Miracle-dz/UniFAR-FTUs huggingface dataset:
An Extended Marker-Based Tracking System for Augmented Reality

Fiducial marker systems consist of unique patterns mounted in the environment and computer vision algorithms that help automatically find features in digital camera images. They are useful for Augmented Reality (AR), robot navigation, 3D modeling, and other applications. In this paper we introduce an extension of marker-based approaches. For some applications which need a large working space, we mounted markers onto the ceiling. Two cameras are fixed onto the head-mounted displays (one captures the markers and the other captures the real scene). After calibration of the two cameras, the pose of the camera captures the real scene can be obtained to merge virtual scene.
Clustering Blog Posts Using Tags and Relations in the Blogosphere

Clustered Web pages, such as blog posts, could be used to improve Web search. In this paper, we propose a folksonomy extending framework using relations in the Blogosphere and demonstrate how the framework could be used to help clustering blog posts. We evaluate the framework by comparing it with content-based folksonomy extending approach. Experiment results show that the framework does help the clustering process.
Two-class Linear Discriminant Analysis for Face Recognition

In this paper, we present a novel face recognition system that uses two-class linear discriminant analysis for classification. In this approach a single M-class linear discriminant classifier is divided into M two-class linear discriminant classifiers. This formulation provides many advantages like more discrimination between classes, simpler calculation of projection vectors and easier update of the database with new individuals. We tested the proposed algorithm on the CMU PIE and Yale face databases. Significant performance improvements are observed, especially when the number of individuals to be classified increases.
Probabilistic Rail Vehicle Localization With Eddy Current Sensors in Topological Maps

Precise localization of rail vehicles is a key element toward the development and deployment of novel train control systems that offer enhanced security and efficiency. Typically, research on train navigation systems approaches this task either by data fusion of an increasing number of onboard sensors or by additional infrastructure installations that are combined with the localization of a global navigation satellite system (GNSS). The former approach is cost intensive and only gradually improves reliability and availability of localization information, whereas the latter approach suffers from the absence of satellite signals in places that are important for railroad applications such as tunnels or railway stations. In contrast, this paper employs a novel single eddy current sensor (ECS) mounted on the rail vehicle that directly pursues observations of the rail on a topological map. The localization task is formulated in a model-based probabilistic framework that enables us to derive signal processing techniques for board-autonomous speed estimation and recognition of particular events such as railroad switches by pattern recognition. In particular, turnouts are detected by Bayesian inference based on hidden Markov models (HMMs). In the final step, position on a topological map is estimated by sequential Monte Carlo sampling that combines speed and event information acquired from the ECS signal. Experiments with simulated and real-world data from an experimental rail vehicle indicate that the proposed system yields position and speed information of high reliability in real time.
Frequency‐Temporal Filtering for a Robust Audio Fingerprinting Scheme in Real‐Noise Environments

In a real environment, sound recordings are commonly distorted by channel and background noise, and the performance of audio identification is mainly degraded by them. Recently, Philips introduced a robust and efficient audio fingerprinting scheme applying a differential (high‐pass filtering) to the frequency‐time sequence of the perceptual filter‐bank energies. In practice, however, the robustness of the audio fingerprinting scheme is still important in a real environment. In this letter, we introduce alternatives to the frequency‐temporal filtering combination for an extension method of Philips’ audio fingerprinting scheme to achieve robustness to channel and background noise under the conditions of a real situation. Our experimental results show that the proposed filtering combination improves noise robustness in audio identification.
Loop equations for the semiclassical 2-matrix model with hard edges

The 2-matrix model can be defined in a setting more general than polynomial potentials, namely, the semiclassical matrix model. In this case, the potentials are such that their derivatives are rational functions, and the integration paths for eigenvalues are arbitrary homology classes of paths for which the integral is convergent. This choice includes in particular the case where the integration path has fixed endpoints, called hard edges. The hard edges induce boundary contributions in the loop equations. The purpose of this paper is to give the loop equations in that semi-classical setting.
Navigation Aiding by a Hybrid Laser-Camera Motion Estimator for Micro Aerial Vehicles

Micro Air Vehicles (MAVs) equipped with various sensors are able to carry out autonomous flights. However, the self-localization of autonomous agents is mostly dependent on Global Navigation Satellite Systems (GNSS). In order to provide an accurate navigation solution in absence of GNSS signals, this article presents a hybrid sensor. The hybrid sensor is a deep integration of a monocular camera and a 2D laser rangefinder so that the motion of the MAV is estimated. This realization is expected to be more flexible in terms of environments compared to laser-scan-matching approaches. The estimated ego-motion is then integrated in the MAV’s navigation system. However, first, the knowledge about the pose between both sensors is obtained by proposing an improved calibration method. For both calibration and ego-motion estimation, 3D-to-2D correspondences are used and the Perspective-3-Point (P3P) problem is solved. Moreover, the covariance estimation of the relative motion is presented. The experiments show very accurate calibration and navigation results.
Unseen Visible Watermarking

A novel data-hiding methodology, denoted as unseen visible watermarking (UVW), is proposed. The proposed scheme is inspired by real-world watermarks and possesses advantages of both visible and invisible watermarking schemes. After watermark embedding, the differences between the original work and the stego work are imperceptible under normal viewing conditions. However, when the hidden message is to be extracted, no explicit watermark extracting module is required. Semantically-meaningful watermark patterns can be directly recognized from the stego work as long as common imaging-related functions, e.g. gamma-correction or even simply changing the user-viewing angle relative to the LCD monitor, are performed. The proposed scheme outperforms existing invisible watermarking methods in its capability to practically convey metadata to users of legacy display devices lacking renewal capability. On the other hand, it does not suffer from the annoying quality-degradation problem of visible watermarking schemes. Limitations and possible extensions of the proposed schemes are also addressed. We believe that many interesting new applications can be facilitated using such unseen visible watermarking schemes.
Galactic cannibalism and cold dark matter density profiles

Using N-body simulations, we show that the process of formation of the brightest cluster galaxy through dissipationless galactic cannibalism can affect the inner cluster dark matter density profile. In particular, we use as a realistic test case the dynamical evolution of the galaxy cluster C0337-2522 at redshift z = 0.59, hosting in its centre a group of five elliptical galaxies which are likely to be the progenitor of a central giant elliptical. After the formation of the brightest cluster galaxy, the inner cluster dark matter density profile is significantly flatter (logarithmic slope 0.49? β? 0.90) than the original cusp (β = 1), as a consequence of dynamical friction heating of the massive galaxies against the diffuse cluster dark matter. In our simulations we have assumed that the cluster galaxies are made of stars only. We also show that the presence of galactic dark matter haloes can steepen the cluster central density profile. We conclude that galactic cannibalism could be a viable physical mechanism to reconcile - at least at the cluster scale - the flat dark matter haloes inferred observationally in some galaxy clusters with the steep haloes predicted by cosmological simulations.
Teachers' Understanding of Chronic Pain and its Impact on Students' Functioning

iii TABLE OF CONTENTS . v LIST OF TABLES . vi CHAPTER I: INTRODUCTION . 1 CHAPTER II: LITERATURE REVIEW . 3 Impact of Chronic Abdominal Pain . 4 Impact of Chronic Pain on School Functioning . 5 Teachers' Perceptions of Students with Chronic Pain . 7 School Systems' Responses to Students with Chronic Pain . 8 Conclusion . 9 CHAPTER III: METHODOLOGY . 11 Participants . 11 Instrument . 12 Procedures . 12 CHAPTER IV: RESULTS . 13 CHAPTER V: DISCUSSION. 16 Limitations and Future Research . 17 Conclusion . 18 REFERENCES . 19 APPENDICES . 23 APPENDIX A: INFORMED CONSENT TO PARTICIPATE AS A RESEARCH SUBJECT . 23 APPENDIX B: SURVEY . 26
Does Negative Priming Reflect Inhibitory Mechanisms? A Review and Integration of Conflicting Views

Negative priming has traditionally been viewed as a reflection of an inhibitory mechanism of attention. However, recent accounts have suggested that negative priming does not reflect inhibitory mechanisms. Rather, slowed reaction times on negative priming trials are either due to retrieval of incompatible response tags or of mismatching perceptual information, or due to extra processes needed to distinguish past from present information. In contrast, it is proposed that there is no firm evidence to discount inhibition models. In fact, although retrieval processes can be implicated in negative priming effects, understanding of these requires consideration of the inhibitory processes involved in selecting information for goal-directed behaviour.
Dual formulation of spin network evolution

We illustrate the relationship between spin networks and their dual representation by labelled triangulations of space in 2+1 and 3+1 dimensions. We apply this to the recent proposal for causal evolution of spin networks. The result is labelled spatial triangulations evolving with transition amplitudes given by labelled spacetime simplices. The formalism is very similar to simplicial gravity, however, the triangulations represent combinatorics and not an approximation to the spatial manifold. The distinction between future and past nodes which can be ordered in causal sets also exists here. Spacelike and timelike slices can be defined and the foliation is allowed to vary. We clarify the choice of the two rules in the causal spin network evolution, and the assumption of trivalent spin networks for 2+1 spacetime dimensions and four-valent for 3+1. As a direct application, the problem of the exponential growth of the causal model is remedied. The result is a clear and more rigid graphical understanding of evolution of combinatorial spin networks, on which further work can be based.
Interaction of Microtubule-associated Protein-2 and p63

Neurons are polarized cells presenting two distinct compartments, dendrites and an axon. Dendrites can be distinguished from the axon by the presence of rough endoplasmic reticulum (RER). The mechanism by which the structure and distribution of the RER is maintained in these cells is poorly understood. In the present study, we investigated the role of the dendritic microtubule-associated protein-2 (MAP2) in the RER membrane positioning by comparing their distribution in brain subcellular fractions and in primary hippocampal cells and by examining the MAP2-microtubule interaction with RER membranes in vitro. Subcellular fractionation of rat brain revealed a high MAP2 content in a subfraction enriched with the endoplasmic reticulum markers ribophorin and p63. Electron microscope morphometry confirmed the enrichment of this subfraction with RER membranes. In cultured hippocampal neurons, MAP2 and p63 were found to concomitantly compartmentalize to the dendritic processes during neuronal differentiation. Protein blot overlays using purified MAP2c protein revealed its interaction with p63, and immunoprecipitation experiments performed in HeLa cells showed that this interaction involves the projection domain of MAP2. In an in vitro reconstitution assay, MAP2-containing microtubules were observed to bind to RER membranes in contrast to microtubules containing tau, the axonal MAP. This binding of MAP2c microtubules was reduced when an anti-p63 antibody was added to the assay. The present results suggest that MAP2 is involved in the association of RER membranes with microtubules and thereby could participate in the differential distribution of RER membranes within a neuron.
Processing XPath queries with forward and downward axes over XML streams

We propose an XPath processing algorithm that efficiently evaluates XPath queries in XP{↓, →, *, []} over XML streams. An XPath query is expressed with axes, which are binary relations between nodes in XML streams: '↓' identifies the child/descendant axes and '→' indicates the following/following-sibling axes. The proposed algorithm evaluates XPath queries within one XML parsing pass and outputs the fragments found in XML streams as the query results. The difficulty of XP{↓, →, *, []} evaluation lies in establishing dynamic scope control for the following/following-sibling axes. The algorithm uses double-layered non-deterministic finite automata (NFA) to resolve this issue. First layer NFA is compiled from XPath queries and is able to evaluate sub-queries in XP{↓, →, *}. Second layer NFA handles predicate parts. It is dynamically maintained during XML parsing: a state is constructed from a pair of the corresponding state in the first layer automaton and the currently parsed node in the XML stream. Layered NFA achieves O(|D||Q|) time complexity by introducing a state sharing technique, which avoids the exponential growth in the state size of Layered NFA by eliminating redundant transitions. We validate the efficiency of the algorithm through empirical experiments and show that Layered NFA is up to four times faster, and twice as fast on average, than existing algorithms.
Towards Cost-Effective Storage Provisioning for DBMSs ( Extended Version )

Data center operators face a bewildering set of choices when considering how to provision resources on machines with complex I/O subsystems. Modern I/O subsystems often have a rich mix of fast, high performing, but expensive SSDs sitting alongside with cheaper but relatively slower (for random accesses) traditional hard disk drives. The data center operators need to determine how to provision the I/O resources for specific workloads so as to abide by existing Service Level Agreements (SLAs), while minimizing the total operating cost (TOC) of running the workload, where the TOC includes the amortized hardware costs and the run time energy costs. The focus of this paper is on introducing this new problem of TOC-based storage allocation, cast in a framework that is compatible with traditional DBMS query optimization and query processing architecture. We also present a heuristic-based solution to this problem, called DOT. We have implemented DOT in PostgreSQL, and experiments using TPC-H and TPC-C demonstrate significant TOC reduction by DOT in various settings.
METÁFORAS SOBRE EMOÇÕES: UMA CENA COGNITIVA DE TEATRO E DE FORÇA METAPHORS ABOUT EMOTIONS: A COGNITIVE FRAMEWORK OF STAGE AND FORCE.

In this paper, metaphors about emotions are described. These emotions are conceptualized according to different ontological categories. Notwithstanding these ontological differences, the metaphors described show many conceptual similarities. The hypothesis put forward is that such conceptual structures are derived from transitivity, i.e., constructions with subject and direct object. The metaphors described inherit frames connected to transitivity, through the following cognitive models: stagemodel, billiard-ball model and force dynamics model.
Biclustering multivariate data for correlated subspace mining

Exploring feature subspaces is one of promising approaches to analyzing and understanding the important patterns in multivariate data. If relying too much on effective enhancements in manual interventions, the associated results depend heavily on the knowledge and skills of users performing the data analysis. This paper presents a novel approach to extracting feature subspaces from multivariate data by incorporating biclustering techniques. The approach has been maximally automated in the sense that highly-correlated dimensions are automatically grouped to form subspaces, which effectively supports further exploration of them. A key idea behind our approach lies in a new mathematical formulation of asymmetric biclustering, by combining spherical k-means clustering for grouping highly-correlated dimensions, together with ordinary k-means clustering for identifying subsets of data samples. Lower-dimensional representations of data in feature subspaces are successfully visualized by parallel coordinate plot, where we project the data samples of correlated dimensions to one composite axis through dimensionality reduction schemes. Several experimental results of our data analysis together with discussions will be provided to assess the capability of our approach.
An information theoretic charachterization of channel shortening receivers

Optimal data detection of a linear channel can always be implemented through the Viterbi algorithm (VA). However, in many cases of interest the memory of the channel prohibits application of the VA. A popular and conceptually simple method in this case, studied since the early 70s, is to first filter the received signal in order to shorten the memory of the channel, and then to apply a VA that operates with the shorter memory. We shall refer to this as a channel shortening (CS) receiver. Although studied for almost four decades, an information theoretic understanding of what such simple receiver solution is actually doing is not available. In this paper we will show that an optimized CS receiver is implementing the chain rule of mutual information, but only up to the shortened memory that the receiver is operating with. Further, we will show that the tools for analyzing the ensuing achievable rates from an optimized CS receiver are precisely the same as the tools that are used for analyzing the achievable rates of an minimum mean square error (MMSE) receiver.
Skoll: distributed continuous quality assurance

Quality assurance (QA) tasks, such as testing, profiling, and performance evaluation, have historically been done in-house on developer-generated workloads and regression suites. Since this approach is inadequate for many systems, tools and processes are being developed to improve software quality by increasing user participation in the QA process. A limitation of these approaches is that they focus on isolated mechanisms, not on the coordination and control policies and tools needed to make the global QA process efficient, effective, and scalable. To address these issues, we have initiated the Skoll project, which is developing and validating novel software QA processes and tools that leverage the extensive computing resources of worldwide user communities in a distributed, continuous manner to significantly and rapidly improve software quality. This paper provides several contributions to the study of distributed continuous QA. First, it illustrates the structure and functionality of a generic around-the-world, around-the-clock QA process and describes several sophisticated tools that support this process. Second, it describes several QA scenarios built using these tools and process. Finally, it presents a feasibility study applying these scenarios to a 1MLOC+ software package called ACE+TAO. While much work remains to be done, the study suggests that the Skoll process and tools effectively manage and control distributed, continuous QA processes. Using Skoll we rapidly identified problems that had taken the ACE+TAO developers substantially longer to find and several of which had previously not been found. Moreover, automatic analysis of QA task results often provided developers information that quickly led them to the root cause of the problems.
Retinal Blood Vessel Segmentation and Optic Disc Detection Using Combination of Spatial Domain Techniques

— Medical imaging is the process of creating visual representations of the interior portion of a human body for clinical analysis. Medical imaging reveals the internal structures hidden by the skin and bones, as well as to diagnose and treat disease. It also helps in identifying the abnormalities. Medical imaging technology helps doctors to see the interior portions of the human body and made easy for diagnosis. Segmentation of retinal blood vessels assists in identifying various diseases such as diabetes mellitus, hypertension, macular degeneration, glaucoma etc. The early detection of these diseases is important to prevent the patients from reaching severity. This method makes use of edge detection and morphological operators to segment the retinal blood vessels. Our method also consists of automatically detecting the position of the Optic Disc in digital retinal fundus images. Input images are obtained from DRIVE and STARE datasets.
Hybrid Optimisation Method Using PGA and SQP Algorithm

This paper investigates the hybridisation of two very different optimisation methods, namely the parallel genetic algorithm (PGA) and sequential quadratic programming (SQP) algorithm. The different characteristics of genetic-based and traditional quadratic programming-based methods are discussed and to what extent the hybrid method can benefit the solving of optimisation problems with nonlinear complex objective and constraint functions. Experiments show the hybrid method effectively combines the robust and global search property of parallel genetic algorithms with the high convergence velocity of the sequential quadratic programming algorithm, thereby reducing computation time, maintaining robustness and increasing solution quality