On Using Active Learning and Self-Training when Mining Performance Discussions on Stack Overflow

Abundant data is the key to successful machine learning. However, supervised learning requires annotated data that are often hard to obtain. In a classification task with limited resources, Active Learning (AL) promises to guide annotators to examples that bring the most value for a classifier. AL can be successfully combined with self-training, i.e., extending a training set with the unlabelled examples for which a classifier is the most certain. We report our experiences on using AL in a systematic manner to train an SVM classifier for Stack Overflow posts discussing performance of software components. We show that the training examples deemed as the most valuable to the classifier are also the most difficult for humans to annotate. Despite carefully evolved annotation criteria, we report low inter-rater agreement, but we also propose mitigation strategies. Finally, based on one annotator's work, we show that self-training can improve the classification accuracy. We conclude the paper by discussing implication for future text miners aspiring to use AL and self-training.Comment: Preprint of paper accepted for the Proc. of the 21st International Conference on Evaluation and Assessment in Software Engineering, 201

A Double Fourier-Transform Imaging Algorithm for a 24 GHz FMCW Short-Range Radar

A frequency-modulated continuous-wave radar for short-range target imaging, assembling a transceiver, a PLL, an SP4T switch, and a serial patch antenna array, was realized. A new algorithm based on a double Fourier transform (2D-FT) was developed and compared with the delay and sum (DAS) and multiple signal classification (MUSIC) algorithms proposed in the literature for target detection. The three reconstruction algorithms were applied to simulated canonical cases evidencing radar resolutions close to the theoretical ones. The proposed 2D-FT algorithm exhibits an angle of view greater than 25° and is five times faster than DAS and 20 times faster than the MUSIC one. The realized radar shows a range resolution of 55 cm and an angular resolution of 14° and is able to correctly identify the positions of single and multiple targets in realistic scenarios, with errors lower than 20 cm

Health Care Financing Reforms in Italy: Projects of Jefferson\u27s Center for Research in Medical Education and Health Care

No abstract available

Numerical and experimental comparison among a new hybrid FT-music technique and existing algorithms for through-the-wall radar imaging

A fast low-cost through-the-wall radar imaging (TWRI) system, based on a vector network analyzer (VNA), a couple of switches and an array of Vivaldi antennas, has been designed, realized, and tested. To solve the TWRI inversion problem, an original theoretical modeling for a class of TWRI techniques whose basic functions are the cross-range Fourier transform (FT) of the scattered field and its covariance operator has been proposed. Using these functions, four conventional algorithms, namely the delay and sum (DAS), the FT, the multiple signal classification (MUSIC), the hybrid DAS-MUSIC and a new algorithm, the hybrid FT-MUSIC, have been derived. All these techniques have been implemented and their accuracy and field of view have been tested on canonical scatterers. Then, the algorithms have been applied to measured data collected in different scenarios constituted by a metallic bar or a human subject in the absence and in the presence of a wall between the antenna and the considered targets. Using the proposed TWRI system, it has been possible to detect a subject located up to 5-m away from the radar antenna array through a tuff wall. The proposed FT-MUSIC algorithm has evidenced performances similar to those of the DAS-MUSIC but with significantly lower execution times. Finally, FT-MUSIC performances in terms of field of view and immunity to disturbances are better compared to those of the MUSIC algorithm

Refugees, trauma and adversity-activated development

The nature of the refugee phenomenon is examined and the position of mental health professionals is located in relation to it. The various uses of the word 'trauma' are explored and its application to the refugee context is examined. It is proposed that refugees' response to adversity is not limited to being traumatized but includes resilience and Adversity-Activated Development (AAD). Particular emphasis is given to the distinction between resilience and AAD. The usefulness of the 'Trauma Grid' in the therapeutic process with refugees is also discussed. The Trauma Grid avoids global impressions and enables a more comprehensive and systematic way of identifying the individual refugee's functioning in the context of different levels, i.e. individual, family, community and society/culture. Finally, I discuss implications for therapeutic work with refugees

Bottom-up meta-modelling: An interactive approach

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-33666-9_2Proceedings of 15th International Conference, MODELS 2012, Innsbruck, Austria, September 30–October 5, 2012The intensive use of models in Model-Driven Engineering (MDE) raises the need to develop meta-models with different aims, like the construction of textual and visual modelling languages and the specification of source and target ends of model-to-model transformations. While domain experts have the knowledge about the concepts of the domain, they usually lack the skills to build meta-models. These should be tailored according to their future usage and specific implementation platform, which demands knowledge available only to engineers with great expertise in MDE platforms. These issues hinder a wider adoption of MDE both by domain experts and software engineers. In order to alleviate this situation we propose an interactive, iterative approach to meta-model construction enabling the specification of model fragments by domain experts, with the possibility of using informal drawing tools like Dia. These fragments can be annotated with hints about the intention or needs for certain elements. A meta-model is automatically induced, which can be refactored in an interactive way, and then compiled into an implementation meta-model using profiles and patterns for different platforms and purposes.This work was funded by the Spanish Ministry of Economy and Competitivity (project “Go Lite” TIN2011-24139) and the R&D programme of the Madrid Region (project “e-Madrid” S2009/TIC-1650

Two-year observations of the Jupiter polar regions by JIRAM on board Juno

We observed the evolution of Jupiter's polar cyclonic structures over two years between February 2017 and February 2019, using polar observations by the Jovian InfraRed Auroral Mapper, JIRAM, on the Juno mission. Images and spectra were collected by the instrument in the 5‐μm wavelength range. The images were used to monitor the development of the cyclonic and anticyclonic structures at latitudes higher than 80° both in the northern and the southern hemispheres. Spectroscopic measurements were then used to monitor the abundances of the minor atmospheric constituents water vapor, ammonia, phosphine and germane in the polar regions, where the atmospheric optical depth is less than 1. Finally, we performed a comparative analysis with oceanic cyclones on Earth in an attempt to explain the spectral characteristics of the cyclonic structures we observe in Jupiter's polar atmosphere

Energy/Environment Models: Relationship to Planning in Wisconsin, GDR, Rhone Alps

This report is a description and cross-regional comparison of the institutional structures and modeling methodologies of the three regions participating in the IIASA Research Program on Management of Regional Energy/Environment Systems. Descriptions are presented for the state of Wisconsin (USA), the German Democratic Republic, and the Rhone-Alpes Region (France), by specialists and policy makers from the respective regions. These descriptions demonstrate quite vividly the relationships between the institutional structure of a region and its use of models and planning tools

Using an adoption–biological family design to examine associations between maternal trauma, maternal depressive symptoms, and child internalizing and externalizing behaviors

Maternal trauma is a complex risk factor that has been linked to adverse child outcomes, yet the mechanisms underlying this association are not well understood. This study, which included adoptive and biological families, examined the heritable and environmental mechanisms by which maternal trauma and associated depressive symptoms are linked to child internalizing and externalizing behaviors. Path analyses were used to analyze data from 541 adoptive mother–adopted child (AM–AC) dyads and 126 biological mother–biological child (BM–BC) dyads; the two family types were linked through the same biological mother. Rearing mother’s trauma was associated with child internalizing and externalizing behaviors in AM–AC and BM–BC dyads, and this association was mediated by rearing mothers’ depressive symptoms, with the exception of biological child externalizing behavior, for which biological mother trauma had a direct influence only. Significant associations between maternal trauma and child behavior in dyads that share only environment (i.e., AM–AC dyads) suggest an environmental mechanism of influence for maternal trauma. Significant associations were also observed between maternal depressive symptoms and child internalizing and externalizing behavior in dyads that were only genetically related, with no shared environment (i.e., BM–AC dyads), suggesting a heritable pathway of influence via maternal depressive symptoms

Detection and investigation of extracellular vesicles in serum and urine supernatant of prostate cancer patients

Prostate Cancer (PCa) is one of the most frequently identified urological cancers. PCa patients are often over-diagnosed due to still not highly specific diagnostic methods. The need for more accurate diagnostic tools to prevent overestimated diagnosis and unnecessary treatment of patients with non-malignant conditions is clear, and new markers and methods are strongly desirable. Extracellular vesicles (EVs) hold great promises as liquid biopsy-based markers. Despite the biological and technical issues present in their detection and study, these particles can be found highly abundantly in the biofluid and encompass a wealth of macromolecules that have been reported to be related to many physiological and pathological processes, including cancer onset, metastasis spreading, and treatment resistance. The present study aims to perform a technical feasibility study to develop a new workflow for investigating EVs from several biological sources. Serum and urinary supernatant EVs of PCa, benign prostatic hyperplasia (BPH) patients, and healthy donors were isolated and investigated by a fast, easily performable, and cost-effective cytofluorimetric approach for a multiplex detection of 37 EV-antigens. We also observed significant alterations in serum and urinary supernatant EVs potentially related to BPH and PCa, suggesting a potential clinical application of this workflow