Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Orthonormal Sparsifying Transforms Based on Householder Reflectors

Dictionary learning is the task of determining a data-dependent transform that yields a sparse representation of some observed data. The dictionary learning problem is nonconvex, and usually solved via computationally complex iterative algorithms. Furthermore, the resulting transforms obtained generally lack structure that permits their fast application to data. To address this issue, this paper develops a framework for learning orthonormal dictionaries, which are built from products of a few Householder reflectors. Two algorithms are proposed to learn the reflector coefficients: one that considers a sequential update of the reflectors and one with a simultaneous update of all reflectors that imposes an additional internal orthogonal constraint. The proposed methods have low computational complexity and are shown to converge to local minimum points, which can be described in terms of the spectral properties of the matrices involved. The resulting dictionaries balance between the computational complexity and the quality of the sparse representations by controlling the number of householder reflectors in their product. Simulations of the proposed algorithms are shown in the image processing setting, where well-known fast transforms are available for comparisons. The proposed algorithms have favorable reconstruction error and the advantage of a fast implementation relative to the classical, unstructured dictionaries.
Robust face tracking using colour Dempster-Shafer fusion and particle filter

This paper describes a real time face detection and tracking system. The method consists in modelling the skin face by a pixel fusion process of three colour sources within the framework of the Demster-Shafer theory. The algorithm is composed of two phases. In a simple and fast initialising stage, the user selects successively in an image, a shadowy, an overexposed and a zone of mean intensity of the face. Then the fusion process models the face skin colour. Next, on the video sequence, a tracking phase uses the key idea that the face exterior edges are well approximated as an ellipse including the skin colour blob resulting from the fusion process. As ellipse detection gets easily disturbed in cluttered environments by edges caused by non-face objects, a simple and fast efficient least squares method for ellipse fitting is used. The ellipse parameters are taken into account by a stochastic algorithm using a particle filter in order to realise a robust face tracking in position, size and pose. The originality of the method consists in modelling the face skin by a pixel fusion process of three independant cognitive colour sources. Moreover, mass sets are determined from a priori models taking into account contextual variables specific to the face under study. Hence, the face specificity which is to present shadowy (neck) and overexposed zones (nose, front) is considered, so that sensitivity to lighting conditions decreases. Results of face skin modelling, fusion, ellipse fitting and tracking are illustrated and discussed in this paper. The limits of the method and future work are also commented in conclusion
The Complexity of Model Checking for Knowledge Update

The authors have recently proposed a formal theory of knowledge update based on the semantics of modal logic S5 (Baral & Zhang 2001). In that system, an agent's knowledge set is represented as a S5 formula and update on agent's knowledge is implemented by updating the corresponding Kripke models of the agent's knowledge set. In this paper , we further investigate the computational complexity of model checking for knowledge update. We rst show that in general the model checking for knowledge update is P 3-complete, which places the problem at one layer higher in the polynomial hierarchy than the traditional model based belief update (e.g. PMA). We then identify a subclass of knowledge update problems that has polynomial time complexity for model checking. We point out that some important knowledge update problems belong to this subclass. We also address other subclasses of knowledge update problems for which the complexity of model checking ranges from NP-complete to P 2-complete.
Modulation codes for flash memory based on load-balancing theory

In this paper, we consider modulation codes for practical multilevel flash memory storage systems with q cell levels. Instead of maximizing the lifetime of the device [7], [1], [2], [4], we maximize the average amount of information stored per cell-level, which is defined as storage efficiency. Using this framework, we show that the worst-case criterion [7], [1], [2] and the average-case criterion [4] are two extreme cases of our objective function. A self-randomized modulation code is proposed which is asymptotically optimal, as q → ∞, for an arbitrary input alphabet and i.i. d. input distribution. In practical flash memory systems, the number of cell-levels q is only moderately large. So the asymptotic performance as q → ∞ may not tell the whole story. Using the tools from load-balancing theory, we analyze the storage efficiency of the self-randomized modulation code. The result shows that only a fraction of the cells are utilized when the number of cell-levels q is only moderately large. We also propose a load-balancing modulation code, based on a phenomenon known as “the power of two random choices” [10], to improve the storage efficiency of practical systems. Theoretical analysis and simulation results show that our load-balancing modulation codes can provide significant gain to practical flash memory storage systems. Though pseudo-random, our approach achieves the same load-balancing performance, for i.i. d. inputs, as a purely random approach based on the power of two random choices.
Distributed localization of networked cameras

Camera networks are perhaps the most common type of sensor network and are deployed in a variety of real-world applications including surveillance, intelligent environments and scientific remote monitoring. A key problem in deploying a network of cameras is calibration, i.e., determining the location and orientation of each sensor so that observations in an image can be mapped to locations in the real world. This paper proposes a fully distributed approach for camera network calibration. The cameras collaborate to track an object that moves through the environment and reason probabilistically about which camera poses are consistent with the observed images. This reasoning employs sophisticated techniques for handling the difficult nonlinearities imposed by projective transformations, as well as the dense correlations that arise between distant cameras. Our method requires minimal overlap of the cameras' fields of view and makes very few assumptions about the motion of the object. In contrast to existing approaches, which are centralized, our distributed algorithm scales easily to very large camera networks. We evaluate the system on a real camera network with 25 nodes as well as simulated camera networks of up to 50 cameras and demonstrate that our approach performs well even when communication is lossy
Design and Experimental Verification of Pseudoelastic-Based Constant-Force Springs

Constant-force springs were designed with Ni-Ti pseudoelastic alloy. Through local concentration of flexural deformations, the design produces “pseodoelastic hinges” under relatively small deformations. Constant moments at these “pseudoelastic hinges” produce a relatively constant level of spring force under increasing deformations. Local concentration of flexural deformations are achieved in this design through bracing the spring element outside the locations where deformations concentrate. Experimental data verified the desirable constant-force behavior of the springs and their desirable fatigue life, relaxation attributes, and corrosion resistance. The pseudoelastic spring design presented here is subject of approved and pending U.S. patent applications.
Anisotropic photoresponse of layered 2D SnS-based near infrared photodetectors

We fabricated near-infrared (NIR) photodetectors with two-dimensional (2D) single crystal orthorhombic SnS nanosheets. The as-fabricated devices exhibited an excellent photoresponsivity of 365 A W−1 under 808 nm light illumination with an excellent external quantum efficiency of 5.70 × 104, which can be further increased to 635 A W−1 and 9.92 × 104 by Au nanoparticle decoration. An anisotropic photoresponse was found for the SnS-based NIR photodetectors and the conductivity and photoconductivity along the zigzag direction are much greater than those along the armchair direction. Treated with oxygen plasma, the effects of defects on the anisotropic photoresponse were further investigated. These results provide a deeper understanding of the electrical and photoelectrical properties of 2D SnS nanosheet based devices.
Defect cost flow model: a Bayesian network for predicting defect correction effort

Background. Software defect prediction has been one of the central topics of software engineering. Predicted defect counts have been used mainly to assess software quality and estimate the defect correction effort (DCE). However, in many cases these defect counts are not good indicators for DCE. Therefore, in this study DCE has been modeled from a different perspective. Defects originating from various development phases have different impact on the overall DCE, especially defects shifting from one phase to another. To reduce the DCE of a software product it is important to assess every development phase along with its specific characteristics and focus on the shift of defects over phases. Aims. The aim of this paper is to build a model for effort prediction at different development stages. Our model is mainly focused on a dynamic DCE changing from one development phase to another. It reflects the increasing cost of correcting defects which are introduced in early, but found in later development phases. Research Method. The modeling technique used in this study is a Bayesian network which, among many others, has three important capabilities: reflecting causal relationships, combining expert knowledge with empirical data and incorporating uncertainty. The procedure of model development contains a set of iterations including the following steps: problem analysis, data analysis, model enhancement with simulation runs and model validation. Results. The developed Defect Cost Flow Model (DCFM) reflects the widely used V-model, an international standard for developing information technology systems. It has been pre-calibrated with empirical data from past projects developed at Robert Bosch GmbH. The analysis of evaluation scenarios confirms that DCFM correctly incorporates known qualitative and quantitative relationships. Because of its causal structure it can be used intuitively by end-users. Conclusion. Typical cost benefit optimization strategies regarding the optimal effort spent on quality measures tend to optimize locally, e.g. every development phase is optimized separately in its own domain. In contrast to that, the DCFM demonstrates that even cost intensive quality measures pay off when the overall DCE of specific features is considered.
HMM-based synthesis of creaky voice

Creaky voice, also referred to as vocal fry, is a voice quality frequently produced in many languages, in both read and conversational speech. To enhance the naturalness of speech synthesis, these latter should be able to generate speech in all its expressive diversity, including creaky voice. The present study looks to exploit our recent developments, including creaky voice detection, prediction of creaky voice from context, and rendering of creaky excitation, into a fully functioning and automatic HMMbased synthesis system. HMM-based synthetic creaky voices are built and evaluated in subjective listening tests, which show that the best synthetic creaky voices are rated more natural and more creaky compared to a conventional voice. A non-creaky voice is also successfully transformed to use creak by modifying the F0 contour and excitation of the predicted creaky parts. The transformed voice is rated equal in terms of naturalness and clearly more creaky compared to the original voice. Index Terms: speech synthesis, creaky voice, contextual factors, F0 estimation, excitation modeling
Dynamics of range margins for metapopulations under climate change

We link spatially explicit climate change predictions to a dynamic metapopulation model. Predictions of species' responses to climate change, incorporating metapopulation dynamics and elements of dispersal, allow us to explore the range margin dynamics for two lagomorphs of conservation concern. Although the lagomorphs have very different distribution patterns, shifts at the edge of the range were more pronounced than shifts in the overall metapopulation. For Romerolagus diazi (volcano rabbit), the lower elevation range limit shifted upslope by approximately 700 m. This reduced the area occupied by the metapopulation, as the mountain peak currently lacks suitable vegetation. For Lepus timidus (European mountain hare), we modelled the British metapopulation. Increasing the dispersive estimate caused the metapopulation to shift faster on the northern range margin (leading edge). By contrast, it caused the metapopulation to respond to climate change slower, rather than faster, on the southern range margin (trailing edge). The differential responses of the leading and trailing range margins and the relative sensitivity of range limits to climate change compared with that of the metapopulation centroid have important implications for where conservation monitoring should be targeted. Our study demonstrates the importance and possibility of moving from simple bioclimatic envelope models to second-generation models that incorporate both dynamic climate change and metapopulation dynamics.
Elevated pyrogenic cytokines in heatstroke.

STUDY OBJECTIVES Heatstroke, characterized by hyperthermia and neurologic abnormalities, can cause shock, adult respiratory distress syndrome, and multiorgan failure culminating in death. The mediation of metabolic changes and tissue damage is not fully understood. Recent evidence suggests the involvement of endotoxin, tumor necrosis factor alpha (TNF-alpha), and interleukin 1 alpha (IL-1 alpha) and we hypothesized that other pyrogenic cytokines may be implicated. DESIGN Prospective analysis. SETTING Heatstroke Center in Makkah (Mecca), Saudi Arabia. MEASUREMENTS AND RESULTS We measured plasma IL-1 beta, IL-6, and interferon gamma (INF-gamma) concentrations by enzyme-linked immunosorbent assay in 28 heatstroke patients at the time of hospital admission (precooling) and after complete cooling (postcooling), and in 10 normal control subjects. We measured C-reactive protein (CRP) as a marker of acute phase response and calculated severity of illness using the simplified acute physiology score. Twenty-five male and 3 female subjects had mean (+/- SEM) rectal temperature of 41.2 +/- 0.2 degrees C. IL-6, IL-1 beta, and INF-gamma concentrations were elevated in 100 percent, 39 percent, and 50 percent of patients to (mean +/- SEM) 220 +/- 44 pg/ml, 42 +/- 14 pg/ml, and 1,180 +/- 879 pg/ml, respectively (normal control values: < 3.5 pg/ml, < 4.5 pg/ml, < 20 pg/ml). The CRP value was elevated in 72 percent of patients to 152 +/- 40 mg/L (control value: 0 to 17 mg/L). The IL-6 concentrations correlated with severity of illness (r = 0.516, p = 0.03); two patients with the highest concentrations died. There was no significant correlation between circulating levels of IL-6, IL-1 beta, INF-gamma, and temperature, or between IL-6, IL-1 beta, and CRP. Postcooling, IL-6, and IL-1 beta were still above normal control values; INF-gamma could be detected in one patient only. CONCLUSION Our findings of elevated circulating IL-6, IL-1 beta, and INF-gamma in the presence of acute phase response, and correlation with severity of illness, suggest that these cytokines have a role in the pathogenesis of heatstroke, which could lead to new therapeutic strategies.
Structural Health Monitoring System of Composite Beams with Surface Bonded and Embedded Fibre Bragg Grating Sensors

Fibre Bragg Grating (FBG) sensors are frequently being used for Structural Health Monitoring (SHM) of aerospace structures. One of the most important advantages of using FBG sensors is that it is possible to embed them into composites. In this paper, manufacturing methods of composite specimens with embedded FBG sensors are given. To avoid stress concentrations at ingress/egress regions of fibre optic wires, PTFE (Teflon) tubes were used during manufacturing. Moreover, FBG connectors melt at high curing temperatures. Therefore, those connectors were cut and after manufacturing, these connectors were spliced back to the FBG sensors. Embedded FBG’s were then checked and the correct wavelength data were taken. All the sensors were observed as intact and ready for bending tests. Procedure for bending tests is also explained including applied loads, boundary conditions, test setup and the peripheral equipment. Results of bending tests show that the system is an appropriate one for SHM purposes.
Spacecraft formation reconfiguration with dynamic collision avoidance

In this paper we present three different solutions to the collision avoidance problem for spacecraft formations based on the Null-Space Based (NSB) behavioral control concept. In the first case, a constant sized sphere of safety area is centered on each spacecraft and obstacle, and the collision avoidance task is activated when this area is entered using a constant repulsive gain similar to what has been proposed for robotics in earlier publications. In the second case we make use of a variable state dependent gain for increasing the level of repulsiveness for each safety sphere to completely avoid collisions. In the third case the sphere is resized based on the relative position and velocity vectors, such that evasive maneuvers are initiated earlier when on collision course, but kept small when passing by. Through Lyapunov analysis we show that the equilibriumpoint of the follower spacecraft dynamics in closed-loop with a sliding surface based controller is uniformly globally exponentially stable when no collisions are detected, and that collisions will not occur when the collision avoidance task is active by scaling the variable state dependent gain. Simulation results are presented comparing the performance of the proposed methods during a formation reconfiguration maneuver.
Unsupervised Long-Term Routine Modelling Using Dynamic Bayesian Networks

Routine can be defined as the frequent and regular activity patterns over a specified timescale (e.g. daily/weekly routine). In this work, we capture routine patterns for a single person from long- term visual data using a Dynamic Bayesian Network (DBN). Assuming a person always performs purposeful activities at corresponding locations; spatial, pose and time-of-day information are used as sources of input for routine modelling. We assess variations of the independence assumptions within the DBN model among selected features. Unlike traditional models that are supervisedly trained, we automatically select the number of hidden states for fully unsupervised discovery of a single person's indoor routine. We emphasize unsupervised learning as it is practically unrealistic to obtain ground-truth labels for long term behaviours. The datasets used in this work are long term recordings of non-scripted activities in their native environments, each lasting for six days. The first captures the routine of three individuals in an office kitchen; the second is recorded in a residential kitchen. We evaluate the routine by comparing to ground-truth when present, using exhaustive search to relate discovered patterns to ground-truth ones. We also propose a graphical visualisation to represent and qualitatively evaluate the discovered routine.
Integrative Approaches to the Study of Baleen Whale Diving Behavior, Feeding Performance, and Foraging Ecology

For many marine organisms, especially large whales that cannot be studied in laboratory settings, our ability to obtain basic behavioral and physiological data is limited, because these organisms occupy offshore habitats and spend a majority of their time underwater. A class of multisensor, suction-cup-attached archival tags has revolutionized the study of large baleen whales, particularly with respect to the predatory strategies used by these gigantic bulk filter feeders to exploit abundant oceanic resources. By integrating these data with those from other disciplines, researchers have uncovered a diverse and extraordinary set of underwater behaviors, ranging from acrobatic diving maneuvers to extreme feeding events during which whales engulf volumes of prey-laden water that are much larger than their own body. This research framework not only improves our knowledge of the individual performance and behavior of these keystone predators but also informs our ability to understand the dynamics of complex marine ecosystems.
SUBSISTENCE AS AN ECONOMIC SYSTEM IN ALASKA : THEORETICAL AND POLICY IMPLICATIONS

\ . c : ' . The purpose of this paper is to provide better definition of subsistence use _ . in Alaska by drawing upon research findings in economic anthropology. Findings indicate that subsistence is a system for the local production and distribution of goods, services, and other nonmaterial products. This economic systd, while . often interactive with,larger marke)t ,economies, is a of risk and insecurity through local provision of da Its relationship to cash is explored in some detail, labor, land, resources, anh other inputs. imed at the minimization ily f? o< and other needs. along with investment of I . Also explored is the continued role and viability of villages in the mod&n . world. The relationship of changing social and environmental factors to subsistence patterns is described. -. , Implications for resource managers are drawn using the framework of subsi'stence economics as an organizing principle. * . 4 . * . s. *-. a----. Novemoer 3, 1YtlU -CL, 8 4 . ' . '. ' . c Much of the difficulty in the implementation of Alaska's Subsistence Law is . based on the lack of co\nsensus about the-definition of subsistence. This paper will suggest that this difficulty results from a too limited definition of subsistence, a definition found in the dictionary and common parlance. This paper will further suggest that the uses protected by the Subsistence Law derive from a recognition and appreciation of a socially significant 1 1 subsistence economic system affecting a significant portion of the State's
Adverse Drug Events in the Elderly Population Admitted to a Tertiary Care Hospital

EXECUTIVE SUMMARY Older adults take almost one‐third of the drugs prescribed today yet represent only about 12 percent of the population. Adverse drug events are common in this population, but often these events appear to be preventable. Interest in adverse events related to the use of prescription drugs has rarely been higher or broader. The research community continues to develop new tools to study adverse effects of drugs in individuals and populations. However, the published literature on drugrelated adverse events is fraught with problems, starting with the original reports and extending to systematic reviews. Prospective data are missing, adverse drug events are poorly described, and analytical methods are questionable. This leads to problems with imprecise estimates and generalizability of results.