Miracle-dz/UniFAR-FTUs huggingface dataset:
A local feature based compensation scheme for unsmooth video coding

In this paper, a local feature based compensation scheme is proposed for unsmooth video coding. Unlike natural video sequences, video sequences captured by mobile device, often have unsmooth changes, which makes the scene content have a sharp change in geometric deformation and photometric transformation. Unfortunately, the unsmooth changes are often difficult to be reduced by block motion compensation. Different from the method used in the traditional video coding scheme, this paper proposes a novel local feature based compensation scheme utilizing the technology of multi-reference frames motion compensation. Firstly the geometric distortions are eliminated through geometric model estimation utilizing the correlations between the current encoding frame and the frames in reference buffers. Then we obtain the deformed prediction frame through the photometric transformation module to compensate the illumination changes. Finally, the predicted frames are substituted into the reference buffers for video encoding. Experiments show that the proposed method can achieve better video quality with lower stream compared with the traditional method.
Wavelet Analysis of Business Cycles for validation of Probability of Default : How does the current credit crunch in fl ue nc es mo de l validation ?

According to Basel II, the Probability of Default (PD) should be a long-term average of 1-year default rates. In this paper, long term is interpreted as one business cycle. When the PD is compared with the actual observed default rates in the PD rating validation process, two questions are relevant: how long is a business cycle and where are we in the business cycle? We present two techniques in order to address these questions: Fourier analysis and wavelet analysis. The analysis of default rates in the period 1981-2007 from Standard & Poors reveals two business cycles of 10.67 years.
Integrated electromyography visualization with multi temporal resolution

For the analysis and comparison of electromyography (EMG) signals from different patients, standardization techniques are used to calculate the integrated EMG signal (iEMG), useful to evaluate the level of activity of different muscles. The iEMG corresponds to the area under the rectified curve (AUC). Currently, monitoring and follow-up of these patients is done in regular health exams where the evolution of patients is assessed. The monitoring includes performing multiple clinical trials. The goal of this paper is to help medical staff assessing the evolution of amyotrophic lateral sclerosis (ALS) disease by analyzing the collected data. The signal, described by the electromyogram, can be measured applying conductive elements or electrodes to the skin surface. The electrical activity of skeletal muscles is continuously measured for at least 24 hours. In this work we used an appropriate data model to store data generated by EMGs, optimized for analytical processing. We implemented aWeb API in order to provide access to the model data in an agnostic way, both to database management systems and data consumers. We implemented a web application to visualize data through the use of several interactive charts. Usability testing helped to validate the solution, confirming the ease of use of the web application and the fulfillment of all the proposed goals. The telemonitoring ALS patients doesn't change mortality but reduces the need for hospitalization and costs for patient.
Predictive Regressions with Time-Varying Coefficients

We evaluate predictive regressions that explicitly consider the time-variation of coefficients in a comprehensive Bayesian framework. For monthly returns of the S&P 500 index, we demonstrate statistical as well as economic evidence of out-of-sample predictability: relative to an investor using the historic mean, an investor using our methodology could have earned consistently positive utility gains (between 1.8% and 5.8% per year over different time periods). We also find that predictive models with constant coefficients are dominated by models with time-varying coefficients. Finally, we show a strong link between out-of-sample predictability and the business cycle.
Collaborative discovery in a simple reasoning task Action editor :

In psychological experimental studies on scientific discovery, discussions have been made on the effects of collaborative discovery using simple experimental tasks, such as Wason s 2-4-6 task. Generally speaking, however, these studies have not explained the prominent effects of multiple subjects collaboratively discovering a target. In the present study, we identify situations in which the effects of collaboration emerge, and why they emerge, by combining a computer simulation method that employs our computational model as a cognitive simulator with a method based on laboratory studies. We basically control two factors, i.e. the hypothesis-testing strategy used by the subjects and the nature of the target that the subjects are required to find, both of which have been identified by previous psychological studies as key factors determining the subjects performance. The computer simulations show that the performance of combined two systems in collaborative discovery exceeds that of each system in independent discovery, but only when the two systems try to find a target having the nature of generality by repeatedly conducting a positive test. This finding is also confirmed by psychological experiments designed to verify the computer simulations. Moreover, through a theoretical analysis, we show that this effect of collaboration is provided by the emergence of negative tests from the interaction of the two systems (or humans) repeating only a positive test. 2003 Elsevier B.V. All rights reserved.
Coexistence of QoS and Best-Effort Flows - Routing and Scheduling

The future high-speed networks will need to support diverse tra(cid:14)c and provide services to (cid:13)ows with Quality of Service (QoS) requirements as well as to best e(cid:11)ort (cid:13)ows. In this paper we analyze the coexistence of the QoS and best e(cid:11)ort (cid:13)ows from the routing and scheduling point of view. We concentrate in our routing and scheduling analysis on the network bandwidth resource. We present two sets of source routing algorithms: (1) the bandwidth-constrained routing with imprecise state information for QoS (cid:13)ows, and (2) the maxmin fair routing for best e(cid:11)ort (cid:13)ows. The routing analysis includes an extensive description of various algorithms in their domains and their complexity discussion. Furthermore, we discuss two level hierarchical scheduling which is tailored towards the needs raised by the coexistence of QoS and best e(cid:11)ort (cid:13)ows. We show that this scheduling design accomplishes two de-sign goals (1) guaranteeing QoS for QoS (cid:13)ows and (2) ensuring fairness for best e(cid:11)ort (cid:13)ows, and the overhead is reasonably smalland comparable with the time complexity of the single-level fair queuing scheduling.
An economic analysis of cartel behavior within the NCAA.

The goal of this paper was to analyze the cartel behavior of the National Collegiate Athletic Association. The NCAA, with over 1,000 members, has overseen intercollegiate athletic competition and established rules of play. In addition, the NCAA has maintained a cartel agreement to maximize profits for its members. However, to maintain a cartel, the expected costs of violating the agreement must be greater than the expected benefits of violation. Within this paper, an economic model using NCAA Division I men's basketball tournament revenue data was developed to determine when teams had an incentive to violate the cartel agreement—that is, commit a rules violation. Tournament revenue data from 1982 to 1990 was obtained for teams in six conferences (Big East, Big 10, Pacific 10, Southeastern; Atlantic Coast, and Big 8). The economic model revealed that teams in the Big East, Big 10, and Pacific 10 conferences had the greatest financial incentive to violate NCAA regulations. The information provided in this p.
Cassini RADAR Sequence Planning and Instrument Performance

The Cassini RADAR is a multimode instrument used to map the surface of Titan, the atmosphere of Saturn, the Saturn ring system, and to explore the properties of the icy satellites. Four different active mode bandwidths and a passive radiometer mode provide a wide range of flexibility in taking measurements. The scatterometer mode is used for real aperture imaging of Titan, high-altitude (around 20 000 km) synthetic aperture imaging of Titan and Iapetus, and long range (up to 700 000 km) detection of disk integrated albedos for satellites in the Saturn system. Two SAR modes are used for high- and medium-resolution (300-1000 m) imaging of Titan's surface during close flybys. A high-bandwidth altimeter mode is used for topographic profiling in selected areas with a range resolution of about 35 m. The passive radiometer mode is used to map emission from Titan, from Saturn's atmosphere, from the rings, and from the icy satellites. Repeated scans with differing polarizations using both active and passive data provide data that can usefully constrain models of surface composition and structure. The radar and radiometer receivers show very good stability, and calibration observations have provided an absolute calibration good to about 1.3 dB. Relative uncertainties within a pass and between passes can be even smaller. Data are currently being processed and delivered to the planetary data system at quarterly intervals one year after being acquired.
Integration of Synchronous Input in Dentate Granule Cells ... Integration of Synchronous Input in Dentate Granule Cells ..... Clustered Input Is Integrated Linearly with a Gain

is stable over a larger range of ∆t, indicating that the propagation of EPSPs from the dendritic sites to the soma increases the integration time window for EPSP summation (fig. 3.8d). We observed very similar properties in the computational model with application of identical compound mock EPSCs (virtual recording sites indicated in fig. 3.9a, example traces in fig. 3.9b, analysis of the three model granule cells in fig. 3.9c, d). This property of granule cell dendrites arises because the fast rising phases of either compound EPSPs with a high degree of synchrony (∆t ≈ 0 ms) or those of individual EPSPs with very low synchrony (∆t > 50 ms) are particularly strongly filtered during propagation to the soma. In contrast, the overall rising phases of compound EPSPs with intermediate synchrony are slower, and are therefore attenuated less. These results establish that the frequency-dependent properties of thin granule cell dendrites render EPSP summation less sensitive to input synchrony by increasing the somatic time window for temporal integration of synaptic input. Whereas the results so far shed light on the voltage transfer properties of granule cell dendrites, they do not allow insights into the processing of spatiotemporal input patterns mediated by the release of glutamate. We therefore used multisite two-photon uncaging of MNI-caged-glutamate to explore how granule cell dendrites integrate synchronous synaptic inputs. We measured the summation of uncaging-evoked excitatory postsynaptic potentials (gluEPSPs, amplitudes and rise times of gluEPSPs are independent of distance of the uncaging sites, fig. 3.10) evoked by stimulation of up to 13 spines on individual dendritic branches (fig. 3.11). Stimulating increasing numbers of inputs with a high degree of synchrony resulted in a monotonic increase in the magnitude of the resulting gluEPSPs (fig. 3.11b, c). We examined this summation of individual gluEPSPs further by comparing the measured gluEPSPs to the expected magnitude of EPSPs derived as the arithmetic sum of the individual single spine gluEPSPs (fig. 3.11c). Dendritic branches in granule cells exhibited a linear summation of gluEPSPs with gain in most branches (individual example in
TNeT: Tensor-Based Neighborhood Discovery in Traffic Networks

Traffic networks comprise of sensors monitoring large numbers of roadways and highways with multiple lanes. Data from such sensors can be used for various monitoring tasks such as identifying high usage roads, traffic congestion and HOV lane demarcations. In this paper we propose a method to identify spatial and temporal neighborhoods in such traffic sensor networks. This approach can be used to demarcate HOV lane restrictions at certain time periods and at certain key locations on heavy usage highways. In many cases HOV lane restrictions are dynamic and our approach can provide automatic input to which time periods and locations should be designated as HOV lanes. We propose a spatio-temporal representation model for traffic networks, which models the spatio-temporal data using high-order tensor instead of the traditional vector model. We use tensor operations and tools, such as the High-order Singular Value Decomposition(HOSVD) for dimension reduction. Subsequently, a traditional clustering algorithm such as k-means is applied in the tensor subspace. For temporal neighborhood discovery we apply K-means to the subspace of time. Similarly, for spatial neighborhoods we apply K-means to the subspace of space. In real world traffic data we found that tensor based representations produce much more accurate results than traditional models. In this paper our focus is on traffic datasets which are typically spatio-temporal in nature as they measure a phenomenon at a particular location over a period of time, however this approach is generalizable to other spatiotemporal datasets as well.
Robust constrained model predictive control for linear time-varying systems with norm-bounded uncertainty

In this paper, we propose a robust constrained model predictive control (RCMPC) for stabilizing processes with norm-bounded uncertainty. This type of uncertainty is used to avoid on-line computational burdens. The robust stability comes with a guarantee described by parameter-dependent Lyapunov function (PDLF). The control law based on PDLF is potentially less conservative than that based on single Lyapunov function (SLF), due to additional degree of freedom. We give numerical examples based on a single non-isothermal CSTR system to illustrate the effectiveness of this algorithm.
Alertwheel: radial bipartite graph visualization applied to intrusion detection system alerts

Intrusion detection systems, or IDSs, are network security tools that generate huge quantities of information which are challenging to analyze. Information visualization is essential for efficiently parsing these data to discover the underlying causes of computer security breaches. AlertWheel is a user interface featuring a novel radial overview visualization, as well as filtering, drilling down, and saving and annotating subsets of data, to support the workflow of real network defense analysts. In designing AlertWheel, we identified new ways of displaying bipartite graphs (i.e., network diagrams showing links between two sets of nodes). The links in AlertWheel's visualizations are positioned and shaped to avoid occlusion of data, and three different edge bundling techniques are used to reduce clutter.
A Strategic, Area-wide Contingency Planning Model for Oil Spill Cleanup Operations with Application Demonstrated to the Galveston Bay Area*

This paper develops a general integer programming model for strategic, area-wide contingency planning of oil spill cleanup operations. Model inputs include the set of risk points and the likely spill scenarios and response requirements for each, the sites of existing storage locations and the inventory of components at each, and potential sites for new storage locations. The model prescribes a minimum total cost plan to either build new storage locations, expand existing ones, or both, to purchase new components and pre-position them, and a contingency plan that determines which response systems should be composed to enable an effective time-phased response for each likely spill scenario. A family of heuristics based on linear programming (LP) is devised to resolve this strategic problem, providing an area-wide contingency plan. The heuristics are evaluated on a set of 10 test problems that involve 1869 general integer variables and 3264 constraints. Computational tests indicate that four heuristics are quite effective, prescribing solutions for each of 10 test cases within 1.41% of optimum and within a few minutes runtime. This study focused on modeling the Galveston Bay Area, and the test problems represent application in that area. A sensitivity analysis is demonstrated by assessing the impacts of component availability and the degradation of cleanup capability over time. Use of the model as a decision support aid by responsible parties, contractors, governmental organizations and others is described.
The energetic benefits of tendon springs in running: is the reduction of muscle work important?

The distal muscle-tendon units of cursorial species are commonly composed of short muscle fibres and long, compliant tendons. It is assumed that the ability of these tendons to store and return mechanical energy over the course of a stride, thus avoiding the cyclic absorption and regeneration of mechanical energy by active muscle, offers some metabolic energy savings during running. However, this assumption has not been tested directly. We used muscle ergometry and myothermic measurements to determine the cost of force production in muscles acting isometrically, as they could if mechanical energy was stored and returned by tendon, and undergoing active stretch–shorten cycles, as they would if mechanical energy was absorbed and regenerated by muscle. We found no detectable difference in the cost of force production in isometric cycles compared with stretch–shorten cycles. This result suggests that replacing muscle stretch–shorten work with tendon elastic energy storage and recovery does not reduce the cost of force production. This calls into question the assumption that reduction of muscle work drove the evolution of long distal tendons. We propose that the energetic benefits of tendons are derived primarily from their effect on muscle and limb architecture rather than their ability to reduce the cyclic work of muscle.
Energy-Efficient Multiuser MIMO Downlink Transmissions in Massively Distributed Antenna Systems with Predefined Capacity Constraints

Massively distributed antenna system is a promising architecture to enhance the system performance in future broadband wireless access beyond the Long Term Evolution (LTE) and Long Term Evolution Advanced (LTE-A) standards. Reduction of the power consumption of such systems is an important issue in their practical realization. This paper presents a technique to optimize the power consumed by a massively distributed antenna system in a multiuser downlink scenario subjected to throughput constraints. More specifically, the power consumed under the target sum-capacity constraint is optimized. We use zero-force beam forming scheme to simplify our analysis and derive optimal rate allocation among the users. Simulation results confirm that the energy consumption can be reduced considerably while the throughput constraint is satisfied.
Enhanced experimental metastasis of ultraviolet light-induced fibrosarcomas in ultraviolet light-irradiated syngeneic mice.

Some ultraviolet light (UV)-induced fibrosarcomas produce more experimental pulmonary tumor colonies in UV-irradiated hosts than in normal syngeneic recipients. The number of experimental metastases produced following i.v. injection of these tumors increases in proportion to the dose of UV radiation. This enhancement can be transferred with lymphoid cells to lethally X-irradiated recipients and with partially purified T-lymphocytes to untreated syngeneic mice. Some UV-induced fibrosarcomas do not form experimental metastases readily, even in UV-irradiated recipients, suggesting that both immunological and nonimmunological factors are important in limiting metastasis formation.
Using Tiny Trusted Third Parties to Enhance Secure Two-Party Computations

Secure Multiparty Computation (SMC), in its many forms, has received theoretical attention for more than two decades, yielding many protocols for many settings. One common thread is that the protocols cannot in actuality use a Trusted Third Party (TTP), even though this is conceptually the simplest and most general way to solve SMC problems. Thus, current protocols involve only the direct players (who do not trust each other), and incur a cost which is sometimes considerable. Recent work in practical security has seen the development of devices intended to be used as actually trustworthy third parties, namely the secure coprocessor (SCop), like the IBM 4758. This opens the door for a different approach to SMC problems, utilizing these new TTPs. One major challenge is executing large programs on large inputs using a TTP with very limited protected memory (which can be adequately shielded), and a slow processor, while preserving the trust properties that an ideal TTP provides. We propose to investigate the use of real TTPs to help with the solution of SMC problems. We would like to investigate in particular the balance between solutions which do not use a TTP (and so have access to fast processing with large memory) and those which do (and so avoid some of the algorithmic overheads of the other solutions). We have already investigated the use of such TTPs to solve the Private Information Retrieval (PIR) problem, which is one important instance of SMC. The rest of the thesis will be targeted at general SMC, which is currently solved by blinding a boolean circuit which computes the desired function. This approach has several sources of overhead, some due to the circuit representation and some due to the blinding. We propose to investigate how moving some functionality into a SCop TTP, and thus avoiding the blinded circuit overhead, can improve the performance of existing SMC solutions. Recently a prototype system for general secure two-party computation, Fairplay, has been developed, which we can use as a starting point and also as a point of reference for performance analysis. Since limited memory size appears to be a salient feature of highly trustworthy devices (and certainly a feature of current high-end devices), we are basing all our designs on the assumption that the protected memory is tiny. This should allow less expensive devices to be used. We have outlined how a new-generation tiny TTP can be optimized for a common class of bottleneck algorithms used in TTP-assisted SMC applications. We expect a speed improvement of several orders of magnitude over the 4758, in a very small device. We will next build an initial FPGA prototype of such a tiny TTP, and report on its performance and size. ∗Advised by Sean Smith