pinecone/core-2020-05-10-deduplication huggingface dataset:
Thresholds for error probability measures of business process models

The quality of conceptual business process models is highly relevant for the design of corresponding information systems. In particular, a precise measurement of model characteristics can be beneficial from a business perspective, helping to save costs thanks to early error detection. This is just as true from a software engineering point of view. In this latter case, models facilitate stakeholder communication and software system design. Research has investigated several proposals as regards measures for business process models, from a rather correlational perspective. This is helpful for understanding, for example size and complexity as general driving forces of error probability. Yet, design decisions usually have to build on thresholds, which can reliably indicate that a certain counter-action has to be taken. This cannot be achieved only by providing measures; it requires a systematic identification of effective and meaningful thresholds. In this paper, we derive thresholds for a set of structural measures for predicting errors in conceptual process models. To this end, we use a collection of 2,000 business process models from practice as a means of determining thresholds, applying an adaptation of the ROC curves method. Furthermore, an extensive validation of the derived thresholds was conducted by using 429 EPC models from an Australian financial institution. Finally, significant thresholds were adapted to refine existing modeling guidelines in a quantitative way
An ontology-based framework for semantic grid service composition

The Semantic Grid aims at enhancing Grid architectures by\ud
knowledge engineering techniques. The service notion is central in this approach. Service-level agreements, called contracts, are formed to define the service usage conditions. Ontology technology can form the framework to capture semantical conditions for contracts. Often, applications of Grid services involve a combination of several services. We present an ontology-based framework for service composition for the Semantic Grid. We take a process-oriented view of services, achieving an intrinsic\ud
representation of services and their composition in an ontology
Optimizing Logistic Regression Coefficients for Discrimination and Calibration Using Estimation of Distribution Algorithms.

Logistic regression is a simple and efficient supervised learning algorithm for estimating the probability of an outcome or class variable. In spite of its simplicity, logistic regression has shown very good performance in a range of fields. It is widely accepted in a range of fields because its results are easy to interpret. Fitting the logistic regression model usually involves using the principle of maximum likelihood. The Newton–Raphson algorithm is the most common numerical approach for obtaining the coefficients maximizing the likelihood of the data.  This work presents a novel approach for fitting the logistic regression model based on estimation of distribution algorithms (EDAs), a tool for evolutionary computation. EDAs are suitable not only for maximizing the likelihood, but also for maximizing the area under the receiver operating characteristic curve (AUC).  Thus, we tackle the logistic regression problem from a double perspective: likelihood-based to calibrate the model and AUC-based to discriminate between the different classes. Under these two objectives of calibration and discrimination, the Pareto front can be obtained in our EDA framework. These fronts are compared with those yielded by a multiobjective EDA recently introduced in the literature
Teaching about Madrid: A Collaborative Agents-Based Distributed Learning Course

Interactive art courses require a huge amount of computational resources to be running on real time. These computational resources are even bigger if the course has been designed as a Virtual Environment with which students can interact. In this paper, we present an initiative that has been develop in a close collaboration between two Spanish Universities: Universidad Politécnica de Madrid and Universidad Rey Juan Carlos with the aim of join two previous research project: a Collaborative Awareness Model for Task-Balancing-Delivery (CAMT) in clusters and the “Teaching about Madrid” course, which provides a cultural interactive background of the capital of Spain
Pulsating flow and convective heat transfer in a cavity with inlet and outlet sections

This paper deals with the study of 2-D, laminar, pulsating flow inside a heated rectangular cavity with different aspect ratios. The cooling liquid (water with temperature dependent viscosity and thermal conductivity) comes and leaves the cavity via inlet and outlet ports. The flow topology is characterised by the large recirculation regions that exist at inner corners of the cavity. These low velocity regions cause the heat transfer to be small when compared, for instance, to that of a straight channel. We study the effect that a prescribed pulsation at the inlet port has on the cavity heat transfer. This pulsating boundary condition, of the unsteady Poiseuille type, is described by its frequency and the amplitude of the pressure gradient. The time averaged Reynolds number of the flow, based on the hydraulic diameter of the inlet channel, is 100 and we consider that the dimensionless pulsation frequency (Strouhal number) varies in the range from 0.0 to 0.4. We show that the prescribed pulsation enhances heat transfer in the cavity and that the mechanism that causes this enhancement appears to be the periodic change in the recirculation flow pattern generated by the pulsation. Regarding the quantitative extent of heat transfer recovery, we find that appropriate selection of the pulsation parameters allows for the cavity to behave like a straight channel that is the configuration with the highest Nusselt number
High-temperature mechanical properties of aluminium alloys reinforced with titanium diboride (TiB2) particles

The physical and mechanical properties of metal matrix composites were improved by the addition of reinforcements. The mechanical properties of particulate-reinforced metal-matrix composites based on aluminium alloys (6061 and 7015) at high temperatures were studied. Titanium diboride (TiB2) particles were used as the reinforcement. All the composites were produced by hot extrusion. The tensile properties and fracture characteristics of these materials were investigated at room temperature and at high temperatures to determine their ultimate strength and strain to failure. The fracture surface was analysed by scanning electron microscopy. TiB2 particles provide high stability of the aluminium alloys (6061 and 7015) in the fabrication process. An improvement in the mechanical behaviour was achieved by adding TiB2 particles as reinforcement in both the aluminium alloys. Adding TiB2 particles reduces the ductility of the aluminium alloys but does not change the microscopic mode of failure, and the fracture surface exhibits a ductile appearance with dimples formed by coalescence
Particle swarm-based olfactory guided search

Abstract  This article presents a new algorithm for searching odour sources across large search spaces with groups of mobile robots. The proposed algorithm is inspired in the particle swarm optimization (PSO) method. In this method, the search space is sampled by dynamic particles that use their knowledge about the previous sampled space and share this knowledge with other neighbour searching particles allowing the emergence of efficient local searching behaviours. In this case, chemical searching cues about the potential existence of upwind odour sources are exchanged. By default, the agents tend to avoid each other, leading to the emergence of exploration behaviours when no chemical cue exists in the neighbourhood. This behaviour improves the global searching performance.  The article explains the relevance of searching odour sources with autonomous agents and identifies the main difficulties for solving this problem. A major difficulty is related with the chaotic nature of the odour transport in the atmosphere due to turbulent phenomena. The characteristics of this problem are described in detail and a simulation framework for testing and analysing different odour searching algorithms was constructed. The proposed PSO-based searching algorithm and modified versions of gradient-based searching and biased random walk-based searching strategies were tested in different environmental conditions and the results, showing the effectiveness of the proposed strategy, were analysed and discussed.http://dx.doi.org/10.1007/s10514-006-7567-
Data transformation and query management in personal health sensor networks

Sensor technology has been exploited in many application areas ranging from climate monitoring, to traffic management, and healthcare. The role of these sensors is to monitor human beings, the environment or instrumentation and provide continuous streams of information regarding their status or well being. In the case study presented in this work, the network is provided by football teams with sensors generating continuous heart rate values during a number of different sporting activities. In wireless networks such as these, the requirement is for methods of data management and transformation in order to present data in a format suited to high level queries. In effect, what is required is a traditional database-style query interface where domain experts can continue to probe for the answers required in more specialised environments. The challenge arises from the gap that emerges between the low level sensor output and the high level user requirements of the domain experts. This paper describes a process to close this gap by automatically harvesting the raw sensor data and providing semantic enrichment through the addition of context data
Comparative metal distribution in scalp hair of Pakistani and Irish referents and diabetes mellitus patients

Background: The essential metals, chromium (Cr), magnesium (Mg), manganese (Mn) and zinc (Zn), are necessary for many metabolic processes and their homeostasis is crucial for life. The toxic metals, cadmium (Cd) and lead (Pb), have no beneficial role in human metabolism. The aim of this study was to investigate the levels of Cd, Cr, Mg, Mn, Pb, and Zn in scalp hair samples of type 2 diabetes mellitus patients of both genders, ages ranging from 30 to 50 y, and belong to urban areas of Ireland and Pakistan. For comparison purposes, age matched non-diabetic subjects of both countries were selected as referents. Methods: The concentrations of metals in scalp hair samples were measured by inductively coupled plasma atomic emission spectrophotometer and atomic absorption spectrophotometer after microwave-assisted acid digestion. The validity and accuracy of the methodology were checked by conventional wet-acid-digestion method and using certified reference materials. Results: The mean values of Cd and Pb were significantly higher in scalp hair samples of both Pakistani and Irish diabetic patients as compared to referents of both countries (P<0.001). In contrast, lower Cr, Mg, Mn, and Zn (P<0.01) concentrations were detected in scalp hair derived from patients with type 2 diabetes versus healthy subjects of both countries. Conclusion: This study showed that, increased toxic elements and decreased essential elements are associated with diabetes mellitus. Therefore, these elements may play a role in the development and pathogenesis of diabetes mellitus
Numerical Simulations of Void Linkage in Model Materials using a Nonlocal Ductile Damage Approximation

Experiments on the growth and linkage of 10 μm diameter holes laser drilled in high precision patterns into Al-plates were modelled with finite elements. The simulations used geometries identical to those of the experiments and incorporated ductile damage by element removal under the control of a ductile damage indicator based on the micromechanical studies of Rice and Tracey. A regularization of the problem was achieved through an integral-type nonlocal model based on the smoothing of the rate of a damage indicator D over a characteristic length L. The simulation does not predict the experimentally observed damage acceleration either in the case where no damage is included or when only a local damage model is used. However, the full three-dimensional simulations based on the nonlocal damage methodology do predict both the failure path and the failure strain at void linkage for almost all configurations studied. For the cases considered the critical parameter controlling the local deformations at void linkage was found to be the ratio between hole diameter and hole spacing
Mealiness assessment in apples using MRI techniques

Small samples of Top Red apples stored 6 months under controlled atmosphere (expected to be non-mealy) and 2°C (expected to be mealy) have been used for MRI imaging. Multi-slice-multi-echo magnetic resonance images (64*64 pixels) have been recorded with a 8 ms echo time. Three out of four apples corresponding to the sample maintained under controlled atmosphere did not developed mealiness while three out of four fruits corresponding to the sample stored at 2°C became mealy after 6 months of storage. The minimum T2 values obtained for the mealy apples show to be significantly lower (F = 13.21) when compared with non-mealy apples pointing that a more desegregated structure and a lower juiciness content leads to lower T2 signal. Also, there is a significant linear correlation (r = −0.76) between the number of pixels with a T2 value below 35 ms within a fruit image and the deformation parameter registered during the Magness–Taylor firmness test. Finally, all T2 maps of mealy apples show a regional variation of contrast which is not shown for non-mealy apples. Significant differences (F = 19.43) between mealy and non-mealy apples are found in the histograms of the T2 maps as mealy apples show a skew histogram combined with a “tail” in their high T2 extreme which is not shown in the histograms of non-mealy apples. These histogram features are also shown for an apple showing internal breakdown indicating that in mealy apples there is a differential water movement that may precede internal breakdown
Multifractal analysis of discretized X-ray CT images for the characterization of soil macropore structures

A correct statistical model of soil pore structure can be critical for understanding flow and transport processes in soils, and creating synthetic soil pore spaces for hypothetical and model testing, and evaluating similarity of pore spaces of different soils. Advanced visualization techniques such as X-ray computed tomography (CT) offer new opportunities of exploring heterogeneity of soil properties at horizon or aggregate scales. Simple fractal models such as fractional Brownian motion that have been proposed to capture the complex behavior of soil spatial variation at field scale rarely simulate irregularity patterns displayed by spatial series of soil properties. The objective of this work was to use CT data to test the hypothesis that soil pore structure at the horizon scale may be represented by multifractal models. X-ray CT scans of twelve, water-saturated, 20-cm long soil columns with diameters of 7.5 cm were analyzed. A reconstruction algorithm was applied to convert the X-ray CT data into a stack of 1480 grayscale digital images with a voxel resolution of 110 microns and a cross-sectional size of 690 × 690 pixels. The images were binarized and the spatial series of the percentage of void space vs. depth was analyzed to evaluate the applicability of the multifractal model. The series of depth-dependent macroporosity values exhibited a well-defined multifractal structure that was revealed by singularity and Rényi spectra. The long-range dependencies in these series were parameterized by the Hurst exponent. Values of the Hurst exponent close to one were observed indicating the strong persistence in variations of porosity with depth. The multifractal modeling of soil macropore structure can be an efficient method for parameterizing and simulating the vertical spatial heterogeneity of soil pore space
Wind turbine wakes for wind energy

During recent years, wind energy has moved from an emerging technology to a nearly competitive technology. This fact, coupled with an increasing global focus on environmental concern and a political desire of a certain level of diversification in the energy supply, ensures wind energy an important role in the future electricity market. For this challenge to be met in a cost-efficient way, a substantial part of new wind turbine installations is foreseen to be erected in big onshore or offshore wind farms. This fact makes the production, loading and reliability of turbines operating under such conditions of particular interest
High precision pressure sensors based on SAW devices in the GHz range

In this paper, an AlN/free-standing nanocrystalline diamond (NCD) system is proposed in order to process high frequency surface acoustic wave (SAW) resonators for sensing applications. The main problem of synthetic diamond is its high surface roughness that worsens the sputtered AlN quality and hence the device response. In order to study the feasibility of this structure, AlN films from 150 nm up to 1200 nm thick have been deposited on free-standing NCD. We have then analysed the influence of the AlN layer thickness on its crystal quality and device response. Optimized thin films of 300 nm have been used to fabricate of one-port SAW resonators operating in the 10–14 GHz frequency range. A SAW based sensor pressure with a sensibility of 0.33 MHz/bar has been fabricated
Variation of PM2.5 concentrations in relation to street washing activities

Several studies conducted in urban areas have pointed out that road dust resuspension contributes significantly to PM concentration levels. Street washing is one of the methods proposed to reduce resuspended road dust contributions to ambient PM concentrations. As resuspended particles are mainly found in the coarse mode, published studies investigating the effects of street washing have focused on PM10 size fraction. As the PM2.5 mass fraction of particles originating from mechanical abrasion processes may still be significant we conducted a study in order to evaluate the effects of street washing on the mitigation of resuspension of fine particles. The PM2.5 mass concentration data were examined and integrated with the occurrence of street washing activities. In addition, the effect of the meteorological variability, traffic flow and street washing activities, on ambient PM2.5 levels was valuated by means of a multivariate regression model. The results revealed that traffic  low is the most important factor that controls PM2.5 hourly concentrations while street washing activities did not influence fine particle mass levels
Finite element code-based modeling of a multi-feature isolation system and passive alleviation of possible inner pounding

The existing seismic isolation systems are based on well-known and accepted physical principles, but they are still having some functional drawbacks. As an attempt of improvement, the Roll-N-Cage (RNC) isolator has been recently proposed. It is designed to achieve a balance in controlling isolator displacement demands and structural accelerations. It provides in a single unit all the necessary functions of vertical rigid support, horizontal flexibility with enhanced stability, resistance to low service loads and minor vibration, and hysteretic energy dissipation characteristics. It is characterized by two unique features that are a self-braking (buffer) and a self-recentering mechanism. This paper presents an advanced representation of the main and unique features of the RNC isolator using an available finite element code called SAP2000. The validity of the obtained SAP2000 model is then checked using experimental, numerical and analytical results. Then, the paper investigates the merits and demerits of activating the built-in buffer mechanism on both structural pounding mitigation and isolation efficiency. The paper addresses the problem of passive alleviation of possible inner pounding within the RNC isolator, which may arise due to the activation of its self-braking mechanism under sever excitations such as near-fault earthquakes. The results show that the obtained finite element code-based model can closely match and accurately predict the overall behavior of the RNC isolator with effectively small errors. Moreover, the inherent buffer mechanism of the RNC isolator could mitigate or even eliminate direct structure-tostructure pounding under severe excitation considering limited septation gaps between adjacent structures. In addition, the increase of inherent hysteretic damping of the RNC isolator can efficiently limit its peak displacement together with the severity of the possibly developed inner pounding and, therefore, alleviate or even eliminate the possibly arising negative effects of the buffer mechanism on the overall RNC-isolated structural responses
Temporally flat top pulse generation from gain switched semiconductor lasers based on a polarization interferometer with variable transfer function

We propose the use of a polarization based interferometer with variable transfer function for the generation of temporally flat top pulses from gain switched single mode semiconductor lasers. The main advantage of the presented technique is its flexibility in terms of input pulse characteristics, as pulse duration, spectral bandwidth and operating wavelength. Theoretical predictions and experimental demonstrations are presented and the proposed technique is applied to two different semiconductor laser sources emitting in the 1550 nm region. Flat top pulses are successfully obtained with input seed pulses with duration ranging from 40 ps to 100 ps
Extension of analytical indicial aerodynamics to generic trapezoidal wings in subsonic flow

Analytical indicial aerodynamic functions are calculated for several trapezoidal wings in subsonic flow, with a Mach number 0.3≤ Ma≤ 0.7. The formulation herein proposed extends well-known aerodynamic theories, which are limited to thin aerofoils in incompressible flow, to generic trapezoidal wing planforms. Firstly, a thorough study is executed to assess the accuracy and limitation of analytical predictions, using unsteady results from two state-of-the-art computational fluid dynamics solvers as cross-validated benchmarks. Indicial functions are calculated for a step change in the angle of attack and for a sharp-edge gust, each for four wing configurations and three Mach numbers. Then, analytical and computational indicial responses are used to predict dynamic derivatives and the maximum lift coefficient following an encounter with a one-minus-cosine gust. It is found that the analytical results are in excellent agreement with the computational results for all test cases. In particular, the deviation of the analytical results from the computational results is within the scatter or uncertainty in the data arising from using two computational fluid dynamics solvers. This indicates the usefulness of the developed analytical theories
Grasping trapezoidal objects

When grasping rectangular or circular objects with a precision grip the digits close in on the object in opposite directions.
 In doing so the digits move perpendicular to the local surface orientation as they approach opposite sides of the object.
 This perpendicular approach is advantageous for accurately placing the digits. Trapezoidal objects have non-parallel surfaces
 so that moving the digits in opposite directions would make the digits approach the contact surfaces at an angle that is not
 90. In this study we examined whether this happens, or whether subjects tend to approach trapezoidal objects’ surfaces perpendicularly.
 We used objects of different sizes and with different surface slants. Subjects tended to approach the object’s surfaces orthogonally,
 suggesting that they aim for an optimal precision of digit placement rather than simply closing their hand as it reaches the
 object