Miracle-dz/UniFAR-FTUs huggingface dataset:
The Pragmatic Evaluation of Tool System Interoperability

Collaborative communities are increasingly supported by systems of information and communication tools. Much current research and development focuses on the technical and semantic aspects of tool system interoperability. However, for developing effective tool systems, their pragmatic evaluation is also essential. This implies that the usage context of tools is taken into account. In this paper, we envision an approach to the pragmatic evaluation of tool system interoperability. Its main elements are a conceptualization of the tool system, its usage context, and an evaluation processs. With these basic elements, pragmatic evaluation can be operationalized in many different ways. We illustrate our approach with several real-world examples.
BayesWipe: A Scalable Probabilistic Framework for Cleaning BigData

Recent efforts in data cleaning of structured data have focused exclusively on problems like data deduplication, record matching, and data standardization; none of the approaches addressing these problems focus on fixing incorrect attribute values in tuples. Correcting values in tuples is typically performed by a minimum cost repair of tuples that violate static constraints like CFDs (which have to be provided by domain experts, or learned from a clean sample of the database). In this paper, we provide a method for correcting individual attribute values in a structured database using a Bayesian generative model and a statistical error model learned from the noisy database directly. We thus avoid the necessity for a domain expert or clean master data. We also show how to efficiently perform consistent query answering using this model over a dirty database, in case write permissions to the database are unavailable. We evaluate our methods over both synthetic and real data.
Bearer service allocation and pricing in heterogeneous wireless networks

In next generation heterogeneous wireless networks, a user with a multi-mode terminal may have network access for different bearer services using various access technologies. In such a scenario, the user will select the best access network with good QoS and low cost. A profit-seeking network service provider, in order to maximize his revenue and be competitive in the market, has to efficiently utilize limited resources, and properly price the bearer services. Based on analysis and simulations, a simple allocation policy is proposed with the aim to maximize network capacity and user QoS, which can also simplify network selection process. In addition, the pricing policy for multi-services in heterogeneous wireless networks is also investigated in this paper.
Animating soft substances with implicit surfaces

This paper presents a hybrid model for animation of soft inelastic substance which undergo topological changes, e.g. separation and fusion and which fit with the objects they are in contact with. The model uses a particle system coated with a smooth iso-surface that is used for performing collision detection, precise contact modeling and integration of response forces. The animation technique solves three problems inherent in implicit modeling. Firstly, local volume controllers are defined to insure constant volume deformation, even during highly inelastic processes such as splitting or fusion. Secondly, we avoid unwanted distance blending between disconnected pieces of the same substance. Finally, we simulate both collisions and progressive merging under compression between implicit surfaces that do not blend together. Parameter tuning is facilitated by the layered model and animation is generated at interactive rates.
Estimation of unresolved targets number based on Gerschgorin disks

Targets number estimation is an important part to the resolution of unresolved targets. Based on Gerschgorin disks estimation (GDE), we propose a method to estimate unresolved targets number with a single snapshot. The proposed method consists of the virtual image array spatial smoothing (VIASS) and improved Gerschgorin disks estimation (IGDE). A full rank covariance matrix can be obtained while avoiding reduction of effective array aperture by VIASS. Furthermore, this method improves the decision criteria. It's easily applied to radar system since the adaptive detection threshold of IGDE. Several simulation results demonstrate the good performance of this method.
Oil price prediction using ensemble machine learning

Crude oil price forecasting is a challenging task due to its complex nonlinear and chaotic behavior. During the last couple of decades, both academicians and practitioners devoted proactive knowledge to address this issue. A strand of them has focused on some key factors that may influence the crude oil price prediction accuracy. This paper extends this particular branch of recent works by considering a number of influential features as inputs to test the forecasting performance of daily WTI crude oil price covering the period 4th January 1999 through 10th October 2012. Empirical results indicate that the proposed methods are efficient and warrant further research in this field.
Characterization of high-voltage charge-trapping effects in GaN-based power HEMTs

We investigate the effects and the causes of highvoltage charge-trapping phenomena in AlGaN/GaN Schottky-HEMTs grown on SiC substrate, and we present an high-voltage pulsed system, implemented by a cost-effective fully-customable modular solution. The characterization methodology includes double-pulsed ID-VD measurements, time-resolved RON recovery transients, and leakage-currents analysis. The observed parasitic dynamic RON-increase is triggered by high drain-voltage (>50V), and likely originates from the trapping of parasitic electrons supplied by leakage currents at the crystallographic defect-states located within the epitaxial structure.
Privacy Preserving Aggregate Query of OLAP for Accurate Answers

In recent years, privacy protection has become an important topic when cooperative computation is performed in distributed environments. This paper puts forward efficient protocols for computing the multi-dimensional aggregates in distributed environments while keeping privacy preserving. We propose a novel model, which contains two crucial stages: local computation and cooperative computation based on secure multiparty computation protocols for privacy-preserving on-line analytical processing. According to the new model, we develop approaches to privacy-preserving count aggregate query over both horizontally partitioned data and vertically partitioned data. We, meanwhile, propose an efficient sub-protocol Two-Round Secure Sum Protocol. Theoretical analysis indicates that our solutions are secure and the answers are exactly accurate, that is, they can securely obtain the exact answer to aggregate query without revealing anything about their confidential data to each other. We also analyze detailedly the communication cost and computation complexity of our schemes in the paper and it shows that the new solutions have good linear complexity. No privacy loss and exact accuracy are two main significant advantages of our new schemes.
Numerical Simulation of Hydraulic Fracturing in TightGas Shale Reservoirs

Hydraulic fracturing of tight gas shales is a relatively new method of producing economically from extremely low permeability reservoirs. Due to the low permeability, it is crucial that fracturing treatments are able to efficiently create regions of enhanced permeability in the reservoir. The mechanical properties of prospective shale mean that stress interactions between adjacent fractures can be of real consequence to the efficiency of the treatment, and alternative treatments to mitigate these effects have been designed. The aim of this research is to conduct numerical simulation of alternative treatment designs, and objectively evaluate critical parameters. In particular, key aspects of the socalled Texas Two Step method are simulated. This treatment aims to create zones of altered stress anisotropy between pressurised fractures. This study examines the behaviour of said zones as the distance between the fractures is altered, in parallel with literature describing the method. Explanations for unusual fracture curvature behaviour are provided. Further studies examine fracture reorientation within a modified stress field such as that created by the treatment. Rates of reorientation are measured under varying levels of stress anisotropy, initial fracture length and orientation to the stress field. The influence of pre existing natural fractures on the path of a hydraulic fracture is investigated through further simulations. The effects of natural fracture permeability and interface properties are studied. The impact of shear stress caused by a propagating fracture is also examined, and the possible implications for interpretation of microseismic data discussed. Finally, a new treatment for simultaneous fracturing with reduced stress shadowing is proposed and simulated.
Parallel Program Performance Prediction and Collaborative Filtering Techniques

Hardware trends point to architectures with increasing numbers of cores and heterogeneity [1]. However, software developed today can only be tested in significantly smaller platforms, due to cost and availability of such platforms. Accurate performance prediction mechanisms would provide many benefits, including improved platform provisioning, which is a significant problem in cloud computing, and could also help identify the hardware characteristics that impede performance. This research proposal presents two different approaches to performance predictions: a regression based approach for message-passing applications [2] and a performance modeling toolkit that combines application characteristics and target architecture models to produce cross-architecture performance predictions [3]. Summarizing their advantages and limitations, we conclude that a different approach might be more successful, by using techniques from a different area of computer systems, namely collaborative filtering. Consequently, we present and compare different item-based collaborative filtering recommendation algorithms [4] that can be used to identify similarities given a set of common characteristics and present the opportunities, combining ideas from the aforementioned works, for research in the area of performance predictions using collaborative filtering algorithms.
Communicating the Neuroscience of Psychopathy and Its Influence on Moral Behavior: Protocol of Two Experimental Studies

Neuroscience has identified brain structures and functions that correlate with psychopathic tendencies. Since psychopathic traits can be traced back to physical neural attributes, it has been argued that psychopaths are not truly responsible for their actions and therefore should not be blamed for their psychopathic behaviors. This experimental research aims to evaluate what effect communicating this theory of psychopathy has on the moral behavior of lay people. If psychopathy is blamed on the brain, people may feel less morally responsible for their own psychopathic tendencies and therefore may be more likely to display those tendencies. An online study will provide participants with false feedback about their psychopathic traits supposedly based on their digital footprint (i.e., Facebook likes), thus classifying them as having either above-average or below-average psychopathic traits and describing psychopathy in cognitive or neurobiological terms. This particular study will assess the extent to which lay people are influenced by feedback regarding their psychopathic traits, and how this might affect their moral behavior in online tasks. Public recognition of these potential negative consequences of neuroscience communication will also be assessed. A field study using the lost letter technique will be conducted to examine lay people’s endorsement of neurobiological, as compared to cognitive, explanations of criminal behavior. This field and online experimental research could inform the future communication of neuroscience to the public in a way that is sensitive to the potential negative consequences of communicating such science. In particular, this research may have implications for the future means by which neurobiological predictors of offending can be safely communicated to offenders.
Plasma IL‐6, plasma VEGF, and serum YKL‐40: relationship with disease activity and radiographic progression in rheumatoid arthritis patients treated with infliximab and methotrexate

Department of Rheumatology, Herlev Hospital, University of Copenhagen, Department of Rheumatology, H:S Hvidovre Hospital, University of Copenhagen, Department of Rheumatology, H:S Rigshospitalet, University of Copenhagen, Department of Radiology, H:S Rigshospitalet, University of Copenhagen, and Department of Surgical Gastroenterology, H:S Hvidovre Hospital, University of Copenhagen, Copenhagen, Denmark
Adaptive Feature-Space Conformal Transformation for Imbalanced-Data Learning

When the training instances of the target class are heavily outnumbered by non-target training instances, SVMs can be ineffective in determining the class boundary. To remedy this problem, we propose an adaptive conformal transformation (ACT) algorithm. ACT considers feature-space distance and the class-imbalance ratio when it performs conformal transformation on a kernel function. Experimental results on UCI and real-world datasets show ACT to be effective in improving class prediction accuracy
Outdoor-to-Indoor Office MIMO Measurements and Analysis at 5.2 GHz

The outdoor-to-indoor wireless propagation channel is of interest for cellular and wireless local area network applications. This paper presents the measurement results and analysis based on our multiple-input-multiple-output (MIMO) measurement campaign, which is one of the first to characterize the outdoor-to-indoor channel. The measurements were performed at 5.2 GHz; the receiver was placed indoors at 53 different locations in an office building, and the transmitter was placed at three "base station" positions on a nearby rooftop. We report on the root-mean-square (RMS) angular spread, building penetration, and other statistical parameters that characterize the channel. Our analysis is focused on three MIMO channel assumptions often used in stochastic models. 1) It is commonly assumed that the channel matrix can be represented as a sum of a line-of-sight (LOS) contribution and a zero-mean complex Gaussian distribution. Our investigation shows that this model does not adequately represent our measurement data. 2) It is often assumed that the Rician if-factor is equal to the power ratio of the LOS component and the other multipath components (MPCs). We show that this is not the case, and we highlight the difference between the Rician if-factor often associated with LOS channels and a similar power ratio for the estimated LOS MPC. 3) A widespread assumption is that the full correlation matrix of the channel can be decomposed into a Kronecker product of the correlation matrices at the transmit and receive array. Our investigations show that the direction-of-arrival (DOA) spectrum noticeably depends on the direction-of-departure (DOD); therefore, the Kronecker model is not applicable, and models with less-restrictive assumptions on the channel, e.g., the Weichselberger model or the full correlation model, should be used.
The Effects of Music Genre on Young People's Alcohol Consumption: An Experimental Observational Study

The aim of this study was to test whether exposure to specific music genres in a social drinking setting leads to differences in drinking levels. An observational experimental design was used in which we invited peer groups of young adults into a bar lab, a lab which is furnished like an ordinary, small pub. Between two tasks, people had a break of 50 minutes in which they could order nonalcoholic and alcoholic beverages. During the break, participants were exposed to a specific music genre: popular, hard rock, rap, or classical music. Those groups who were exposed to classical music drank significantly more alcohol than those who were exposed to other music genres. This pattern is quite robust and does not depend on participants’ sex or age, drinking habits, own music preference, and relative importance of music in participant's lives. The study's limitations are mentioned.
Planning and Optimization of Resources Deployment: Application to Crisis Management

Crisis management challenges decision support systems designers. One problem in the decision marking is to develop systems able to help the coordination of the different involved teams. Another challenge is to make the system work with a degraded communication infrastructure. Each workstation or embedded application must be able to help to make a decision with a degraded network by taking into account the potential decisions made by other agents. We propose in this article a multiagent model, based on an ant colony optimization, and designed to manage the complexity in the deployment of resources to solve a crisis. This model is able to manage data uncertainty, and its global goal is to optimize, in a stable way, fitness functions, like saving lives, defined by multiple users. Moreover, thanks to a reflexive process, the model is able to manage the effects into the environment of its decisions, in order to take more appropriate decisions. Thanks to our transactional model, the system is also able to take into account a large data amount without exploring all potential solutions. The graphical interface should be able to make the user defining rules database. Then, if the nature of the crisis is deeply unchanged, users should be able to change rules' databases.
Sustained Activities and Retrieval in a Computational Model of the Perirhinal Cortex

The perirhinal cortex is involved not only in object recognition and novelty detection but also in multimodal integration, reward association, and visual working memory. We propose a computational model that focuses on the role of the perirhinal cortex in working memory, particularly with respect to sustained activities and memory retrieval. This model describes how different partial informations are integrated into assemblies of neurons that represent the identity of an object. Through dopaminergic modulation, the resulting clusters can retrieve the global information with recurrent interactions between neurons. Dopamine leads to sustained activities after stimulus disappearance that form the basis of the involvement of the perirhinal cortex in visual working memory processes. The information carried by a cluster can also be retrieved by a partial thalamic or prefrontal stimulation. Thus, we suggest that areas involved in planning and memory coordination encode a pointer to access the detailed information encoded in the associative cortex such as the perirhinal cortex.
Psychiatric profiles and patterns of cerebral blood flow in focal epilepsy: interactions between depression, obsessionality, and perfusion related to the laterality of the epilepsy.

OBJECTIVES: In a study of patients with focal epilepsy the hypothesis was explored that different measurements of psychopathology are related to specific distributions of cerebral perfusion. METHODS: Forty patients had SPECT performed with (99m)Tc-HMPAO. In addition, patients received a psychiatric evaluation with the following psychiatric questionnaires: the Beck depression inventory, the Leyton obsessionality inventory, the Bear-Fedio questionnaire, and the social stress and support interview. Patients were analysed in two groups according to the laterality of the epilepsy. Nine patients were excluded based on poor quality scans (n = 1), unlateralised epilepsy (n = 4), and left or ambidextrous handedness (n = 4). RESULTS: There were no overall differences between the left and right epilepsy groups on measures of psychopathology. Associations were found between scores on some of the rating scales and regional cerebral blood flow. Specifically, for patients with left sided epilepsy, higher scores on the Beck depression inventory were associated with lower contralateral temporal and bilateral frontal perfusion, and higher occipital perfusion. For patients with right sided epilepsy higher scores on the Leyton obsessionality inventory were associated with increased perfusion in ipsilateral temporal, thalamic, and basal ganglia regions and bilateral frontal regions. CONCLUSION: The results do not support the notion that lateralised epileptogenic lesions are associated with different levels of depression, obsessionality, or personality traits. They support the view that certain psychopathological symptom patterns are related to specific regional dysfunctions depending on the laterality of a hemispheric lesion.
Dielectric and electromechanical properties of rare earth calcium oxyborate piezoelectric crystals at high temperatures

The electrical resistivity, dielectric, and electromechanical properties of ReCa<sub>4</sub>O(BO<sub>3</sub>)<sub>3</sub> (ReCOB; Re = Er, Y, Gd, Sm, Nd, Pr, and La) piezoelectric crystals were investigated as a function of temperature up to 1000°C. Of the studied crystals, ErCOB and YCOB were found to possess extremely high resistivity (p): p >; 3 × 10<sup>7</sup> ω. cm at 1000°C. The property variation in ReCOB crystals is discussed with respect to their disordered structure. The highest electromechanical coupling factor κ<sub>26</sub> and piezoelectric coefficient d<sub>26</sub> at 1000°C, were achieved in PrCOB crystals, with values being on the order of 24.7% and 13.1 pC/N, respectively. The high thermal stability of the electromechanical properties, with variation less than 25%, together with the low dielectric loss (<;46%) and high mechanical quality factor (>;1500) at elevated temperatures of 1000°C, make ErCOB, YCOB, and GdCOB crystals promising for ultrahigh temperature electromechanical applications.
Architectural design of adaptive distributed multimedia systems

In the context of a collaborative research project funded by the Canadian Institute for Telecommunications Research (CITR), we have developed a prototype system for remote access to News-on-Demand. This system allows the user to remotely access a multimedia database, containing news clips in the form of multimedia documents, over ATM and other types of networks. Special attention is given to quality of service (QoS) negotiation and adaptation. For instance, a given document may exist in different versions on different sites and possibly corresponding to different presentation qualities, such as video and audio quality, size of display and cast. A graphical interface is available for the user to select his preferences and provides the possibility of obtaining examples of specific quality features. The QoS negotiation and adaptation features allow for the selection of the best configuration for a given user request and for automatic adaptation in case of changes to the system parameters, such as network or server congestion. We present in this paper an abstract architectural design of our adaptive distributed multimedia system for remote access to multimedia databases. This design focused on the aspects of the system which are essential for QoS negotiation and adaptation, which is our main concern in the ongoing CITR research project. The paper gives a functional overview of the system and details its structural and behavioral aspects. An abstract application programming interface (API) is given and issues related to the transition from the abstract system design to an implementation are discussed.