Miracle-dz/UniFAR-FTUs huggingface dataset:
VR and Laser-Based Interaction in Virtual Environments Using a Dual-Purpose Interaction Metaphor

In this paper we present a dual-purpose interaction metaphor for desktop-based and virtual reality (VR) interaction in VR system environments. Many VR interaction techniques enable users to perform 6 degrees of freedom (DOF) manipulation tasks. However, designers of most GUIs have only standard desktop devices in mind for using them. Therefore porting desktop applications to VR systems often fails since no techniques exist for making the full functionality of the GUI accessible to the user. VR interaction techniques lack support for combining both VR and desktop-based interaction, e.g., the control of the operating system and 2D menu handling. In this paper we present a dualpurpose interaction metaphor based on laser pen interaction, which is capable of performing both desktop-based and VR interaction tasks.
Evolution and biogeography of Centaurea section Acrocentron inferred from nuclear and plastid DNA sequence analyses.

BACKGROUND AND AIMS Section Acrocentron of the genus Centaurea is one of the largest sections of Centaurea with approx. 100 species. The geographic distribution, centred in the Mediterranean, makes it an excellent example for studies of the biogeographic history of this biodiversity-rich region. METHODS Plastid (trnH-psbA) and nuclear (ITS and ETS) DNA sequence analysis was used for phylogenetic reconstruction. Ancestral biogeographic patterns were inferred by dispersal-vicariance analysis (DIVA). KEY RESULTS The resulting phylogeny has implications for the sectional classification of Acrocentron and confirms merging sect. Chamaecyanus into Acrocentron as a subsection. Previous suggestions of an eastern Mediterranean origin of the group are confirmed. The main centres of diversification established in previous studies are now strongly supported. Expansion of the group in two different radiations that followed patently diverse paths is inferred. CONCLUSIONS Radiation followed two waves, widely separated in time scale. The oldest one, from Turkey to Greece and the northern Balkans and then to North Africa and Iberia, should be dated at the end of the Miocene in the Messinian period. It reached the Iberian Peninsula from the south, following a route that is landmarked by several relictic taxa in Sicily and North Africa. A later radiation during the Holocene interglacial periods followed, involving species from the north of the Balkan Peninsula, along a Eurasian pathway running from Central Iberia to the steppes of Kazakhstan. A generalized pattern of reticulation is also evident from the results, indicating past contacts between presently separated species. Molecular data also confirmed the extent of hybridization within Acrocentron and were successful in reconstructing the paleogeography of the section.
Image Quality Assessment Using Oriented Multichannel Pyramidal Decomposition and Artificial Neural Network Data Postprocessing General Description of the Proposed Model Decomposition Decomposition Rmse / Mae Image Quality Score

The novel method for the quality assessment of compressed images is described in this paper. Quality scores (highly correlated with experimental) are estimated using oriented multi-channel pyramidal decomposition and artificial neural network as a postprocessor. 1. INTRODUCTION Image quality assessment plays important role in the systems for data storage and transmission where the amount of data should be minimized. In order to achieve a high performance of the image compression system we need to investigate the effect of coding arti-facts on the image quality. Good knowledge of the dependencies between impairments and perceived image quality helps to optimize the whole imaging system including the compression algorithms. There are two methods for the image quality assessment: subjective [1] and objective [2]. Subjective methods (evaluation by the group of human observers) offer the most precise results, but these methods are time consuming, costly and they cannot be easily automated. Among the objective quality evaluation methods belong methods using mathematical characteristics and methods utilizing model of the Human Visual System (HVS). There is no universally usable objective characteristic that allows describing the whole variety of distortions incurred by today imaging systems. In this paper, we propose a novel method for image quality evaluation, which uses multichannel pyramidal decomposition [2] (decomposing an image into many spatial frequency bands and orientations) and Root Mean Square Error (RMSE) computation in these bands as an impairment feature extractor. An Artificial Neural Network (ANN) [3] is then used as a combiner and classifier to obtain the resulting quality rating scores. The proposed quality assessment model has been trained and tested using a set of greyscale images distorted by image compression algorithms. Good quality score prediction has been demonstrated in terms of Pearson correlation between the subjective Mean Opinion Scores (MOS) and model output. The model structure is depicted in Fig. 1. It consists of the two main parts: the impairment feature extraction block and ANN as a combiner. The original and distorted images are decomposed into several bands to extract RMSE of error image at different orientations and resolutions. Additionally RMSE and Mean Absolute Error (MAE) for the whole error image are computed. The output impairment vector of the feature extraction block contains 16 RMSE values for different orientations and resolutions, total RMSE and total MAE. The impairment features form the input to the second block – ANN. The impairment feature vector is processed by the feed-forward backpropagation …
Training-related adaptations in motor unit discharge rate in young and older adults.

BACKGROUND This study evaluated changes in motor unit (MU) firing rates in young and older adults during exercise training. METHODS Vastus lateralis MU discharge rates were measured in 8 young and 7 older adults. Each participant performed isometric knee extension contractions at 10%, 50%, and 100% of maximal voluntary contraction or effort (MVC) on two separate occasions. Participants then completed a 6-week resistance exercise training protocol. RESULTS Significant increases in maximal force were observed as early as 1 week after the first baseline testing session, and these were accompanied by increases in the MU discharge rate. Exercise training increased maximal voluntary force by 29% and 36% in the young and older adults, respectively. Motor unit discharge rates at 100% of maximal effort were significantly greater in the young (24.7 pps) than in the older adults (17.8 pps). Furthermore, the young adults also exhibited significantly greater discharge rates at 50% MVC, but there were no differences at the 10% force level. Maximal MU discharge rates increased during the 1-week period separating the two initial testing sessions. After the 6-week training period, maximal MU discharge rates were 15% higher for the young adults and 49% higher for the older adults. No changes in discharge rates were observed for either group at 10% or 50% MVC after exercise training. CONCLUSIONS The early increase in maximal MU discharge rate with repeated maximal force assessment may comprise an important neural mechanism mediating early, rapid gains in muscular force capability.
Development of Land Surface Temperature Retrieval Algorithm from the MTSAT-2 Data

Land surface temperature (LST) is a one of the key variables of land surface which can be estimated from geostationary meteorological satellite. In this study, we have developed the three sets of LST retrieval algorithm from MTSAT-2 data through the radiative transfer simulations under various atmospheric profiles (TIGR data), satellite zenith angle, spectral emissivity, and surface lapse rate conditions using MODTRAN 4. The three LST algorithms are daytime, nighttime and total LST algorithms. The weighting method based on the solar zenith angle is developed for the consistent retrieval of LST at the early morning and evening time. The spectral emissivity of two thermal infrared channels is estimated by using vegetation coverage method with land cover map and 15-day normalized vegetation index data. In general, the three LST algorithms well estimated the LST without regard to the satellite zenith angle, water vapour amount, and surface lapse rate. However, the daytime LST algorithm shows a large bias especially for the warm LST (> 300 K) at day time conditions. The night LST algorithm shows a relatively large error for the LST (260 ~ 280K) at the night time conditions. The sensitivity analysis showed that the performance of weighting method is clearly improved regardless of the impacting conditions although the improvements of the weighted LST compared to the total LST are quite different according to the atmospheric and surface lapse rate conditions. The validation results of daytime (nighttime) LST with MODIS LST showed that the correlation coefficients, bias and RMSE are about 0.62~0.93 (0.44~0.83), -1.47~1.53 (-1.80~0.17), and 2.25~4.77 (2.15~4.27), respectively. However, the performance of daytime/nighttime LST algorithms is slightly degraded compared to that of the total LST algorithm.
Comprehensive analysis of software countermeasures against fault attacks

Fault tolerant software against fault attacks constitutes an important class of countermeasures for embedded systems. In this work, we implemented and systematically analyzed a comprehensive set of 19 different strategies for software countermeasures with respect to protection effectiveness as well as time and memory efficiency. We evaluated the performance and security of all implementations by fault injections into a microcontroller simulator based on an ARM Cortex-M3. Our results show that some rather simple countermeasures outperform other more sophisticated methods due to their low memory and/or performance overhead. Further, combinations of countermeasures show strong characteristics and can lead to a high fault coverage, while keeping additional resources at a minimum. The results obtained in this study provide developers of secure software for embedded systems with a solid basis to decide on the right type of fault attack countermeasure for their application.
Automatic Debugging of Concurrent Programs through Active Sampling of Low Dimensional Random Projections

Concurrent computer programs are fast becoming prevalent in many critical applications. Unfortunately, these programs are especially difficult to test and debug. Recently, it has been suggested that injecting random timing noise into many points within a program can assist in eliciting bugs within the program. Upon eliciting the bug, it is necessary to identify a minimal set of points that indicate the source of the bug to the programmer. In this paper, we pose this problem as an active feature selection problem. We propose an algorithm called the iterative group sampling algorithm that iteratively samples a lower dimensional projection of the program space and identifies candidate relevant points. We analyze the convergence properties of this algorithm. We test the proposed algorithm on several real-world programs and show its superior performance. Finally, we show the algorithms' performance on a large concurrent program.
Assessing the Influence of Patients' Perceptions of Physicians' Cultural Competence on Patient Satisfaction in an Appalachian Ohio Context

ABSTRACT Existing literature has found that Appalachia is a region with slow economic growth, health disparities, and a unique culture. However, little is known about the intersection of health and culture in an Appalachian context. To that end, we surveyed 306 participants from the patient base at a local clinical system serving three Appalachian Ohio counties in the United States (Athens, Jackson, and Gallia) to measure the influence of four dimensions of patients' perception of physicians' cultural competence on patient satisfaction with the direct clinical encounter. Analysis of variance and median split analysis found an association between patients' perceptions of physicians' cultural competence and patient satisfaction with the direct clinical encounter. These findings contribute to understanding cultural competence in unique contexts and will help stakeholders better understand the needs of Appalachian Ohio residents in receiving culturally competent health care.
IMP + Exc over decorated logic

In this paper, we facilitate the reasoning about impure programming languages, by annotating terms with “decorations” that describe what computational (side) effect evaluation of a term may involve. In a pointfree categorical language, called the “decorated logic”, we formalize the mutable state and the exception effects first seperately, and then combined, exploiting a nice duality between them. The combined decorated logic is used as the target language for the denotational semantics of the IMP+Exc imperative programming language, and allows us to prove equivalences between programs written in IMP+Exc. The combined logic is encoded in Coq, and this encoding is used to certify some program equivalence proofs.
Engines of speciation: a comparative study in birds of prey

Sexual selection as a promoter of speciation has received much attention in recent years, but has produced highly equivocal evidence. Here, I test whether sexual conflict is related to species richness among genera in accipitrid birds of prey using phylogenetically controlled comparative analyses. Increased species richness was associated with both ‘male‐win’ as well as ‘female‐win’ situations, i.e. males being able to promote gene flow through mating or females being able to restrict gene flow through female choice. Species richness was higher when plumage differed between males and females and in polygynous breeding systems compared with monogamous ones. To assess the relative importance of sexual conflict and natural selection as correlates of species richness simultaneously, I also performed a multivariate analysis of correlates of species richness. Population density, plumage polymorphism, geographic range size and breeding latitude were predictors of species richness for birds of prey. These results stress the importance of both sexual and natural selection in determining species richness but with a clear overall emphasis on natural selection in birds of prey.
Test vector embedding in accumulators with stored carry in O(1) time

In test set embedding Built-In Self Test (BIST) schemes a precomputed test set is embedded into the sequence generated by a hardware generator. These schemes have to evaluate the location of each test pattern in the sequence as fast as possible, in order to test as many as possible candidate configurations of the test pattern generator; this problem is known as the test vector-embedding problem. In this paper we present a O(1) solution to the test vector-embedding problem for sequences generated by accumulators.
Tissue Counter Analysis of Histologic Sections of Melanoma: Influence of Mask Size and Shape, Feature Selection, Statistical Methods and Tissue Preparation

Background: Tissue counter analysis is an image analysis tool designed for the detection of structures in complex images at the macroscopic or microscopic scale. As a basic principle, small square or circular measuring masks are randomly placed across the image and image analysis parameters are obtained for each mask. Based on learning sets, statistical classification procedures are generated which facilitate an automated classification of new data sets. Objective: To evaluate the influence of the size and shape of the measuring masks as well as the importance of feature selection, statistical procedures and technical preparation of slides on the performance of tissue counter analysis in microscopic images. As main quality measure of the final classification procedure, the percentage of elements that were correctly classified was used. Study design: H&E‐stained slides of 25 primary cutaneous melanomas were evaluated by tissue counter analysis for the recognition of melanoma elements (section area occupied by tumour cells) in contrast to other tissue elements and background elements. Circular and square measuring masks, various subsets of image analysis features and classification and regression trees compared with linear discriminant analysis as statistical alternatives were used. The percentage of elements that were correctly classified by the various classification procedures was assessed. In order to evaluate the applicability to slides obtained from different laboratories, the best procedure was automatically applied in a test set of another 50 cases of primary melanoma derived from the same laboratory as the learning set and two test sets of 20 cases each derived from two different laboratories, and the measurements of melanoma area in these cases were compared with conventional assessment of vertical tumour thickness. Results: Square measuring masks were slightly superior to circular masks, and larger masks (64 or 128 pixels in diameter) were superior to smaller masks (8 to 32 pixels in diameter). As far as the subsets of image analysis features were concerned, colour features were superior to densitometric and Haralick texture features. Statistical moments of the grey level distribution were of least significance. CART (classification and regression tree) analysis turned out to be superior to linear discriminant analysis. In the best setting, 95% of melanoma tissue elements were correctly recognized. Automated measurement of melanoma area in the independent test sets yielded a correlation of r=0.846 with vertical tumour thickness (p < 0.001), similar to the relationship reported for manual measurements. The test sets obtained from different laboratories yielded comparable results. Conclusions: Large, square measuring masks, colour features and CART analysis provide a useful setting for the automated measurement of melanoma tissue in tissue counter analysis, which can also be used for slides derived from different laboratories.
Measurement-based 3D-simulation models for elements of power line communications network

This paper presents 3D-simulation models for typical power line communication (PLC) network elements based on permittivity measurement results. We show that, e.g., materials of typically used plugs and sockets contribute to the overall performance of a PLC system especially at high frequencies. The work describes the main components of home and office area low voltage power distribution networks and disassembles the components into 3D-simulation models that can be used to analyze the data networking performance of the PLC network. The novel results indicate that the materials of the elements have an effect on the transmission properties and that should be taken into account. These effects have been analyzed using generated simulation models for the elements of the PLC network. The verification of transmission characteristics measurements using the constructed test bed of a PLC network segment and in a real low power office PLC network have been done.
Writer Adaptation with Style Transfer Mapping

Adapting a writer-independent classifier toward the unique handwriting style of a particular writer has the potential to significantly increase accuracy for personalized handwriting recognition. This paper proposes a novel framework of style transfer mapping (STM) for writer adaptation. The STM is a writer-specific class-independent feature transformation which has a closed-form solution. After style transfer mapping, the data of different writers are projected onto a style-free space, where the writer-independent classifier needs no change to classify the transformed data and can achieve significantly higher accuracy. The framework of STM can be combined with different types of classifiers for supervised, unsupervised, and semi-supervised adaptation, where writer-specific data can be either labeled or unlabeled and need not cover all classes. In this paper, we combine STM with the state-of-the-art classifiers for large-category Chinese handwriting recognition: learning vector quantization (LVQ) and modified quadratic discriminant function (MQDF). Experiments on the online Chinese handwriting database CASIA-OLHWDB demonstrate that STM-based adaptation is very efficient and effective in improving classification accuracy. Semi-supervised adaptation achieves the best performance, while unsupervised adaptation is even better than supervised adaptation. On handwritten text data, semi-supervised adaptation achieves error reduction rates 31.95 and 25.00 percent by LVQ and MQDF, respectively.
Picture Gesture Authentication

Picture gesture authentication has been recently introduced as an alternative login experience to text-based password on touch-screen devices. In particular, the newly on market Microsoft Windows 8™ operating system adopts such an alternative authentication to complement its traditional text-based authentication. We present an empirical analysis of picture gesture authentication on more than 10,000 picture passwords collected from more than 800 subjects through online user studies. Based on the findings of our user studies, we propose a novel attack framework that is capable of cracking passwords on previously unseen pictures in a picture gesture authentication system. Our approach is based on the concept of selection function that models users’ thought processes in selecting picture passwords. Our evaluation results show the proposed approach could crack a considerable portion of picture passwords under different settings. Based on the empirical analysis and attack results, we comparatively evaluate picture gesture authentication using a set of criteria for a better understanding of its advantages and limitations.
Organization of the Presynaptic Active Zone by ERC2/CAST1-Dependent Clustering of the Tandem PDZ Protein Syntenin-1

Presynaptic active zones contain a cytoskeletal matrix called the CAZ, which is thought to play a critical role in the regulation of active zone formation and neurotransmitter release. Recent studies have identified several CAZ components, but little is known about how they contribute to the molecular organization of active zones. Here, we report a novel PDZ [postsynaptic density-95/Discs large/zona occludens-1] interaction between the CAZ protein ERC2/CAST1 and the tandem PDZ protein syntenin-1, which is known to associate with diverse synaptic proteins, including glutamate receptor subunits, SynCAM, and β-neurexin. This interaction promotes the localization of syntenin-1 at presynaptic ERC2 clusters. In addition to the PDZ interaction, multimerization of both ERC2 and syntenin-1 mediates syntenin-1 clustering. These results suggest that ERC2 promotes presynaptic syntenin-1 clustering by two distinct mechanisms and that syntenin-1 may contribute to the molecular organization of active zones by linking ERC2 and other CAZ components to diverse syntenin-1-associated synaptic proteins.
Impulsive noise removal from images using sparse representation and optimization methods

In this paper, we propose a new method for impulsive noise removal from images. It uses the sparsity of natural images when they are expanded by mean of a good learned dictionary. The zeros in sparse domain give us an idea to reconstruct the pixels that are corrupted by random-value impulse noises. This idea comes from this reality that noisy image in sparse domain of original image will not have a sparse representation as much as original image sparsity. In this method we assume that the proper dictionary to achieve image in sparse domain is available.