Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Pose Estimation from a Single Image via Distance Matrix Regression

This paper addresses the problem of 3D human pose estimation from a single image. We follow a standard two-step pipeline by first detecting the 2D position of the N body joints, and then using these observations to infer 3D pose. For the first step, we use a recent CNN-based detector. For the second step, most existing approaches perform 2N -to3N regression of the Cartesian joint coordinates. We show that more precise pose estimates can be obtained by representing both the 2D and 3D human poses using N ×N distance matrices, and formulating the problem as a 2D-to-3D distance matrix regression. For learning such a regressor we leverage on simple Neural Network architectures, which by construction, enforce positivity and symmetry of the predicted matrices. The approach has also the advantage to naturally handle missing observations and allowing to hypothesize the position of non-observed joints. Quantitative results on Humaneva and Human3.6M datasets demonstrate consistent performance gains over state-of-the-art. Qualitative evaluation on the images in-the-wild of the LSP dataset, using the regressor learned on Human3.6M, reveals very promising generalization results.
Effects of radioactive debris from nuclear explosions on the electrical conductivity of the lower atmosphere

An increase in the ionization near the ground due to the fallout from a radioactive cloud formed by a nuclear explosion will increase the conductivity and lower the potential gradient in the lower atmosphere. Records of atmospheric conductivity and potential gradient from the Tucson Magnetic Observatory are compared with records of the deposition of atomic debris on the ground following the Nevada tests.
Holocene environmental history of a peatland in the Lena River valley, Siberia

A 3.86 m core of peat and organic lake mud from a polygonal peatland in the Lena River valley of Siberia was radiocarbon dated and analyzed for pollen, plant macrofossils, chrysophyte stomatocysts, stable isotopes, and charcoal. At around 7200 BP, a shallow lake or open-water wetland supported diverse aquatic macrophytes. The site had transformed initially into a richer fen with Carex, Comarum palustris, and Drepanocladus and later a poorer fen with Sphagnum which persisted until around 3000 BP. Fire may have been responsible for silt being blown onto the peatland, which changed the hydrological and geochemical conditions for development of the poor fen. Ice accretion led to an increase in the height of the centre of the polygon and expansion of Sphagnum peatland . 18 O values become progressively more enriched, which reflects more direct input of summer precipitation waters and less groundwater during this period. Finally, the peatland surface was elevated sufficiently to limit water and nutrient supply, thereby allowing Ericaceae and Betula to grow at the coring site. Fire burned the peatland surface and may have exaggerated the extremely slow rate of peat accumulation. Fire may also be a factor in maintaining the open Larix dahurica forest in the region today, while climate may be contributing to reducing postfire regeneration. Fire and climate together may be controlling the character and composition of forests near tree line in the Lena River valley of this part of Siberia. Resume : Une carotte de tourbe et de boue organique lacustre diune longueur de 3,86 m prOlevOe dans une tourbire polygonale dans la vallOe de la rivire Lena, en SibOrie, a OtO datOe au radiocarbone et analysOe pour les pollens, plantes
Cost Sharing Mechanisms for Fair Pricing of Resources Usage

We propose a simple and intuitive cost mechanism which assigns costs for the competitive usage of $m$ resources by $n$ selfish agents. Each agent has an individual demand; demands are drawn according to some probability distribution. The cost paid by an agent for a resource she chooses is the total demand put on the resource divided by the number of agents who chose that same resource. So, resources charge costs in an equitable, fair way, while each resource makes no profit out of the agents. We call our model the Fair Pricing model. Its fair cost mechanism induces a non-cooperative game among the agents. To evaluate the Nash equilibria of this game, we introduce the Diffuse Price of Anarchy, as an extension of the Price of Anarchy that takes into account the probability distribution on the demands. We prove: (1) Pure Nash equilibria may not exist, unless all chosen demands are identical. In contrast, we have been able to prove that pure Nash equilibria do exist for two closely related cost sharing models, namely the Average Cost Pricing and the Serial Cost Sharing models. (2) A fully mixed Nash equilibrium exists for all possible choices of the demands. Further on, the fully mixed Nash equilibrium is the unique Nash equilibrium in case there are only two agents. (3) In the worst-case choice of demands, the Price of Anarchy is $Theta (n)$; for the special case of two agents, the Price of Anarchy is less than $2 - frac{1}{m}$. (4) Assume now that demands are drawn from a bounded, independent probability distribution, where all demands are identically distributed and each is at most a (universal for the class) constant times its expectation. Then, the Diffuse Price of Anarchy is at most that same constant, which is just 2 when each demand is distributed symmetrically around its expectation.
Testing with Concepts and Axioms in C + + Anya

Modern development practices encourage extensive testing of code while it is still under development, using unit tests to check individual code units in isolation. Such tests are typically case-based, checking a likely error scenario or an error that has previously been identified and fixed. Coming up with good test cases is challenging, and focusing on individual tests can distract from creating tests that cover the full functionality. Axioms, known from program specification, allow for an alternative way of generating test cases, where the intended functionality is described as rules or equations that can be checked automatically. Axioms are proposed as part of the concept feature of the upcoming C++0x standard. In this paper, we describe how tests may be generated automatically from axioms in C++ concepts, and supplied with appropriate test data to form effective automated unit tests.
${{\cal Q} {\cal D}}$-Learning: A Collaborative Distributed Strategy for Multi-Agent Reinforcement Learning Through  ${\rm Consensus} + {\rm Innovations}$

The paper develops <formula formulatype="inline"> <tex Notation="TeX">${{\cal Q} {\cal D}}$</tex></formula>-learning, a distributed version of reinforcement <formula formulatype="inline"><tex Notation="TeX">$Q$</tex> </formula>-learning, for multi-agent Markov decision processes (MDPs); the agents have no prior information on the global state transition and on the local agent cost statistics. The network agents minimize a network-averaged infinite horizon discounted cost, by local processing and by collaborating through mutual information exchange over a sparse (possibly stochastic) communication network. The agents respond differently (depending on their instantaneous one-stage random costs) to a global controlled state and the control actions of a remote controller. When each agent is aware only of its local online cost data and the inter-agent communication network is weakly connected, we prove that <formula formulatype="inline"> <tex Notation="TeX">${{\cal Q} {\cal D}}$</tex></formula>-learning, a <formula formulatype="inline"> <tex Notation="TeX">$\rm consensus + innovations$</tex></formula> algorithm with mixed time-scale stochastic dynamics, converges asymptotically almost surely to the desired value function and to the optimal stationary control policy at each network agent.
Simulating the Impact of Climate Change on Runoff in a Typical River Catchment of the Loess Plateau, China

AbstractGlobal warming will have direct impacts on regional water resources by accelerating the hydrological cycle. Hydrological simulation is an important approach to studying climate change impacts. In this paper, a snowmelt-based water balance model (SWBM) was used to simulate the effect of climate change on runoff in the Kuye River catchment of the Loess Plateau, China. Results indicated that the SWBM is suitable for simulating monthly discharge into arid catchments. The response of runoff in the Kuye River catchment to climate change is nonlinear, and runoff is more sensitive to changes in precipitation than to changes in temperature. The projections indicated that the Kuye River catchment would undergo more flooding in the 2020s, and global warming would probably shorten the main flood season in the catchment, with greater discharge occurring in August. Although projected changes in annual runoff are uncertain, the possibilities of regional water shortages and regional flooding are essential issues .
MULTICLASS SUPPORT VECTOR MACHINES AND METRIC MULTIDIMENSIONAL SCALING FOR FACIAL EXPRESSION RECOGNITION

In this paper, a novel method for the recognition of facial expressions in videos is proposed. The system first extracts the deformed Candide facial grid that corresponds to the facial expression depicted in the video sequence. The mean Euclidean distance of the deformed grids is then calculated to create a new metric multidimensional scaling. The classification of the sample under examination to one of the 7 possible classes of facial expressions, i.e. anger, disgust, fear, happiness, sadness, surprise and neutral, is performed using multiclass SVMs defined in the new space. The experiments were performed using the Cohn-Kanade database and the results show that the above mentioned system can achieve an accuracy of 95.6%.
Non-Interfering Gvt Computation via Asynchronous Global Reductions

GVT computation has been a significant problem in Time Warp implementations since it affects the completion time of the simulation. We present a new method for computing GVT using inexpensive hardware designed to support synchronization in parallel computations. The main contribution of this paper is this new GVT algorithm. Unlike previous methods, the computation of GVT using our method does not interfere with the simulation. For the LP's, the cost of obtaining GVT is reduced to insignificance. Preliminary studies indicate that our method provides very accurate GVT.
Effect of long internal waves on the quality of water withdrawn from a stratified reservoir

The properties of water withdrawn from a stratified reservoir are investigated in a field study conducted in Lake Burragorang, Australia. It is shown that temperature and turbidity fluctuations of the extracted water are directly correlated to the vertical displacement of the thermal structure of the reservoir immediately in front of the offtake and the thickness of the selective withdrawal layer. Scaling of the unsteady withdrawal revealed that the timescale associated with the formation of selective withdrawal is an order of magnitude smaller than the typical period of the internal wave. This means the withdrawal layer is acting as a filter, extracting water of a particular quality as it is swept past the outlet by the internal seiches; the steady-state theory of the selective withdrawal can be used to predict outflow temperature fluctuations in reservoirs where long internal waves are present. To correctly interpret other outflow water parameters, such as turbidity or dissolved oxygen, it is important .
Global trends (1996–2003) of total column precipitable water observed by Global Ozone Monitoring Experiment (GOME) on ERS‐2 and their relation to near‐surface temperature

[1] We have analyzed global trends of total column precipitable water from measurements of the Global Ozone Monitoring Experiment (GOME) on the European Research Satellite (ERS-2) for the period January 1996 to June 2003. In contrast to other satellite retrieval methods of total column precipitable water, our analysis does not rely on a priori assumptions or additional information; thus it is particularly well suited to trend studies. The chosen wavelength range in the red spectral region ensures similar sensitivity for observations over land and ocean and thus a consistent global picture. To minimize the influence of clouds on the water vapor trends, we selected observations under mainly clear-sky conditions. The temporal evolution of the monthly or yearly averaged total column precipitable water, especially in the tropics, is highly correlated to that of the near-surface temperature, indicating that the global atmospheric humidity is mainly driven by Clausius-Clapeyron's principle. The magnitude of the dependence on near-surface temperature indicates a strong water vapor feedback. The spatial patterns of the water vapor trends show both positive and negative signs. Especially over the oceans, trend patterns very similar to those of near-surface temperature are found. In contrast, over Northern Hemispheric continents the trend patterns are much less correlated, and even opposite trends for water vapor and the near-surface temperatures are found. During the period 1996–2002 the globally and yearly averaged total column precipitable water increased by 2.8 ± 0.8% (excluding the ENSO period).
2 Bloom Filters and Garbled Bloom Filters

Record linkage allows data from different sources to be integrated to facilitate data mining tasks. However, in many cases, records have to be linked by personally identifiable information. To prevent privacy breaches, ideally records should be linked in a private way such that no information other than the matching result is leaked in the process. In this paper, we present an exact Private Record Linkage (PRL) protocol and an approximate PRL protocol. The exact PRL protocol is based on Oblivious Bloom Intersection, which is an efficient private set intersection protocol. The approximate PRL protocol extends the exact PRL protocol by incorporating Locality Sensitive Hash functions. Both protocols are secure in the semihonest model. We also report the evaluation results based on our C implementation of the protocols. The results show that our protocols are efficient and effective.
Aalborg Universitet ARQ strategies for MIMO eigenmode transmission with adaptive modulation and coding

Packet retransmission strategies are presented for MIMO eigenmode transmission where adaptive modulation and coding (AMC) is implemented. The retransmission design is based on weighted linear MMSE. It includes the transmit and receiver filter, the power and eigenmode allocation and AMC level when new packets are transmitted. The weight matrix of WMMSE is used to appropriately weight streams with different AMC levels in order to maximize the system throughput. Simulations show that the choice of the weight factors has a major impact on the performance.
Tunable frequency ferromagnetic resonance of Co nanowire arrays

In order to overcome the current limitations of metallic systems for microwave applications, columnar arrays of Co nanowires with variable wire lengths were electrochemically grown using anodic alumina membranes with thickness of ~100 μm and pore diameters around 70 nm. The Co nanowires tend to present a strong hcp-magnetocrystalline anisotropy directed in the plane perpendicular to the wires axis. The combination of shape anisotropy directed along the wire axis (depending on the wire length) and the hcp magneto-crystalline anisotropy (due to structure) causes a shift from in-plane to out-of-plane spontaneous magnetization with relevant saturation and remanence magnetization values. Different types of magnetic behavior may then lead to ferromagnetic resonance frequencies shifting from 20 to 40 GHz at zero applied field.
Link-State Routing with Hop-by-Hop Forwarding Can Achieve Optimal Traffic Engineering

Link-state routing with hop-by-hop forwarding is widely used in the Internet today. The current versions of these protocols, like OSPF, split traffic evenly over shortest paths based on link weights. However, optimizing the link weights for OSPF to the offered traffic is an NP-hard problem, and even the best setting of the weights can deviate significantly from an optimal distribution of the traffic. In this paper, we propose a new link-state routing protocol, PEFT, that splits traffic over multiple paths with an exponential penalty on longer paths. Unlike its predecessor, DEFT, our new protocol provably achieves optimal traffic engineering while retaining the simplicity of hop-by-hop forwarding. A gain of 15 % in capacity utilization over OSPF is demonstrated using the Abilene topology and traffic traces. The new protocol also leads to significant reduction in the time needed to compute the best link weights. Both the protocol and the computational methods are developed in a new conceptual framework, called network entropy maximization, which is used to identify the traffic distributions that are not only optimal but also realizable by link-state routing.
An optimal algorithm for approximate nearest neighbor searching

Let S denote a set of n points in d-dimensional space, Rd, and let dist(p, g) denote the distance between two points in any Minkowski metric. For any real E > 0 and q E Rd, a point p E S is a (1 + c)-approximate nearest neighbor of q if, for all p’ E S, we have dist(p, q)/dist(p’,q) 5 (1 + E). We show how to preprocess a set of n points in Rd in O(nlog n) time and O(n) space, so that given a query point p E Rd, and e > 0, a (1 + c)-approximate nearest neighbor of q can be computed in O(log n) time. Constant factors depend on d and C. We show that given an integer k 1 1, (1 + c)-approximations to the L-nearest neighbors of q can be computed in O(k log n) time.
Enumerating the k closest pairs optimally

Let S be a set of n points in D-dimensional space, where D is a constant, and let k be an integer between 1 and (/sub 2//sup n/) An algorithm is given that computes the k closest pairs in the set S in O(nlogn+k) time, using O(n+k) space. The algorithm fits in the algebraic decision tree model and is, therefore, optimal. <<ETX>>
Training recurrent networks online without backtracking

We introduce the "NoBackTrack" algorithm to train the parameters of dynamical systems such as recurrent neural networks. This algorithm works in an online, memoryless setting, thus requiring no backpropagation through time, and is scalable, avoiding the large computational and memory cost of maintaining the full gradient of the current state with respect to the parameters. The algorithm essentially maintains, at each time, a single search direction in parameter space. The evolution of this search direction is partly stochastic and is constructed in such a way to provide, at every time, an unbiased random estimate of the gradient of the loss function with respect to the parameters. Because the gradient estimate is unbiased, on average over time the parameter is updated as it should. The resulting gradient estimate can then be fed to a lightweight Kalman-like filter to yield an improved algorithm. For recurrent neural networks, the resulting algorithms scale linearly with the number of parameters. Preliminary tests on a simple task show that the stochastic approximation of the gradient introduced in the algorithm does not seem to introduce too much noise in the trajectory, compared to maintaining the full gradient, and confirm the good performance and scalability of the Kalman-like version of NoBackTrack.
A Regional Measure of Neighborhood Multiple Environmental Deprivation: Relationships with Health and Health Inequalities

The health impacts of simultaneous exposure to multiple adverse environmental factors are of concern in the United Kingdom. UK-wide indicators exist, but context-specific finer resolution measures are lacking. An environmental deprivation index was developed for 398 neighborhoods (average population = 760) in a Scottish council area, including measures of air pollution, noise pollution, traffic environment, undesirable land uses, and crime. Adverse environmental conditions were related to ill health in the region and implicated in wider socioeconomic health inequalities. The results suggest an independent role for environmental deprivation in explaining poor health and health inequalities.
Comparing the Effect of Preprocessing Transformations on Methods of Land-Use Classification Derived From Spectral Soil Measurements

Advanced classifiers, e.g., partial least squares discriminant analysis (PLS-DA) and random forests (RF), have been recently used to model reflectance spectral data in general, and of soil properties in particular, since their spectra are multivariate and highly collinear. Preprocessing transformations (PPTs) can improve the classification accuracy by increasing the variability between classes while decreasing the variability within classes. Such PPTs are common practice prior to a PLS-DA, but are rarely used for RF. The objectives of this paper are twofold: to compare the performances of PLS-DA and RF for modeling the spectral reflectance of soil in changed land-uses with different treatments and to compare the effects of nine different PPTs on the prediction accuracy of each of these classification methods. Differences in six physical, biological, and chemical soil properties of changed land-uses from the northern Negev Desert in Israel were evaluated. Significant differences were found between soil properties, which are used to classify land-uses and treatments. Depending on the dataset, different PPTs improved the classification accuracy by 11%-24% and 32%-42% for PLS-DA and RF, respectively, in comparison to the spectra without PPT. Out of the PPTs tested, the generalized least squares weighting (GLSW)-based transformations were found to be the most effective for most classifications using both PLS-DA and RF. Our results show that both PLS-DA and RF are suitable classifiers for spectral data, provided that an appropriate PPT is applied.
International Conference on Robotics and Automation Designing Open Loop Plans for Planar Micro Manipulation

This paper describes a test-bed for planar micro manipulation tasks and a framework for planning based on quasi-static models of mechanical systems with frictional contacts. We show how planar peg-in-the-hole assembly tasks can be performed using randomized motion planning techniques with Mason’s models for quasi-static manipulation. Finally, we present simulation and experimental results.
Improved Text-Independent Speaker Identification using Fused MFCC & IMFCC Feature Sets based on Gaussian Filter

requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for speech related applications. On a recent contribution by authors, it has been shown that the Inverted Mel-Frequency Cepstral Coefficients (IMFCC) is useful feature set for SI, which contains complementary information present in high frequency region. This paper introduces the Gaussian shaped filter (GF) while calculating MFCC and IMFCC in place of typical triangular shaped bins. The objective is to introduce a higher amount of correlation between subband outputs. The performances of both MFCC & IMFCC improve with GF over conventional triangular filter (TF) based implementation, individually as well as in combination. With GMM as speaker modeling paradigm, the performances of proposed GF based MFCC and IMFCC in individual and fused mode have been verified in two standard databases YOHO, (Microphone Speech) and POLYCOST (Telephone Speech) each of which has more than 130 speakers.