Miracle-dz/UniFAR-FTUs huggingface dataset:
VRIO : A Speech Processing Unit for Virtual Reality and Real-World Scenarios-An Experience Report

Human Computer Interaction (HCI) summarizes research and engineering activities related to the communication between human beings and all sorts of “computerized” machines. Within this domain, substantial amount of work is dedicated to the idea of using the human voice as a natural interface for accessing computer systems. The VRIO speech processing unit represents one example of such an interface, where users control the machine via spoken commands. While the application of VRIO was originally intended for Virtual Reality (VR) environments only, a major redesign of VRIO’s architecture allows its application to arbitrary scenarios, e.g. within ubiquitous and pervasive environments. This paper describes the revised architecture of VRIO as well as examples of its application in VR environments and for real-world scenarios.
Value-Based Segmentation of U.S. Luxury Consumers: Conceptual Replication and Model Validation

The primary objective of this study was to understand the U.S. consumers’ luxury value perceptions using Luxury Value Perception (LVP) model (Wiedmann, Hennigs & Siebel, 2009). The study replicated the procedure used in Wiedmann et al.’s (2009) article to validate the dimensions of the LVP model in the U.S. context. Data were collected using an online survey through Amazon Mechanical Turk. The findings revealed the applicability of the LVP model in the U.S. context and revealed interesting differences in luxury value perceptions among U.S. and German consumers. This study advances theory as it is the first to validate the latent luxury value construct as influenced by individual, social and functional luxury value perceptions in the U.S. context. The LVP model helped identify luxury value drivers of U.S. consumers and cluster them in homogenous segments. These findings may potentially help U.S. luxury brand marketers to know the needs and values of different customer segments, ultimately helping them to develop effective brand positioning strategies in a competitive marketplace.
Spatially Stratified Correspondence Sampling for Real-Time Point Cloud Tracking

In this paper we propose a novel spatially stratified sampling technique for evaluating the likelihood function in particle filters. In particular, we show that in the case where the measurement function uses spatial correspondence, we can greatly reduce computational cost by exploiting spatial structure to avoid redundant computations. We present results which quantitatively show that the technique permits equivalent, and in some cases, greater accuracy, as a reference point cloud particle filter at significantly faster run-times. We also compare to a GPU implementation, and show that we can exceed their performance on the CPU. In addition, we present results on a multi-target tracking application, demonstrating that the increases in efficiency permit online 6DoF multi-target tracking on standard hardware.
Stick to the Plan? A Revealed-Preference Study of Behavioural Impacts of Traffic Information

We estimate a revealed-preference scheduling model of morning peak behaviour that allows us to determine the impact of traffic information on traveller behaviour. Specifically, we distinguish between the marginal impact of expected travel times versus that of deviations from this expectation upon user behaviour. We find that participants that chose to receive a smart-phone with traffic information as a reward in our experiment respond to the deviation of actual travel times from the expectation, which they did not do before. This we interpret as evidence that traffic information indeed affects behaviour. We also find that participants who did not choose the smart-phone, but instead opted for monetary rewards, also respond to the deviation of actual travel times from the expectation. This suggests that these drivers use other sources of information to help their trip planning.
Multiple Scattering of Elastic Waves by Subsurface Fractures and Cavities

Comprehensive studies in geophysics and seismology have dealt with scattering phenomena in unbounded elastic domains containing fractures or cavities. Other studies have been carried out to investigate scattering by discontinuities located near a free surface. In this last case, the presence of fractures and cavities significantly affects wave motion and, in some cases, large resonant peaks may appear. To study these resonant peaks and describe how they can be affected by the presence of other near-free-surface fractures or cavities we propose the use of the indirect boundary element method to simulate 2D scattering of elastic P and SV waves. The geometries considered are planar and elliptic cracks and cavities. This method establishes a system of integral equations that allows us to compute the diffracted displacement and traction fields. We present our results in both frequency and time domains. In the planar cracks located near the free surface, we validate the method by comparing results with those of a previously published study. We develop several examples of various fractures and cavities to show resonance effects and total scattered displace- ment fields, where one can observe conspicuous peaks in the frequency domain and important wave interactions in the time domain. Finally, we show how our dimen- sionless graphs can be used to deal with materials like clay, sand, or gravel and compare the response with finite-element analysis of elastic beams.
Efficient Representation and Manipulation of Switching Functions Based on Ordered Kronecker Functional Decision Diagrams

An efficient package for construction of and operation on ordered Kronecker Functional Decision Diagrams (OKFDD) is presented. OKFDDs are a generalization of OBDDs and OFDDs and as such provide a more compact representation of the functions than either of the two decision diagrams. In this paper basic properties of OKFDDs and their efficient representation and manipulation are presented. Based on the comparison of the three decision diagrams for several benchmark functions, a 25% improve ment in size over OBDDs is observed for OKFDDs.
WEB SIMILARITY MEASUREMENTS USING ANT – BASED SEARCH ALGORITHM

In this paper, a web search algorithm is proposed, which aims to enhance the amount of the relevant information in respect to a user’s query. The proposed algorithm is based on the Ant Colony Optimization algorithm (ACO), employing in parallel document similarity issues from the field of information retrieval. Ant Colony Optimization algorithms were inspired through the observation of ant colonies. In our approach, ants are used as agents through Internet, which are capable of collecting information in each node they visit and generate routing paths through the web. The term similarity [1] is used to describe documents with contiguous content
Convergent Iterative Closest-Point Algorithm to Accomodate Anisotropic and Inhomogenous Localization Error

Since its introduction in the early 1990s, the Iterative Closest Point (ICP) algorithm has become one of the most well-known methods for geometric alignment of 3D models. Given two roughly aligned shapes represented by two point sets, the algorithm iteratively establishes point correspondences given the current alignment of the data and computes a rigid transformation accordingly. From a statistical point of view, however, it implicitly assumes that the points are observed with isotropic Gaussian noise. In this paper, we show that this assumption may lead to errors and generalize the ICP such that it can account for anisotropic and inhomogenous localization errors. We 1) provide a formal description of the algorithm, 2) extend it to registration of partially overlapping surfaces, 3) prove its convergence, 4) derive the required covariance matrices for a set of selected applications, and 5) present means for optimizing the runtime. An evaluation on publicly available surface meshes as well as on a set of meshes extracted from medical imaging data shows a dramatic increase in accuracy compared to the original ICP, especially in the case of partial surface registration. As point-based surface registration is a central component in various applications, the potential impact of the proposed method is high.
Anisotropic Franklin bases on polygonal domains

Franklin systems induced by Courant elements over multilevel nested triangulations of polygonal domains in ℝ2 are explored. Mild conditions are imposed on the triangulations which prevent them from deterioration and at the same time allow for a lot of flexibility and, in particular, arbitrarily sharp angles. It is shown that such anisotropic Franklin systems are Schauder bases for C and L 1, and unconditional bases for Lp (1 < p < ∞) and the corresponding Hardy spaces H 1. It is also proved that the anisotropic H 1 is exactly the space of all functions in L 1 for which the corresponding Franklin system expansions converge unconditionally in L 1. Finally, it is shown that the Franklin bases characterize the corresponding anisotropic BMO spaces. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Metaphor in Latin Descriptions of Reading and Meaning

In this article, metaphors for reading and meaning in Latin are considered from the perspective of conceptual metaphor theory. The focus is on (1) ascriptions of agency and personhood to inanimate entities such as words, texts, and books, and how the notions of (2) the container and (3) the path help to structure Latin descriptions of the relationship between words and ideas. The article closes with a case study of the noun intentio. By demonstrating the existence of these metaphors in Latin (building on previous scholarship), the article augments the historical and transcultural evidence for conceptual metaphor theory, further substantiates the theory’s explanatory value, and illustrates the dangers of taking English metaphors of meaning and intention inherited from Latin at face value.
Asymptotically Optimal Nonlinear Filtering: Theory and Examples with Application to Target State Estimation

The State-Dependent Riccati Equation (SDRE) filter, which is derived by constructing the dual of the well-known SDRE nonlinear regulator control design technique, has been studied in various papers, with mainly practical investigations of the filter. Until recently, theoretical aspects of the filter had not been fully investigated, leaving many unanswered questions, such as stability and convergence of the filter. The authors conducted an investigation of the conditions under which the state estimate given by this algorithm converges asymptotically to the first order minimum variance estimate given by the extended Kalman filter (EKF). Conditions for determining a region of stability for the SDRE filter were also investigated. The analysis was based on stable manifold theory and Hamilton-Jacobi-Bellman (HJB) equations. In this paper, the motivation for introducing HJB equations is justified with mathematical rigor, which is given by reference to the maximum likelihood approach to deriving the EKF. The application of the SDRE filter is then demonstrated on challenging examples to illustrate the theoretical aspects and design flexibility (additional degrees of freedom) of the algorithm when loss of observability is encountered. In particular, a realistic and detailed evaluation of the filter is carried out for the problem of target state estimation in an advanced tactical missile guidance application for analysis in the optimal guidance problem for air-air engagements using only passive sensor (angle-only) information. Simulation results are presented which show dramatic tracking improvement using the SDRE target tracker.
A Single-Stage Interleaved Resonant Bridgeless Boost Rectifier with High-Frequency Isolation

This paper proposes a novel single-phase single-stage ac–dc converter with high-frequency isolation and power factor correction. Unlike the two-stage ac–dc converters, the high-frequency pulsating voltage is obtained directly from the power factor correction semistage and is applied directly to the dc–dc semistage. The proposed topology is designed to be operated in the continuous conduction mode (CCM), and therefore, there is no need for additional input filter. In addition, the interleaving operation helps reducing the current stress and gets a better electro-magnetic interference performance. Moreover, all of the power switches in the proposed topology can achieve soft-switching commutation. Furthermore, the intermediate dc-link capacitor is no longer directly connected to the dc–dc stage and the capacitance can be reduced greatly; therefore, the bulk capacitor is replaced by a film capacitor. Frequency characteristics and time-domain analysis of the LLC resonant tank is presented in this paper to analyze the characteristics of the proposed converter. Finally, a prototype that converts universal input voltage ranging from 110 to 220 V into 400-V dc output was built and tested to verify the analysis.
Development of a Model and Simulation Framework for a Modular Robotic Leg

As research in the field of mobile robotics continues to advance, legged robots in different forms and shapes find a variety of applications on rough terrain where wheeled robots fail to operate in practice. For this reason, a modular legged robot platform is being developed at WPI. This research focuses on developing a mathematical model and then building a simulation to verify the model for a single leg for this platform. The robot platform is modular in the sense that leg modules can be removed and added to predetermined ports on the robot chassis. The modularity of a legged robot is a significant advancement in mobile robotics technology as it enables a single robot to take on different body configurations depending on circumstances and environment to achieve its goals. It also poses a challenge in terms of overall design as it requires autonomous operation of the leg. The goal for this research is to in part fulfill the need for a mathematical model for an autonomous leg. This research investigates the development of a kinematic and dynamic model for the leg, a step trajectory for walking, a simulation of the system to verify the dynamic model, and various functions and scripts to identify shortcomings within the model. This research uses Mathworks Matlab and Wolfram Mathematica to develop the mathematical model, and Matlab Simulink SimMechanics and Matlab functions to build a simulation. Both the mathematical model and simulation follow the classic design of other legged robots, utilizing Lagrangian dynamics, the Jacobian, and simulation tools. The result is a project that is unique in that it drives a robot leg almost independently with very limited communication to a central controller.
Performance of a wireless media access protocol on a Markovian fading channel

The throughput performance of a wireless media access protocol taking into account the effect of channel fading is analyzed. For efficient access on the uplink (mobile-to-base), the protocol makes use of the uplink channel status information which is conveyed to the mobile through a busy/idle flag on the downlink (base-to-mobile link). A first-order Markov model is used to describe the packet successes and failures on a Rayleigh fading channel. A closed-form expression for the throughput is derived by modeling the system as a finite-state, discrete-time Markov chain. The analytical results obtained through the first-order Markov approximation of the channel are compared to those obtained from an i.i. d channel model. The Markovian fading channel model is shown to provide better performance results than the i.i. d channel model. Results obtained by direct simulation of the fading process and the protocol operation show that a first-order Markov approximation of the fading process is quite accurate.
Extracting Information in Molecular Biology : Towards a Complete Chain of Tools

We present a complete chain of tools for knowledge extraction from raw specialized texts. Our approach is original in several ways, which were necessary in order to obtain a tool able to deal with the intricacies of the molecular biology literature. We particularly focussed on the topic of DNAbinding proteins. Instead of concentrating on each step of the chain in isolation, we tried to improve each step in view of an application to the next one. Instead of considering preferably the "highest levels," that is information extraction, we worked intensively on the lowest ones, namely cleaning and tagging the texts. In order to facilitate the conception of "clever" extraction patterns, we performed a large amount of work for classifying the terms in conceptual classes, which we claim to be significant for the domain of DNA-binding proteins: the extraction patterns can be written as relations among concepts instead of relations among textual forms as it is usual. Introduction and motivation In order to understand better genome architectures and dynamics, it is important to spot most of the actual knowledge about DNA-binding proteins. This kind of protein recognizes the DNA molecule, binds itself to it, and modifies the DNA architecture. However, the number of biological papers electronically available is constantly increasing making it more and more difficult to grasp the whole of the available information. It begins thus necessary to gather automatically this information out of very large amounts of data, in order to discover new and relevant relations between pieces of scattered information. These new discoveries will lead to test new hypotheses and develop biological models relative to the eukaryotic gene regulation. Our objective is thus to develop a multi-level text mining method to extract biological relationships between S. cerevisiae DNA-binding proteins from a large corpus of six thousand Medline abstracts. Our future goal is to validate this method on the full papers. The first part of our work is the construction of conceptual classes related to this field, using the raw unannotated texts Performing knowledge extraction from texts demands the completion of several successive steps, including the building of an ontology. The amount of time requested by an expert to structure knowledge in such a way causes a relative lack of such tools in the various specialized fields. Automation or semi-automation is therefore necessary, and this paper present some progress on the topic of automating one crucial and unavoidable step in the process of ontology building, namely the gathering of significant terms ("terminology") that will constitute the nodes of the ontology.
P-adic Continued Fractions

Continued fractions in R have a single definition and algorithms for approximating them are well known. There also exists a well known result which states that p m, m 2 Q, always has a periodic continued fraction representation. In Qp, the field of p-adics, however, there are competing and non-equivalent definitions of continued fractions and no single algorithm exists which always produces a periodic continued fraction for p m. In Jerzy Browkin’s 1978 and 2000 papers, Continued Fractions in Local Fields, I and II, respectively, Browkin presents two definitions for a p-adic continued fraction and presents several algorithms for computing continued fraction approximations to p-adic square roots with the end-goal of finding periodic continued fraction expansions. This paper will serve as an introduction to p-adic numbers and as an exploration of the definitions and algorithms associated with p-adic continued fractions.
Optimal Re-Dispatching of Cascaded Hydropower Plants Using Quadratic Programming and Chance-Constrained Programming

Stochastic production from wind power plants imposes additional uncertainty in power system operation. It can cause problems in load and generation balancing in the power system and can also cause congestion in the transmission network. This paper deals with the problems of congestion in the transmission network, which are caused by the production of wind power plants. An optimization model for corrective congestion management is developed. Congestions are relieved by re-dispatching several cascaded hydropower plants. Optimization methodology covers the optimization period of one day divided into the 24 segments for each hour. The developed optimization methodology consists of two optimization stages. The objective of the first optimization stage is to obtain an optimal day-ahead dispatch plan of the hydropower plants that maximizes profit from selling energy to the day-ahead electricity market. If such a dispatch plan, together with the wind power plant production, causes congestion in the transmission network, the second optimization stage is started. The objective of the second optimization stage is the minimization of the re-dispatching of cascaded hydropower plants in order to avoid possible congestion. The concept of chance-constrained programming is used in order to consider uncertain wind power production. The first optimization stage is defined as a mixed-integer linear programming problem and the second optimization stage is defined as a quadratic programming (QP) problem, in combination with chance-constrained programming. The developed optimization model is tested and verified using the model of a real-life power system.
Fast amplitude compression in hearing aids improves audibility but degrades speech information transmission

Common types of hearing impairment are caused mainly by a loss of nearly instantaneous compressive amplification in the inner ear. Therefore, it seems plausible that the loss might be compensated by fast frequency-dependent compression in the hearing aid. We simulated impaired listeners' auditory analysis of hearing-aid processed speech in noise using a functional auditory model. Using hidden Markov signal models, we estimated the mutual information between the phonetic structure of clean speech and the neural output from the auditory model, with fast and slow versions of hearing-aid compression. The long-term speech spectrum of amplified sound was identical in both systems, as specified individually by the widely accepted NAL prescription for the gain frequency response. The calculation showed clearly better speech-to-auditory information transmission with slow quasi-linear amplification than with fast hearing-aid compression, for speech in speech-shaped noise at signal-to-noise ratios ranging from -10 to +20 dB.
Let's take photos together: exploring asymmetrical interaction abilities on mobile camera phones

Mobile phones have become common tools for photography. Despite the fact that photos are social artifacts, mobile phones afford the act of photo taking only as an individual activity. Photo taking that involves more than one photographer has been envisioned to create positive outcomes and experiences. We implemented this vision with mobile camera phones, exploring how this would influence photo taking practices and experiences. We conducted a user study where altogether 22 participants (11 pairs) were using a novel mobile photography method based on asymmetrical interaction abilities, comparing that with two traditional methods. We present the collaborative practices emerged in different photography methods and report user experience findings particularly with regard to enforced collaboration in mobile photo taking. The results highlight benefits and positive experiences in collaborative photo taking. We discuss lessons learned and point out design implications that come into play when designing for mobile collocated collaboration.