Miracle-dz/UniFAR-FTUs huggingface dataset:
A Model-Based Framework for Legal Policy Simulation and Compliance Checking

Information systems implementing requirements from laws and regulations, such as taxes and social benefits, need to be thoroughly verified to demonstrate their compliance. Several Verification and Validation (V&V) techniques, such as reliability testing, and modeling and simulation, can be used for assessing that such systems meet their legal. Typically, one has to model the expected (legal) behavior of the system in a form that can be executed (simulated), subject the resulting models and the system to the same input data, and then compare the observed behavior of the model simulation and system execution. Existing V&V techniques often rely on code and complex logical expressions with no intuitive appeal to legal experts for specifying the expected behavior of a given system. Subsequently, one has no practical way to validate with legal experts that the underlying legal requirements are indeed complete and constitute a faithful representation of what needs to be implemented. Further, manually defining the expected behavior of a system and its test oracles is a tedious and error-prone task. The challenge here is to find a suitable knowledge representation that can be understood by all the involved stakeholders, e.g., software engineers and legal experts, but that remains complete and precise enough to enable automated analysis such as simulation and testing. As real data is seldom accessible in highly regulated domains, V&V requires the generation of synthetic testing data that can be used to build confidence in the reliability of the system under test. In particular, such data has to be structurally and logically well-formed to raise meaningful failures that can help reasoning about the reliability of the system under test. Further, the data should exhibit as much as possible the actual or anticipated system usage to help mimic how the system would behave under realistic circumstances. Generating such data is not a trivial task as the underlying data schemas are usually large and subject to numerous complex domain-related logical constraints. In this thesis, we investigate the use of the Unified Modeling Language (UML) and model-driven technologies, e.g., model to code transformations, to facilitate V&V activities for information systems that have to conform to laws and regulations, while tackling the above challenges. All our technical solutions have been developed and empirically evaluated in close collaboration with a government administration. Concretely, the technical solutions covered by this thesis include: - A modeling notation and methodology for formalizing legal policies. We propose a modeling notation and methodology for building abstract interpretations of the law. Models built using our methodology are simple enough to be understood by the involved stakeholders and are, at the same time, detailed enough to enable automated V&V activities. - A model-based simulation framework. We develop a model-based framework and associated tool support for simulating legal policies, when formalized…
Spectral efficiency for FDMA and DS-CDMA in cellular systems

The spectral efficiency achieved by FDMA and DS-CDMA schemes during cellular operation in an additive white Gaussian noise (AWGN) and a Rayleigh fading environment is evaluated in terms of the assigned downlink and uplink channel capacity (in the Shannon sense). In particular, in Rayleigh fading, channel capacity is estimated in an average sense considering the inherent diversity potential that each scheme provides as a physical means for fading mitigation. However, in contrast to cellular FDMA, multiple-access and co-channel interference that are present in cellular DS-CDMA cause substantial spectral efficiency reduction. Hence, it is analytically shown that, under normalized conditions, FDMA spectral efficiency is always higher than that of DS-CDMA regardless the fact that DS-CDMA systems reduce the channel capacity degradation that is caused by signal fading.
Moment and curvature preserving technique for accurate ellipse boundary detection

Circles and their elliptic projections are very commonly used image features in computer vision applications. Thus, it is very important to be able to determine their location in an accurate manner. A technique for determining an ellipse boundary with subpixel precision is proposed. The technique, called the moment and curvature preserving detection (MCP), utilizes the first three intensity moments and the intensity gradient of the image. The idea of using moments for subpixel edge detection is not new, but in the case of ellipses the moments do not provide sufficient information for precise detection. However, if the local curvature is augmented to the observations, the ellipse boundary can be determined reliably.
Neural coding by redundancy reduction and correlation

Redundancy reduction as a form of neural coding has been a topic of large research interest. A number of strategies has been proposed, but the one which is attracting the most attention assumes that this coding is carried out so that the output signals are mutually independent. In this work we go one step further and suggest an algorithm that separates also non-orthogonal signals (i.e. dependent signals). The resulting algorithm is very simple, as it is computationally economical and based on second order statistics that, as it is well know, is more robust to errors than higher order statistics. Moreover, the permutation/scaling problem is also avoided. The framework is given with a biological background, and we point out that the algorithm can also be used in other applications such as biomedical engineering and telecommunications.
Generation of 460 GHz radiation by photomixing in low-temperature-grown MBE GaAs

We report on the fabrication and characterization of LT GaAs photomixers for generation of 460 GHz radiation. Resonant cavity structures and devices with various finger contacts geometry are used to enhance the photomixer performance. The DC responsivity shows only slight suppression with increased optical power in the range of 0.17-45 mW, i.e. space-charge effects are suppressed. A good agreement between the microwave power and DC responsivity (P/sub out/ /spl sim/ R/sup 2/) is obtained. Our results indicate that significant improvement in the output power, up to /spl sim/1 /spl mu/W of microwave radiation, can be obtained.
Sampling-Based RBDO Using Probabilistic Sensitivity Analysis and Virtual Support Vector Machine

In this paper, a sampling-based RBDO method using a classification method is presented. The probabilistic sensitivity analysis is used to compute sensitivities of probabilistic constraints with respect to random variables. Since the probabilistic sensitivity analysis requires only the limit state function, and not the response surface or sensitivity of the response, an efficient classification method can be used for a sampling-based RBDO. The proposed virtual support vector machine (VSVM), which is a classification method, is a support vector machine (SVM) with virtual samples. By introducing virtual samples, VSVM overcomes the deficiency in existing SVM that uses only classification information as their input. In this paper, the universal Kriging method is used to obtain locations of virtual samples to improve the accuracy of the limit state function for highly nonlinear problems. A sequential sampling strategy effectively inserts new samples near the limit state function. In sampling-based RBDO, Monte Carlo simulation (MCS) is used for the reliability analysis and probabilistic sensitivity analysis. Since SVM is an explicit classification method, unlike implicit methods, computational cost for evaluating a large number of MCS samples can be significantly reduced. Several efficiency strategies, such as the hyper-spherical local window for generation of the limit state function and the Transformations/Gibbs sampling method to generate uniform samples in the hyper-sphere, are also applied. Examples show that the proposed sampling-based RBDO using VSVM yields better efficiency in terms of the number of required samples and the computational cost for evaluating MCS samples while maintaining accuracy similar to that of sampling-based RBDO using the implicit dynamic Kriging (D-Kriging) method. © 2012 ASME
Trajectory reconstruction for self-localization and map building

We describe a method for the reconstruction of a driven trajectory of a mobile robot if the begin and end states of the trajectory are known, and intermediate readings from odometry are available. Our method uses a Kalman filter to combine a forward and backward dead-reckoning trajectory. We show that our method is more reliable for long trajectories than just combining the dead-reckoning trajectories independently.
Reconstruction algorithms for electromagnetic imaging

Two algorithms for image reconstruction in electromagnetic imaging are proposed. The first approach concerns the application of a hybrid version of the genetic algorithm to tomographic imaging of dielectric configurations. In the second approach, buried inhomogeneities are schematized as multilayer infinite dielectric cylinders with elliptic cross sections. An efficient recursive analytical procedure is used for the forward scattering computation. A cost function is constructed in which the field is expressed in a series solution of Mathieu functions. Starting with the input scattered data, the iterative minimization of the function is performed by a new optimization method called a memetic algorithm.
Joint source channel decoding using bit-reliability information and source statistics

A new joint source channel decoding technique called channel coded optimal estimation (CCOE) is introduced. Bit-reliability information of the received source-encoder bits and the redundant bits of a systematic channel code are combined with the source-signal statistics to calculate the a-posteriori probabilities for all possibly transmitted codewords. The probabilities are used to estimate the transmitted signal at the receiver.
A stable solution of time domain electric field integral equation

In this paper, we present a new formulation using the time-domain electric field integral equation (TD-EFIE) to obtain transient scattering responses from arbitrarily shaped three-dimensional conducting bodies. The time derivative of the magnetic vector potential is approximated with a central finite difference and the scalar potential is time-averaged by dividing it into two terms. This approach with an implicit method using a central difference results in accurate and stable transient scattering responses from conducting objects.
Speed-up Feature Detector using Adaptive Accelerated Segment Test

ABSTRACT Image matching using local features of an image patch is a primary stage for various higher level computer vision applications such as object recognition, motion tracking, simultaneous localization and mapping, stereo vision, and so on. A feature from accelerated segment test (FAST) has shown to be a superior feature detector in terms of computational speed. In our previous research, we presented a feature detector that improves the speed of FAST. In this study, we extend it to speed up it further. Experimental results on benchmark data-sets reveal that the new method speeds up FAST detector better than our previous detector with marginal improvement in repeatability score. A comprehensive review of related feature detectors is also provided to place our work in context.
On the properties of frequency weighted balanced truncation techniques

In this paper, we show that when the input and output weights are co-inner and inner respectively, the three frequency weighted balanced truncation techniques: D.F. Enns technique (1984), Lin and Chiu's technique, and G. Wang et al. technique (1999) are all equivalent to the unweighted balanced truncation technique.
Greedy cached query rewriting in content-oriented XML web engine

As XML emerge information representation and exchanging standard on the Web, XML turns into primary choice in many E-commercial applications. In web application, XML query receives much more attention. Unlike traditional web search, XML query directly returns needed information, and its engine caches query results rather than physical web pages. Such query is also called Content-Oriented Web query. In the XML query engine, it is more difficult to utilize the cached material to answer the user query than traditional web search engine because the former could be reduced to the answering semi-structured query using views, which is essentially an NP problem. Traditional algorithms take exponential time in the size of query and views, in addition, they takes no information generated in some special application into account. In the paper, a novel method was proposed under XML query engine environment, which makes use of the information that could be obtained in XML query engine as heuristic knowledge to prune the exponential query rewriting plan space. Theoretical analysis shows that the algorithm is polynomial time complexity in the size of query and view definition. The primary result of our prototype--COMMIX shows that the algorithm is valid and efficient.
Improvements of ITU-R field strength prediction method for land mobile services

During implementation, it was found that the popular field strength prediction method for land mobile services defined by ITU-R recommendations has several vaguenesses. First of all, several important situations are not defined precisely. Also, an important correction factor, valid for years, was surprisingly changed in the latest version of the recommendations. In order to resolve the mentioned problems, different approaches were considered and tested over data collected by extensive measurements. The measurements were carried out in the 900 MHz frequency band in the area of Belgrade, Yugoslavia, a typical European town of a size of 2 million inhabitants. In addition, for all the approaches considered correction factors for 9 different land usage (clutter) category types are determined.
An interactive system for the visualization and measurement extraction in medical images

The visualization of medical images, e.g. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), and the utilization of measurement tools to define distances, areas and volumes are very important to health professionals. The quantitative analysis of spatial relations among structures is useful for medical diagnosis. This work describes a visualization system that provides interactive measurement tools. MRI images acquired from a phantom were used to increase system accuracy.
Trace-based Micro-analytic Measurement of Self-Regulated Learning Processes

To keep pace with today’s rapidly growing knowledge-driven society, productive self-regulation of one’s learning processes are essential. We introduce and discuss a trace-based measurement protocol to measure the effects of scaffolding interventions on self-regulated learning (SRL) processes. It guides tracing of learners’ actions in a learning environment on the fly and translating these data into indicators of engagement in SRL processes that reflect learners’ use of scaffolding interventions and contingencies between those events. Graphs of users’ learning actions in a learning environment are produced. Our trace-based protocol offers a new methodological approach to investigating SRL and new ways to examine factors that affect learners’ use of self-regulatory processes in technology-enhanced learning environments. Our application of the protocol was described in a study about Learn-B, a learning environment for SRL in the workplace. The findings of the work presented in this paper indicate that future research can gain substantially by using learning analytics based on users’ trace data and merging them with other quantitative and qualitative techniques for researching SRL beliefs and processes.
A comparison of planar versus volumetric numerical observers for detection task performance in whole-body PET imaging

The goal of this project is to determine if there is a difference between planar and volumetric numerical observers. The motivation comes from the use of a volumetric (3D) display of image data (i.e. three orthogonal views through a volume image) to assess whole-body PET images in most, if not all, clinical PET centers. Studies of correlations between numerical observers and human observers (e.g. using receiver operating characteristic (ROC) detection analysis), however, typically use a planar (2D) display and analysis methodology. For images where axial noise correlations exist, Wells et al. [IEEE-TNS, 47:037-1044, 2000] have shown significant differences between single-slice and multi-slice ROC studies, implying that ROC-type studies utilizing a volumetric image display will also yield different results from a single or multi-slice image displays. In particular, planar implementations of the non-prewhitening matched filter (NPWMF) and the channelized Hotelling observer (CHO) have been extensively investigated as surrogates for measuring human detection task performance. To determine if there is a difference between planar and volumetric numerical observers, we analyzed the behavior of 2D and 3D implementations of the NPWMF and CHO numerical observers with multiple realizations of images with noise properties similar to those of whole-body PET oncology imaging. Initial results indicate that there is a significant difference increase in SNR or delectability of volumetric numerical observers relative to planar observers. This implies that volumetric and planar numerical observers may have different strengths of correlation with human observer performance, and that these correlations should be determined prior to using numerical observers to optimize algorithm or protocol performance for whole-body PET imaging.
Feasibility study of using small satellite synthetic aperture radar for global 3D imaging

This paper deals with the feasibility study of using small satellite constellation to perform Interferometric Synthetic Aperture Radar (InSAR) global 3D imaging. A scheme in which three exactly identical small satellites make up a constellation is given. Two of them flying along parallel orbits with a little different ascending nodes observe the same area and make interferometry without any time decorrelation. The third flies along another orbit with a certain angular separation behind the two satellites, and observes the same area in a short revisit time. These three satellites together can form differential interferometry, which is of great benefit to observe surface changes with short time baseline. Simulation is conducted in this paper to perform a mission study. The results show the potentiality of the system for accurate global three-dimensional measurements.
Analysis of heart rate and its variation affecting image quality and optimized reconstruction window in retrospective ECG-gated coronary angiography using multi-detector row CT

It is clinically important to study the effect of heart rate and its variation on image quality, and selection of optimized window in coronary angiography using multi-detector row CT (MDCT). We performed contrast-enhanced coronary angiography using MDCT in 83 patients. Sixty cases with available information of heart rate were enrolled in this study. We systemically analyzed the effect of heart rate and its variation. Two radiologists rated image quality as follows: 4, excellent; 3, good; 2, fair; 1, bad. Cardiac cycle windows at 70 and 40% were routinely selected for image reconstruction. Both of 40% and 70% reconstructed images were available only to fifty-seven cases. Optimized window was rated as 1 when 40% reconstruction was better quality than 70%, as 2 when 40% reconstruction was the same as 70%, and as 3 when 70% reconstruction was better than 40%.
The CIP2k first level trigger system at the H1 experiment at HERA

The ep-collider HERA at DESY, Germany, and the high energy physics experiments HI and ZEUS were upgraded in the years 2000-2002. The expected specified luminosity is five times higher than before. One of the upgrade projects was to build a set of new multi wire proportional chambers (CIP2k) providing information to distinguish between events induced by the beam background, and ep-interactions on an early stage of the trigger. This new first level trigger system provides a trigger decision using a total of about 10,000 channels of the chamber at a speed of 10.4 MHz. The system is realized in large field programmable gate arrays (FPGA) in order to comply with the timing requirements, which are necessary for a dead time free trigger decision within 1.5 /spl mu/s. This is achieved by simultaneous event pipelining and readout while preparing the trigger decision. The total data throughput rate is 108 GB/s. The system is developed in the hardware description language Verilog. Special attention is drawn to an integrated error correction system in the FPGA, which cannot be realized in hard wired electronics. This system is necessary to ensure maximum pattern recognition efficiency even at high occupancy. The CIP2k trigger system was installed in 2001 in parallel to the HERA startup and is now being commissioned in order to reach its best performance. The flexible programmable hardware clearly is a big advantage here.
A Distributed Computing Model for Wu’s Method

As Wu’s method, based on symbolic computation, has found applications in more and more fields, it is challenged by more and more complicated calculation problems. The soul of the method, dividing and ruling problem, is very suitable for distributed computation. In this paper, a high performance computing technique is introduced into the symbolic computation and a distributed computing model (DCM) for Wu’s method over Internet is put forward. First, the feasibility and requirement for distributed computation of Wu’s method is analyzed. Then the data communications for big integers and polynomials are put forward in detail, and finally the design and implementation for DCM based on ELIMINO and Globus Toolkits 3 are presented.
Towards the introduction of human perception in a natural scene classification system

We develop a method to optimize a machine-based semantic categorization of natural images according to human perception. First, the categories are determined through a psychophysical experiment. The similarity matrices obtained from the human responses are analyzed by a multidimensional scaling technique called curvilinear component analysis (CCA). The same is done with an automatic image indexing system based on similarities between the outputs of Gabor filters applied to the images. Then we show that, by using the human categorization to balance the filter outputs, the system's performance may be significantly improved.
Convergence prediction for iterative decoding of threefold concatenated systems

We show how to use EXIT charts for convergence prediction of a threefold serially concatenated system. The corresponding chart has three dimensions and allows us to appropriately select system parameters and to find an optimal schedule of decoding iterations between the three decoders of such a system. Convergence thresholds are obtained to determine the minimal signal-to-noise ratios for which convergence is possible. It turns out that threefold concatenated systems do not achieve any additional performance gain compared to suitably designed twofold systems. We conclude that a threefold concatenation should be considered only when the decoders cannot be chosen freely.