Miracle-dz/UniFAR-FTUs huggingface dataset:
Toshiba at TRECVID 2009: Surveillance Event Detection Task

In this paper, we describe the Toshiba event detection system for TRECVID surveillance event detection task [1] that detects three TRECVID required events (E05:PersonRuns, E19:ElevatorNoEntry, and E20:OpposingFlow). Our system (“Toshiba_1 p-cohog_1”) consists of four components: (1) robust change detection based on the combination of pixel intensity histogram, PTESC (Peripheral TErnary Sign Correlation), and PrBPRRC (Probabilistic Bi-polar Radial Reach Correlation) that is robust against illumination changes and background movements, (2) human detection using the CoHOG (Co-occurrence Histograms of Oriented Gradients) feature that outperforms the one using the HOG (Histogram of Oriented Gradient) feature, (3) human tracking using linear estimation and color histogram matching, and (4) event detection based on change detection and human tracking. We briefly describe the four components.
Statistical Dialog Management Methodologies for Real Applications

In this paper we present a proposal for the development of dialog systems that, on the one hand, takes into account the benefits of using standards like VoiceXML, whilst on the other, includes a statistical dialog module to avoid the effort of manually defining the dialog strategy. This module is trained using a labeled dialog corpus, and selects the next system response considering a classification process that takes into account the dialog history. Thus, system developers only need to define a set of VoiceXML files, each including a system prompt and the associated grammar to recognize the users responses to the prompt. We have applied this technique to develop a dialog system in VoiceXML that provides railway information in Spanish.
Switching types of drug-eluting stents does not prevent repeated in-stent restenosis in patients with coronary drug-eluting stent restenosis

ObjectivesWe treated patients experiencing drug-eluting stent (DES) restenosis with plain old balloon angioplasty (POBA), implantation of the same type of DES [homogeneous drug-eluting stent (HOMO-DES)], or implantation of a different type of DES [heterogeneous drug-eluting stent (HETERO-DES)], and compared the efficacy and safety of these procedures for the prevention of repeated in-stent restenosis (ISR). BackgroundIn patients with de-novo coronary lesions, DES implantation is associated with a markedly reduced restenosis rate as compared with that associated with a bare metal stent and POBA. However, the optimal management strategy for patients with DES ISR remains unknown. Patients and methodsWe identified 191 consecutive DES ISR lesions from 183 patients who required clinically driven revascularization and divided them into three groups according to the treatment: 38 lesions were treated with POBA, 38 with HOMO-DES, and 115 with HETERO-DES. ResultsThe incidence of target lesion revascularization (TLR) was 42.1% (16/38), 15.8% (6/38), and 16.5% (19/115) in the POBA, HOMO-DES, and HETERO-DES groups (POBA vs. HOMO, HETERO-DES; P=0.002, respectively). Multivariate analysis indicated that diabetes [odds ratio (OR), 3.4], hemodialysis (OR, 7.74), nonfocal ISR patterns (OR, 3.35), previous myocardial infarction (OR, 3.26), and POBA (OR, 8.84) were independent predictors of TLR. ConclusionA strategy involving repeated DES implantation was superior to POBA for preventing recurrent restenosis. Treatment with a different type or generation of DES does not appear to reduce the incidence of TLR. Moreover, we identified certain useful factors for facilitating appropriate and early triage in the patients with repeated DES ISR.
Elastic correction of dead-reckoning errors in map building

A major problem in map building is due to the imprecision of sensor measures. In this paper we propose a technique, called elastic correction, for correcting the dead-reckoning errors made during the exploration of an unknown environment by a robot capable of identifying landmarks. Knowledge of the environment being acquired is modelled by a relational graph whose vertices and arcs represent, respectively, landmarks and inter-landmark routes. Elastic correction is based on an analogy between this graph and a mechanical structure: the map is regarded as a truss where each route is an elastic bar and each landmark a node. Errors are corrected as a result of the deformations induced from the forces arising within the structure as inconsistent measures are taken. The uncertainty on odometry is modelled by the elasticity parameters characterizing the structure.
Multi-sensor optimal robust information fusion for uncertain systems with colored noises

A problem of multi-sensor robust information fusion for uncertain systems with colored noises is investigated. A new multi-sensor optimal information fusion steady-state robust filter weighted by matrix and scalars with uncertain parameters is given using robust filter theory based on linear least variance information fusion criterion. Compared with existing filter, the proposed robust steady-state filter considers the perturbation factor in the solution to the weighting matrices, the optimal parameter and the filter. Simulation example shows the effectiveness of the proposed method.
Evolution of natural-resource taxation in developing countries

This paper examines the long-term evolution of objectives and instruments of taxation of non-renewable natural-resource endowments in a wide spectrum of developing countries other than Mid-East oil exporters. A comparison of the function and effects of private-sector transnational corporations (TNCs), production-sharing contracts (PSCs) and other instruments in several less-developed countries (LDCs) finds differences that amount to little more than differences in labeling. 98 references, 1 table.
Going to Brussels: A Population Perspective on Interest Representation in the EU

In this paper, we propose a new research strategy to better link interest representation studies to the study of European Integration. To assess the role of interest groups in European integration, we need comparative research designs to systematically vary contextual factors that shape the role of interest groups in a democracy. We develop a new comparative research strategy by focusing on organizational diversity of interest group populations. We define organizational diversity in terms of a policy orientation (i.e. the exercise of influence) and the means employed (i.e. participation of members). Based on a comparison of EU and a Dutch sample of interest groups, we find that membership orientation seems to be more important at the national level and that a policy orientation is more important at the EU level. We find that interest group activity is important throughout a wide range of policy domains and varies in terms of interests across national and European areas of competence. The business bias at the EU-level may be less normatively problematic given the inherent systemic characteristics of the EU. Our results confirm the usefulness of our research strategy in developing comparative designs in interest representation research and may be a start in building bridges between two important yet separate studies of EU policy making.
Preserving structural properties in anonymization of social networks

A social network is a collection of social entities and the relations among them. Collection and sharing of such network data for analysis raise significant privacy concerns for the involved individuals, especially when human users are involved. To address such privacy concerns, several techniques, such as k-anonymity based approaches, have been proposed in the literature. However, such approaches introduce a large amount of distortion to the original social network graphs, thus raising serious questions about their utility for useful social network analysis. Consequently, these techniques may never be applied in practice. In this paper, we emphasize the use of network structural semantics in the social network analysis theory to address this problem. We propose an approach for enhancing anonymization techniques that preserves the structural semantics of the original social network by using the notion of roles and positions. We present experimental results that demonstrate that our approach can significantly help in preserving graph and social network theoretic properties of the original social networks, and hence improve utility of the anonymized data.
The impact of the European Union on foreign policy-making in Hungary, Romania and Slovakia: institutional adaptation, learning and socialization

This article discusses the influence of the process of European integration on the foreign policy-making in the new member states from Central and Eastern Europe, using as case-studies Hungary, Romania and Slovakia. The impact of the integration process is examined from an institutionalist perspective. The paper is especially interested in the institutional change of the coordination of foreign policy-making at both national and European levels, and on the process of learning and socialization of national representatives participating and interacting with the EU system of foreign policy.
Functional transformations of odor inputs in the mouse olfactory bulb

Sensory inputs from the nasal epithelium to the olfactory bulb (OB) are organized as a discrete map in the glomerular layer (GL). This map is then modulated by distinct types of local neurons and transmitted to higher brain areas via mitral and tufted cells. Little is known about the functional organization of the circuits downstream of glomeruli. We used in vivo two-photon calcium imaging for large scale functional mapping of distinct neuronal populations in the mouse OB, at single cell resolution. Specifically, we imaged odor responses of mitral cells (MCs), tufted cells (TCs) and glomerular interneurons (GL-INs). Mitral cells population activity was heterogeneous and only mildly correlated with the olfactory receptor neuron (ORN) inputs, supporting the view that discrete input maps undergo significant transformations at the output level of the OB. In contrast, population activity profiles of TCs were dense, and highly correlated with the odor inputs in both space and time. Glomerular interneurons were also highly correlated with the ORN inputs, but showed higher activation thresholds suggesting that these neurons are driven by strongly activated glomeruli. Temporally, upon persistent odor exposure, TCs quickly adapted. In contrast, both MCs and GL-INs showed diverse temporal response patterns, suggesting that GL-INs could contribute to the transformations MCs undergo at slow time scales. Our data suggest that sensory odor maps are transformed by TCs and MCs in different ways forming two distinct and parallel information streams.
Semiclassicality and decoherence of cosmological perturbations

Transition to the semiclassical behaviour and the decoherence process for inhomogeneous perturbations generated from the vacuum state during an inflationary stage in the early Universe are considered in both the Heisenberg and the Schrodinger representations to show explicitly that both approaches lead to the same prediction: the equivalence of these quantum perturbations to classical perturbations having stochastic Gaussian amplitudes and belonging to the quasi-isotropic mode. This equivalence and the decoherence are achieved once the exponentially small (in terms of the squeezing parameter ) decaying mode is neglected. In the quasi-classical limit , the perturbation mode functions can be made real by a time-independent phase rotation; this is shown to be equivalent to a fixed relation between squeezing angle and phase for all modes in the squeezed-state formalism. Though the present state of the gravitational wave background is not a squeezed quantum state in the strict sense and the squeezing parameters loose their direct meaning due to interaction with the environment and other processes, the standard predictions for the rms values of the perturbations generated during inflation are not affected by these mechanisms (at least, for scales of interest in cosmological applications). This stochastic background still occupies a small part of phase space.
Characterization of Dual Corona-Electrostatic Electrodes for Electrostatic Processes Applications

The dual corona-electrostatic electrodes consist of one or several ionizing elements (wires, needles, and blades) attached to a metallic support. This paper analyzes the characteristic features of a particular type of such electrodes and formulates recommendations on their design and utilization. The experiments focused on several models of dual corona-electrostatic electrodes, the ionizing element being the edge of a thin metallic blade. The tested devices had similar cylindrical metallic supports but blades of different sizes. Thus, it was possible to investigate the influence of electrode geometry on corona onset voltage and spark-over threshold in configurations that are specific to industrial electrostatic processes. Most of the experiments were performed by using roll-type electrostatic separators. A special experimental setup was employed for the study of the distribution of corona current density at the surface of a plate collecting electrode. For the model having the blade edge closer to the metallic support, the corona onset voltage was higher, and the corona discharge affected a smaller area at the surface of the collector. These experiments are discussed in relation with the results of the numerical analysis of the electric field generated by the different electrode configurations. At a given voltage and distance between the ionizing element and the collector, the presence of the cylindrical support diminishes the electric field at the edge of the blade and distorts the field lines. These effects were exploited in the design of the electrode system of an electrostatic separator for the recycling industry.
Efficiency droop in III-nitride LEDs: Overview and carrier lifetime analysis

Gallium Nitride based light-emitting diodes (LEDs) are on the verge of enabling mainstream solid-state lighting. Their efficiency, however, is limited by a phenomenon known as droop which quenches internal quantum efficiency at high current density. We will review recent experimental results characterizing droop, and compare them to the various theories proposed these last years to explain this phenomenon.
An empirical analysis of heavy-tails behavior of financial data: The case for power laws

This article aims at underlying the importance of a correct modelling of the heavy-tail behavior of extreme values of financial data for an accurate risk estimation. Many financial models assume that prices follow normal distributions. This is not true for real market data, as stock (log-)returns show heavy-tails. In order to overcome this, price variations can be modeled using stable distribution, but then, as shown in this study, we observe that it over-estimates the Value-at-Risk. To overcome these empirical inconsistencies for normal or stable distributions, we analyze the tail behavior of price variations and show further evidence that power-law distributions are to be considered in risk models. Indeed, the efficiency of power-law risk models is proved by comprehensive backtesting experiments on the Value-at-Risk conducted on NYSE Euronext Paris stocks over the period 2001-2011.
Target Detection and Tracking for Video Surveillance

Target detection and tracking is an important problem in the automatic surveillance system. This paper proposes a Combined Gaussian Hidden Markov Model based Kalman Filter (CGHMM-KF) scheme for tracking people in multiple camera sensor network for monitoring and tracking of target (person/vehicle) in secured area. To detect the target under different illumination conditions, HMM with Mixture of Gaussians (MoG) is adapted. The MoG estimates the background and detects the foreground and the HMM modeling technique captures the shape of the desired object from the foreground. Finally, tracking of multiple targets is done by Kalman Filter (KF) with a bounding box, indicating the location of the person even with the motion in the background. The area of coverage can be extended dynamically using multiple cameras. The proposed approach provides better detection and tracking of person even in the presence of occlusion, target miss association and multiple persons in the environment.
GENERATION OF FEMTOSECOND ELECTRON PULSES

At the Fast Neutron Research Facility (FNRF), Chiang Mai University (Thailand), the SURIYA project has been established aiming to produce femtosecond electron pulses utilizing a combination of an S-band thermionic rfgun and a magnetic bunch compressor ( -magnet). A specially designed rf-gun has been constructed to obtain optimum beam characteristics for the best bunch compression. Simulation results show that bunch lengths as short as about 50 fs rms can be expected at the experimental station. The electron bunch lengths will be determined using autocorrelation of coherent transition radiation (TR) through a Michelson interferometer. The paper discusses beam dynamics studies, design, fabrication and cold tests of the rf-gun as well as presents the project current status and forth-coming experiments.
Bayesian Online Multitask Learning of Gaussian Processes

Standard single-task kernel methods have recently been extended to the case of multitask learning in the context of regularization theory. There are experimental results, especially in biomedicine, showing the benefit of the multitask approach compared to the single-task one. However, a possible drawback is computational complexity. For instance, when regularization networks are used, complexity scales as the cube of the overall number of training data, which may be large when several tasks are involved. The aim of this paper is to derive an efficient computational scheme for an important class of multitask kernels. More precisely, a quadratic loss is assumed and each task consists of the sum of a common term and a task-specific one. Within a Bayesian setting, a recursive online algorithm is obtained, which updates both estimates and confidence intervals as new data become available. The algorithm is tested on two simulated problems and a real data set relative to xenobiotics administration in human patients.
Wavelet Processing Implementation in Digital Hardware

The paper describes an architecture and design of digital circuit dedicated for wavelet transform calculation, being a part of complex pattern recognition and control algorithm. The target application is artificial hand controlled by the nervous system of handicapped human, setting strict requirements on timing. Speed/size trade-off is discussed in general and in the context of this particular application. Floating point arithmetic was applied, based on the in-house developed solutions. The concept was implemented using VHDL, verified and successfully synthesized for FPGA programmable logic.
On Existence Proofs for Multiple RFID Tags

The ability to securely authenticate RFID (radio-frequency identification) tags is of paramount importance in RFID-tagged applications where the integrity of the system as well its security can be compromised by an adversary. RFID tags have resource constraints including limited memory and processing capacity which restrict utilization of cryptographic primitives that have been used in other applications. We consider the case where two or more RFID tags need to be simultaneously scanned. Juels (2004) provided a proof for the simultaneous existence of two RFID tags. Saito and Sakurai (2005) later showed the proof described in Juels (2004) to be vulnerable to `replay attack', and proposed new proofs to alleviate this problem. However, the proofs provided by Saiko and Sakurai (2005) are not immune to `replay attack. ' We propose a modified proof and provide its security analysis
A psychoacoustics based sound onset detection algorithm for polyphonic audio

We propose a new sound onset detection method using principles of psychoacoustics. Our algorithm mimics the human auditory system to detect onsets in polyphonic audio.A filterbank based processing scheme is used that allows for a more robust detection of onsets using a popular model of loudness. We show the versatility of our algorithm by evaluating itpsilas performance over a wide range of sounds.
Outage efficient strategies for network MIMO with partial CSIT

We consider a multi-cell MIMO downlink (network MIMO) where B base-stations (BS) with M antennas, connected to a central station (CS), transmit K messages to K single-antenna user terminals (UT) simultaneously. Although many works have shown the potential benefits of network MIMO, the conclusion critically depends on the underlying assumption of perfect channel state information at transmitters (CSIT). In this paper, we propose an outage-efficient strategy that requires only partial CSIT. Namely, with side information of all UT's messages and local CSIT, each BS applies zero-forcing (ZF) beamforming in a distributed manner, which creates K parallel MISO channels. Based on the statistical knowledge of these parallel channels, the CS performs a robust power allocation that jointly minimizes the outage probability of K UTs and achieves a diversity gain of B(M − K + 1) per UT. Numerical results show that even with partial CSIT network MIMO can be beneficial by providing high data rates with a sufficient reliability to individual users.
Assessing Preferential Trading Agreements Using the Sussex Framework

Preferential trading arrangements involving developing and developed countries are proliferating. These are both difficult to assess and call on scarce analytical and negotiating resources particularly but not only in developing countries. The Sussex Framework, developed with DFID support, is designed to cut through these difficulties. It is a logical framework which allows the user to set out the elements of any particular proposed agreement in a clear, rigorous and consistent way, derive a set of diagnostic statistics from readily available trade and trade barriers databases and use them to assess a set of policy ‘rules of thumb’ which will allow an over all judgement on the likely balance of economic welfare effects to be drawn. The framework deals with both shallow integration (removing border barriers) and deep integration (facilitating trade by dealing with trade-impeding factors operating behind the frontier); all in a way designed to make parsimonious use of scarce analytical and negotiating resources.
The Frequency of Langerhans Islets β-Cells Autoantibodies (Anti-GAD) in Georgian Children and Adolescents with Chronic Autoimmune Thyroiditis

Aim. Chronic autoimmune thyroiditis and type 1 diabetes mellitus are organ-specific autoimmune diseases. There is large evidence that autoimmunity against the thyroid gland in patients with type 1 diabetes mellitus is increased, but little is known about anti-islet cell autoimmune status in patients with chronic autoimmune thyroiditis. We evaluated the concentration of antibodies against glutamic acid decarboxylase (GAD) which are widely used as a diagnostic and predictive tool for type 1 diabetes mellitus, in school-aged Georgian children with chronic autoimmune thyroiditis. Methods. The frequency of anti-GAD antibodies was measured in Georgian school-aged children with chronic autoimmune thyroiditis and compared to healthy age and sex matched controls. Results. Of the 41 patients with chronic autoimmune thyroiditis 4 (9.8%) were positive for GAD antibodies. The frequency of GAD positivity in the chronic autoimmune thyroiditis group was significantly higher than in the control subjects (P = 0.036). Conclusion. In the study we found that the frequency of GAD antibody positivity in autoimmune thyroiditis patients was significantly higher (9.8%, P = 0.036) than in the control group. Our findings support the concept that patients with autoimmune thyroid disease may develop type 1 diabetes mellitus in future life.