Effect of ZnO layer thickness upon optoelectrical properties of NiO/ ZnO heterojunction prepared at room temperature

In this work, p-NiO/n-ZnO heterostructures were successfully prepared at room temperature using RF sputtering technique. The influence of ZnO layer thickness on the performance of the heterojunction was investigated. The deposited ZnO layers have a hexagonal Wurtzite structure with preferable growth orientations along (002) and (103) for thinner films. Increasing the thickness results in more crystallographic orientation randomness. The current–voltage measurements of the realized heterojunctions showed a clear rectifying behavior. The measured ideality factor varies from 2.5 to 1.6 according to the thickness of ZnO layer. The series resistance of the device is enlarged with increasing ZnO thickness. The deduced parameters from the I–V characteristics suggest that 200 nm is the optimal thickness of the ZnO layer according to our experimental conditions. We attribute the relatively better performance of this thickness to achieving reasonable compensation between serial resistance and ideality factor. The best heterojunction was tested and successfully used as a UV detector.     

Improving weld formability by a novel dual-rotation bobbin tool friction stir welding

A novel dual-rotation bobbin tool friction stir welding (DBT-FSW) was developed, in which the upper shoulder (US) and lower shoulder (LS) have different rotational speeds. This process was tried to weld 3.2 mm thick aluminum-lithium alloy sheets. The metallographic analysis and torque measurement were carried out to characterize the weld formability. Experimental results show that compared to conventional bobbin tool friction stir welding, the DBT-FSW has an excellent process stability, and can produce the defect-free joints in a wider range of welding parameters. These can be attributed to the significant improvement of material flow caused by the formation of a staggered layer structure and the unbalanced force between the US and LS during the DBT-FSW process.     

Cross-Layer Optimization of Dynamic Packet Assignment for Video Transmission Over IEEE 802.11e Networks

Video transmission over IEEE 802.11e wireless networks still shows poor performance for large bandwidth demand and frequently changed environments. Thus, several enhancements of IEEE 802.11e were proposed. On the other hand, big frames and simultaneous sending of adjacent frames always cause packet dropping for buffer overflow. In the past, we proposed an IEEE 802.11e enhancement named DFAA and a content aware mechanism to solve the above problems. The motivation of this paper is to find a proper way to integrate these two mechanisms. A DFAA enhancement (DFAA-E) is proposed to make up the insufficiency of content aware mechanism. Experiments results show that the combination of DFAA-E and content aware mechanism improves the video decoded quality greatly. And its performance can be further enhanced by selecting the suitable settings of certain parameters.     

On Application of Carbon-Containing Electrode Materials in Technology of Electrospark Alloying: Part 1. Peculiarities of Coating Formation Using Electrospark Treatment of Titanium Alloy OT4-1

Electrospark treatment of OT4-1 titanium alloy was performed sequentially with a STIM-20N hard-alloy electrode (TiC–20% Ni) and carbon-containing material (graphite and carbon-based composite materials). Kinetics of the mass transfer of the hard-alloy electrode was studied. The cathode mass loss during the first minute of the treatment was established. The kinetics results were processed using the methods of mathematical statistics. The erosion resistance of the applied carbon-containing materials was determined. Phase composition and relief of the coatings formed were analyzed. It was found that the application of the carbon-containing material increases the content of refractory phases in the coatings. Increase in the time of the treatment using the carbon-containing materials decreases the roughness of the coatings.     

Medicine Meets Thermal Spray Technology: A Review of Patents

The patent literature concerning thermal spraying for biomedical applications is reviewed in this contribution. The patents were compiled from multiple databases search spanning the 2005-2018 period. For clarity and ease of reading, the results have been grouped into sections according to four individual material groups (apatites, titanium, oxide ceramics, other), with the secondary sorting criterion being related to the specific bioapplication areas (maxillofacial, orthopedic, methods). Lastly, the patents are grouped according to the selected thermal spray method within the individual subsections. In the paper, recent R&D trends in this field are further identified and briefly commented.     

Assessment of Dam Overtopping Reliability using SUFI Based Overtopping Threshold Curve

Estimation of earth-fill dam height and dimension of spillway are strongly depend on accurate evaluation of dam overtopping reliability. Ideally, whole random and effective variables on overtopping should be considered for dam overtopping reliability assessment. However, taking into account all affecting random variables as well as overtopping reliability assessment using algorithms such as Monte Carlo (MC) could be excessively time consuming and impossible in some cases. In this study, new approach has been introduced as conditional reliability method and it has been tried to reduce the simulations time significantly by using combination of rainfall threshold theory, SUFI (Sequential Uncertainty Fitting) and MC methods. According two defined indexes, the obtain results shown, the relative error of new approach in computation of Jamishan dam overtopping reliability is less than 0.23%. Also, time saving in new method against to regular MC method is more than 87%. So, the new introduced method has more efficiency with acceptable accuracy for assessment of dam overtopping reliability. In addition, among hydrological and hydraulic uncertainties, hydrological uncertainties have more effect on overtopping reliability.     

Reoptimization framework and policy analysis for maritime inventory routing under uncertainty

We study a maritime inventory routing problem, in which shipments between production and consumption nodes are carried out by a fleet of vessels. The vessels have specific capacities and can be chartered under different agreements. The inventory levels of all consumption nodes and some production nodes should be maintained within specified bounds; for the remaining production nodes, orders should be picked up within pre-defined time windows. We propose a discrete-time mixed-integer programming model. In the face of new information and uncertainty, this optimization model has to be re-solved, as the horizon is rolled forward. We discuss how to account for different sources of uncertainty. We present a rolling-horizon reoptimization framework that allows us to study different policies that impact the quality of the implemented solution, so we can identify the optimal set of policies.     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.