Effect of Lateral Cracks on Fracture Toughness Determined by the Surface-Crack-in-Flexure Method

The surface-crack-in-flexure (SCF) method uses a Knoop indenter to create small, semielliptical surface precracks in beam specimens. Lateral cracks may interfere with the primary median crack and cause errors of up to 10% in determination of fracture toughness, particularly for materials for which the fracture toughness is ∼3 MPa·m^1/2 or less. Although the residual-stress-damage zone is ground or polished away by hand by removing 4.5–5 times the indentation depth, this amount may not be sufficient to completely remove the lateral cracks in low-fracture-toughness materials. A series of tests were conducted on sintered alpha silicon carbide with different amounts of material removed after indentation. Once the lateral cracks were fully removed, the SCF results concurred with single-edged-precracked-beam and chevron-notched-beam data collected in accordance with ASTM Designation C1421. A simple remedy for the SCF method is to examine the outer ground surface for remnants of lateral cracks before fracture and to remove more material if necessary.     

Node cooperation in hybrid ad hoc networks

A hybrid ad hoc network is a structure-based network that is extended using multihop communications. Indeed, in this kind of network, the existence of a communication link between the mobile station and the base station is not required: A mobile station that has no direct connection with a base station can use other mobile stations as relays. Compared with conventional (single-hop) structure-based networks, this new generation can lead to a better use of the available spectrum and to a reduction of infrastructure costs. However, these benefits would vanish if the mobile nodes did not properly cooperate and forward packets for other nodes. In this paper, we propose a charging and rewarding scheme to encourage the most fundamental operation, namely packet forwarding. We use "MAC layering" to reduce the space overhead in the packets and a stream cipher encryption mechanism to provide "implicit. authentication" of the nodes involved in the communication. We analyze the robustness of our protocols against rational and malicious attacks. We show that-using our solution-collaboration is rational for selfish nodes. We also show that our protocols thwart rational attacks and detect malicious attacks.     

Automatic Channel Detection Using DNN on 2D Seismic Data

Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon resources. Channels are among the most important geological features interpreters analyze to locate petroleum reservoirs. However, manual channel picking is both time consuming and tedious. Moreover, similar to any other process dependent on human intervention, manual channel picking is error prone and inconsistent. To address these issues, automatic channel detection is both necessary and important for efficient and accurate seismic interpretation. Modern systems make use of real-time image processing techniques for different tasks. Automatic channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil companies. In this paper, we propose an innovative automatic channel detection algorithm based on machine learning techniques. The new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation process. The algorithm uses deep neural network to train the classifier with both the channel and non-channel patches. We provide a field data example to demonstrate the performance of the new algorithm. The training phase gave a maximum accuracy of 84.6% for the classifier and it performed even better in the testing phase, giving a maximum accuracy of 90%.     

Effect of equal channel angular extrusion on the microstructure and superplasticity of an Al-Li alloy

This research investigates the use of equal channel angular extrusion (ECAE) processing to produce a superplastic form of the aluminum alloy 2098. The starting material was a hot-rolled and precipitation-hardened plate with elongated grains of width 67–92 μm, and a composition in weight percent of 2.2% Li, 1.3% Cu, 0.73% Mg, 0.05% Zr, balance Al. Microstructural evolution was investigated with optical and transmission electron microscopy (TEM) and microhardness measurements after each step of a multipass ECAE process. ECAE produced a submicron grain structure with an average size of about 0.5 μm. The sub-grain microstructure size was a function of the magnitude of the input strain and the extrusion temperature. Misorientation angles of the developed submicron structure increase with increasing number of passes at warm working temperatures. Superplastic behavior of the ECAE-processed alloy was achieved. However, the low zirconium content of the 2098 alloy resulted in grain growth of the refined structure at the superplastic processing temperatures, placing a lower limit on the deformation rates that can be used.     

Interpretation of way-finding healthcare symbols by a multicultural population: Navigation signage design for global health

The interpretation of way-finding symbols for healthcare facilities in a multicultural community was assessed in a cross-sectional study. One hundred participants recruited from Al Ain city in the United Arab Emirates were asked to interpret 28 healthcare symbols developed at Hablamos Juntos (such as vaccinations and laboratory) as well as 18 general-purpose symbols (such as elevators and restrooms). The mean age was 27.6 years (16–55 years) of whom 84 (84%) were females. Healthcare symbols were more difficult to comprehend than general-purpose signs. Symbols referring to abstract concepts were the most misinterpreted including oncology, diabetes education, outpatient clinic, interpretive services, pharmacy, internal medicine, registration, social services, obstetrics and gynecology, pediatrics and infectious diseases. Interpretation rates varied across cultural backgrounds and increased with higher education and younger age. Signage within healthcare facilities should be tested among older persons, those with limited literacy and across a wide range of cultures.     

Calculation of single adsorption isotherms from gravimetrically measured binary gas mixture adsorption isotherms on activated carbon at high pressures

A method is developed for the calculation of single-component adsorption isotherms from gravimetrically measured binary gas mixture adsorption isotherms at high pressures, at two temperatures and for different mole fractions of the gas phase. The adsorption of nitrogen/methane on active carbon Norit R1 is taken as an experimental example.     

Coronavirus disease 2019 (COVID-19): survival analysis using deep learning and Cox regression model

Pattern Analysis and Applications - Coronavirus (COVID-19) is one of the most serious problems that has caused stopping the wheel of life all over the world. It is widely spread to the extent that...     

Active XML-based Web data integration

Today, the Web is the largest source of information worldwide. There is currently a strong trend for decision-making applications such as Data Warehousing (DW) and Business Intelligence (BI) to move onto the Web, especially in the cloud. Integrating data into DW/BI applications is a critical and time-consuming task. To make better decisions in DW/BI applications, next generation data integration poses new requirements to data integration systems, over those posed by traditional data integration. In this paper, we propose a generic, metadata-based, service-oriented, and event-driven approach for integrating Web data timely and autonomously. Beside handling data heterogeneity, distribution and interoperability, our approach satisfies near real-time requirements and realize active data integration. For this sake, we design and develop a framework that utilizes Web standards (e.g., XML and Web services) for tackling data heterogeneity, distribution and interoperability issues. Moreover, our framework utilizes Active XML (AXML) to warehouse passive data as well as services to integrate active and dynamic data on-the-fly. AXML embedded services and changes detection services ensure near real-time data integration. Furthermore, the idea of integrating Web data actively and autonomously revolves around mining events logged by the data integration environment. Therefore, we propose an incremental XML-based algorithm for mining association rules from logged events. Then, we define active rules dynamically upon mined data to automate and reactivate integration tasks. Finally, as a proof of concept, we implement a framework prototype as a Web application using open-source tools.     

Fractional Order Nonlinear Bone Remodeling Dynamics Using the Supervised Neural Network

This study aims to solve the nonlinear fractional-order mathematical model (FOMM) by using the normal and dysregulated bone remodeling of the myeloma bone disease (MBD). For the more precise performance of the model, fractional-order derivatives have been used to solve the disease model numerically. The FOMM is preliminarily designed to focus on the critical interactions between bone resorption or osteoclasts (OC) and bone formation or osteoblasts (OB). The connections of OC and OB are represented by a nonlinear differential system based on the cellular components, which depict stable fluctuation in the usual bone case and unstable fluctuation through the MBD. Untreated myeloma causes by increasing the OC and reducing the osteoblasts, resulting in net bone waste the tumor growth. The solutions of the FOMM will be provided by using the stochastic framework based on the Levenberg-Marquardt backpropagation (LVMBP) neural networks (NN), i.e., LVMBPNN. The mathematical performances of three variations of the fractional-order derivative based on the nonlinear disease model using the LVMPNN. The static structural performances are 82% for investigation and 9% for both learning and certification. The performances of the LVMBPNN are authenticated by using the results of the Adams-Bashforth-Moulton mechanism. To accomplish the capability, steadiness, accuracy, and ability of the LVMBPNN, the performances of the error histograms (EHs), mean square error (MSE), recurrence, and state transitions (STs) will be provided.     

SIMS and RBS analysis of leached glass: Reliability of RSF method for SIMS quantification

The reliability of the relative sensitivity factor (RSF) approach for secondary ion mass spectrometry (SIMS) quantification of the leached layers on glass was investigated by measuring comparable samples of glass with SIMS and RBS (Rutherford backscattering spectrometry). The RSF factors were calculated using the nominal bulk compositions. Accurate results can be obtained only when the leached layer and the bulk glass have the same major elemental compositions (Si and O) and the matrix effect is inhibited. The concentrations of the different elements in the leached layer obtained from the comparable samples measured by SIMS and RBS are coincident within a factor of 2This paper is a part of a thesis submitted in partial fulfilment of the requirements for the PhD degree at the University of Technology of Vienna, 1991. The paper was orally presented in a symposium, Analysis of Working Materials, held in Vienna, 22–29 May 1991.