Miracle-dz/UniFAR-FTUs huggingface dataset:
An Evaluation of Calibration Methods for Data Mining Models in Simulation Problems

Data mining can help us in decision making by using data to obtain accurate models upon which evaluate several options. In general, data mining is used for a specific area in isolation, and models from different areas of a business/organisation are not usually related, so optimal local decisions are good. The problem is when we have to make several decision and they are interwoven with each other. In this case, in general, the best local decisions do not make the best global result. Therefore, we propose using simulation to merge the local data mining models and to obtain a good global result. In this work, we apply simulation to face a customer relationship management (CRM) problem, i.e., a direct-marketing campaign design where several alternative products have to be offered to the same house list of customers. Usually, the decisions make by the data mining models are accompanied with probabilities. If we merge these local probabilistic models, we will need accurate probabilities. If we have not had realistic probabilities, it probably will not affect to the local model, but it will be a disaster when the local models were combined. To assure accurate probabilities, we calibrate the probabilities of the models. So, in order to improve model combination, we also analyse the main calibration techniques and propose a new one inspired in binning-based methods in which the calibrated probabilities are obtained from k instances. Our calibration method use all the problem attributes to calculate the calibrated probabilities, while the classical calibration methods only use the estimated probability. Moreover, our proposed method has the advantage that it can be applied to multiclass problems directly, something that other calibration methods cannot. In general, calibrated models are necessary in complex scenarios where several models have to be combined if we want to obtain good overall results, since a single uncalibrated local model can make the overall model diverge.
Delineating the effect of market orientation on services performance: a component-wise approach

This article attempts to delve deeper into the relationship between the three core components of market orientation and service performance, settle literature inconsistencies and provide insights into the role of each component. A conceptual model is presented in which a synergetic mechanism among the market orientation components and their link to service performance is proposed. The model is tested in the context of travel and tourism services by gathering data from Greece and Lithuania and using structural equation modelling. The results indicate that customer orientation is the only direct determinant of service performance, whereas competitor orientation and inter-functional coordination exhibit indirect effects through customer orientation. The study provides new directions to market orientation research and assists marketing managers of services firms in gaining a better understanding of the concept and its implementation for accomplishing optimal performance results.
Spectrally dependent locations of hot‐spots in nanoparticle clusters

We study the optical response of clusters of metallic nanospheres in the electrostatic approximation, using a spherical harmonic representation of the electric field. Field enhancement and near field interactions between the spheres are investigated numerically. Symmetry properties of certain clusters give rise to highly localized maxima of the electric field, denoted “hot spots. ” From numerical experiments performed at optical frequencies of the incident light, it is found that various geometrical configurations exhibit interesting phenomena; in particular, that hot spots move spatially around as a function of the frequency of the incident light. We present simulation results for the simplest nanoparticle cluster known to exhibit these interesting phenomena, namely, a regular octahedron.
Does real estate transparency matter for foreign real estate investments

The purpose of this paper is to examine the impact of real estate transparency ( RET ) on foreign real estate investments ( FREI ). Most of the previous studies have argued that the free flow of information and the fair and consistent application of local property laws could attract greater amounts of FREI . Using observations from 32 countries covering 2004, 2006, 2008 and 2010 and applying fixed-effect and the generalized method of moments ( GMM ) techniques, our empirical results reveal that RET is not a major determinant of FREI . However, we find that the effect of RET on FREI is dependent on its interaction with the level of income implying that the higher the level of income in the host country, the higher the effect of RET on FREI . Finally, the results show that foreign direct investment (FDI) in other sector, market size and property prices are important determinants of FREI .
SAMPLE SELECTION BIAS WITH MULTIPLE SELECTION RULES: APPLICATION WITH RESIDENTIAL RELOCATION, ATTRITION, AND ACTIVITY PARTICIPATION IN PUGET SOUND TRANSPORTATION PANEL

Two sources of sample selection bias emerging simultaneously from panel attrition and residential relocation and their effect on activity participation are examined. The data used were from two time points (Wave 1 in 1989 and Wave 2 in 1990) of the Puget Sound Transportation Panel. Data regarding relocation decisions, taking place between Wave 1 and Wave 2, are available for the households that participated in both waves (participants) and are not available for the households that participated in the first wave only (dropouts). Double selection was associated with the possible simultaneous or sequential decision process underlying participation in the survey and household residential relocation. The method used is based on a bivariate probit model that accounts for selectivity. The method emerges from the unknown relocation status of the dropouts in Wave 2. Subsequent creation of correction terms, needed to account for the lack of data on dropout households' activity participation in Wave 2, uses the probit model. The method, called the Tunali method, is a two-step procedure that follows the usual Heckman method. The models estimated, that is, the bivariate probit model of double-selection and activity participation linear regressions corrected and uncorrected for selection, are provided.
Work-Life Balance, Perceived Stress, & Locus of control: A Chain of Interrelated Predicaments

This study aims at verifying whether a lower level of perceived stress combined with a high level of control predict a higher level of perceived work life balance for employees in the Lebanese banking sector. Primary data was collected using 195 surveys that were distributed in several commercial banks in Lebanon. Correlations and regression were performed to test the suggested hypotheses. According to the result of this study, work life balance is positively affected by an increased level of control as well as a decreased level of perceived stress. Thus, organizations should make sure that their employees are experiencing a “fair” level of work life balance to ensure a maximized level of job performance, job satisfaction, and maximum organizational efficiency and productivity. Moreover, locus of control should be taken into consideration during the screening process of potential employees. Further research should concentrate more on women with an internal locus of control, on employees in other work sectors in Lebanon, on men working in banks, and on the role that employees’ work involvement and commitment levels play in affecting their perceived levels of stress and work life balance.
Model-based detection of sensor faults under changing temperature conditions

Nowadays, a variety of civil, aeronautic or mechanical engineering structures need regular inspections. While non-destructive testing has become state of the art, there is a trend towards online testing on demand using built-in sensors. A vast amount of in-service monitoring, as part of structural health monitoring, uses piezoelectric elements. Their deployment requires a control of the sensor performance in order to prevent false alarm. Several kinds of damage can influence the sensor performance, for example, degradation of piezoceramic or adhesive, debonding or breakage of the element. Therefore, this paper aims to detect damage of circular piezoelectric elements and their bonding layers during in-service monitoring. For this purpose, a local method, using the coupled electro-mechanical admittance, is proposed. However, changing environmental and operational conditions such as temperature have an effect on the measured quantities, masking the damage. To cope with this, the dynamic behaviour of an attached piezoelectric element including temperature trends is modelled to enable physics-based temperature compensation. This novel combination of an improved analytical model, updated according to impedance measurements, realizes a method less dependent on experimental baseline data, than the sole comparison of experimental data, established in many monitoring systems. By comparison with experimentally obtained electro-mechanical susceptance the physical model of circular piezoelectric elements is validated. The feasibility of the proposed method is presented employing experimental data of piezoelectric elements mounted on aluminium coupons, partly damaged with degradation and sensor breakage. The application produces promising results, detecting the created defects.
COMPARISON BETWEEN ESTIMATES OF THE POTENTIAL PROPORTION WITH AND WITHOUT STANDARDIZATION FOR A NON-CONFOUNDER

A covariate is not a confounder if it is not a risk factor to disease, or if it has the same distribution in the exposed and unexposed populations. Standardiza- tion for a confounder can reduce confounding bias, but that for a non-confounder cannot. A question argued by many authors asks whether or not standardization of a non-confounder can improve the precision of estimation. This paper discusses the hypothetical or potential proportion of individuals in the exposed population who would have developed the disease had they not been exposed. It is shown that the precision of estimation of the hypothetical proportion cannot usually be improved by using standardization for a non-confounder, no matter how one re-categorizes the non-confounder.
Ionizing radiation effects on CMOS imagers manufactured in deep submicron process

We present here a study on both CMOS sensors and elementary structures (photodiodes and in-pixel MOSFETs) manufactured in a deep submicron process dedicated to imaging. We designed a test chip made of one 128×128-3T-pixel array with 10 μm pitch and more than 120 isolated test structures including photodiodes and MOSFETs with various implants and different sizes. All these devices were exposed to ionizing radiation up to 100 krad and their responses were correlated to identify the CMOS sensor weaknesses. Characterizations in darkness and under illumination demonstrated that dark current increase is the major sensor degradation. Shallow trench isolation was identified to be responsible for this degradation as it increases the number of generation centers in photodiode depletion regions. Consequences on hardness assurance and hardening-by-design are discussed.
Linking Transformational Leadership to Student Teachers’ Efficacy: Contributions of Mentor Teachers’ Leadership Behaviors

A literature review of student interns’ (often referred to as student teachers or pre-service teachers)efficacy beliefs revealed that most studies have focused on the effects of teacher efficacy on teachereffectiveness and student achievement. However, the role that mentor teachers (often referred to ascooperating teachers or collaborating teachers) play in the growth of efficacy beliefs of student internshas received little attention, and the empirical evidence is insufficient. A teacher’s sense of efficacy hasbeen defined as "the teacher’s belief in his or her capability to organize and execute courses of actionrequired to successfully accomplish a specific teaching task in a particular context" (Tschannen-Moran& Woolfolk Hoy, 1998, p. 233). Teacher efficacy has been correlated with education innovations(Cousins & Walker, 2000), classroom management (Woolfolk, Rosoff, & Hoy, 1990), teaching effort(Allinder, 1994), and commitment to teaching (Coladarci, 1992). According to Erdem & Demirel(2007), the teachers’ sense of efficacy is crucial to manage classroom, organize and teach courses,and motivate and communicate students for learning effectively. Teacher efficacy also has been linkedto student motivations (Midgley, Feldlaufer, & Eccles, 1989), academic achievement (Ashton & Webb,1986; Moore & Esselman, 1992; Ross, 1992; Muijs & Reynolds, 2002), and classroom behavior(Tschannen-Moran & Woolfolk Hoy, 2001).
Impact of local-negative-feedback on the MRS avalanche photodetector operation

Metal-Resistance-Semiconductor (MRS) photodetectors are characterized by a resistive layer placed in series to an avalanching region. In this paper, we report the characterization of such devices, we define a parameter extraction procedure, and we derive a quantitative model of the MRS operation. Due to the presence of the ohmic layer, the detector works as an ensemble of pixels with separately stabilized operating bias. In this way, compared to avalanche photodiodes (APDs), MRS achieve superior gain uniformity with the same sensitive area. However, there are still aspects of the fabrication technology and of the detector structure which have to be improved.
Probabilistic Graphs Using ClusteringAlgorithm with Efficient Performance

Probabilistic Graphs is observed that correlations may exist among adjacent edges in various probabilistic graphs of the data mining community. Typically, data mining clustering has been modeled as the problem of training a binary cluster using reviews automated for positive or negative sentiment result. Cluster, sentiment is expressed differently in different domains, and annotating corpora for every possible domain of interest is costly Automatic clustering of sentiment is important for numerous applications such as exploratory data analysis, such as data compression, information retrieval, image segmentation, etc. Cluster evaluate the effectiveness and efficiency of our algorithms and pruning methods through comprehensive experiments. Cluster use the created thesaurus to expand feature vectors during train and test times in a binary classifier. Cluster define the problem of clustering correlated probabilistic graphs. To solve the challenging problem, Cluster propose two algorithms, namely the SPEEDR’s/ PEEDR’s and the CPG’S clustering algorithm. For each of the proposed algorithms, Cluster develop several pruning techniques to further improve their efficiency.
The Identification of Salient Beliefs concerning University Students' Decisions to Participate in Sport

The aim of this study was to identify salient beliefs toward university-provided recreational sport in first-year undergraduate students. A purposive sample of 76 students (36 males, 40 females; mean age: 19.2 ± 1.7 years) undertaking various degree subjects at a higher education institution in the North of England, United Kingdom, was used in the study. The instrument was a theory-based open-ended questionnaire informed by the Theory of Planned Behavior, addressing behavioral, normative, and control beliefs. Thematic content analysis and coding was conducted on 30 randomly selected questionnaires followed by a frequency count to identify the modal salient beliefs. The modal set revealed 17 beliefs from a possible 53: six behavioral, five normative, and six control. These beliefs were related to health benefits, enjoyment, friendships, time constraints, study workloads, awareness, and the perception of family, friends, and academics. The results highlight the factors that should be targeted for intervention and provide data to be utilized for a second main quantitative study which will identify more specific belief targets. Due to equivocal intervention success, this formative research can serve to help increase the number of students participating in university recreational sport.
A Geochemical Study of Selected Samples from the Basement Cores Recovered at Sites 447, 448, 449, 450, and 451, Deep Sea Drilling Project Leg 59

Deep Sea Drilling Project Legs 59 and 60 drilled 15 sites along an east-west transect at 18°N from the West Philippine Basin to the Mariana Trench (Fig. 1) in order to study the nature and genesis of the back-arc, marginal basins and the remnant and active arcs of the region. Leg 59 drilled at five sites at the western end of the traverse: Site 447 in the West Philippine Basin; Site 448 on the Palau-Kyushu Ridge; Sites 449 and 450 in the Parece Vela Basin; and Site 451 on the West Mariana Ridge. Penetration into basaltic basement of these sites was 183.5 meters at 447 (8 basalt flows); 623 meters at 448 (46 basalt flows, sills, and dikes and volcaniclastic units); 40.5 meters at 449 (2 basalt flows); 7 meters at 450 (1 basalt intrusion); and 4 meters of basalt breccia at 451 overlain by 861 meters of volcaniclastic sedimentary rocks. The petrology, mineralogy, and geochemistry of these cores have been described by Mattey et al. (this volume). They have distinguished the main igneous units recovered on the basis of X-ray fluorescence (XRF), whole rock geochemical data, microprobe data for minerals and glasses, and petrography. From these data we have chosen 17 samples which are representative of the main compositional units and subjected them to epithermal neutron activation analysis (Chayla et al., 1973; Jaffrezic et al., in press) to obtain high precision data for a number of trace elements (viz. Sc, Co, Cs, La, Ce, Eu, Tb, Hf, Ta, Th, and U) which could not be obtained by XRF. The core intervals of the 17 samples are given in Table 1 together with a summary of the nature and size of the compositional units from which they are taken. Major and trace element analyses of the samples are given in Table 2. One aim of this study has been to compare the composition of these rocks with those erupted in other tectonic environments to elucidate the chemical characteristics of basaltic crust formed at active plate margins which consist of a series of remnant island arcs and interarc basins. Data for mid-ocean ridge basalts and the lava series of Japan have been particularly useful to us in this respect.
Prediction of Stance Time and Force Symmetries using Instrumented Shoe Insoles for Use in Rehabilitation and Weight-Bearing Regimens

Objective: Evaluate predictions of stance time symmetry and stance force symmetry from wireless bilateral instrumented shoe insoles designed for rehabilitation using smartphone applications to provide real-time feedback. Design: Cross-sectional study. Subjects: Five subjects with no known gait abnormalities. Methods: Subjects performed ten trials of three conditions: walking without a limp, limping on the right foot, and limping on the left foot, with data captured simultaneously with two force plates and the instrumented shoe insoles. Linear regression analyses were used to develop prediction equations and significance. Results: The regression between the instrumented shoe insole and the force plate resulted in R-squared values ranging from 0.952 to 0.998 for stance time symmetry using symmetry ratio, and from 0.936 to 0.994 for stance force symmetry using a cumulative loading measure for force. With peak and average loading measures, R-squared values were lower and more variable. Conclusion: Symmetry based on stance times or stance forces was highly predicted using the instrumented shoe insoles. Instrumented shoe insoles and real-time feedback on a smartphone could be used in the future for improving patient compliance with weight-bearing regimens or other time or force based symmetry analyses outside of the gait laboratory setting.
Recommending social platform content using deep learning A reccurrent neural network model as an alternative to existing recommender systems

In this thesis a model based on artificial neural networks, seeing how they have found successes in a variety of fields in recent years, is proposed as an alternative to existing recommender systems. A recurrent neural network model is built for recommending content to users on the social forum Reddit based on the titles of posts. The model is compared against Facebook’s fastText classifier and a model based on N-grams. The model proposed is performing close to, but not as well as either fastText or the N-grams based model. The model does not show any real advantages in its current state but a lot of potential improvements are proposed.
THz-ToF techniques for the detection of inherent discontinuities in dielectric materials based on a SAFT – and an optical layer reconstruction algorithm

Electromagnetic waves with frequencies between 0.1 and 10 THz are described as THz-radiation (T-ray). The ability to penetrate dielectric materials makes T-rays attractive to reveal discontinuities in polymer and ceramic materials. THz-Time Domain Spectroscopy Systems (THz-TDS) are available on the market today which operates with THz-pulses transmitted and received by optically pumped semiconductor antennas. In THz-TDS the travelling time (ToF) and shape of the pulse is changed if it interacts with the dielectric material and its inherent disconti-nuities. A tomogram of the object under the test can be reconstructed from time of flight diffraction (ToFD) scans if a synthetic focusing aperture (SAFT) algorithm is applied. Otherwise, planar discontinuities like cracks in plastics or delaminated lay-ers in composites can be abstracted as layers located at any angle in relation to the outer sample surface direction. A tomogram from the scanned sample can then be reconstructed in case the interactions of electromagnetic pulses with the existing in-herent interfaces are detectable and a model is assumed which describes the device under the test as multilayer structure composed of thin layers with different dielec-tric properties. A short description of both the SAFT – and Optical Layer algorithm for the recon-struction of the inherent structure is initially given. Measurements on representative samples with a variety of artificially produced small and large scale. Reconstructed tomograms are presented to discuss and evaluate the benefits and limits of the two different reconstruction approaches.
Soliton ensembles and solitonic structures

The article deals with the analysis of three complicated one-dimensional evolution equations, the solutions of which can be classified as soliton ensembles or solitonic structures. The case studies from the physical viewpoint are: (i) martensitic–austenitic alloys; (ii) hyperelastic rod and (iii) granular materials. The corresponding evolution equations governing the propagation of longitudinal waves include higher order nonlinear and dispersive terms and are nonintegrable. Numerical simulation is carried out by the pseudospectral method. The first class of solutions involves solitons with nonvanishing oscillatory tails and wave packets called solitonic structures. The second class includes special soliton ensembles or more exactly – plaited solitons. The emergence of such entities and their interaction demonstrate the solitonic character of waves.