Miracle-dz/UniFAR-FTUs huggingface dataset:
Promoting Historical Thinking in Schools through Low Fidelity, Low-Cost, Easily Reproduceable, Tangible and Embodied Interactions

Many ubiquitous technologies, such as augmented and virtual reality, virtual field trips, tangible environments and interactive installations are continuously being examined for learning about history. All these approaches strive to offer an inter-active, explorative, authentic, and exact regeneration of the past and, they are demanding both in regards to their cost and to their development requirements; hence, they are far from accessible in school contexts. In this study, we will ex-amine, whether interactive low-fidelity low-cost approximations of the real objects, and conditions of the past, together with whole-body interactions may enable historical understanding in a playful manner. To evaluate this claim, sixty-six (66) students of 6th grade played with an interactive environment with the characteristics mentioned, in twenty (20) groups. Afterwards, students were asked to complete a questionnaire assessing their historical understanding and their experience. Additionally, all groups participated in brief group interviews. Students were very positive towards the environment and considered it as enjoyable, intriguing and effective. They claimed that it is preferable to both traditional ways of classroom learning and learning devices like tablets and mobiles. According to our results, the requirements for seamless authenticity may not apply for primary school students and this conclusion opens up a lot of opportunities for moving away from traditional means of learning about history.
Spatial correlation between lightning strikes and whistler observations

A whistler wave is a Very Low frequency (VLF) trace that obtains its characteristics from dispersive propagation in the magnetosphere. Field-aligned ducts of enhanced plasma density ensure the propagation from one hemisphere to the other. The origin of these signals is lightning strikes that emit radiation which spans the entire spectrum with the bulk being in the VLF band. The VLF portion can travel great distances within the Earth-ionosphere waveguide (EIWG) before penetrating through the ionosphere, and exciting a duct. The relative location, compared to the duct, of those strikes that cause whistlers is unknown. It is of interest to examine where the whistlers that have been observed at Tihany, Hungary, and Dunedin, Nerv Zealand, originate. This is one tool to gain further understanding of the properties, especially the plasma density structure, of the ionosphere and the magnetosphere. Therefore time series with observed whistlers from these stations has been correlated with lightning data obtained from the World Wide Lightning Location Network (WWLLN). The results show that whistlers observed at Tihany mainly originate from lightning in an area surrounding the magnetic conjugate point which is situated in the ocean just off East London, South Africa. This area, called the source region, has a radius slightly less than 1000 km. Whistlers also originate from lightning activity over the rest of Southern Africa and the northern parts of South America. A clear diurnal distinction is seen in that the correlation is maximized when the whistler station and the source region are covered in darkness. This is believed to relate to the diurnal variation of the ionospheric profile, which becomes more transparent to VLF waves at night. A similar diurnal correlation pattern for Dunedin was also obtained. The general correlation results for Dunedin were very sporadic. Whistler statistics for the two stations and lightning statistics for the Tihany's magnetic conjugate point are also presented. It reveals a general diurnal maximum in received whistlers in dark hours for Tihany with absolute maximum at 1 UTC and for Dunedin, the maximum occurs in the afternoon with absolute maximum at 15 UTC. It also reveals a seasonal maximum when the conjugate point is in the summer season. The lightning statistics for Tihany's magnetic conjugate point reveals a diurnal maximurn ranging from the afternoon until a couple of hour after midnight. Something worth noting is the delay between the peaks of lightning activity and whistler registration at Tihany. The lightning activity peaks around 18 UTC. The explanation is once again believed to relate to the behavior of the ionosphere in darkness.
Progress of 2-micron Detectors for Application to Lidar Remote Sensing

AlGaAsSb/InGaAsSb heterojunction phototransistors were developed at Astropower, Inc under Laser Risk Reduction Program (LRRP) for operation in the 2-micron region. These phototransistors were optimized for 2-micron detection and have high quantum efficiency (>60%), high gain (>10(exp 3)) and low noise-equivalent- power (<5x10(exp -14) W/Hz), while operating at low bias voltage. One of these phototransistors was tested in lidar mode using the 2-micron CO2 Differential Absorption Lidar (DIAL) system currently under development under the Instrument Incubator Program (IIP) at NASA Langley. Lidar measurements included detecting atmospheric structures consisting of thin clouds in the mid-altitude and near-field boundary layer. These test results are very promising for the application of phototransistors for the two-micron lidar remote sensing. In addition, HgCdTe avalanche photodiodes (APD) acquired from Raytheon were used in atmospheric testing at 2-microns. A discussion of these measurements is also presented in this paper.
Evaluation of performance for different filtering methods in CT brain images

This paper presents the comparison of filtering methods for a contrast enhancement of computed tomography (CT) brain images. Each method consists of three filter consecutively which is a combination of the low order linear filter such as Gaussian filter, disk filter, average filter and median filter with an adaptive filter method and unsharp filter. The process starts with filtering the CT brain image using low order linear filter, then proceeds with adaptive averaging filter and ends with unsharp filter. In this paper, there are two criteria, peak signal to noise ratio and mean square error, that were adopted for performance assessment. Our preliminary results showed that the combination of Gaussian filter with adaptive filter and unsharp filter gives the good result in removing the noise and edge detection. This method improved the CT brain image and the gyri and sulci can be easily identified.
Limitations imposed by cloud cover on multitemporal visible band satellite data sets from polar regions

The study of surface features and processes on glaciers, ice caps and ice sheets often requires multitemporal data in order to take account of the dynamic behaviour of snow and ice. Satellite remote sensing provides an important means of acquiring such data sets from polar regions, but the effectiveness of visible (VIS) and near-infrared (NIR) wavebands is severely limited by the frequent presence of cloud cover. As well as preventing direct imaging of the surface, cloud cover can be difficult to discriminate from snow and ice because of its similarly high reflectivity. This paper describes a detailed quantitative study of the limitations imposed by cloud cover. The number of potentially useful images which could have been acquired from a study area in Svalbard for the April-September period for 1980–89 is determined. Meteorological data from two stations analyzed over this study period show that fewer than 10% of the available satellite overpasses occurred during cloud-free periods. A cloud cover level of three octas or less, used to define high quality imagery, occurred 29% and 32% of the time at the two stations. Markedly seasonal variations are found which can be explained in terms of the regional climate such that during the months August and September the probability of obtaining a cloud-free Landsat image every year is effectively zero. Analysis of several years of Landsat Quick Look images for other regions of Svalbard confirms these findings. However, a similar series for the Scoresby Sund region of East Greenland shows a much higher percentage of low cloud scenes and no marked seasonality.
Image Processing Methods for Dynamical Intracellular Processes Analysis in QuantitativeFluorescence Microscopy

We propose in this manuscript a study of the instrumentation required for the quantification in frequency domain fluorescence lifetime imaging microscopy (FD FLIM). A FD FLIM measurement is defined as a series of images with sinusoidal intensity variations. The fluorescence lifetime is defined as the nanosecondscale delay between excitation and emission of fluorescence. We propose two main contributions in the area: a modeling of the image process and noise introduced by the acquisition system (ICCD sensor); a robust statistical method for lifetime estimation on moving structures and intracellular vesicles. The second part presents a contribution to the tracking of multiple particles presenting heterogeneous transports in dense conditions. We focus here on the switching between confined diffusion in the cytosol and motormediated active transport in random directions. We show that current multiple model filtering and gating strategies fail at estimating unpredictable transitions between Brownian and directed displacements. We propose a new algorithm, based on the u-track algorithm [Jaqaman et al., 2008], based on a set of Kalman filters adapted to several motion types, for each tracked object. The algorithm has been evaluated on simulated and real data (vimentin, virus) data. We show that our method outperforms competing methods in the targeted scenario, but also on more homogeneous types of dynamics challenged by density.
A Hybrid Feature Selection Method for Software Defect Prediction

Software Defect Prediction (SDP) is one of the important ways of software quality assurance, which uses the metric data to predict whether software module is defect. The quality of data influences the perfection of the prediction model. The high latitude containing some unnecessary features is one of the quality problem that dataset. To solve this problem, we proposed a hybrid feature selection (HFS) method combined different feature sorting technology. Firstly, we calculate the values of each feature include chi-squared (cs), Information gain (IG) and Pearson Correlation coefficient, respectively. Secondly, we sort the features based on the ranking of the three values to select features. Finally, we use the random forest to build the model. In order to validity the approach, we did experiments on 5 datasets in NASA. The result shows that our approach can select a smaller subset of features to improve the preformation in F-measure.
Credit scoring for a microcredit data set using the synthetic minority oversampling technique and ensemble classifiers

Although microfinance organizations play an important role in developing economies, decision support models for microfinance credit scoring have not been sufficiently covered in the literature, particularly for microcredit enterprises. The aim of this paper is to create a three‐class model that can improve credit risk assessment in the microfinance context. The real‐world microcredit data set used in this study includes data from retail, micro, and small enterprises. To the best of the authors' knowledge, existing research on microfinance credit scoring has been limited to regression and genetic algorithms, thereby excluding novel machine learning algorithms. The aim of this research is to close this gap. The proposed models predict default events by analysing different ensemble classification methods that empower the effects of the synthetic minority oversampling technique (SMOTE) used in the preprocessing of the imbalanced microcredit data set. Initial results have shown improvement in the prediction results for certain classes when the oversampling technique with homogeneous and heterogeneous ensemble classifier methods was applied. A prediction improvement for all classes was achieved via application of SMOTE and the Consolidated Trees Construction algorithm together with Rotation Forest. To obtain a complete view of all aspects, an additional set of metrics is used in the evaluation of performance.
Challenges in Designing Software Architectures for Web-Based Biomedical Signal Analysis

In contemporary explorations of biomedical data, there is a strong inclination towards software platforms that offer ubiquitous access and ease of use. Traditional biomedical signal analysis, such as detection of disorders in electrocardiogram recordings is considered as difficult task. There are many approaches to tackle such tasks, but the common assumption is that such an analysis should be performed both offline (after data collection) and particularly off the web, using MATLAB (or Octave) programs or other specialized software. There has been little effort involved in complete web solutions for biomedical signal analysis, which, compared to traditional analysis, have many advantages: access from afar, browser-only software requirements, reliance on fast server solutions for calculations, etc. This chapter considers web systems for biomedical signal analysis and describes their software architecture design aspects. It examines its applications: home care, medical education, signal repositories with visualization capabilities, signal analysis environments with data mining. The focus is on challenges involving these systems, like: data privacy, frontend workflow, frontend and backend interactions, database design, integration of data analysis and reporting libraries, programming language issues, etc. We emphasize that little work was published regarding architectural considerations in this setting and highlight the importance of overcoming these issues.
HILS-Based Development of a Relative Position and Orientation Measurement System for Platooning Vehicles with Coupling Devices

: We propose a new platooning vehicle that uses a coupling device not for the traction of following vehicles but for the measurement of relative position and orientation between leading and following vehicles. The following vehicles are driven by their own motors. This paper reports development of the relative position and orientation measurement system. In the coupling device, multiple distance sensors are equipped around the pin. These sensors acquire the distance between the pin and a hexagonal ring. The array of distance values is converted to the relative position and orientation of vehicles using two methods: (1) Geometric method and (2) Data look-up method. After a prototype of the proposed measurement system is implemented, it is evaluated using hardware in the loop simulation (HILS) that simulates multiple vehicles’ platooning drive. Therefore, the system capabilities have been evaluated not only by the measurement precision but also by the platooning performance. The experimentally obtained results demonstrate that the proposed measurement system is su ﬃ ciently valid and feasible. The data look-up method exhibits especially superior performance because it uses no geometric conditions explicitly.
Investigating first-generation students’ perceptions of library personnel

PurposeThe purpose of this paper is to investigate the perceived role of library personnel in supporting first-generation students at Penn State University Libraries, and also how students’ perceptions of library personnel change over time, and the various experiences that influenced their changes in perception.Design/methodology/approachThis study employed focus groups to solicit input from first-generation students. A four-step team-based approach to qualitative coding process was developed including the development of a codebook informed by common themes and concepts drawn from the literature.FindingsFindings indicate that operating from a deficit of library cultural capital often results in low awareness of available services and changes in perception are more influenced by personal exploration than limited interactions with personnel. Further, while currently employed interventions are well targeted, opportunities exist for enhancing efforts.Research limitations/implicationsAs this is a case study, the findings are not generalizable. Per conducting only four focus groups, the experiences of participants may not represent the typical scope of personnel-related interactions.Originality/valueThis study adds to the limited body of evidence that first-generation students’ struggle from a deficit of library-related cultural capital.
Design, Modeling and Simulation of a Reconfigurable Wheelchair with Stand-sit-sleep Facilities

Standing feature of the wheelchair allows the disabled to be able to reach different heights and thus gives enhanced navigations in different conditions. Wheelchair with back seat adjustment helps in health preservation as well as daily living activities including trunk positioning, functional enhancement stability and gait balance. Thus, paper presents the design, modeling and simulation of a reconfigurable wheelchair with stand-sit-sleep facilities. Key areas focused on maximizing safety, optimizing the size with minimizing cost and weight of the newly designed wheelchair. The contribution of paper are (i) Kinematic concept of the reconfigurable wheelchair (ii) Synthesis of the proposed wheelchair mechanism (iii) CAD modeling using the Top down modeling approach (iv) Multi-body dynamics Simulation and stress simulation of model. Wheelchair design has been analyzed and verified by using MSC ADAMS and ANSYS simulation tools. The developed model will help in improving the functional capabilities of wheelchair users allowing enhanced independence and quality of life (QoL).
Measurement error and data collection methods: effects on estimates from event history data

Event history data from panel surveys typically display a concentration of transitions at the seam between waves of data collection. This â€˜seam effectâ€™ is likely to bias estimated durations of benefit receipt, attenuate the estimated effects of explanatory factors on conditional exit probabilities and bias estimated duration dependence. This paper uses benefit histories from survey reports and matched administrative records to assess the extent of bias in key estimates. The paper also evaluates the effectiveness at reducing bias of dependent interviewing techniques, where information collected in a previous interview is used to remind the respondent of sources reported previously, or to verify that sources no longer reported have truly ended.
First experiments in viewshed uncertainty : simulating fuzzy viewsheds

Calculation of the viewshed from a digital elevation model (OEM) is a common capability of a GIS packages. Two mistaken assumptions are made, however: first, that the OEM is accurate, and second that the viewshed is a Boolean phenomenon. The inaccuracy of the OEM data is acknowledged in reporting of the root-mean-squared error. The mistake of the Boolean viewshed is recognizable in the real-world experience of most individuals. In this paper multiple realizations of an error simulation algorithm are used to generate multiple Boolean viewsheds which are then cumulated to yield an image of the viewshed with all the properties of a fuzzy set, Le. , a fuzzy viewshed. Alternative parameterizations of the basic algorithm are presented, and the differences are explored.
Establishing a relative positioning system to achieve mobile localization

There are an increasing number of situations in which the location of some digital device is known, but the methods to communicate with it are unknown. These situations can frustrate users and lead to the non-adoption to new, beneficial technologies. To combat this, I propose a relative positioning system between digital devices in order for each device to learn the relative locations of nearby devices. I explore three separate methods of establishing this positioning system. The first uses ultrasonic range-finding to localize nearby devices. The second uses WiFi range finding between mobile devices and stationary WiFi access points. The final method uses machine vision to jointly localize two devices observing the same scene from different angle. Ultimately none of these methods were fully implemented, but an analysis is given for the advantages and disadvantages of using these methods. Thesis Supervisor: Chris Schmandt Title: Principal Research Scientist at MIT Media Lab
Hybrid Five-level Inverter Based On Half-bridge/anpc Topologies

This paper presents the analysis of a novel hybrid five-level bidirectional converter topology based on Half-Bridge and ANPC (Active Neutral Point Clamped) topologies, designed for high power, high voltage applications. The available switching states for a five-level application are presented, which are used to propose several modulation techniques, aiming to increase the efficiency by reducing the number of switching transitions per period, and to reduce the THD and WTHD. Thus, it was selected a modulation technique that allowed half of the switches to operate at low switching frequency (60 Hz), while the other half commutate in high switching frequency, at 1020 Hz, which reduces the losses and the output voltage harmonic Artigo submetido em 26/03/2012. Primeira revisão em 09/05/2012, segunda revisão em 26/06/2012. Aceito para publicação em 30/06/2012 por recomendação do editor Henrique A.C. Braga. content. In order to validate the proposed topology, experimental results from a prototype connected to a 2.3 kW load are presented, with 220 V rms output voltage and 0.92 power factor. The prototype presents a THD around 30.45% and a WTHD of 1.72%.
Fast object detection based on binary deep convolution neural networks

In this study, a fast object detection algorithm based on binary deep convolution neural networks (CNNs) is proposed. Convolution kernels of different sizes are used to predict classes and bounding boxes of multi-scale objects directly in the last feature map of a deep CNN. In this way, rapid object detection with acceptable precision loss is achieved. In addition, binary quantisation for weight values and input data of each layer is used to squeeze the networks for faster object detection. Compared to full-precision convolution, the proposed binary deep CNNs for object detection results in 62 times faster convolutional operations and 32 times memory saving in theory, what's more, the proposed method is easy to be implemented in embedded computing systems because of the binary operation for convolution and low memory requirement. Experimental results on Pascal VOC2007 validate the effectiveness of the authors’ proposed method.
Image Quantization in Psoriasis Using K-Mean Clustering

Along with technology that is very fast image processing with high quality can be presented and displayed in many ways. The image has detailed information that can cause problems during processing. Image quantization is done as a preprocessing stage to reduce the number of colors in the image so that the resulting image approaches the original image. The purpose of this study is to group clusters of characteristics with the same image value.
The 2D Type-3 Non-Uniform FFT in CUDA

─ We present the parallel implementation on Graphics Processing Units (GPUs) of a type-3 NonUniform FFT (NUFFT) approach, namely, of a NUFFT for which data and results are located at irregular points. The performance of the algorithm is assessed against that of a parallel implementation of the same algorithm on multi-core CPUs using OpenMP directives. Index Terms ─ CUDA, Non-Uniform FFT, OpenMP.