real world applications. One of the methods to overcome these problems is to make use of multimodal biometric authentication systems, which combine information from multiple modalities to arrive at a decision. Multimodal biometric systems are those which utilize, or capability of utilizing, more than one physiological or behavioral characteristic for enrollment, verification, or identification. Studies have demonstrated that multimodal biometric systems can achieve better performance compared with Unimodal systems. We discuss here different multimodal sources, multimodal architectures & different fusion techniques used in multimodal biometric systems.
A 3D Spatial Fluid Model for Wireless Networks

In this article we develop a three dimensional (3D) analytical model of wireless networks. We establish an analytical expression of the SINR (Signal to Interference plus Noise Ratio) of user equipments (UE), by using a 3D fluid model approach of the network. This model enables to evaluate in a simple way the cumulative distribution function of the SINR, and therefore the performance, the quality of service and the coverage of wireless networks, with a high accuracy. The use of this 3D wireless network model, instead of a standard two-dimensional one, in order to analyze wireless networks, is particularly interesting. Indeed, this 3D model enables to establish more accurate performance and quality of services results than a 2D one.
The Effects of FDI and Public Expenditure on Economic Growth: From Theoretical Model to Empirical Evidence

The existing endogenous growth theory considers either the effects of FDI or public expenditures on economic growth separately. As far as we concerned, no theoretical growth model has taken into account the interaction effect of these two factors. As found out by Le and Suruga (forthcoming), there is evidence that excessive spending in public expenditures can hinder the beneficial impact of FDI. This article examines some other potential relationships between FDI and public expenditure and proposes that more efforts should be contributed in building a theoretical model which presents the interrelationship between these factors in determining the long-term economic growth rate.
A Note on the Fundamental Theorem of Asset Pricing Under Model Uncertainty

We show that the recent results on the Fundamental Theorem of Asset Pricing and the super-hedging theorem in the context of model uncertainty can be extended to the case in which the options available for static hedging (hedging options) are quoted with bid-ask spreads. In this set-up, we need to work with the notion of robust no-arbitrage which turns out to be equivalent to no-arbitrage under the additional assumption that hedging options with non-zero spread are non-redundant. A key result is the closedness of the set of attainable claims, which requires a new proof in our setting.
Experiences with coupled simulation of mechatronic and electronic systems

Mechatronic as well as electronic systems are very often heterogeneous. Simulating the dynamic system behavior with a single system simulator is in principle possible but requires a considerable modeling effort. To support this approach, generalized KIRCHHOFFian networks [1], [2], [3] could be applied very successfully. But from the engineer‘s point of view it is much more convenient to model directly the different subsystems in their original physical domain or on the most appropriate level of abstraction. To simulate the whole system different simulators (related to the subsystems) have to be coupled. In this way it is possible to simulate multi-physics systems, hybrid ( = continuous + discrete ) systems, and lumped-distributed systems. Sometimes, simulator coupling is the ultima ratio in simulating multi-domain problems.
High Capacity Associative Memory Models with Bipolar and Binary , Biased Patterns

The high capacity associative memory model is interesting due to its significantly higher capacity when compared with the standard Hopfield model. These networks can use either bipolar or binary patterns, which may also be biased. This paper investigates the performance of a high capacity associative memory model trained with biased patterns, using either bipolar or binary representations. Our results indicate that the binary network performs less well under low bias, but better in other situations, compared with the bipolar network.
A mathematical framework for statistical QoS and capacity studies in OFDM networks

This paper presents a mathematical modeling framework for studying the capacity of multi-cell orthogonal frequency division multiplexing networks in single- and multi-service scenarios with various quality of service (QoS) constraints. The framework is built around a feasible network load concept which relates cell resource utilization and interference-dependent resource demand generated by traffic. The feasible load problem is formulated for a general irregular network with non-uniform traffic distribution. Unlike in earlier works, the proposed model explicitly takes into account interference which is load- and service-dependent and models the service constraints on a time scale longer than the typical scheduling interval. A computationally efficient stochastic model is proposed for a regular network deployment with a user distribution pattern repeated over cells and then enhanced with QoS constraints. As an example application, the capacity region problem is studied and numerical results are presented for a realistic network setup. The framework can further be used, for example, for studying radio resource management algorithms or optimizing QoS parameters with respect to an operator QoS policy.
Series Elastic Actuators for legged robots

Series Elastic Actuators provide many benefits in force control of robots in unconstrained environments. These benefits include high force fidelity, extremely low impedance, low friction, and good force control bandwidth. Series Elastic Actuators employ a novel mechanical design architecture which goes against the common machine design principal of "stiffer is better. " A compliant element is placed between the gear train and driven load to intentionally reduce the stiffness of the actuator. A position sensor measures the deflection, and the force output is accurately calculated using Hooke’s Law (F=Kx). A control loop then servos the actuator to the desired output force. The resulting actuator has inherent shock tolerance, high force fidelity and extremely low impedance. These characteristics are desirable in many applications including legged robots, exoskeletons for human performance amplification, robotic arms, haptic interfaces, and adaptive suspensions. We describe several variations of Series Elastic Actuators that have been developed using both electric and hydraulic components.
THE COSMIC EVOLUTION OF ACTIVE GALACTIC NUCLEI IN GALAXY CLUSTERS

We present the surface density of luminous active galactic nuclei (AGNs) associated with a uniformly selected galaxy cluster sample identified in the 8.5 deg2 Boötes field of the NOAO Deep Wide-Field Survey. The clusters are distributed over a large range of redshift (0 < z < 1.5), and we identify AGN using three different selection criteria: mid-IR color, radio luminosity, and X-ray luminosity. Relative to the field, we note a clear overdensity of the number of AGNs within 0.5 Mpc of the cluster centers at z > 0.5. The amplitude of this AGN overdensity increases with redshift. Although there are significant differences between the AGN populations probed by each selection technique, the rise in cluster AGN surface density generally increases more steeply than that of field quasars. In particular, X-ray-selected AGNs are at least 3 times more prevalent in clusters at 1 < z < 1.5 compared to clusters at 0.5 < z < 1. This effect is stronger than can be explained by the evolving median richness of our cluster sample. We thus confirm the existence of a Butcher–Oemler-type effect for AGN in galaxy clusters, with the number of AGNs in clusters increasing with redshift.
Asymmetric Flux Barrier and Skew Design Optimization of Reluctance Synchronous Machines

In this paper, an investigation into an alternative topology for reluctance synchronous machine rotor flux barriers is presented. The investigated topology employs a high number of flux barrier variables with an alternative asymmetric rotor structure. The focus in this paper is on maximizing average torque and minimizing torque ripple, using finite element-based design optimization, in order to study the possibility of achieving acceptably low torque ripple. A subsequent investigation into the effect of rotor skew on the proposed optimized design to reduce torque ripple even further is also conducted, as well as the manufacturing and testing of the proposed flux barrier prototype.
International Conference on Intelligent and Advanced Systems 2007 ~ 263 Bio-Signal Identification using Simple Growing RBF-Network ( OLACA )

An enhanced online adaptive centre allocation algorithms (or resource allocation network (RAN)) using simple/ stochastic back-propagation method with minimal weight update variant are developed for Direct-Link Radial Basis Function (DRBF) networks. These algorithms are developed primarily for applications with fast sampling rate which demands significant reduction in computation load per iteration. The new algorithms are evaluated on a chaotic nonlinear biological based time series signals such as electroencephalographic (EEG) and electrocardiography (ECG). The EEG and ECG signals not only shows non-stationary behaviour but also large oscillation or changes. When the sample time is in milliseconds, both neural network adaptation and weight update must take place within the short time frame thus any learning rule must be computationally simple. The second order techniques, such as Extended Kalman Filter (EKF), need large amount of memory O(N) and computationally intensive. The main goal of this paper is to develop a simple back-propagation based (SBP) resource allocation network (RAN), or also known as sequential learning technique using Radial Basis Function by incorporating Gaussian kernel, in order to identify (model) EEG and ECG signals. Simulation results show the modeled data show good representation of the original signals with less prediction error.
Smart Stereovision Based Gaze Control for Navigation in Low-Feature Unknown Indoor Environments

State-of-the-art mobile robot navigation systems usually consider Gaze control and locomotion planning to be independent modules. We present an integrated gaze control strategy that maximizes the collection of relevant 3D measurements of environment. The presented work results in a more reliable environment representation compared to state-of-the-art approaches for unknown, dynamic indoor environment. In our particular approach, Grid based mapping is employed for path planning purposes. Such an approach demands a sufficient amount of 3D information from stereovision sensors for effective navigation, especially in environments with relatively less number of features such as plain walls and floors. We conduct several experiments in such environments and compare our results with contemporary stereovision based mapping and path planning approaches. We present results of multiple experiments, to show the effectiveness of our system to be able to navigate in low-feature environments using solely, stereovision based gaze control strategy for path planning.
Frames as visual links between paintings and the museum environment: an analysis of statistical image properties

Frames provide a visual link between artworks and their surround. We asked how image properties change as an observer zooms out from viewing a painting alone, to viewing the painting with its frame and, finally, the framed painting in its museum environment (museum scene). To address this question, we determined three higher-order image properties that are based on histograms of oriented luminance gradients. First, complexity was measured as the sum of the strengths of all gradients in the image. Second, we determined the self-similarity of histograms of the orientated gradients at different levels of spatial analysis. Third, we analyzed how much gradient strength varied across orientations (anisotropy). Results were obtained for three art museums that exhibited paintings from three major periods of Western art. In all three museums, the mean complexity of the frames was higher than that of the paintings or the museum scenes. Frames thus provide a barrier of complexity between the paintings and their exterior. By contrast, self-similarity and anisotropy values of images of framed paintings were intermediate between the images of the paintings and the museum scenes, i.e., the frames provided a transition between the paintings and their surround. We also observed differences between the three museums that may reflect modified frame usage in different art periods. For example, frames in the museum for 20th century art tended to be smaller and less complex than in the two other two museums that exhibit paintings from earlier art periods (13th–18th century and 19th century, respectively). Finally, we found that the three properties did not depend on the type of reproduction of the paintings (photographs in museums, scans from books or images from the Google Art Project). To the best of our knowledge, this study is the first to investigate the relation between frames and paintings by measuring physically defined, higher-order image properties.
The role of promastigote secretory gel in the origin and transmission of the infective stage of Leishmania mexicana by the sandfly Lutzomyia longipalpis

Transmission of leishmaniasis is effected by a specific developmental stage, the metacyclic promastigote. The precursors of metacyclic promastigotes were a distinct subpopulation of parasites, identified for the first time as a new stage in the life-cycle and named leptomonad promastigotes. Microdissection of infected sandflies into 4 midgut regions and foregut allowed precursor-product relationships to be established for amastigote-procyclic promastigote, procyclic-nectomonad promastigote, nectomonad-leptomonad promastigote and leptomonad-metacyclic promastigote developmental switches. Metacyclic promastigotes occurred mainly in the thoracic midgut and cardia, coincident with the accumulation of a promastigote secretory gel (PSG) plug in these anterior regions. The gel-like plug was isolated from flies with mature infections and found to contain predominantly leptomonad promastigotes. The PSG plug also contained the majority (75%) of the total metacyclic promastigote population in the sandflies, which were concentrated at the anterior pole. The PSG plug was found to be the main site of metacyclogenesis, and acted as a reservoir of leptomonad promastigotes from which metacyclic forms differentiated and migrated forward to promote the infective potential of the fly. The PSG plug occluded and distorted the midgut, forcing the stomodeal valve open and affecting the feeding success of the sandflies, such that they experienced difficulty in taking a full meal. Collectively, these data support the role of the PSG in the transmission of leishmaniasis, by conditioning the midgut environment for metacyclogenesis and altering the feeding ability of infected sandflies.
Layout-driven SOC test architecture design for test time and wire length minimization

This paper extends existing SOC test architecture design approaches that minimize required tester vector memory depth and test application time, with the capability to minimize the wire length required by the test architecture. We present a simple, Yet effective wire length cost model for test architectures together with a new test architecture design algorithm that minimizes both test time and wire length. The user specifies the relative weight of the costs of test time versus wire length. In an integrated fashion, the algorithm partitions the total available TAM width over individual TAMs, assigns the modules to these TAMs, and orders the modules within one TAM such that the total cost is minimized. Experimental results on five benchmark SOCs show that we can ()brain savings of up to 86% in wiring costs at the expense of <4% in test time.