The Last Inch at 70 Miles Per Hour

More recently, personal area network connectivity in vehicles has evolved, bringing with it a new set of challenges and associated opportunities. Principal among these challenges is the last-inch problem. The telecommunications industry uses the term "last mile" to refer to the challenge of bringing high-bandwidth connectivity to individual homes. We use the term "last inch" to characterize the challenges of delivering computing services through in-vehicle human-machine interfaces (HMIs) to users who are sometimes driving at speeds upwards of 70 miles per hour. We focus on the nonfunctional requirements of security, privacy, usability, and reliability (SPUR)). These attributes both encompass safety concerns and offer insight into the consumer experience. We took the SPUR requirements into account in designing our vehicle consumer services interface (VCSI), a service-oriented middleware architecture that we've implemented in a demonstration vehicle     

Effects of thermo-mechanical treatments on mechanical properties of AA2219 gas tungsten arc welds

Fusion zone of AA2219 alloy gas tungsten arc welds was subjected to compressive deformation by rolling the crown of the weld in the welding direction. Twelve percent compressive deformation improved the as-weld hardness from 75 to 100 VHN. The yield strength increased from 125 to 220 MPa. The welds made by pulsed current technique exhibited better strength and ductility compared to their continuous current weld counterparts, both in the as-welded condition and the deformed condition. The improvement in strength was found to be due to dislocation loops formed near the grain boundaries in the fusion zone. Direct aging of fusion zone at 190 °C, increased the yield strength significantly from 125 to about 200 MPa. Aging of the deformed fusion zone did not improve tensile strength further.     

Performance of a metallic gas diffusion layer for PEM fuel cells

A novel metallic porous medium with improved thermal and electrical conductivities and controllable porosity was developed based on micro/nano technology for its potential application in PEM fuel cells. In this work to demonstrate its applicability, the gas diffusion medium, made of 12.5 μm thick copper foil, was tested in an operational fuel cell. The small thickness and straight-pore feature of this novel material provides improved water management even at low flow rates. The performance does not decline at lower flow rates, unlike conventional gas diffusion layers. It has been shown that the performance can be further enhanced by increasing the in-plane transport. The improvements of such gas diffusion layer, including pore shape, porosity, and surface properties, are fully discussed.     

A hydrodynamic network model for interdigitated flow fields

The flow field is one of the main components of a fuel cell, which distributes the reactants to the active area of the cell and evacuates the products formed. Interdigitated flow field (IFF) is one among the different types of flow field designs that forces the reactants or products to flow through the electrode, thereby increasing the cell performance by decreasing concentration polarization loss, however, at the cost of higher-pressure drop. Prior understanding of the reactant and water vapour distribution in a flow field helps in obtaining the best flow field design. In the present paper, a model for the flow distribution and the pressure drop in an IFF has been developed using the analogy between fluid flow and electrical network in which the pressure is made analogous to the voltage and the flow rate to the current. The model, which ultimately reduces to the solution of a set of simultaneous algebraic equations, is capable of predicting the flow split among a set of inlet and outlet channels of an interdigitated flow field as well as the overall pressure drop for laminar, turbulent and two-phase flow conditions for arbitrary number of parallel channels. The results from the hydrodynamic network model have been validated against CFD simulations. This model can therefore be used for the optimization of interdigitated flow field design.     

Recent progress on synthetic strategies and applications of transition metal phosphides in energy storage and conversion

Continuous advancements in the field of energy conversion and storage, including the development, evaluation of abundant and inexpensive materials with good electrochemical performance, aim to meet the future energy demands. Transition metal phosphides (TMPs) have recently emerged as excellent energy conversion and storage materials due to their highly active surface sites, electrical conductivity, thermal and structural stability. TMPs exhibit numerous other desirable properties, like hardness and chemical stability, which result from the presence of strong M ? P bonds in the molecules. In this work, comprehensive review of recent advancements in research concerning TMPs and their applications in the area of energy conversion and storage was conducted. Additionally, the frequently employed synthetic strategies for the production of TMPs were investigated. Particularly, hydrogen and oxygen evolution reactions (HER and OER), dye-sensitized solar cells for energy conversion and storage, lithium-ion batteries, and supercapacitors were examined. TMPs display remarkable electrochemical behavior due to the synergistic effects of various compositions and surface structures. Moreover, the M-centers and P-sites possess high electrocatalytic activity. The P-sites of phosphides are negatively charged; thus, they attract protons, enhancing the HER/OER activities. Eventhough platinum-based electrocatalysts perform best in HER, their bifunctional properties have not been extensively studied due to poor OER activities. In energy storage, TMPs used as efficient and stable electrodes owing to their low charge-discharge potentials, high theoretical specific capacities, and a decreased ion-diffusion pathway. Finally, the challenges, future perspectives in the area of energy are discussed and several approaches for the improvement of multifunctional TMPs are proposed.     

Preparation and Characterization of Ni0.5Zn0.5Fe2O4 + Polyurethane Nanocomposites Using Melt Mixing Method

Silicon - In this study, nanocomposites of Ni0.5Zn0.5Fe2O4/polyurethane were prepared by melt mixing method and determined the influence of amount of Ni0.5Zn0.5Fe2O4 (0, 0.5, 1, 2, and 3 wt%)...     

Internet of Dental Things (IoDT), Intraoral Wireless Sensors,and Teledentistry: A Novel Model for Prevention of Dental Caries

Wireless Personal Communications - Dental caries is a complex, multifactorial, transmissible biofilm-initiated oral disease, which results in loss of tooth structure. Oral microbial flora, pH of...     

An Optimal Deep Learning Based Computer-Aided Diagnosis System for Diabetic Retinopathy

Diabetic Retinopathy (DR) is a significant blinding disease that poses serious threat to human vision rapidly. Classification and severity grading of DR are difficult processes to accomplish. Traditionally, it depends on ophthalmoscopically-visible symptoms of growing severity, which is then ranked in a stepwise scale from no retinopathy to various levels of DR severity. This paper presents an ensemble of Orthogonal Learning Particle Swarm Optimization (OPSO) algorithm-based Convolutional Neural Network (CNN) Model EOPSO-CNN in order to perform DR detection and grading. The proposed EOPSO-CNN model involves three main processes such as preprocessing, feature extraction, and classification. The proposed model initially involves preprocessing stage which removes the presence of noise in the input image. Then, the watershed algorithm is applied to segment the preprocessed images. Followed by, feature extraction takes place by leveraging EOPSO-CNN model. Finally, the extracted feature vectors are provided to a Decision Tree (DT) classifier to classify the DR images. The study experiments were carried out using Messidor DR Dataset and the results showed an extraordinary performance by the proposed method over compared methods in a considerable way. The simulation outcome offered the maximum classification with accuracy, sensitivity, and specificity values being 98.47%, 96.43%, and 99.02% respectively.     

LoRaWan Sensitivity Analysis and Prevention Strategies Against Wireless DoS Attacks

Wireless Personal Communications - New wireless IoT technology provides smart pseudo intelligent solutions that will have a big impact on the infrastructures and the society in the future to come....