Miracle-dz/UniFAR-FTUs huggingface dataset:
Is the Quality of Education Improving in Brazil? Some Empirical Tests from a Market Based Perspective

This paper studies the evolution of the quality of education in Brazil in the last fifty years. It begins explaining why there was a genesis of a low quality education in the country during this period and the role such bad quality may have had on its economic efficiency and development. Some tests of the hypothesis that there has been improvement in the quality of education in the last fifty years are presented. The results support the idea, but as a consequence of lack of priority on public policies and social changes, which engaged women on the labour market, there was a sensible fall in the quality of education in Brazil in the same period. This certainly increased the costs of productivity improvements and catch up, thus consisting in a serious liability for the future development of the country.
Performance Analysis of a Suprathreshold Stochastic Resonance Based Nonlinear Detector

In this paper we introduce a nonlinear detector based on the phenomenon of suprathreshold stochastic resonance (SSR). We first present a model (an array of 1-bit quantizers) that demonstrates the SSR phenomenon. We then use this as a pre-processor to the conventional matched filter. We employ the Neyman-Pearson(NP) detection strategy and compare the performances of the matched filter, the SSR-based detector and the optimal detector. Although the proposed detector is non-optimal, for non-Gaussian noises with heavy tails (leptokurtic) it shows better performance than the matched filter. In situations where the noise is known to be leptokurtic without the availability of the exact knowledge of its distribution, the proposed detector turns out to be a better choice than the matched filter.
AN ANALYSIS OF THE IMPACT OF CETA PROGRAMS ON PARTICIPANTS' EARNINGS

This paper provides estimates of the impact of CETA programs on participants' postprogram earnings using matched comparison groups developed from a "nearest-neighbor" matching technique. Our basic results indicate that CETA has a negative and statistically significant earnings impact for adult men, and a modest, but not statistically significant, positive earnings impact for adult women. This pattern, however, is quite sensitive to whether individuals without recent labor market attachment are included in the comparison group and to how close to the date of enrollment preprogram earnings are measured.
Adaptive IMMPF for bearing-only maneuvering target tracking in Wireless Sensor networks

In this paper, the problem of maneuvering target tracking in a bearing-only Wireless Sensor network (WSN) is considered. To estimate the state variables of the moving target with nonlinear dynamics, Particle Filter (PF) is applied. Moreover, Interacting Multiple Model (IMM) algorithm is used to cope with target maneuvers. To reduce the computational cost of Interacting Multiple Model Particle Filter (IMMPF) algorithm, a novel adaptive sample set size is proposed based on the output estimation error. Besides, a new resampling method is suggested to deal with varying number of samples. The estimation results of the proposed adaptive IMMPF are compared with that of IMMPF with fixed number of samples, in terms of accuracy and computation time.
A New Millimeter-Wave Small-Signal Modeling Approach for pHEMTs Accounting for the Output Conductance Time Delay

A new technique is developed for determining analytically a millimeter-wave small-signal equivalent-circuit model of GaAs pseudomorphic HEMTs from scattering parameter measurements. In order to obtain a good agreement between model simulations and measurements up to 90 GHz, the conventional intrinsic output conductance is substituted by a voltage-controlled current source with a time delay. Consequently, a simple and accurate extraction procedure is proposed for taking into account the introduction of the output conductance time delay.
A framework for integrating web services and multi-agent systems

Web-service technologies are vitally important in integrating business applications with other applications for realizing service-oriented architecture. But there are two major challenges in this technology: (i) not effectively accounting semantics and non-functional attributes of service discovery request in service discovery and search process; (ii) high interaction between human and machine for meeting human needs. In this paper, an approach was used for solving the first problem that uses fuzzy logic in expressing service non-functional attributes. To solve the second problem, i.e. to decrease human-machine interaction and to increase machine-machine interaction on one hand and to increase the scalability of web service discovery approach on the other hand, the approach of integrating web technology with FIPA software agents technology was used. The proposed framework allows the interaction of web services and agent services by Broker. We describe how to analyze agent/web service discovery/publication request and linking them. Despite the content so DF registry and UDDI registry are inconsistent, but web service suggestion is possible for agent service discovery request by using ACL2SOAP and SOAP2ACL converter and vice versa.
dcTPM: A Generic Architecture for Dynamic Context Management

With the emergence of new technologies the requirements for trusted platforms are constantly changing. Thus, the current Trusted Platform Modules (TPMs) have to cope with issues they have not been designed for. One such deficit of current TPMs is the inability to support multiple stakeholders as in mobile computing, virtualization, and cloud computing applications. In such scenarios, a TPM has to attest the state of their applications on the platform to each stakeholder and to additionally protect their individual assets. Therefore, we present a novel architecture, called Dynamic-Context TPM (dcTPM), to satisfy the needs of each participant in multiple stakeholder applications. Though there exist related approaches in literature, they address only software-based TPM instances. In contrast, the architecture proposed in this paper supports not only software-based TPMs, but also dedicated hardware TPMs or a combination of both for each stakeholder. As an additional asset, the dcTPM architecture enables a dynamic exchange of contexts (TPM instances) without any modification of the underlying architecture. This architecture has been implemented as a proof-of-concept on top of a Xilinx Virtex-5 FPGA platform, demonstrating a test case with off-the-shelf hardware and software TPMs.
Parameter extrapolation to ungauged basins with a hydrological distributed model in a regional framework

Abstract. A Regional Water Resources study was performed at basins within and draining to the Basque Country Region (N of Spain), with a total area of approximately 8500 km2. The objective was to obtain daily and monthly long-term discharges in 567 points, most of them ungauged, with basin areas ranging from 0.25 to 1850 km2. In order to extrapolate the calibrations at gauged points to the ungauged ones, a distributed and conceptually based model called TETIS was used. In TETIS the runoff production is modelled using five linked tanks at the each cell with different outflow relationships at each tank, which represents the main hydrological processes as snowmelt, evapotranspiration, overland flow, interflow and base flow. The routing along the channels' network couples its geomorphologic characteristics with the kinematic wave approach. The parameter estimation methodology tries to distinguish between the effective parameter used in the model at the cell scale, and the watershed characteristic estimated from the available information, being the best estimation without losing its physical meaning. The relationship between them can be considered as a correction function or, in its simple form, a correction factor. The correction factor can take into account the model input errors, the temporal and spatial scale effects and the watershed characteristics. Therefore, it is reasonable to assume the correction factor is the same for each parameter to all cells within the watershed. This approach reduces drastically the number of parameter to be calibrated, because only the common correction factors are calibrated instead of parameter maps (number of parameters times the number of cells). In this way, the calibration can be performed using automatic methodologies. In this work, the Shuffled Complex Evolution – University of Arizona, SCE-UA algorithm was used. The available recent year's data was used to calibrate the model in 20 of the most representative flow gauge stations in 18 basins with a Nash-Sutcliffe index higher than 0.6 (10 higher than 0.8). The calibrated correction factors at each basin were similar but not equal. The validation process (in time and space) was performed using the remaining data in all flow gauge stations (62), with 42 basins with a Nash-Sutcliffe index higher than 0.5 (25 higher than 0.7). Deficient calibration and validations were always related with flow gauge stations very close to the karstic springs. These results confirmed that it was feasible and efficient to use the SCE-UA algorithm for the automatic calibration of distributed conceptual models and the calibrated model could be used at ungauged basins. Finally, meteorological information from the past 50 years at a daily scale was used to generate a daily discharges series at 567 selected points.
Visually and Phonologically Similar Characters in Incorrect Simplified Chinese Words

Visually and phonologically similar characters are major contributing factors for errors in Chinese text. By defining appropriate similarity measures that consider extended Cangjie codes, we can identify visually similar characters within a fraction of a second. Relying on the pronunciation information noted for individual characters in Chinese lexicons, we can compute a list of characters that are phonologically similar to a given character. We collected 621 incorrect Chinese words reported on the Internet, and analyzed the causes of these errors. 83% of these errors were related to phonological similarity, and 48% of them were related to visual similarity between the involved characters. Generating the lists of phonologically and visually similar characters, our programs were able to contain more than 90% of the incorrect characters in the reported errors.
An Improved Wireless Broadcasting Retransmission Approach Based on Network Coding

Based on the retransmission approach in wireless broadcasting based on network coding (NCWBR), which would decline the performance of the network and increase the retransmission numbers if the same node has more than two losing packets, we present an improved version of NCWBR, which can utilize multiple coded packets to decode data packets (Improved NCWBR). Theoretical analysis reveals that this way can ensure the solvability in the received nodes, and have the lower retransmission numbers. Simulation results indicate that compared with NCWBR approach, the approach presented in this paper can effectively reduce the retransmission numbers and improve the efficiency of transmission.
Stabilizability and Norm-Optimal Control Design subject to Sparsity Constraints

Consider that a linear time-invariant (LTI) plant is given and that we wish to design a stabilizing controller for it. Admissible controllers are LTI and must comply with a pre-selected sparsity pattern. The sparsity pattern is assumed to be quadratically invariant (QI) with respect to the plant, which, from prior results, guarantees that there is a convex parametrization of all admissible stabilizing controllers provided that an initial admissible stable stabilizing controller is provided. This paper addresses the previously unsolved problem of determining necessary and sufficient conditions for the existence of an admissible stabilizing controller. The main idea is to cast the existence of such a controller as the feasibility of an exact model-matching problem with stability restrictions, which can be tackled using existing methods. Furthermore, we show that, when it exists, the solution of the model-matching problem can be used to compute an admissible stabilizing controller. This method also leads to a convex parametrization that may be viewed as an extension of Youla's classical approach so as to incorporate sparsity constraints. Applications of this parametrization on the design of norm-optimal controllers via convex methods are also explored. An illustrative example is provided, and a special case is discussed for which the exact model matching problem has a unique and easily computable solution.
Document Image Understanding for Digital Library Access

In the last years, the spread of computers and the Internet have caused a significant amount of documents to be available in electronic form. Collecting them in digital repositories raised problems that go beyond simple acquisition issues, and cause the need for organizing and classifying them in order to improve the effectiveness and efficiency of the retrieval procedure. The obvious solution of manually creating and maintaining an updated index is clearly infeasible, due to the huge amount of data under consideration, thus there is a strong interest in methods that can provide solutions for automatically acquiring such a knowledge. In this paper we propose the intensive application of intelligent techniques from document acquisition to the extraction of significant text, to be exploited for later categorization and information retrieval purposes. Experiments proving the viability of the proposed approach in the real-world sample application domain of automatic Scientific Conference Management are also reported.
Electrostatic Modelling of Multiple Mobile Sinks in Wireless Sensor Networks

Sensor networks are constituted by cheap devices with limited energy supply. Therefore, it is crucial to design algorithms that optimize the energy usage of these devices and thus prolong the lifetime of the network. In this paper we present a novel method to deploy multiple sinks optimally in a sensor network, based on an electrostatic model. We assign positive or negative charges to sensor nodes depending on their energy level, and positive charges to sinks. Different charges attract each other, while charges of the same type shove each other. We show that, by properly setting these charges, the sink nodes can reach a position of equilibrium. Furthermore, we study how to move these mobile sinks during the operation of the network by dynamically changing the charges assigned to the sensor nodes and sinks. By comparing our adaptive strategy to three other solutions we show that it outperforms all the other approaches as far as network lifetime is concerned.
The Xeno-canto Collection and its Relation to Sound Recognition and Classification

This paper discusses distinguishing characteristics of the Xeno- canto bird sound collection. The main aim is to indicate the relation between automated recognition of bird sounds (or feature recognition in digital recordings more generally) and curating large bioacoustics col- lections. Not only do large collections make it easier to design robust algorithmic approaches to automated species classiers, those same al- gorithms should also become useful in determining the actual content of the collections.
Narrowing the semantic gap in natural images

Over two decades of intensive research, researchers employed many different approaches to solve the what so called “semantic gap” problem in image indexing and retrieval. Yet, the gap is still recognized as a barrier to progress, and further work is needed to bridge (or at least) narrow the gap. This suggests that more emphasis should be placed on understanding how humans perceive images. This study measures the effectiveness of two image indexing techniques for estimating similarities between images; the semantic basis functions and the affective basis functions. These indexing techniques aim at providing a measure of similarity between outdoor natural images as humans see it. The results presented in this study suggest that the semantic basis functions outperform the affective basis functions, and are able to index the content of outdoor natural images in a manner that allows retrieval of images that have been judged to be subjectively similar.
The Influence of Subgroup Dynamics on Knowledge Coordination in Distributed Teams: A Transactive Memory System and Group Faultline Perspective

With the rapid growth of globalization, distributed teams have become increasingly common in organizations. This research investigates the impact of inter-subgroup dynamics on knowledge coordination in distributed teams. To address this research question, we extend and apply theory from two primary sources – Transactive Memory Systems (TMS) theory and the faultline model. The paper uses data collected from 22 distributed MBA student teams to provide several novel insights into how perceived faultlines impact team processes (knowledge coordination) and outcomes (team performance and member satisfaction). First, perceived faultlines reduce knowledge coordination, which is an important antecedent of team performance and member satisfaction. Second, knowledge coordination fully mediates the negative effect of perceived faultines on team performance and member satisfaction. Third, low levels of TMS not only impair performance, but also reduce member satisfaction in distributed teams. Implications for research and practice are discussed together with potential avenues for future research.
Fusing robot behaviors for human-level tasks

Behavior-based control is one of the most widely used approaches for autonomous robot control. However, in many robot systems, there is often a disconnect between a user's desired task-level behavior and a robot's preprogrammed (innate) capabilities. Typically, the space of robot behavior is limited to sequential performances, switching between the robot's available skills. Such limited expression does not necessarily overlap with the space of desired robot behavior, leaving users unable to express their true desired control policy to the robot To bridge this divide, a new approach is proposed, which integrates state estimation (as a particle filter), learning by demonstration, and behavior-based control into an approach for robot learning. While these methods have typically been used in different contexts, we demonstrate the ability to use state estimation in order to learn a user's intended control policy from demonstration as a linear combination of innate behaviors. Through a specific navigation task, this method demonstrates how the same task-level behavior can be learned with different combinations of innate behaviors.
Discriminating Similar Languages: Evaluations and Explorations

We present an analysis of the performance of machine learning classifiers on discriminating between similar languages and language varieties. We carried out a number of experiments using the results of the two editions of the Discriminating between Similar Languages (DSL) shared task. We investigate the progress made between the two tasks, estimate an upper bound on possible performance using ensemble and oracle combination, and provide learning curves to help us understand which languages are more challenging. A number of difficult sentences are identified and investigated further with human annotation
An Interaction Device using Computer Vision Techniques

This paper presents a six degrees of freedom (6 DoF) optical tracking device for interaction in desktop VR applications. The device uses three webcams mounted on a box and uses computer vision techniques to detect the movements of white markers over a black background. We present the process of movements' detection and how this information is adapted to be applied in interaction events and to simulate a 3D mouse device.
Web Services for Comparative Data Analysis of Emissions Inventories

This paper describes the development and application of web services for comparing US and global emission inventories. Web services and service oriented architectures are providing new ways to support emissions modelers and analysts as they provide a web browser based environment for accessing and analyzing emissions data and inventories. Traditional emissions data analyses that can be conducted using web applications reduce the effort associated with accessing data, formatting data, and running analyses. The web application presented here supports an “offline” analysis conducted by the authors for reconciling and comparing regional and global emissions inventories. The focus of the analysis was the reconciliation of global inventories developed using “top down” methods with regional inventories developed using localized “bottom up” methods for a domain covering the continental United States. Part of that analysis is reconstructed using web services, including the spatial allocation of point source US EPA NEI data to a 1x1 degree grid and calculation of differences and ratios between the gridded NEI and EDGAR inventories. The online application is made possible through dynamic internet access to emissions inventory data and web standards for connecting data access services with data analysis and map visualization services. The same analysis services can be quickly re-applied when emissions data are updated or applied to new comparisons with other inventories. The analysis web services are openly available online (www.neisgei.org) for other emissions or non-emissions applications.
A semi analytic approach to the robust stability of quasipolynomials

Abstract A semi-analytic tool for the study of the robust stability of time delay systems is presented. The approach is based on graphical methods. The conditions of the Finite Nyquist Theorem for quasipolynomials given in (Santos et al. , 2003b) are improved. The Finite Inclusions Theorem for polytopic and interval quasipolynomials families is derived. An algorithm describing how to apply this new technique to analyze the robust stability of families of quasipolynomials is presented. The effectivity of this algorithm, which is implemented in Matlab, is validated with the analysis of two examples.
A Survey of Scratch-Pad Memory Management Techniques for low-power and -energy

Scratch-Pad Memories (SPMs) are considered to be effective in helping reduce memory energy consumption. However, the variety of SPM management techniques complicates the choice of the right one to implement. In this paper, we first give a synthesis on existing SPM management techniques for low-power and -energy outlining their comparative advantages, drawbacks and trade-offs. Then, we propose a new general classification which encompasses most existing research works. This classification has the advantage of clearly exhibiting lesser explored techniques, hence providing hints for future research.
Cognitive Predictors of Accuracy in Quality Control Checking

Labelling errors on fresh produce are estimated to cost the UK supermarket industry £50m per year in product recalls and wastage. Such errors occur despite robust quality control procedures. Given the financial and environmental impact of these errors, it is important to understand whether label-checking performance can be predicted by individual differences in cognitive abilities. To this end, participants carried out a simulated label-checking task together with a number of measures of information processing speed, attention, short-term/working memory, and mind-wandering. Accuracy of label checking was found to be significantly predicted by three of the measures, with better short-term verbal memory being most strongly associated with performance. Cognitive tests such as these provide a means of identifying how well employees are likely to perform when undertaking such tasks and, if necessary, how they should be supported in that role, possibly forming a screening battery when recruiting new quality control staff. The findings highlight the importance of determining the component processes of cognition which contribute to performance in real-world work environments.