Miracle-dz/UniFAR-FTUs huggingface dataset:
Forenscope: a framework for live forensics

Current post-mortem cyber-forensic techniques may cause significant disruption to the evidence gathering process by breaking active network connections and unmounting encrypted disks. Although newer live forensic analysis tools can preserve active state, they may taint evidence by leaving footprints in memory. To help address these concerns we present Forenscope, a framework that allows an investigator to examine the state of an active system without the effects of taint or forensic blurriness caused by analyzing a running system. We show how Forenscope can fit into accepted workflows to improve the evidence gathering process. Forenscope preserves the state of the running system and allows running processes, open files, encrypted filesystems and open network sockets to persist during the analysis process. Forenscope has been tested on live systems to show that it does not operationally disrupt critical processes and that it can perform an analysis in less than 15 seconds while using only 125 KB of memory. We show that Forenscope can detect stealth rootkits, neutralize threats and expedite the investigation process by finding evidence in memory.
Three-Dimensional Simulations of Standing Accretion Shock Instability in Core-Collapse Supernovae

We have studied nonaxisymmetric standing accretion shock instabilities, or SASI, using three-dimensional (3D) hydrodynamical simulations. This is an extension of our previous study of axisymmetric SASI. We have prepared a spherically symmetric and steady accretion flow through a standing shock wave onto a proto-neutron star, taking into account a realistic equation of state and neutrino heating and cooling. This unperturbed model is meant to represent approximately the typical postbounce phase of core-collapse supernovae. We then added a small perturbation (~1%) to the radial velocity and computed the ensuing evolutions. Both axisymmetric and nonaxisymmetric perturbations have been imposed. We have applied mode analysis to the nonspherical deformation of the shock surface, using spherical harmonics. We have found that (1) the growth rates of SASI are degenerate with respect to the azimuthal index m of the spherical harmonics Ylm, just as expected for a spherically symmetric background; (2) nonlinear mode couplings produce only m = 0 modes for axisymmetric perturbations, whereas m≠ 0 modes are also generated in the nonaxisymmetric cases, according to the selection rule for quadratic couplings; (3) the nonlinear saturation level of each mode is lower in general for 3D than for 2D, because a larger number of modes contribute to turbulence in 3D; (4) low-l modes are dominant in the nonlinear phase; (5) equipartition is nearly established among different m modes in the nonlinear phase; (6) spectra with respect to l obey power laws with a slope slightly steeper for 3D; and (7) although these features are common to the models with and without a shock revival at the end of the simulation, the dominance of low- l modes is more remarkable in the models with a shock revival.
Biopsychosocial Medicine Relationship between Gender Role, Anger Expression, Thermal Discomfort and Sleep Onset Latency in Women

Background: Women with thermal discomfort from cold extremities (hands and feet; TDCE) often suffer from prolonged sleep onset latency (SOL). Suppressed anger could contribute to the genesis of both TDCE and prolonged SOL. The aim of the study was to test the hypothesis whether stereotypic feminine gender socialization (SFGS) is related to anger suppression (experienced anger inwards, Anger-In), which in turn could affect TDCE and SOL.
Energy Preservation of Mobile Handset's using Multicore Technology

Energy preservation is increasingly becoming a core prerequisite in the design of computer systems. On the desktop and on servers, the main driver for preservation is the cost of powering and cooling computer systems, and the environmental impact of ubiquitous PCs and massive data centers. For the fast growing intelligent and mobile embedded devices sector, green necessities are driven by the need to extend battery life and enhance product performance.Both multicore silicon and virtualization technology are enjoying increasing deployment in intelligent devices of all kinds. This paper examines current assumptions about Multicore, power management, and virtualization, especially in mobile devices and it demonstrates how Multicore processors require reconsidering of power management to preserve energy.
A robotic system for interpreting images into painted artwork

We report on a robotic system that can physically produce paintings with a wide range of artistic media such as acrylic paint on canvas. The system is composed of an articulated painting arm and a machine-learning algorithm aimed at determining a series of brushstrokes that will transfer a given electronic image onto canvas. An artist controlling the system is able to influence the resulting art piece through choice of various parameters, such as the palette, brush types and brushstroke parameters. Alternatively, an artist is able to influence the outcome through varying the algorithmic parameters and feedback of the learning algorithm itself. In these results, a genetic algorithm used a painting simulation to optimize similarity between the target and the source images.
Welcome Theoretical Foundations of Buffer Stock Saving

“Buffer-stock” versions of the dynamic stochastic optimizing model of saving are now standard in the consumption literature. This paper builds theoretical foundations for rigorous understanding of the main characteristics of buffer stock models, including the existence of a target level of wealth and the proposition that aggregate consumption growth equals aggregate income growth in a small open economy populated by buffer stock consumers.
Visual Word Selection without Re-Coding and Re-Pooling

The Bag-of-Words (BoW) representation is widely used in computer vision. The size of the codebook impacts the time and space complexity of the applications that use BoW. Thus, given a training set for a particular computer vision task, a key problem is pruning a large codebook to select only a subset of visual words. Evaluating possible selections of words to be included in the pruned codebook can be computationally prohibitive; in a brute-force scheme, evaluating each pruned codebook requires re-coding of all features extracted from training images to words in the candidate codebook and then re-pooling the words to obtain a representation of each image, e.g., histogram of visual word frequencies. In this paper, a method is proposed that selects and evaluates a subset of words from an initially large codebook, without the need for re-coding or re-pooling. Formulations are proposed for two commonly-used schemes: hard and soft (kernel) coding of visual words with average-pooling. The effectiveness of these formulations is evaluated on the 15 Scenes and Caltech 10 benchmarks.
Separable Codes for Attention and Luminance Contrast in the Primary Visual Cortex

The visual system encodes the features of visual stimuli as well as their behavioral relevance. Stimuli with a high luminance contrast evoke more activity in the visual cortex than stimuli with a low contrast. At the same time, attended stimuli evoke more activity than nonattended stimuli. There is a debate about how visual features and attention jointly determine neuronal activity in the visual cortex. Some studies suggested that attention increases apparent contrast (Reynolds et al., 2000), others that attention amplifies responses by a constant factor (Williford and Maunsell, 2006), and yet others that attention and contrast have largely additive effects (Buracas and Boynton, 2007; Thiele et al., 2009). The influence of attention on contrast sensitivity differs between neurons, raising the possibility that attention and contrast could be coded conjointly in a population of neurons. Here we investigate this possibility by recording neuronal activity at multiple sites in the primary visual cortex of macaque monkeys using multielectrode recording techniques and support vector machines to decode attended stimuli as well as stimulus contrast. We find that many, but not all, V1 neurons are influenced by attention and that the effects of attention and contrast are additive on average. Stimulus contrast can be decoded from neuronal responses not strongly modulated by attention, whereas the attended stimulus can be decoded as the difference in activity of cells that are influenced by attention and cells that are not. The success of the approach suggests that visual attention and stimulus contrast are represented by largely separable codes.
Unscented Transform for SLAM Using Gaussian Mixture Model with Particle Filter

The aims of the Simultaneous Localization and Mapping (SLAM) in a real-world environment is to obtain faster processing speed, more precise predictable results, and better system approximation and consistency. This paper proposes a combination of the Gaussian Mixture Model (GMM) with Particle Filter (PF) and Unscented Kalman Filter (UKF) for the robot SLAM. Also, the PF Markov Chain Monte Carlo (MCMC)method is applied to get a better particle distribution. The application of the SLAM process will depend on the incoming measurement data; whether there is a landmark signal being detected or not. In the former condition, the new landmark position computing, the GMM updating and, the robot and the landmark position updating are needed and, in the latter case,robot and landmark position are predicted through a prediction equation. From the experimental results, it can be seen that the processing speed and the precision of the proposed method are better than that of the FAST SLAM and the UKF SLAM,especially in a dense map environment.
Representing time in multimedia systems

As multimedia systems integrate a variety of temporally interrelated media items, synchronization is an important issue in those systems. One part of synchronization is the representation of temporal information. Time models are needed to specify temporal interrelations. With the emerging interactive media, deterministic models are replaced by indeterministic models with more expressiveness. Therefore, this paper classifies and evaluates a selection of the most common existing models by their expressiveness. Additionally, a temporal model based on temporal operators is proposed providing high-level abstractions and a high degree of expressiveness for multimedia systems. <<ETX>>
Diagnostic Challenge of Diffusion Tensor Imaging in a Patient With Hemiplegia After Traumatic Brain Injury

A 51-year-old man showed hemiplegia on his right side after a traumatic brain injury (TBI). On initial brain computed tomography (CT) scan, an acute subdural hemorrhage in the right cerebral convexity and severe degrees of midline shifting and subfalcine herniation to the left side were evident. On follow-up brain magnetic resonance imaging (MRI), there were multiple microhemorrhages in the left parietal and occipital subcortical regions. To explain the occurrence of right hemiplegia after brain damage which dominantly on the right side of brain, we used diffusion tensor imaging (DTI) to reconstruct the corticospinal tract (CST), which showed nearly complete injury on the left CST. We also performed motor-evoked potentials, and stimulation of left motor cortex evoked no response on both sides of upper extremity. We report a case of patient with hemiplegia after TBI and elucidation of the case by DTI rather than CT and MRI.
Removing achromatic reflections from color images with application to artwork imaging

We propose a general approach to remove reflections from a color image acquired through a semi-transparent medium, and show its application to the restoration of images of paintings framed behind glass and manuscripts laminated for conservation purposes, affected by the reflection of a light source. The problem is modeled by assuming that the unwanted reflection is an achromatic or monochromatic image that combines additively with the real transmitted image of the object of interest. In the absence of information about the mixing coefficients, we adopted a blind source separation technique that exploits the dependence of the three color channels of the original image, and the independence of the reflected image. In particular, these constraints are forced on the image gradients rather than on the intensity images. The algorithm is constituted of a step for the estimation, via independent component analysis of the model parameters, followed by a regularization technique to estimate the component images. The algorithm is very fast and provides promising results.
Power-Aware Activity Monitoring Using Distributed Wearable Sensors

Monitoring human movements using wireless wearable sensors finds applications in a variety of domains including healthcare and wellness. In these systems, sensory devices are tightly integrated with the human body and infer status of the user through signal and information processing. Typically, highly accurate observations can be made at the cost of deploying a sufficiently large number of sensors, which in turn results in increased energy consumption of the system and reduced adherence to using the system. Therefore, optimizing power consumption of the system while maintaining acceptable accuracy plays a crucial role in realizing these stringent resource constraint systems. In this paper, we present an activity monitoring approach that minimizes power consumption of the system subject to a lower bound on the classification accuracy. The system utilizes computationally simple template-matching blocks that perform classifications on individual sensor nodes. The system further employs a boosting approach to enhance accuracy of the distributed classifier by selecting a subset of sensors optimized in terms of power consumption and capable of achieving a given lower bound accuracy criterion. A proof-of-concept evaluation with three participants performing 14 transitional actions was conducted, where collected signals were segmented and labeled manually for each action. The results indicated that the proposed approach provides more than a 65% reduction in the power consumption of the signal processing, while maintaining 80% sensitivity in classifying human movements.
AN INTERPOLATION THEOREM IN TORIC VARIETIES

class in the Picard group of X. ¯ Dans la lignee d'un theoreme de Wood, on donne des conditions necessaires et suffisantes pour qu'une famille de germes d'hypersurfaces analytiques d'une variete torique projective lisse X s'interpole par une hypersurface algebrique de classe de Picard donnee.
Restitution movement for a low cost driving simulator

This paper deals with motion control problem for a 2 DOF small driving simulator. The main idea is to test and compare performances of different Washout algorithms applied to such platform category. The experimentations allow us to have the best compromise between quality of the human perception, implementation complexity and platform architecture type. Implementation of different washout algorithms (optimal, adaptive and classical one) are discussed. For an objective comparison, the classic algorithm was synthesized so as to take into account the human perception thresholds and the platform workspace limitations. A modelling of a second DOF (seat tilting) is given and simulated to show the inertial effect of the seat movement. Finally, psychophysics study, experimental results and conclusion are given
Connectedness of spaces of symplectic embeddings

We prove that the space of symplectic packings of ${\Bbb C}P^2$ by $k$ equal balls is connected for $3\leq k\leq 6$. The proof is based on Gromov-Witten invariants and on the inflation technique due to Lalonde and McDuff.
Two steps reinforcement learning

When applying reinforcement learning in domains with very large or continuous state spaces, the experience obtained by the learning agent in the interaction with the environment must be generalized. The generalization methods are usually based on the approximation of the value functions used to compute the action policy and tackled in two different ways. On the one hand by using an approximation of the value functions based on a supervized learning method. On the other hand, by discretizing the environment to use a tabular representation of the value functions. In this work, we propose an algorithm that uses both approaches to use the benefits of both mechanisms, allowing a higher performance. The approach is based on two learning phases. In the first one, a learner is used as a supervized function approximator, but using a machine learning technique which also outputs a state space discretization of the environment, such as nearest prototype classifiers or decision trees do. In the second learning phase, the space discretization computed in the first phase is used to obtain a tabular representation of the value function computed in the previous phase, allowing a tuning of such value function approximation. Experiments in different domains show that executing both learning phases improves the results obtained executing only the first one. The results take into account the resources used and the performance of the learned behavior. © 2008 Wiley Periodicals, Inc.
Global organization of the Wordnet lexicon

The lexicon consists of a set of word meanings and their semantic relationships. A systematic representation of the English lexicon based in psycholinguistic considerations has been put together in the database Wordnet in a long-term collaborative effort. We present here a quantitative study of the graph structure of Wordnet to understand the global organization of the lexicon. Semantic links follow power-law, scale-invariant behaviors typical of self-organizing networks. Polysemy (the ambiguity of an individual word) is one of the links in the semantic network, relating the different meanings of a common word. Polysemous links have a profound impact in the organization of the semantic graph, conforming it as a small world network, with clusters of high traffic (hubs) representing abstract concepts such as line, head, or circle. Our results show that: (i) Wordnet has global properties common to many self-organized systems, and (ii) polysemy organizes the semantic graph in a compact and categorical representation, in a way that may explain the ubiquity of polysemy across languages.
Pick the right guy: CQI-based LTE forwarder selection in VANETs

Periodical collection of data from vehicles inside a target area is of interest for many applications in the context of Intelligent Transportation Systems (ITS). Long Term Evolution (LTE) has been identified as a good candidate technology for supporting such type of applications — particularly for the non-safety domain. However, a high number of vehicles intermittently reporting their information via LTE can introduce a very high load on the LTE access network. In this context, the use of heterogeneous networking technologies can yield significant offloading of LTE — here, WLAN and Dedicated Short-Range Communication (DSRC) technology can support local data aggregation. In this paper, we propose an on-the-fly distributed clustering algorithm that uses both LTE and DSRC networks in the forwarder selection process. Our results clearly indicate that it is crucial to consider parameters drawn from both networking platforms for selecting the right forwarders. In particular, we show for the first time that relying on the Channel Quality Indicator (CQI) has a substantial impact. We demonstrate that our solution is able to significantly reduce the LTE channel utilization with respect to other state of the art approaches.
Random sampling of large planar maps and convex polyhedra

We present a versatile almost uniform random generator for planar embeddings of graphs (usually called \emph{maps}). This simple pseudo-algorithm is linear on average and gives in a few seconds random maps with up to one million edges or vertices. The class of planar graphs that can be obtained includes graphs of convex polyhedra (or 3-connected planar graphs) and convex irreducible triangulations (or 4-connected maximal planar graphs). Our algorithm relies on a combinatorial approach. First, new simpler compact encodings are defined using canonical unlabelled covering trees. Second, a general \emph{extraction/rejection} pseudo-algorithm is defined for composed structures. If correctly \emph{tuned} (we provide the necessary analysis for maps), it applies efficiently to a much wider class of planar graphs than previously known methods.
A review on Privacy Preservation and Collaborative Data Mining

Privacy preservation is major issue in current data transmission over internet and cloud network. For the integrity and security of data various methods are used such as cryptography, data transformation, Steganography, watermarking and many more method. In consequence of all these method some data mining technique is used. The data mining technique provide Varity of algorithm for privacy preservation. The collaborative data mining technique used different agent method for the integrity of security of data during transmission. Issues about privacy-preserving data mining have emerged globally, but still the main problem is that non- sensitive information or unclassified data, one is able to infer sensitive information that is not supposed to be disclosed. Data collection is a necessary step in data mining process. Due to privacy reasons, collecting data from different parries becomes difficult. In this paper presents the review of privacy persevering technique used data mining.
Data assimilation for marine monitoring and prediction: The MERCATOR operational assimilation systems and the MERSEA developments

During the past 15 years, a number of initiatives have been undertaken at national level to develop ocean forecasting systems operating at regional and/or global scales. The co‐ordination between these efforts has been organized internationally through the Global Ocean Data Assimilation Experiment (GODAE). The French MERCATOR project is one of the leading participants in GODAE. The MERCATOR systems routinely assimilate a variety of observations such as multi‐satellite altimeter data, sea‐surface temperature and in situ temperature and salinity profiles, focusing on high‐resolution scales of the ocean dynamics.
Greedy Convex Embeddings for Ad-Hoc Networks

Recent advances in networked systems and wireless communications have set the stage for applications with wide-ranging benefits. Perhaps the most natural problem in such systems is the ” efficient” propagation of locally stored data. In order to address this problem, the notion of greedy embedding was defined by Papadimitriou and Ratajczak, where the authors conjectured that every 3-connected planar graph has a greedy embedding (possibly planar and convex) in the Euclidean plane. Recently, the greedy embedding conjecture was proved by Leighton and Moitra. However, their algorithm does not result in a drawing that is planar and convex in the Euclidean plane for all 3-connected planar graphs. Here we consider the planar convex greedy embedding conjecture and give a probabilistic proof for the existence of such embeddings. In addition, we discuss a second proof which is almost immediate in the case of an embedding into the 3-dimensional sphere.