Miracle-dz/UniFAR-FTUs huggingface dataset:
Experiments with E-Voting Technology: Experiences and Lessons

A secure PKI based system for e-voting was developed. We tested the application, several organizational aspects, and usability in fourteen field trials. In this paper we describe the method and findings. What do we learn about turnout, about the logistics of organizing e-voting, and about usability and reliability of the system in practice?
Improving the Ridge Based Fingerprint Recognition Method Using Sweat Pores

Among several biometric traits possible to be used for people identification, fingerprint is still the most used. Current automated fingerprint identification systems are based on ridge patterns and minutiae, classified as first and second level features, respectively. However, the development of new fingerprint sensors and the growing demand for more secure systems are leading to the use of additional discriminative fingerprint characteristics known as third level features, such as the sweat pores. Recent researches on fingerprint recognition have focused on fingerprint fragments, in which methods based only on first and second level features tend to obtain low recognition rates. This paper proposes a robust method de- veloped for fingerprint recognition from fingerprint fragments based on ridges and sweat pores. We have extended a ridge- based fingerprint recognition method previously proposed in the literature, based on Hough Transform, by incorporating sweat pores information in the matching step. Experimental results showed that although the reduction of Equal Error Rate is modest, a significant improvement was observed when analyzing the FMR100 and FMR1000 metrics, which are more suitable for high security applications. For these two metrics, the proposed approach obtained a reduction superior to 10% of the rates, when compared to the original ridge-based approach.
Experimenting with the Novel Approaches in Text Steganography

As is commonly known, the steganographic algorithms employ images, audio, video or text files as the medium to ensure hidden exchange of information between multiple contenders to protect the data from the prying eyes. However, using text as the target medium is relatively difficult as compared to the other target media, because of the lack of available redundant information in a text file. In this paper, in the backdrop of the limitations in the prevalent text based steganographic approaches, we propose simple, yet novel approaches that overcome the same. Our approaches are based on combining the random character sequence and feature coding methods to hide a character. We also analytically evaluate the approaches based on metrics viz. hiding strength, time overhead and memory overhead entailed. As compared to other methods, we believe the approaches proposed impart increased randomness and thus aid higher security at lower overhead.
Distributed task-based execution engine for support of text-mining processes

This paper describes design and implementation aspects for extension of our original software system developed in Java for support of information retrieval and text mining with specialized execution engine for different type of tasks. Some of our experiences and specific requirements of the real applications lead us to idea give the system possibility to run the tasks in distributive way. The result of the idea is task-based execution engine, which represents middleware-like transparent layer (mostly for programmers who want to re-use functionality of our package) for running of different tasks in multi-thread environment. The original system is being developed as open source with the intention to provide an easy extensible, modular framework for pre-processing, indexing and further exploration of large text collections. This specialized execution engine has been implemented within APVV project called PoZnaŤ (Support for knowledge creation processes) in order to extend proposed text-mining platform for educational and experimental purposes. Conceptual architecture of the system is provided as well as details regarding our extension of library like usage of content repository paradigm, representation and encapsulation of tasks, implementation of the engine itself and its role within PoZnaŤ platform.
Design of precoding and equalisation for broadband MIMO transmission

We propose a new approach to broadband {MIMO} precoding and equalisation by the use of a broadband singular value decomposition to decouple the {MIMO} system matrix into independent subchannels. {I}n a second step, {ISI} present in the subchannels is eliminated using methods developed for {SISO} systems. {A} numerical example is given.
Ongoing Epileptiform Activity in the Post-Ischemic Hippocampus Is Associated with a Permanent Shift of the Excitatory–Inhibitory Synaptic Balance in CA3 Pyramidal Neurons

Ischemic strokes are often associated with late-onset epilepsy, but the underlying mechanisms are poorly understood. In the hippocampus, which is one of the regions most sensitive to ischemic challenge, global ischemia induces a complete loss of CA1 pyramidal neurons, whereas the resistant CA3 pyramidal neurons display a long-term hyperexcitability several months after the insult. The mechanisms of this long-term hyperexcitability remain unknown despite its clinical implication. Using chronic in vivo EEG recordings and in vitro field recordings in slices, we now report spontaneous interictal epileptiform discharges in the CA3 area of the hippocampus from post-ischemic rats several months after the insult. Whole-cell recordings from CA3 pyramidal neurons, revealed a permanent reduction in the frequency of spontaneous and miniature GABAergic IPSCs and a parallel increase in the frequency of spontaneous and miniature glutamatergic postsynaptic currents. Global ischemia also induced a dramatic loss of GABAergic interneurons and terminals together with an increase in glutamatergic terminals in the CA3 area of the hippocampus. Altogether, our results show a morpho-functional reorganization in the CA3 network several months after global ischemia, resulting in a net shift in the excitatory–inhibitory balance toward excitation that may constitute a substrate for the generation of epileptiform discharges in the post-ischemic hippocampus.
APPLYING GENETIC ALGORITHMS TO IMPROVE FORECASTING BY GAUSSIAN PROCESSES

Gaussian processes are supervised learning tools. Just like Supervised Artificial Neural Network, Gaussian Processes distill data structure from real data. However, since there are some disadvantages of Gaussian Processes, this research introduces Genetic Algorithms to obtain the optimal parameter values for Gaussian processes in order to improve the learning capabilities on forecasting real time series financial data. This improvement could increase the learning speed and avoid the pre-setting of parameter values which affect the forecasting results.
Pathogenesis of high-altitude pulmonary edema: inflammation is not an etiologic factor.

CONTEXT The pathogenesis of high-altitude pulmonary edema (HAPE) is considered an altered permeability of the alveolar-capillary barrier secondary to intense pulmonary vasoconstriction and high capillary pressure, but previous bronchoalveolar lavage (BAL) findings in well-established HAPE are also consistent with inflammatory etiologic characteristics. OBJECTIVES To determine whether inflammation is a primary event in HAPE and to define the temporal sequence of events in HAPE. DESIGN, SETTING, AND PARTICIPANTS Case study from July through August 1999 of 10 subjects with susceptibility to HAPE and 6 subjects resistant to HAPE, all of whom are nonprofessional alpinists with previous mountaineering experience above 3000 m. MAIN OUTCOME MEASURES Pulmonary artery pressure measurements and BAL findings at low altitude (490 m) and shortly before or at the onset of HAPE at an altitude of 4559 m. RESULTS Subjects who were HAPE susceptible had higher mean (SD) pulmonary artery systolic blood pressures at 4559 m compared with HAPE-resistant subjects (66 vs 37 mm Hg; P =.004). Despite development of HAPE in the majority of HAPE-susceptible subjects, there were no differences in BAL fluid total leukocyte counts between resistant and susceptible subjects or between counts taken at low and high altitudes. Subjects who developed HAPE had BAL fluid with high concentrations of plasma-derived proteins and erythrocytes, but there was no increase in plasma concentrations of surfactant protein A and Clara cell protein. The chest radiograph score was 12.7 for the 3 HAPE-susceptible subjects who developed HAPE before BAL was performed; they were lavaged within 3 to 5 hours. The remainder of the HAPE-susceptible group was lavaged before edema was apparent on radiographs. However, 6 subjects from the HAPE-susceptible group who developed HAPE on the following day had a score on bronchoscopy of 1.5, which increased to 4.6, reflective of mild pulmonary edema. In HAPE cases, there were no elevations in a number of proinflammatory cytokines and eicosanoid and nitric oxide metabolites. CONCLUSIONS Early HAPE is characterized by high pulmonary artery pressures that lead to a protein-rich and mildly hemorrhagic edema, with normal levels of leukocytes, cytokines, and eicosanoids. HAPE is a form of hydrostatic pulmonary edema with altered alveolar-capillary permeability.
Fast Polar Decomposition of an Arbitrary Matrix

The polar decomposition of an $m \times n$ matrix A of full rank, where $m \geqq n$, can be computed using a quadratically convergent algorithm of Higham [SIAM J. Sci. Statist. Comput. , 7(1986), pp. 1160–1174]. The algorithm is based on a Newton iteration involving a matrix inverse. It is shown how, with the use of a preliminary complete orthogonal decomposition, the algorithm can be extended to arbitrary A. The use of the algorithm to compute the positive semidefinite square root of a Hermitian positive semidefinite matrix is also described. A hybrid algorithm that adaptively switches from the matrix inversion based iteration to a matrix multiplication based iteration due to Kovarik, and to Bjorck and Bowie, is formulated. The decision when to switch is made using a condition estimator. This “matrix multiplication rich” algorithm is shown to be more efficient on machines for which matrix multiplication can be executed 1.5 times faster than matrix inversion.
The Effect of Public Service Advertising on Cardiovascular Disease in Korea

Background: Public Service Advertising (PSA) is a public interest message disseminated in the form of an advertisement communication and its main purpose is to promote public behavioral changes regarding a social issue. Korea Centers for Disease Control and Prevention (KCDC) has been delivering PSA by various media. However, the effect of PSAs has never been evaluated. The purpose of this study was to estimate the effects of broadcasted PSA produced by KCDC on cardiovascular disease (CVD). Methods: One thousand adult participants throughout 15 provinces in Korea were chosen through the quota sampling method in 2012. A face-to-face research survey with 13 questions was conducted using a Computer Assisted Personal Interview (CAPI) system. Previous exposure to the PSA message, understanding, and behavioral intention to change was assessed. Results: After watching the PSA, about 75% of participants answered that they could understand the contents well and 70% had willingness to change their behaviors associated with CVD. However, only 24% of participants answered they watched the PSA during the past year. Conclusion: The PSA had positive effects on increasing the level of understanding and intention to change behaviors regarding CVD. However, the level of exposure was low. KCDC should make an effort to increase the public exposure level, which could be an important success factor regarding the PSA. In addition, KCDC should consider customized PSA for vulnerable people such as multi-cultural families, the disabled, and the elderly.
Detection of Glutamic Acid in Oilseed Rape Leaves Using Near Infrared Spectroscopy and the Least Squares-Support Vector Machine

Amino acids are quite important indices to indicate the growth status of oilseed rape under herbicide stress. Near infrared (NIR) spectroscopy combined with chemometrics was applied for fast determination of glutamic acid in oilseed rape leaves. The optimal spectral preprocessing method was obtained after comparing Savitzky-Golay smoothing, standard normal variate, multiplicative scatter correction, first and second derivatives, detrending and direct orthogonal signal correction. Linear and nonlinear calibration methods were developed, including partial least squares (PLS) and least squares-support vector machine (LS-SVM). The most effective wavelengths (EWs) were determined by the successive projections algorithm (SPA), and these wavelengths were used as the inputs of PLS and LS-SVM model. The best prediction results were achieved by SPA-LS-SVM (Raw) model with correlation coefficient r = 0.9943 and root mean squares error of prediction (RMSEP) = 0.0569 for prediction set. These results indicated that NIR spectroscopy combined with SPA-LS-SVM was feasible for the fast and effective detection of glutamic acid in oilseed rape leaves. The selected EWs could be used to develop spectral sensors, and the important and basic amino acid data were helpful to study the function mechanism of herbicide.
Nonlinear Instability of Kink Oscillations due to Shear Motions

First results from a high-resolution three-dimensional nonlinear numerical study of the kink oscillation are presented. We show in detail the development of a shear instability in an untwisted line-tied magnetic flux tube. The instability produces significant deformations of the tube boundary. An extended transition layer may naturally evolve as a result of the shear instability at a sharp transition between the flux tube and the external medium. We also discuss the possible effects of the instability on the process of resonant absorption when an inhomogeneous layer is included in the model. One of the implications of these results is that the azimuthal component of the magnetic field of a stable flux tube in the solar corona, needed to prevent the shear instability, is probably constrained to be in a very specific range.
Lessons Learned in Game Development for Crowdsourced Software Formal Verification

Introduction The history of formal methods and computer security research is long and intertwined. Program logics that were in theory capable of proving security properties of software were developed by the early 1970s [1]. The development of the first security models [2-4] gave rise to a desire to prove that the models did, in fact, enforce the properties that they claimed to, and that an actual implementation of the model was correct with respect to its specification [5; 6]. Optimism reached its peak in the early to mid-1980s [7-11], and the peak of formal methods for security was reached shortly before the publication of the Orange Book [12], where the certification of a system at class A1 required formal methods. Formal verification of software was considered the gold standard evidence that the software enforced a particular set of properties. Soon afterwards, the costs of formal methods, in both time and money, became all too apparent. Mainstream computer security research shifted focus to analysis of cryptographic protocols (e.g. [13; 14]), policies around cryptographic key management [15], and clever fixes for security problems found in contemporary systems [16-19].
Comparative Assessment of Cytokines and Other Inflammatory Markers for the Early Diagnosis of Neonatal Sepsis–A Case Control Study

Objective Cytokines (IL-6, IL-8 and TNF-α), sCD163, and C-reactive protein were serially measured in an attempt to identify a set of tests which can reliably confirm or refute the diagnosis of neonatal sepsis at an early stage. Methods One hundred neonates suspected to have sepsis on clinical grounds and who met the inclusion criteria were enrolled for the study. Based on the positive or negative blood culture reports they were classified as infected (n = 50) and non-infected (n = 50) neonates respectively. Fifty healthy neonates without any signs of sepsis were also included in the study as control group. The initial blood sample was taken on day 0 (at the time of sepsis evaluation) and two further samples were taken on days 1 and 2 for monitoring the clinical progress and response to treatment. In the control group the cord blood and 48 hours venous sample was collected. Plasma CRP (ng/ml), IL-6 (pg/ml), IL-8 (pg/ml), TNF-α (ng/ml) and sCD163 (ng/ml) were determined by double antibody method Enzyme Linked Immunosorbent Assay in all the three blood samples. Results The cut of levels for CRP at >19,689 ng/ml had a sensitivity of 68%, specificity of 92%, for IL-6 at >95.32 pg/ml had a sensitivity of 54%, specificity of 96%, for IL-8 at >70.86 pg/ml had a sensitivity of 78%, specificity of 70%, for sCD163 at >896.78 ng/ml had a sensitivity of 100%, specificity of 88% for the diagnosis of infection before antibiotics. TNF-α levels of >12.6 ng/ml showed 100% sensitivity and 72% specificity for the diagnosis of inflammation. Conclusion The most powerful predictor to differentiate between the non-infected and infected neonates before antibiotics was sCD163. The most powerful indicator for evaluation of prognosis is IL-6. sCD163 can be used alone to screen for sepsis in neonates before the results of blood culture are received.
Building a temporally annotated corpus for information extraction

Although there is now considerable availability of what might be termed ‘low-level’ (e.g. part-of-speech) annotated corpora, such resources are only of limited use for Information Extraction (IE); however, there is only a very limited availability of ‘high-level’ annotated corpora, which are of direct use. Over time it has become evident that ‘intermediate-level’ annotations for, e.g., named entities and coreference chains are also needed in order to build better IE systems. We share this view and believe that other intermediate level annotations are necessary. One such intermediate level is that which marks temporal reference and relations in text. To this end we have devised an annotation scheme for annotating those features and relations in texts which enable us to determine the relative order and, if possible, the absolute time, of the events reported in them. The scheme is being used to construct a temporally annotated corpus. This paper describes the annotation scheme, how we are building this corpus and the corpus that has so far resulted. We have also conducted a small scale experiment to ascertain to what extend superficial IE techniques are likely to be able to determine temporal relations in a text, which illustrates the insights for IE that can accrue from constructing annotated corpora.
Differences in Speech Recognition Between Children with Attention Deficits and Typically Developed Children Disappear When Exposed to 65 dB of Auditory Noise

The most common neuropsychiatric condition in the in children is attention deficit hyperactivity disorder (ADHD), affecting ∼6–9% of the population. ADHD is distinguished by inattention and hyperactive, impulsive behaviors as well as poor performance in various cognitive tasks often leading to failures at school. Sensory and perceptual dysfunctions have also been noticed. Prior research has mainly focused on limitations in executive functioning where differences are often explained by deficits in pre-frontal cortex activation. Less notice has been given to sensory perception and subcortical functioning in ADHD. Recent research has shown that children with ADHD diagnosis have a deviant auditory brain stem response compared to healthy controls. The aim of the present study was to investigate if the speech recognition threshold differs between attentive and children with ADHD symptoms in two environmental sound conditions, with and without external noise. Previous research has namely shown that children with attention deficits can benefit from white noise exposure during cognitive tasks and here we investigate if noise benefit is present during an auditory perceptual task. For this purpose we used a modified Hagerman’s speech recognition test where children with and without attention deficits performed a binaural speech recognition task to assess the speech recognition threshold in no noise and noise conditions (65 dB). Results showed that the inattentive group displayed a higher speech recognition threshold than typically developed children and that the difference in speech recognition threshold disappeared when exposed to noise at supra threshold level. From this we conclude that inattention can partly be explained by sensory perceptual limitations that can possibly be ameliorated through noise exposure.
Defect Recognition of X-Ray Steel Rope Cord Conveyer Belt Image Based on BP Neural Network

BP neural network is used to recognize X-ray steel rope cord conveyer belt image with defect in this paper. Firstly, the model of three layers BP neural network is established, and it is made up of 240 input nodes, 20 hidden layer nodes, and 1 output node. Then, the BP neural network is trained and tested in MATLAB. The results show that X-ray steel rope cord conveyer belt image with defect can be identified by the neural network.
Calibration of an IMU-Camera Cluster Using Planar Mirror Reflection and Its Observability Analysis

This paper describes a novel and a low-cost calibration approach to estimate the relative transformation between an inertial measurement unit (IMU) and a camera, which are rigidly mounted together. The calibration is performed by fusing the measurements from the IMU-camera rig moving in front of a planar mirror. To construct the visual observations, we select a set of key features (KFs) attached to the visual inertial rig where the 3-D positions of the KFs are unknown. During calibration, the system is navigating in front of the planar mirror, while the vision sensor observes the reflections of the KFs in the mirror, and the inertial sensor measures the system's linear accelerations and rotational velocities over time. Our first contribution in this paper is studying the observability properties of IMU-camera calibration parameters. For this visual inertial calibration problem, we derive its time-varying nonlinear state-space model and study its observability properties using the Lie derivative rank condition test. We show that the calibration parameters and the 3-D position of the KFs are observable. As our second contribution, we propose an approach for estimating the calibration parameters along with the 3-D position of the KFs and the dynamics of the analyzed system. The estimation problem is then solved in the unscented Kalman filter framework. We illustrate the findings of our theoretical analysis using both simulations and experiments. The achieved performance indicates that our proposed method can conveniently be used in consumer products like visual inertial-based applications in smartphones for localization, 3-D reconstruction, and surveillance applications.
The multisensory approach to development

Philosophers and psychologists alike have debated for centuries how humans and other species deal with the multiple sources of sensory information that specify the world around them. Recent years have seen a dramatic increase in our understanding of multisensory processes in mature adults, which have led to the conclusion that multisensory processes are ubiquitous in mature psychological functioning. However, developmental research has also shown that multisensory integration takes time to develop and that early experience plays a key role in its development. This chapter describes how the development of multisensory functioning can both constrain and enrich perceptual and cognitive functioning through the lifespan. This chapter also reflects on the history of the field, and draws out some key themes of recent research in multisensory development.