Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Authentication Scheme with Privacy Preserving for Vehicular Ad-hoc Networks

Vehicular ad hoc networks (VANETs) provide opportunities to exchange traffic information among vehicles and infrastructures enhancing the transportation safety and driving experiences. Due to the criticality of exchanged information, message authentication which will not expose the privacy of vehicles is required. The majority of current authentication schemes for VANETs depend primarily on public-key cryptography which brings extra overhead in terms of delay and requires infrastructure support for certificate verification. Symmetric-key based techniques can be more efficient, but they introduce significant key maintenance overheads. In this paper, the authors propose an efficient and lightweight symmetric-key based authentication scheme for VANETs based on group communication. The authors analyze the security properties of our proposed schemes to show the applicability when there is little or no infrastructure support. In addition, the proposed scheme was implemented and tested with real-world vehicle data. Simulation results confirmed the efficiency in terms of delay with respect to other proposed techniques.
pSafety: A Collision Prevention System for Pedestrians Using Smartphone

We implement a collision prevention system, called pSafety, which instantaneously informs pedestrians and drivers of the potential threatening accidents. Unlike other systems, pSafety alerts pedestrians of threatening vehicles coming from not only the line-of-sight, but also non-line-of-sight due to obstructions of the wall corner or other vehicles. pSafety collects GPS information from smartphones of pedestrians and vehicle drivers through mobile networks. The main challenge of pSafety is that current smartphones demonstrate larger distance errors on the order of a few meters due to its intrinsic low-cost GPS receivers. To address the impact of large-error positioning to pSafety, we regard each participant on the map as a sector that indicates a predicted location. We subsequently design the Sector Overlap Detection Algorithm, called SODA, to detect whether two sectors are overlapping in time O(1). To avoid warning fatigue, we additionally provide a threat ranking method to evaluate the degree of risk for each potential collision event. Through our designed App, pedestrians and drivers both could receive a clear view of potential risks and then take proper actions to avoid accidents. In our implementation, we show that pSafety rapidly informs participants (i.e., pedestrians and drivers) and provides each participant a sufficient response time to avoid collision.
Spectroscopic Gravitational Lensing and Limits on the Dark Matter Substructure in Q2237+0305

Spatially resolved spectroscopic data from the CIRPASS integral field unit (IFU) on Gemini are used to measure the gravitational lensing of the four-image quasar Q2237+0305 on different size scales. A method for measuring the substructure present in the lens using observations at multiple wavelengths is demonstrated to be very effective and independent of many of the degeneracies inherent in previous methods. The magnification ratios of the QSO's narrow-line region (NLR) and broad-line region (BLR) are measured and found to disagree with each other and with the published radio and mid-infrared magnification ratios. The disagreement between the BLR ratios and the radio/mid-infrared ratios is interpreted as the result of microlensing by stars in the lens galaxy of the BLR. This implies that the mid-infrared emission region is larger than the BLR and that the BLR is ≲0.1 pc in size. We find a small difference between the shape of the Hβ line in image A and that in the other images. We consider this difference too small and symmetric to be strong evidence for rotation or large-scale infall in the Hβ emission region. The disagreement between the radio/mid-infrared ratios and the NLR ratios is interpreted as a signature of substructure on a larger scale, possibly the missing small-scale structure predicted by the standard cold dark matter (CDM) model. Extensive lensing simulations are performed to obtain a lower limit on the amount of substructure that is required to cause this discrepancy as a function of its mass and the radial profile of the host lens. The substructure surface density is degenerate with the radial profile of the host lens, but if the expectations of the CDM model are taken into account, certain radial profiles and substructure surface densities can be ruled out. A substructure mass scale as large as 108 M☉ is strongly disfavored, while 104 M☉ is too small if the radio and mid-infrared emission regions have the expected sizes of ~10 pc. The standard elliptical isothermal lens mass profile is not compatible with a substructure surface density of Σsub < 280 M☉ pc-2, at the 95% confidence level. This is 4%-7% of the galaxy's surface density (depending on which image position is used to evaluate this). The required substructure surface density at the required mass scale is high in comparison with the present expectations within the CDM model. Lens mass profiles that are flatter than isothermal—where the surface density in dark matter is higher at the image positions—are compatible with smaller quantities of substructure.
Wafer scale fabrication of submicron chessboard gratings using phase masks in proximity lithography

One and two dimensional grating structures with submicron period have a huge number of applications in optics and photonics. Such structures are conventionally fabricated using interference or e-beam lithography. However, both technologies have significant drawbacks. Interference lithography is limited to rather simple geometries and the sequential writing scheme of e-beam lithography leads to time consuming exposures for each grating. We present a novel fabrication technique for this class of microstructures which is based on proximity lithography in a mask aligner. The technology is capable to pattern a complete wafer within less than one minute of exposure time and offers thereby high lateral resolution and a reliable process. Our advancements compared to standard mask aligner lithography are twofold: First of all, we are using periodic binary phase masks instead of chromium masks to generate an aerial image of high resolution and exceptional light efficiency at certain distances behind the mask. Second, a special mask aligner illumination set-up is employed which allows to precisely control the incidence angles of the exposure light. This degree of freedom allows both, to shape the aerial image (e. g. transformation of a periodic spot pattern into a chessboard pattern) and to increase its depth of focus considerably. That way, our technology enables the fabrication of high quality gratings with arbitrary geometry in a fast and stable wafer scale process.
Discrimination Aware Decision Tree Learning

Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the same time does not discriminate on the basis of the given attribute B. This problem is motivated by the fact that often available historic data is biased due to discrimination, e.g., when B denotes ethnicity. Using the standard learners on this data may lead to wrongfully biased classifiers, even if the attribute B is removed from training data. Existing solutions for this problem consist in “cleaning away” the discrimination from the dataset before a classifier is learned. In this paper we study an alternative approach in which the non-discrimination constraint is pushed deeply into a decision tree learner by changing its splitting criterion and pruning strategy. Experimental evaluation shows that the proposed approach advances the state-of-the-art in the sense that the learned decision trees have a lower discrimination than models provided by previous methods, with little loss in accuracy.
Analysis of PINCH function in Drosophila demonstrates its requirement in integrin-dependent cellular processes

Integrins play a crucial role in cell motility, cell proliferation and cell survival. The evolutionarily conserved LIM protein PINCH is postulated to act as part of an integrin-dependent signaling complex. In order to evaluate the role of PINCH in integrin-mediated cellular events, we have tested directly the in vivo function of PINCH in Drosophila melanogaster. We demonstrate that the steamer duck (stck) alleles that were first identified in a screen for potential integrin effectors represent mutations in Drosophila pinch. stck mutants die during embryogenesis, revealing a key role for PINCH in development. Muscle cells within embryos that have compromised PINCH function display disturbed actin organization and cell-substratum adhesion. Mutation of stck also causes failure of integrin-dependent epithelial cell adhesion in the wing. Consistent with the idea that PINCH could contribute to integrin function, PINCH protein colocalizes with βPS integrin at sites of actin filament anchorage in both muscle and wing epithelial cells. Furthermore, we show that integrins are required for proper localization of PINCH at the myotendinous junction. The integrin-linked kinase, ILK, is also essential for integrin function. We demonstrate that Drosophila PINCH and ILK are complexed in vivo and are coincident at the integrin-rich muscle-attachment sites in embryonic muscle. Interestingly, ILK localizes appropriately in stck mutant embryos, therefore the phenotypes exhibited by the stck mutants are not attributable to mislocalization of ILK. Our results provide direct genetic evidence that PINCH is essential for Drosophila development and is required for integrin-dependent cell adhesion.
Protective Effect of Padina arborescens Extract against High Glucose-induced Oxidative Damage in Human Umbilical Vein Endothelial Cells

Dysfunction of endothelial cells is considered a major cause of vascular complications in diabetes. In the present study, we investigated the protective effect of Padina arborescens extract against high glucose-induced oxidative damage in human umbilical vein endothelial cells (HUVECs). High-concentration of glucose (30 mM) treatment induced cytotoxicity whereas Padina arborescens extract protected the cells from high glucose-induced damage and significantly restored cell viability. In addition, lipid peroxidation, intracellular reactive oxygen species (ROS), and nitric oxide (NO) levels induced by high glucose treatment were effectively inhibited by treatment of Padina arborescens extract in a dose-dependent manner. High glucose treatment also induced the overexpressions of inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2) and NF-κB proteins in HUVECs, but Padina arborescens extract treatment reduced the over-expressions of these proteins. These findings indicate the potential benefits of Padina arborescens extract as a valuable source in reducing the oxidative damage induced by high glucose.
Plasma-enhanced atomic layer deposition for antireflection coatings using SiO2 as low-refractive index material

This study focuses on the atomic layer deposition (ALD) of high quality SiO2 thin films for optical application. One of the challenges for the application of dielectric ALD layers in optical coatings is the realization of low absorption and scattering losses. Furthermore the layers have to be prepared with a precise controlled thickness and repeatable optical properties. SiO2 films were deposited using tris[dimethylamino]silane (3DMAS) and oxygen plasma on Si(100)substrates, quartz and BK7 glass substrates at temperatures between 100 °C and 300 °C. Film growth rate and refractive indices of SiO2 thin films were studied as function of deposition temperature. A linear growth behavior of SiO2 ALD films is confirmed, allowing a scalability of film thickness just by counting ALD cycles. The grown films are resistant to abrasion and possess good adhesion to glass substrates. The optical losses of the films are negligible in the investigated spectral range from 250 nm to 1100 nm. An antireflective (AR) coating was prepared by atomic layer deposition using SiO2 as low refractive index material and HfO2 as high refractive index material.
Methodology for voice commands recognition using stochastic classifiers

The incidence of people with motor disabilities in Colombia is around 6.4%, which is a major social problem, because people with such disabilities lose their autonomy to perform basic actions such as displacement. Therefore, we propose a solution to the problem of mobility in people with motor disabilities, allowing to take control of the engines, with a voice comand recognition system. This paper presents a methodology for recognition of isolated spanish words (silla, atrás, adelante, derecha, izquierda, pare). To this end, we use a methodology based on the wavelet transform preprocessing. The characterization of the filtered signal is performed by Mel Cepstral Coefficients and classification stage using hidden Markov models. The methodology has proven to be robust, because the databases used for training the system have been acquired in noisy environments as well as controlled, presenting performances in classification acuracy of 98%.
The effect of opinion clustering on disease outbreaks

Many high-income countries currently experience large outbreaks of vaccine-preventable diseases such as measles despite the availability of highly effective vaccines. This phenomenon lacks an explanation in countries where vaccination rates are rising on an already high level. Here, we build on the growing evidence that belief systems, rather than access to vaccines, are the primary barrier to vaccination in high-income countries, and show how a simple opinion formation process can lead to clusters of unvaccinated individuals, leading to a dramatic increase in disease outbreak probability. In particular, the effect of clustering on outbreak probabilities is strongest when the vaccination coverage is close to the level required to provide herd immunity under the assumption of random mixing. Our results based on computer simulations suggest that the current estimates of vaccination coverage necessary to avoid outbreaks of vaccine-preventable diseases might be too low.
FEM Applied to Evaluate Composite Hardness of SiO2 Film/316 LSS Substrate System

Due to non-ideal tip, performance of instrument and substrate effect, it is difficult to evaluate either composite mechanical properties of thin film/substrate system or the pure film's properties. In order to get composite hardness of thin film and how the substrate takes effect of the film's properties, FEM is used to simulate the indentation process of SiO2 thin films on 316LSS. With experiments, we observe that the hardness heavily depends the thickness of SiO2 film with different thickness deposited on 316 LSS by PVD. By FEM simulation and calculation, composite hardness is found to decrease greatly with increasing indentation depth. As thickness of film keeps constant, there exists a critical indentation depth about 1/20 of film thickness, less than which composite hardness may be regarded as film hardness. Discussion indicates FEM analysis method in this paper may not only play role in determining composite hardness of thin film/hardness system, but also provide a method to calculate pure hardness of thin film.
Long-term follow-up of patients with indication for a implantable defibrillator for primary prevention of death.

BACKGROUND Recent MADIT II and SCD-HeFT trials have led to an expansion of indications for use of prophylactic Implantable Cardioverter Defibrillator (ICD) in patients with severe left-ventricular impairment. This therapy has not been fully adopted in our health care system, mainly due to its high cost. OBJECTIVE To assess total mortality of SCD-HeFT-like patients from our daily practice who are under stable, optimal medical treatment and who have not received an ICD; and to compare it to that of the placebo arm of the SCD-HeFT Trial. METHODS SCD-HeFT-like patients identified from office medical records were included in our study. Total mortality was assessed by telephone contact. Statistical analysis was performed by Student's t-Test, Mann-Whitney Test or chi2 test, depending on the type of variable. Cumulative mortality rates were calculated according to the Kaplan-Meier method. RESULTS Our study comprised 102 patients (seventy-four of which were men) with a median age of 64 years, and an overall median ejection fraction of 25%. We found no differences between our patients and SCD-HeFT patients across these 3 variables. Over a 19.6-month follow-up period, 21 patients died (20.6%) vs. 28.8% of the SCD-HeFT patients. This difference was not statistically significant (p = 0.08). CONCLUSION SCD-HeFT-like patients from our practice had no difference in mortality rate than patients enrolled in the placebo arm of the SCD-HeFT trial. These results suggest that the SCD-HeFT population is representative of our patients.
Invariant Representations for Noisy Speech Recognition

Modern automatic speech recognition (ASR) systems need to be robust under acoustic variability arising from environmental, speaker, channel, and recording conditions. Ensuring such robustness to variability is a challenge in modern day neural network-based ASR systems, especially when all types of variability are not seen during training. We attempt to address this problem by encouraging the neural network acoustic model to learn invariant feature representations. We use ideas from recent research on image generation using Generative Adversarial Networks and domain adaptation ideas extending adversarial gradient-based training. A recent work from Ganin et al. proposes to use adversarial training for image domain adaptation by using an intermediate representation from the main target classification network to deteriorate the domain classifier performance through a separate neural network. Our work focuses on investigating neural architectures which produce representations invariant to noise conditions for ASR. We evaluate the proposed architecture on the Aurora-4 task, a popular benchmark for noise robust ASR. We show that our method generalizes better than the standard multi-condition training especially when only a few noise categories are seen during training.
DRFNet: A lightweight and high accuracy network for resource-limited implementation

With the increased demand of recognition accuracy in image classification, the convolutional neural networks (CNNs) grow rapidly in scale, which makes CNNs more difficult to be deployed on resource-limited platforms. In this paper, we present a lightweight Deep Residual FireNet (DRFNet). The new DRFNet has 26 weight layers and uses the fire module as its basic building module. In its architecture, we use three max-pooling operations, and additionally two average-pooling layers to preserve a higher resolution and larger receptive field. In addition, four bypass connections are used to further improve the accuracy rate. With this new design, the proposed DRFNet has successfully reduced the number of weight parameters to be around 1.85 million, 3% of AlexNet and 1.3% of VGG16. Meanwhile, the new DRFNet has achieved 91.44% top-5 accuracy rate on the ImageNet validation dataset, which is higher than AlexNet, SqueezeNet, VGG16 and GoogLeNet.
Experimental Investigation and Computer Modeling of Optical Switching in Distributed Bragg Reflector and Vertical Cavity Surface Emitting Laser Structures.

Abstract : The optical switching capabilities of Distributed Bragg Reflector (DBR) structures, including Vertical Cavity Surface Emitting Lasers (VCSELs) are examined. Reflectivity switching is demonstrated using both thermal and carrier generated effects to alter the DBR/VCSEL layers' refractive indices. Optical bistability is demonstrated at room temperature, under CW photopumped excitation. The optical bistability hysteresis is controllable by spectral location of the pump on the stop band edge. In the VCSEL, reflective bistability is also evidenced; additionally, this bistability is accompanied by a bistability in the VCSEL lasing output intensity, spot size, and wavelength. Modeling of the DBR/VCSEL thermally induced bistability was accomplished using an iterative, three dimensional Green's function solution to the laser induced heat equation. The model predicts thermally generated bistability, indicating a wavelength dependence, reflectivity jump, self focusing induced spot size change, and wavelength jump commensurate with the experimental data. Reflectivity switching due to carrier effects is also demonstrated, the DBR and VCSELs exhibiting subpicosecond switching speeds and contrast ratios of 3:1. Carrier heating, two photon absorption, and thermal components of the reflectivity switching capabilities are examined and found to be consistent with measured nonlinear response characteristics for the refractive index in AlGaAs.
Race Cars vs. Trailer Trucks: Switch Buffers Sizing vs. Latency Trade-Offs in Data Center Networks

This paper raises the data center designers question of trade-off between high-buffer switches versus low-latency switches. Packet buffer hardware dictates this trade-off due to the constraints of DRAM and SRAM technologies. While the designers who prefer network robust solutions would typically prefer large-buffer switches with settling for high latency, the designers who can adapt applications to the network behavior would prefer the low-latency switches in order to gain better application performance. In this paper, we review the question of switch buffer sizing in data center networks, by considering the switch delay in light of common traffic patterns in data centers. To the best of our knowledge, this is the first paper that discusses the switch buffer sizing question by considering switch latency trade-off. We review previous works on switch buffer sizing given the typical parameters of data center networks, and survey the typical data center traffic patterns that challenge the switch buffer. Also, we provide simulation results that show the effect of switch latency on the effective bandwidth of acknowledgement-based congestion controlled flows. Finally, we discuss the gain that flow control provides to end-to-end network performance.
Dynamic load management for distributed continuous query systems

A distributed stream processing system must adapt to changes in environment parameters and servers' load. We believe a dynamic load management scheme is indispensable for the system to be scalable. In particular, we expect aggressive methods such as query operator migration during runtime to bring long term benefit (especially for long running continuous queries) even though they may incur some short term overhead. However, to date few complete and practical solutions have been proposed for this problem. In this paper, we offer our solution to the problem. More specifically we make the following contributions: We formally define a new metric, performance ratio (PR), to measure the relative performance of each query and the objective for the whole system. By building a new cost model, we identify the heuristics that can be used to approach the objective. We propose a complete and practical distributed load management scheme, which includes a static initial placement scheme for newly, initiated queries as well as a runtime dynamic scheme. We conducted an extensive experimental study that shows the effectiveness of our technique.