Effects of Single versus Multiple Warnings on Driver Performance

Objective: To explore how a single master alarm system affects drivers’ responses when compared to multiple, distinct warnings. Background: Advanced driver warning systems are intended to improve safety, yet inappropriate integration may increase the complexity of driving, especially in high workload situations. This study investigated the effects of auditory alarm scheme, reliability, and collision event-type on driver performance. Method: A 2x2x4 mixed factorial design investigated the impact of two alarm schemes (master vs. individual) and two levels of alarm reliability (high and low) on distracted drivers’ performance across four collision event-types (frontal collision warnings, left and right lane departure warnings, and follow vehicle fast approach). Results: Participants’ reaction times and accuracy rates were significantly affected by the type of collision event and alarm reliability. The use of individual alarms, rather than a single master alarm, did not significantly affect driving performance in terms of reaction time or response accuracy. Conclusion: Even though a master alarm is a relatively uninformative warning, it produced statistically no different reaction times or accuracy results when compared to information-rich auditory icons, some of which were spatially located. In addition, unreliable alarms negatively impacted driver performance, regardless of event type or alarm scheme. Application: These results have important implications for the development and implementation of multiple driver warning systems.This project was sponsored by the Ford Motor Company

Developing Scheme and 802.11 Mesh Networks

Unified pervasive modalities have led to many private advances, including kernels and local-area networks. In fact, few systems engineers would disagree with the simulation of SCSI disks, demonstrates the significant importance of distributed systems. Our focus in this position paper is not on whether the seminal virtual algorithm for the simulation of compilers by V. A. Jackson et al. is NP-complete, but rather on motivating a novel heuristic for the study of IPv4 (Boomdas)

The Co–Au interface in bimetallic nanoparticles: a high resolution STEM study

We report the formation of Au/Co nanoparticles and their characterization by aberration (Cs) corrected scanning transmission electron microscopy (STEM). The nanoparticles were synthesized by inert gas condensation, forming initially core-shell and bimetallic crystals. However, after thermal treatment at normal atmospheric conditions, the Co nanoparticles changed their morphology into a fine layer forming a perfect interface with the gold. The ordering of the zone rich in Co presents a fcc arrangement matching the gold lattice. The atomic analysis on the interface and the comparison of the STEM images with numerical simulations corroborated the atomic substitution of gold by cobalt

Nanoalloying in real time: a high resolution STEM and computer simulation study

Bimetallic nanoparticles constitute a promising type of catalysts, mainly because their physical and chemical properties may be tuned by varying their chemical composition, atomic ordering, and size. Today, the design of novel nanocatalysts is possible through a combination of virtual lab simulations on massive parallel computing and modern electron microscopy with picometre resolution on one hand, and the capability of chemical analysis at the atomic scale on the other. In this work we show how the combination of theoretical calculations and characterization can solve some of the paradoxes reported about nanocatalysts: Au-Pd bimetallic nanoparticles. In particular, we demonstrate the key role played by adsorbates, such as carbon monoxide (CO), on the structure of nanoalloys. Our results imply that surface condition of nanoparticles during synthesis is a parameter of paramount importance.Fil: Mariscal, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaFil: Mayoral, Alba. Universidad de Zaragoza. Instituto de Nanociencia de Aragón; EspañaFil: Olmos Asar, Jimena Anahí. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaFil: Magen, César. Universidad de Zaragoza. Instituto de Nanociencia de Aragón; EspañaFil: Mejia Rosales, Sergio Javier. Universidad Autónoma de Nuevo León; MéxicoFil: Pérez Tijerina, Eduardo. Universidad Autónoma de Nuevo León; MéxicoFil: José Yacamán, Miguel. University of Texas; Estados Unido

A wot-based method for creating digital sentinel twins of iot devices

The data produced by sensors of IoT devices are becoming keystones for organizations to conduct critical decision-making processes. However, delivering information to these processes in real-time represents two challenges for the organizations: the first one is achieving a constant dataflow from IoT to the cloud and the second one is enabling decision-making processes to retrieve data from dataflows in real-time. This paper presents a cloud-based Web of Things method for creating digital twins of IoT devices (named sentinels).The novelty of the proposed approach is that sentinels create an abstract window for decision-making processes to: (a) find data (e.g., properties, events, and data from sensors of IoT devices) or (b) invoke functions (e.g., actions and tasks) from physical devices (PD), as well as from virtual devices (VD). In this approach, the applications and services of decision-making processes deal with sentinels instead of managing complex details associated with the PDs, VDs, and cloud computing infrastructures. A prototype based on the proposed method was implemented to conduct a case study based on a blockchain system for verifying contract violation in sensors used in product transportation logistics. The evaluation showed the effectiveness of sentinels enabling organizations to attain data from IoT sensors and the dataflows used by decision-making processes to convert these data into useful information

Study of Friction and Wear Effects in Aluminum Parts Manufactured via Single Point Incremental Forming Process Using Petroleum and Vegetable Oil-Based Lubricants

This paper focuses on studying how mineral oil, sunflower, soybean, and corn lubricants influence friction and wear effects during the manufacturing of aluminum parts via the single point incremental forming (SPIF) process. To identify how friction, surface roughness, and wear change during the SPIF of aluminum parts, Stribeck curves were plotted as a function of the SPIF process parameters such as vertical step size, wall angle, and tool tip semi-spherical diameter. Furthermore, lubricant effects on the surface of the formed parts are examined by energy dispersive spectroscopy (EDS) and scanning electron microscope (SEM) images, the Alicona optical 3D measurement system, and Fourier-transform infrared spectroscopy (FTIR). Results show that during the SPIF process of the metallic specimens, soybean and corn oils attained the highest friction, along forces, roughness, and wear values. Based on the surface roughness measurements, it can be observed that soybean oil produces the worst surface roughness finish in the direction perpendicular to the tool passes (Ra =1.45 μm) considering a vertical step size of 0.25 mm with a 5 mm tool tip diameter. These findings are confirmed through plotting SPIFed Stribeck curves for the soybean and corn oils that show small hydrodynamic span regime changes for an increasing sample step-size forming process. This article elucidates the effects caused by mineral and vegetable oils on the surface of aluminum parts produced as a function of Single Point Incremental Sheet Forming process parameters

A mutate-and-map protocol for inferring base pairs in structured RNA

Chemical mapping is a widespread technique for structural analysis of nucleic acids in which a molecule's reactivity to different probes is quantified at single-nucleotide resolution and used to constrain structural modeling. This experimental framework has been extensively revisited in the past decade with new strategies for high-throughput read-outs, chemical modification, and rapid data analysis. Recently, we have coupled the technique to high-throughput mutagenesis. Point mutations of a base-paired nucleotide can lead to exposure of not only that nucleotide but also its interaction partner. Carrying out the mutation and mapping for the entire system gives an experimental approximation of the molecules contact map. Here, we give our in-house protocol for this mutate-and-map strategy, based on 96-well capillary electrophoresis, and we provide practical tips on interpreting the data to infer nucleic acid structure.Comment: 22 pages, 5 figure

Control task substitution in semi-automated driving: does it matter what aspects are automated?

Objective: The study was designed to show how driver attention to the road scene and engagement of a choice of secondary tasks are affected by the level of automation provided to assist or take over the basic task of vehicle control. It was also designed to investigate the difference between support in longitudinal control and support in lateral control. Background: There is comparatively little literature on the implications of automation for drivers’ engagement in the driving task and for their willingness to engage in non-driving-related activities. Method: A study was carried out on a high-level driving simulator in which drivers experienced three levels of automation: manual driving, semiautomated driving with either longitudinal or lateral control provided, and highly automated driving with both longitudinal and lateral control provided. Drivers were free to pay attention to the roadway and traffic or to engage in a range of entertainment and grooming tasks. Results: Engagement in the nondriving tasks increased from manual to semiautomated driving and increased further with highly automated driving. There were substantial differences in attention to the road and traffic between the two types of semiautomated driving. Conclusion: The literature on automation and the various task analyses of driving do not currently help to explain the effects that were found. Lateral support and longitudinal support may be the same in terms of levels of automation but appear to be regarded rather differently by drivers

Thermal Transport and Rheological Properties of Hybrid Nanofluids Based on Vegetable Lubricants

Nanofluids based on vegetal oil with different wt.% of carbon nanotubes (CNT), hexagonal boron nitride (h-BN), and its hybrid (h-BN@CNT) were produced to investigate the effects of these nano-additives on the thermal conductivity and rheological properties of nanofluids. Stable suspensions of these oil/nanostructures were produced without the use of stabilizing agents. The dispersed nanostructures were investigated by SEM, EDS, XRD, and XPS, while the thermal conductivity and rheological characteristics were studied by a transient hot-wire method and steady-state flow tests, respectively. Increases in thermal conductivity of up to 39% were observed for fluids produced with 0.5 wt.% of the hybrid nanomaterials. As for the rheological properties, it was verified that both the base fluid and the h-BN suspensions exhibited Newtonian behavior, while the presence of CNT modified this tendency. This change in behavior is attributed to the hydrophobic character of both CNT and the base oil, while h-BN nanostructures have lip-lip “bonds”, giving it a partial ionic character. However, the combination of these nanostructures was fundamental for the synergistic effect on the increase of thermal conductivity with respect to their counterparts

Localized interlayer complexes in heterobilayer transition metal dichalcogenides

We present theoretical results for the radiative rates and doping-dependent photoluminescence spectrum of interlayer excitonic complexes localized by donor impurities in MoSe2/WSe2 twisted heterobilayers, supported by quantum Monte Carlo calculations of binding energies and wave-function overlap integrals. For closely aligned layers, radiative decay is made possible by the momentum spread of the localized complexes' wave functions, resulting in radiative rates of a few μs−1. For strongly misaligned layers, the short-range interaction between the carriers and impurity provides a finite radiative rate with a strong asymptotic twist angle dependence ∝θ−8. Finally, phonon-assisted recombination is considered, with emission of optical phonons in both layers resulting in additional, weaker emission lines, redshifted by the phonon energy