nils-herrmann/clean_scirepeval huggingface dataset:
Blended learning, e learning and mobile learning in mathematics education

In this literature survey we focus on identifying recent advances in research on digital technology in the field of mathematics education. To conduct the survey we have used internet search engines with keywords related to mathematics education and digital technology and have reviewed some of the main international journals, including the ones in Portuguese and Spanish. We identify five sub areas of research, important trends of development, and illustrate them using case studies: mobile technologies, massive open online courses (MOOCs) digital libraries and designing learning objects, collaborative learning using digital technology, and teacher training using blended learning. These examples of case studies may help the reader to understand how recent developments in this area of research have evolved in the last few years. We conclude the report discussing some of the implications that these digital technologies may have for mathematics education research and practice as well as making some recommendations for future research in this area.
A novel methodology for energy performance benchmarking of buildings by means of Linear Mixed Effect Model: The case of space and DHW heating of out patient Healthcare Centres

The current EU energy efficiency directive 2012/27/EU defines the existing building stocks as one of the most promising potential sector for achieving energy saving. Robust methodologies aimed to quantify the potential reduction of energy consumption for large building stocks need to be developed. To this purpose, a benchmarking analysis is necessary in order to support public planners in determining how well a building is performing, in setting credible targets for improving performance or in detecting abnormal energy consumption. In the present work, a novel methodology is proposed to perform a benchmarking analysis particularly suitable for heterogeneous samples of buildings. The methodology is based on the estimation of a statistical model for energy consumption the Linear Mixed Effects Model so as to account for both the fixed effects shared by all individuals within a dataset and the random effects related to particular groups/classes of individuals in the population. The groups of individuals within the population have been classified by resorting to a supervised learning technique. Under this backdrop, a Monte Carlo simulation is worked out to compute the frequency distribution of annual energy consumption and identify a reference value for each group/class of buildings. The benchmarking analysis was tested for a case study of 100 out patient Healthcare Centres in Northern Italy, finally resulting in 12 different frequency distributions for space and Domestic Hot Water heating energy consumption, one for each class of homogeneous class of buildings. From the median value of each frequency distribution, reference values were extracted to be used in a benchmarking analysis. Beyond being flexible, open and upgradeable over time, a benchmarking analysis relying on both a sound statistical basis and on stochastic simulation is indeed able to overcome the limitations of the more common deterministic or one dimensional benchmarking approach.
The Role of WhatsApp in Teaching Vocabulary to Iranian EFL Learners at Junior High School

The availability and the use of mobile messaging applications are increasingly widespread among the new generation of students in Iran. The present study aimed to investigate the role of WhatsApp in the vocabulary learning improvement of Iranian junior high school EFL students. Using a mixed method design, a group of 60 students including 30 male and 30 female students studying at two male and female junior high schools in Isfahan, Iran participated in the study. A pre test and post test were used. Four English classes were instructed and the experimental group received vocabulary instructions electronically four days a week for four weeks using the WhatsApp while the control group was taught vocabularies of their textbook inside the classroom by traditional method used in all Iranian schools for teaching English to students. The results revealed that using WhatsApp had significant role in vocabulary learning of the students. The results also showed that there was not a substantial difference between male and female students regarding their vocabulary knowledge after using WhatsApp. The findings of this study can be beneficial to Iranian EFL students, teachers, language schools, policy makers, and syllabus designers.
QUIZLET IN THE EFL CLASSROOM: ENHANCING ACADEMIC VOCABULARY ACQUISITION OF JAPANESE UNIVERSITY STUDENTS

This study examined the efficacy of using Quizlet, a popular online study tool, to develop L2 English vocabulary. A total of 9 Japanese university EFL students participated in the study. The learners studied Coxhead's (2001) academic vocabulary list (AWL) via Quizlet over the course of 10 weeks. Results of the preand post tests revealed that the learners were able to make statistically significant gains. Moreover, a questionnaire administered by the researcher indicated that the students had positive perceptions of Quizlet to study L2 vocabulary. Specifically, all three constructs studied perceived usefulness, perceived ease of use, and behavioral intention to use Quizlet had mean scores greater than 4 on a 5 point Likert scale, indicating a high level of agreement. Based on these findings, the author supports the use of Quizlet in the EFL classroom.
Clothing Color and Tipping

An online, hypothetical, tipping scenario experiment found that subjects tipped the servers less (not more) when those servers wore a red shirt than when they wore a white or black one and that female subjects perceived a waiter (but not a waitress) as less attractive when wearing a red shirt than when wearing a white or black shirt. These findings are opposite those in the existing literature and suggest that the earlier findings are less generalizable than previously believed and that the process underlying previous clothing color effects on tipping may not be precisely what the researchers thought it was. Possible explanations of the discrepant findings are discussed along with directions for future research and practical implications.
Towards Context aware Border Security Control
Venue: BMSD 2016

Context aware systems allow for adapting the system behaviour to the context situation at hand and we have seen good applicability of context aware systems in domains, such as Mobile Health. Even though this could also be useful for the Border Security domain, applying context awareness in this domain is not trivial since the possible context situations are numerous and difficult to predict. Still, context aware Border Security systems are needed as a possible way to overcome the inevitable shortage of resources along the borders. Smooth and fast border crossing for travellers, in combination with adequate level of security, can be achieved if: (i) at any moment, the context situation is properly captured; (ii) there is potential for behaviour and resources (from the Authorities' side) corresponding to each possible context situation. The context situation capturing is about sensors, data streaming, and so on. Establishing the right behaviour resources is about enterprise modeling and business rules, and it is also about automation that assumes in turn integration of software applications in the overall Border Security system. In this position paper, we address all that, inspired by the SDBC Approach, Enterprise Ontology, Semiotic Norms, and the principles of Context aware Systems. Reporting research in progress, we only present our way of modeling and we identify several domain specific concerns that are related to the application of the built models. We also provide a list of recommendations that are expected to be useful with regard to possible Border Security system developments.
A Model Stitching Architecture for Continuous Full Flight Envelope Simulation of Fixed Wing Aircraft and Rotorcraft from Discrete Point Linear Models

A comprehensive model stitching simulation architecture has been developed, which allows continuous, full flight envelope simulation based on a collection of discrete point linear models and trim data. The model stitching simulation architecture is applicable to any aircraft configuration readily modeled by state equations and for which test data can be obtained. Individual linear models and trim data for specific flight conditions are incorporated with nonlinear elements to produce a continuous, quasi nonlinear simulation model. Extrapolation methods within the model stitching architecture permit accurate simulation of off nominal aircraft loading configurations, including variations in weight, inertia, and center of gravity, and variations in altitude, which together minimize the required number of point models for full envelope simulation. The model stitching simulation architecture is applied herein to a model of a CJ1 business jet and to a model of a UH 60 utility helicopter. For both the fixed wing and the rotorcraft application, configuring the stitched simulation models with 8 discrete point linear models (4 point models each at two altitudes) plus additional trim data was found to allow accurate simulation over the full airspeed and altitude envelope. Flight test implications for the development of stitched models from flight identified point models are presented for fixed wing and rotorcraft applications.
Computing the Globally Optimal Frictionless Fixture in a Discrete Point Set
Venue: IEEE Transactions on Robotics

This paper presents an algorithm to compute the globally optimal fixture with frictionless contacts in a discrete point set on an object. The capability of a fixture to immobilize the object is evaluated by the minimum of the largest conflict of the object with the contacts over all motion directions, which can be reduced to the radius of the largest origin centered ball contained in the convex hull of primitive contacts wrenches. All candidate fixtures (combinations of the discrete points of a certain number) are expressed in a tree structure, in which each node contains a discrete point representing a contact location and each path from the roots to a leaf represents a fixture. A preorder walk of the tree is performed to search for the optimal fixture. Necessary conditions are derived to predict whether the subtree of a node contains a better fixture. If any necessary condition is not met, then all the fixtures contained in the subtree can be simply rejected. By this means only a small portion of the tree will be traversed and the globally optimal fixture can be found more quickly. This algorithm has been tested on various three dimensional objects and has been found to be over ten times faster than the brute force search.
Vision and locomotion shape the interactions between neuron types in mouse visual cortex

Locomotion profoundly changes sensory responses in mouse primary visual cortex. These changes are thought to arise from a disinhibitory circuit, whereby interneurons expressing vasoactive intestinal peptide (Vip) inhibit those expressing somatostatin (Sst) thus disinhibiting pyramidal cells (Pyr) We studied the effect of locomotion on these cell types and on interneurons expressing parvalbumin (Pvalb) in layer 2/3 of mouse V1, and found inconsistencies with the disinhibitory model. Locomotion increased Sst cell responses to large stimuli and to full field gray screen, without decreasing them in Vip cells. Moreover, it increased Vip cell responses to small stimuli, without decreasing them in Sst cells. Signal and noise correlations between cell types provided further evidence against the disinhibitory model. Our data resolve apparent contradictions in the literature and suggest an alternative to the disinhibitory model, where Vip and Sst cells inhibit each other in a circuit whose effect depends on stimulus and behavioral state.
GEOMETRIC MODELS FOR LATERITIC SOIL STABILIZED WITH CEMENT AND BAGASSE ASH

Agricultural and environmental demands for natural aggregates coupled with frequent increases in the price of cement and other binders have consequently escalated the cost of construction, rehabilitation and maintenance of road works. Soil stabilization emerges as an attractive option for providing low cost roads. Bagasse ash is an agricultural material obtained after squeezing out the sweet juice in sugarcane and incinerating the fibrous residue to ash. This residue that would have constituted an environmental problem during disposal and handling could be used as a supplement or partial replacement for cement in the cement bound soil when converted to ash. Thus this study attempted to investigate into the effects of bagasse ash on compaction and strength characteristics of cement stabilized lateritic soil and also to develop geometric models. The compaction, California bearing ratio, unconfined compressive strength and durability tests were carried out on the cement stabilized soil. Constant cement contents of 2% 4% 6% and 8% with variations of bagasse ash from 0% to 20% at 2% intervals and all percentages used were by the weight of dry soil. The multiple regression and the least square approach was used to develop geometric equations which was made less rigorous with Minitab statistical software. The three geometric equations developed covered the relationships of cost of bagasse ash content, optimum moisture content, cement content, California bearing ratio and unconfined compressive strength at 7 days. It was observed that optimum moisture content increased progressively while maximum dry density reduced with increase in bagasse ash content. Also the increase in cement content increased both the optimum moisture content and maximum dry density. In addition, all the strength properties were increased with increase in bagasse ash content and chemistry responsible was also presented. Thus bagasse ash was confirmed to be a good admixture in soil stabilization for road work. The models were calibrated and verified; and were found to be dependable. http:/dx.doi.org/10.4314/njt.v35i4.11
Colloidal Surfaces with Boundaries, Apex Boojums, and Nested Elastic Self Assembly of Nematic Colloids.
Venue: Physical review letters

Self assembly of colloidal particles is poised to become a powerful composite material fabrication technique, but remains challenged by a limited control over the ensuing structures. We develop a new breed of nematic colloids that are physical analogs of a mathematical surface with boundary, interacting with the molecular alignment field without inducing defects when flat. However, made from a thin nanofoil, they can be shaped to prompt formation of self compensating defects that drive preprogramed elastic interactions mediated by the nematic host. To show this, we wrap the nanofoil on all triangular side faces of a pyramid, except its square base. The ensuing pyramidal cones induce point defects with fractional hedgehog charges of opposite signs, spontaneously align with respect to the far field director to form elastic dipoles and nested assemblies with tunable spacing. Nanofoils shaped into octahedrons interact as elastic quadrupoles. Our findings may drive realization of low symmetry colloidal phases.
Spatial pyramid match kernels for brain image classification
Venue: 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI)

The most widely used classification techniques for whole brain image classification rely on kernel machines such as support vector machines and Gaussian processes, due to their computational efficiency, accurate prediction and suitability to tackle the combination of small sample sizes and high dimensionality that make neuroimaging data a challenging problem. Such methods generally make use of linear kernels, which assume an exact correspondence between the voxels in two brain images. This paper introduces spatial pyramid matching kernels from the computer vision literature to this problem, which allow us to relax this assumption to compensate for registration errors. The kernel formulation is compared against linear kernels for the model problems of gender prediction for classification and age prediction for regression, using a nested cross validation procedure to robustly select the optimal kernel parameters and assess the results. The spatial pyramid matching kernel outperforms the linear one in both tasks.
The Need of Nested Grids for Aerial and Satellite Images and Digital Elevation Models

Usual workflows for production, archiving, dissemination and use of Earth observation images (both aerial and from remote sensing satellites) pose big interoperability problems, as for example: non alignment of pixels at the different levels of the pyramids that makes it impossible to overlay, compare and mosaic different orthoimages, without resampling them and the need to apply multiple resamplings and compression decompression cycles. These problems cause great inefficiencies in production, dissemination through web services and processing in "Big Data" environments. Most of them can be avoided, or at least greatly reduced, with the use of a common "nested grid" for mutiresolution production, archiving, dissemination and exploitation of orthoimagery, digital elevation models and other raster data. "Nested grids" are space allocation schemas that organize image footprints, pixel sizes and pixel positions at all pyramid levels, in order to achieve coherent and consistent multiresolution coverage of a whole working area. A "nested grid" must be complemented by an appropriate "tiling schema" ideally based on the "quad tree" concept. In the last years a "de facto standard" grid and Tiling Schema has emerged and has been adopted by virtually all major geospatial data providers. It has also been adopted by OGC in its "WMTS Simple Profile" standard. In this paper we explain how the adequate use of this tiling schema as common nested grid for orthoimagery, DEMs and other types of raster data constitutes the most practical solution to most of the interoperability problems of these types of data.
Survey on Outlier Detection in Data Stream

mining provides a way for finding hidden and useful knowledge from the large amount of data .usually we find any information by finding normal trends or distribution of data .But sometimes rare event or data object may provide information which is very interesting to us .Outlier detection is one of the task of data mining .It finds abnormal data point or sequence hidden in the dataset .Data stream is unbounded sequence of data with explicit or implicit temporal context .Data stream is uncertain and dynamic in nature. Traditional outlier detection techniques for static data which require whole dataset for modelling is not suitable for data stream because whole data stream cannot be stored. Network intrusion detection ,web click stream analysis ,fraud detection ,fault detection in machines ,sensor data analysis are some of the applications of data stream outlier detection .In this paper, we have described several issues in data stream outlier detection and usual approaches or techniques for finding outlier in data stream
Emotion Regulation and the Transdiagnostic Role of Repetitive Negative Thinking in Adolescents with Social Anxiety and Depression
Venue: Cognitive Therapy and Research

Social anxiety and depression are common mental health problems among adolescents and are frequently comorbid. Primary aims of this study were to (1) elucidate the nature of individual differences in specific emotion regulation deficits among adolescents with symptoms of social anxiety and depression, and (2) determine whether repetitive negative thinking (RNT) functions as a transdiagnostic factor. A diverse sample of adolescents (N 1065) completed measures assessing emotion regulation and symptoms of social anxiety and depression. Results indicated that adolescents with high levels of social anxiety and depression symptoms reported decreased emotional awareness, dysregulated emotion expression, and reduced use of emotion management strategies. The hypothesized structural model in which RNT functions as a transdiagnostic factor exhibited a better fit than an alternative model in which worry and rumination function as separate predictors of symptomatology. Findings implicate emotion regulation deficits and RNT in the developmental psychopathology of youth anxiety and mood disorders.
Digital Preprocessed Analog Multiplexed DAC for Ultrawideband Multilevel Transmitter
Venue: Journal of Lightwave Technology

High speed digital to analog converters (DACs) are essential in advanced optical transmission systems, utilizing multilevel modulation formats and pulse shaping technologies. Analog bandwidth of DACs is one of the major limiting factors for the system capacity. In this paper, we present an idea to extend the analog bandwidth of DACs by utilizing a digital preprocessor, two sub DACs, and an analog multiplexer (AMUX) The AMUX is a high speed linear selector, and a frequency domain interpretation of the AMUX's function has led us to devise the digital preprocessing for a seamless extension of the analog bandwidth. This configuration, which we call a digital preprocessed analog multiplexed DAC, provides nearly doubled analog bandwidth compared to that of each subDAC with a symmetric configuration. The idea was verified by a transmission experiment with 160 Gb/s 80 Gbaud Nyquist four level pulse amplitude modulation. In the experiment, we used subDACs with an analog bandwidth of ~20 GHz in combination with an AMUX fabricated with InP heterojunction bipolar transistor technology.
A Wideband RF Mixing DAC Achieving IMD 82 dBc Up to 1.9 GHz
Venue: IEEE Journal of Solid State Circuits

This paper presents a highly linear wideband Mixing DAC architecture. A current steering DAC core and a mixer are co integrated at a unit current cell level. A 1 bit DAC output stage is cascoded by a 1 bit mixer to form the Mixing DAC current cell. An array of such current cells and a system front end construct the Mixing DAC. The system front end includes digital signal processing and data synchronization, global LO driver and sort and combine calibration hardware. To reach high linearity, various techniques are used: digital dither, self measurement and calibration of amplitude and timing errors, local advanced cascoding scheme, bleeding currents, segmentation and accurate scaling of the LSB binary current cells. The proposed approach is validated by a 65 nm CMOS test chip of a dual 16 bit 2 GS/s 4 GHz Mixing DAC with IMD 82 dBc up to 1.9 GHz and output noise lower than 165 dBm/Hz.