Miracle-dz/UniFAR-FTUs huggingface dataset:
Refinement of extracted visual attention areas in video sequences

Visual attention extraction is the ability to rapidly detect the interesting section of a given scene, which is called attention area or region of interest (ROI) in some literature. However, because of the inherent disadvantages of the current attention model structure, the resulted visual attention area is instable along time - that is, the extracted attention areas are quite different even between neighboring frames which are similar in content. Such an un-smooth trajectory of attention areas will lead to impressive subjective quality degradation in attention area based applications like content based video streaming/compression, and this problem cannot be solved simply by smoothing filters. In this paper, we present a strategy to generate stable attention area across time through methods of temporal emendation.
Run-time Adjustment Feedback Services BPEL Process Running Instances Execution platform : shared bpel engine Controller : Customization Logic View : Master Process BPEL Process Running Instances Tenant

Business Process as a Service (BPaaS) is expected to emerge as the next major category of Cloud Computing. The combination of fast expanding technologies with increasing competitiveness will make more and more companies move parts of their business processes into the cloud. This enables them to take advantage of the cloud provider’s expertise and to reduce their cost by sharing resources to exploit economies of scale. In such a multi-tenant setting, the cloud provider has to tailor its business processes to meet the QoS requirements of each tenant. This requires techniques for QoS-aware service selection and prediction. However, there is no one-size-fitsall approach to tackle this challenge. The choice of the most suitable technique typically depends on the particular context and characteristics of the services that are being composed. This paper has the following contributions: To support the provider with the creation of custom-tailored processes, we propose an open middleware that provides the mechanisms to perform requirement-driven customizations on shared process templates. This open middleware supports easy integration of new and existing service selection and prediction techniques.
Merging Closed Pattern Sets in Distributed Multi-Relational Data

We consider the problem of mining closed patterns from multi-relational databases in a distributed environment. Given two lo- cal databases (horizontal partitions) and their sets of closed patterns (concepts), we generate the set of closed patterns in the global database by utilizing the merge (or subposition) operator, studied in the field of Formal Concept Analysis. Since the execution times of the merge opera- tions increase with the increase in the number of local databases, we pro- pose some methods for improving the merge operations. We also present some experimental results using a distributed computation environment based on the MapReduce framework, which shows the effectiveness of the proposed methods.
The Calculus of Jacobian Adaptation

For many problems, the correct behavior of a model depends no t only on its input-output mapping but also on properties of its Jacobian matrix, the matrix of partial der ivatives of the model’s outputs with respect to its inputs. T his paper introduces theJ-propalgorithm, an efficient general method for computing the exa ct p rtial derivatives of a variety of simple functions of the Jacobian of a model with respect to its free p arameters. The algorithm applies to any parametrized doubl ydifferentiable data-driven feedforward model, including nonlinear regression, multilayer perceptrons, and radial basis function networks. J-prop has as special cases some earlier algorithms, such as Tangent Prop and Double Backpropagation, but it can also be used to optimize the eigenvectors, eigenvalues, or deter minant of the Jacobian, making it quite general with respect to the model types, applications, and objective functions that ca n be used. Applications of J-prop include forcing stability and sensitivity conditions, regularization, building low-compl exity encoder-decoder networks, exploiting prior knowled g , designing controllers, and blind source separation.
Dopaminergic Control of the Exploration-Exploitation Trade-Off via the Basal Ganglia

We continuously face the dilemma of choosing between actions that gather new information or actions that exploit existing knowledge. This “exploration-exploitation” trade-off depends on the environment: stability favors exploiting knowledge to maximize gains; volatility favors exploring new options and discovering new outcomes. Here we set out to reconcile recent evidence for dopamine’s involvement in the exploration-exploitation trade-off with the existing evidence for basal ganglia control of action selection, by testing the hypothesis that tonic dopamine in the striatum, the basal ganglia’s input nucleus, sets the current exploration-exploitation trade-off. We first advance the idea of interpreting the basal ganglia output as a probability distribution function for action selection. Using computational models of the full basal ganglia circuit, we showed that, under this interpretation, the actions of dopamine within the striatum change the basal ganglia’s output to favor the level of exploration or exploitation encoded in the probability distribution. We also found that our models predict striatal dopamine controls the exploration-exploitation trade-off if we instead read-out the probability distribution from the target nuclei of the basal ganglia, where their inhibitory input shapes the cortical input to these nuclei. Finally, by integrating the basal ganglia within a reinforcement learning model, we showed how dopamine’s effect on the exploration-exploitation trade-off could be measurable in a forced two-choice task. These simulations also showed how tonic dopamine can appear to affect learning while only directly altering the trade-off. Thus, our models support the hypothesis that changes in tonic dopamine within the striatum can alter the exploration-exploitation trade-off by modulating the output of the basal ganglia.
Attack on RSA Cryptosystem

The RSA cryptosystem is most widely used cryptosystem it may be used to provide both secrecy and digital signatures and its secu- rity is based on the intractability of the integer factorization. The security of RSA algorithm depends on the ability of the hacker to factorize num- bers. New, faster and better methods for factoring numbers are constantly being devised. The Trent best for long numbers is the Number Field Sieve. Although the past work has proven that none of the attacks on RSA cryptosystem were dangerous. Indeed most of the dangers were be- cause of improper use of RSA. In this paper what I am trying to do is to analyze the different types of possible attacks on RSA Cryptosystem.
Fault ride-through capability implementation in wind turbine converters using a decoupled double synchronous reference frame PLL

This work exploits the decoupled double synchronous reference frame PLL (DDSRF-PLL) as an effective method for grid synchronization of WT's power converters in the presence of transient faults in the grid. The DDSRF-PLL uses a dual synchronous reference frame and a decoupling network to effectively separate the positive- and negative-sequence voltage components in a fast and accurate way. Excellent behavior of the DDSRF-PLL is demonstrated experimentally. Once sequence components of the faulty grid voltage are properly identified several algorithms computing current references are developed. Additionally, different power delivery strategies to ride-through grid faults are discussed and simulations results are presented. As a conclusion, it will be demonstrated that certain control strategies ensure a stable operation of the front-end inverter while the grid voltage is supported by means of injection of instantaneous reactive power at the same time.
CprFS: a user-level file system to support consistent file states for checkpoint and restart

Checkpoint and Restart (CPR) is becoming critical to large scale parallel computers, whose Mean Time Between Failures (MTBF) may be much shorter than the execution times of the applications. The CPR mechanism should be able to store and recover the states of virtual memory, communication and files for the applications in a consistent way. However, many CPR tools ignore file states, which may cause errors for applications with file operations on recovery. Some CPR tools adopt library-based approaches or kernel-level file systems to deal with file states, but they only support limited types of file operations which are not sufficient for some applications. Moreover, many library-based approaches are not transparent to user applications because they wrap file APIs. Kernel-level file systems are difficult to deploy in production systems due to unnecessary overhead they may introduce to applications that do not need CPR. In this paper we propose a user-level file system, CprFS, to address these problems. As a file system, CprFS can guarantee transparency to user applications, and is convenient to support arbitrary file operations. It can be deployed on applications' demand to avoid intervention with other applications. Experimental results on micro-benchmarks and real-world applications show that CprFS introduces acceptable overhead and has little impact on checkpointing systems.
Automatic Target Detection and Tracking in FLIR Image Sequences Using Morphological Connected Operator

In this paper, we propose a method for detecting and tracking small targets in forward looking infrared (FLIR) image sequences taken from an airborne moving platform. Firstly, we adopt the morphological connected operator to remove the undesirable clutter in the background. Secondly, the image is decomposed by morphological Haar wavelet, and the wavelet energy image is computed from the horizontal and vertical detail images, and it is fused with the scaled image. Thirdly, the targets are extracted coarse-to-fine by adaptive double thresholding. Finally, targets are modeled by intensity probabilistic density function and tracked using mean shift algorithm. The experiments performed on the AMCOM FLIR data set verify the validity and robustness of the algorithm.
Novasky: Cinematic-quality VoD in a P2P storage cloud

In this paper, we present Novasky, a real-world Video-on-Demand (VoD) system capable of delivering cinematic-quality video streams to end users. The foundation of the Novasky design is a peer-to-peer (P2P) storage cloud, storing and refreshing media streams in a decentralized fashion using local storage spaces of end users. We present our design objectives in Novasky, and how these objectives are achieved using a collection of unique mechanisms, with respect to caching strategies, coding mechanisms, and the maintenance of the supply-demand relationship when it comes to media availability in the P2P storage cloud. The production Novasky system has been implemented with over 100,000 lines of code. It has been deployed in the Tsinghua University campus network, operational since September 2009, attracting 10,000 users to date, and providing over 1,000 cinematic-quality video streams with bit rates of 1 – 2 Mbps. Based on real-world traces collected over 6 months, we show that Novasky can achieve rapid startups within 4 – 9 seconds, and extremely short seek latencies within 3 seconds. Our empirical experiences with Novasky may bring valuable insights to future designs of production-quality P2P storage cloud systems.
Learning of Multi-Modal Stimuli in Hawkmoths

The hawkmoth, Manduca sexta, uses both colour and odour to find flowers when foraging for nectar. In the present study we investigated how vision and olfaction interact during learning. Manduca sexta were equally attracted to a scented blue coloured feeding target (multimodal stimulus) as to one that does not carry any scent (unimodal stimulus; visual) or to an invisible scented target (unimodal stimulus; odour). This naive attraction to multimodal as well as to unimodal stimuli could be manipulated through training. Moths trained to feed from a blue, scented multimodal feeding target will, when tested in a set-up containing all three feeding targets, select the multimodal target as well as the scented, unimodal target, but ignore the visual target. Interestingly, moths trained to feed from a blue, unimodal visual feeding target will select the visual target as well as the scented, multimodal target, but ignore the unimodal odour target. Our results indicate that a multimodal target is perceived as two separate modalities, colour and odour, rather than as a unique fused target. These findings differ from earlier studies of desert ants that perceive combined visual and odour signals as a unique fused stimulus following learning trials.
Statistical theory of intermittency in a multi-scale model of MHD and micro-turbulence

Traditionally the effects of MHD instabilities and micro-instabilities on plasma confinement are investigated separately. However, these two instabilities often occur simultaneously, with the overlap of the dynamics on a broad range of spatial scales. It is thus vital to incorporate these instabilities consistently by a proper multi-scale modeling. Furthermore, there has been an overwhelming evidence that the overall transport of heat and particles is significantly influenced by intermittency (or bursty events) caused by coherent structures. A crucial question in plasma confinement is thus the prediction of the probability distribution functions (PDFs) of the transport due to these structures and of their formation. In this paper, we investigate intermittent transport in a multi-scale model by consistently incorporating both tearing instabilities and micro-instability due to pressure gradient.
Local color transfer via probabilistic segmentation by expectation-maximization

We address the problem of regional color transfer between two natural images by probabilistic segmentation. We use a new expectation-maximization (EM) scheme to impose both spatial and color smoothness to infer natural connectivity among pixels. Unlike previous work, our method takes local color information into consideration, and segment image with soft region boundaries for seamless color transfer and compositing. Our modified EM method has two advantages in color manipulation: first, subject to different levels of color smoothness in image space, our algorithm produces an optimal number of regions upon convergence, where the color statistics in each region can be adequately characterized by a component of a Gaussian mixture model (GMM). Second, we allow a pixel to fall in several regions according to our estimated probability distribution in the EM step, resulting in a transparency-like ratio for compositing different regions seamlessly. Hence, natural color transition across regions can be achieved, where the necessary intra-region and inter-region smoothness are enforced without losing original details. We demonstrate results on a variety of applications including image deblurring, enhanced color transfer, and colorizing gray scale images. Comparisons with previous methods are also presented.
New Ultra-High-Isolation RF Switch Architecture and Its Use for a 10–38-GHz 0.18-$\mu$m BiCMOS Ultra-Wideband Switch

A new RF switch architecture with ultrahigh isolation and possible gain is proposed, analyzed, and demonstrated using 0.18-μm BiCMOS technology. The new RF switch architecture achieves an ultrahigh isolation through implementation of a new RF leaking cancellation technique in which the RF leaking signal is suppressed by combining with its replica using a balun. Its isolation is substantially higher than that produced by a conventional switch topology. An analysis of the new active balun employed in the proposed RF switch is also conducted, showing its distinguished characteristic of good balance across ultra-wide frequency ranges, making possible not only the achievement of extremely high isolation, but also ultra-wideband isolation for the RF switch. Additionally, the active balun also provides some gain to compensate for the inherent loss of the RF switch. The newly designed 0.18-μm BiCMOS RF switch exhibits an ultra-broadband performance from 10 to 38 GHz with - 2.6-dB loss to 0.4-dB gain, isolation from 40 to about 70 dB, and input return loss from 8 to 20 dB under small-signal conditions. Within 35.5-38.5 GHz, its isolation reaches extremely high values, with the highest isolation around 70 dB at 36 GHz, approaching the measurable limit of the vector network analyzer. Measured insertion loss and isolation under large-signal conditions at 35 GHz show around 1-2 and 51.5 dB, respectively. The RF switch consumes a dc current of only 8 mA from a 1.8-V source. The extremely high isolation achievable by the new RF switch demonstrates the possibility of pushing RF system performance limited by switch isolation to a next level.
Addressing credential revocation in grid environments

Credential revocation is a critical problem in grid environments and remains unaddressed in existing grid security solutions. We present our ongoing work in designing a novel grid authentication system, based on Globus GSI, that solves the revocation problem. The focus of this work is to ensure instantaneous revocation of both long-term digital identities of hosts/users and short-lived identities of user proxies. Our system employs mediated RSA (mRSA), adapts Boneh's notion of semi-trusted mediators to suit security in virtual organizations and propagates proxy revocation information as in Micali's NOVO-MODO system. We envision that our system would additionally provide a configuration-free security model for end users and fine-grained management of user credentials.
De-Identification of Clinical Free Text in Dutch with Limited Training Data: A Case Study

In order to analyse the information present in medical records while maintaining patient privacy, there is a basic need for techniques to automatically de-identify the free text information in these records. This paper presents a machine learning deidentification system for clinical free text in Dutch, relying on best practices from the state of the art in de-identification of English-language texts. We combine string and pattern matching features with machine learning algorithms and compare performance of three different experimental setups using Support Vector Machines and Random Forests on a limited data set of one hundred manually obfuscated texts provided by Antwerp University Hospital (UZA). The setup with the best balance in precision and recall during development was tested on an unseen set of raw clinical texts and evaluated manually at the hospital site.
Recovery of the star formation history of the LMC from the VISTA survey of the Magellanic system

The VISTA near infrared survey of the Magellanic System (VMC) will provide deep YJKs photometry reaching stars in the oldest turn-off point throughout the Magellanic Clouds (MCs). As part of the preparation for the survey, we aim to access the accuracy in the star formation history (SFH) that can be expected from VMC data, in particular for the Large Magellanic Cloud (LMC). To this aim, we first simulate VMC images containing not only the LMC stellar populations but also the foreground Milky Way (MW) stars and background galaxies. The simulations cover the whole range of density of LMC field stars. We then perform aperture photometry over these simulated images, access the expected levels of photometric errors and incompleteness, and apply the classical technique of SFH-recovery based on the reconstruction of colour-magnitude diagrams (CMD) via the minimisation of a chi-squared-like statistics. We verify that the foreground MW stars are accurately recovered by the minimisation algorithms, whereas the background galaxies can be largely eliminated from the CMD analysis due to their particular colours and morphologies. We then evaluate the expected errors in the recovered star formation rate as a function of stellar age, SFR(t), starting from models with a known age–metallicity relation (AMR). It turns out that, for a given sky area, the random errors for ages older than ∼0.4 Gyr seem to be independent of the crowding. This can be explained by a counterbalancing effect between the loss of stars from a decrease in the completeness and the gain of stars from an increase in the stellar density. For a spatial resolution of ∼0. 1d eg 2 , the random errors in SFR(t) will be below 20% for this wide range of ages. On the other hand, due to the lower stellar statistics for stars younger than ∼0.4 Gyr, the outer LMC regions will require larger areas to achieve the same level of accuracy in the SFR(t). If we consider the AMR as unknown, the SFHrecovery algorithm is able to accurately recover the input AMR, at the price of an increase of random errors in the SFR(t) by a factor of about 2.5. Experiments of SFH-recovery performed for varying distance modulus and reddening indicate that these parameters can be determined with (relative) accuracies of Δ(m−M)0 ∼ 0.02 mag and ΔEB−V ∼ 0.01 mag, for each individual field over the LMC. The propagation of these errors in the SFR(t) implies systematic errors below 30%. This level of accuracy in the SFR(t) can reveal significant imprints in the dynamical evolution of this unique and nearby stellar system, as well as possible signatures of the past interaction between the MCs and the MW.
Disturbed Flow Promotes Endothelial Senescence via a p53-Dependent Pathway

Objective—Although atherosclerosis is associated with systemic risk factors such as age, high cholesterol, and obesity, plaque formation occurs predominately at branches and bends that are exposed to disturbed patterns of blood flow. The molecular mechanisms that link disturbed flow–generated mechanical forces with arterial injury are uncertain. To illuminate them, we investigated the effects of flow on endothelial cell (EC) senescence. Approach and Results—LDLR−/− (low-density lipoprotein receptor−/−) mice were exposed to a high-fat diet for 2 to 12 weeks (or to a normal chow diet as a control) before the assessment of cellular senescence in aortic ECs. En face staining revealed that senescence-associated &bgr;-galactosidase activity and p53 expression were elevated in ECs at sites of disturbed flow in response to a high-fat diet. By contrast, ECs exposed to undisturbed flow did not express senescence-associated &bgr;-galactosidase or p53. Studies of aortae from healthy pigs (aged 6 months) also revealed enhanced senescence-associated &bgr;-galactosidase staining at sites of disturbed flow. These data suggest that senescent ECs accumulate at disturbed flow sites during atherogenesis. We used in vitro flow systems to examine whether a causal relationship exists between flow and EC senescence. Exposure of cultured ECs to flow (using either an orbital shaker or a syringe-pump flow bioreactor) revealed that disturbed flow promoted EC senescence compared with static conditions, whereas undisturbed flow reduced senescence. Gene silencing studies demonstrated that disturbed flow induced EC senescence via a p53-p21 signaling pathway. Disturbed flow–induced senescent ECs exhibited reduced migration compared with nonsenescent ECs in a scratch wound closure assay, and thus may be defective for arterial repair. However, pharmacological activation of sirtuin 1 (using resveratrol or SRT1720) protected ECs from disturbed flow–induced senescence. Conclusions—Disturbed flow promotes endothelial senescence via a p53-p21–dependent pathway which can be inhibited by activation of sirtuin 1. These observations support the principle that pharmacological activation of sirtuin 1 may promote cardiovascular health by suppressing EC senescence at atheroprone sites.