Synthesis,Structural and Biomedical Characterization of Hydroxyapatite/Borosilicate Bioactive Glass Nanocomposites

Journal of Inorganic and Organometallic Polymers and Materials - In this work, a borosilicate glass sample (5SiO2–45B2O3–20Na2O–25CaO–5Ag2O) was added to nano-sized...     

Islam, Jihad, and Terrorism in Post-9/11 Arabic Discussion Boards

This study analyzed the contents of three of the most popular Arabic-language online message boards regarding the attacks of September 11, 2001 on the United States. Although terrorists claimed that the attacks were committed in the name of Islam, those who posted messages on all three forums rejected this claim. More than 43% of the messages condemned the attacks as a criminal act of terrorism that contradicts the core teachings of Islam. Some 30% saw some justification behind the attacks, even if they felt sorry for the victims and their families. However, those participants viewed the attacks as a political, rather than a religious, issue.     

QuePED: Revisiting queueing networks for the performance evaluation of database designs

Databases form the common component of many software systems. However, performance models specifically targeted at the database design have not been extensively studied. In this paper, we propose QuePED – a queueing network performance evaluation model for database designs. QuePED provides for the performance modelling of database design constructs, including active database rules; thus, deviating from current methods that consider database designs as processing demands on the hardware architecture. We present a formal specification of QuePED and describe its application to database designs. Experimental evaluation has shown the ability of QuePED to capture the steady state performance of an implementation of the TPC-C benchmark.     

Ear recognition with feed-forward artificial neural networks

Biometrics has become one of the most important techniques in recognizing a person’s identity. A person’s face, iris and fingerprint are mostly used in biometrics today. It has been established that there are no two ears exactly alike, even in the cases of identical twins. In this paper, we define a 7-element ear feature set and design and train a feed-forward artificial neural network to recognize a human ear. We train and test the network with 51 ear pictures from 51 different persons. Simulation experiments with various networks with various number of layers and number of neurons per layer and with and without noise are conducted. Results indicate that a 95 % ear recognition accuracy is achieved with a simple 3-layer feed-forward neural network with only a total of 18 neurons even in the presence of some noise. This design outstands previous work in simplicity and implementation cost.     

A novel deep learning neural network for fast-food image classification and prediction using modified loss function

Multimedia Tools and Applications - Accurate food image classification is often critical to accurately monitor the dietary assessment to reduce the risk of different heart-related diseases,...     

Study the Performance of the AC/DC Resistors During Their DC and AC Measurements

Some of traceability chains for the AC resistance measurements are based on AC/DC resistors. In this paper, performance of two types of them with different values has been investigated for their optimum utilization. Tinsley and Cambridge AC/DC resistors have been measured as DC resistors using different measurement methods and as AC resistors at various frequencies. DC direct method using digital reference multimeter is more accurate for the resistance values 1, 10, 100 Ω, and 1 kΩ. For the values 10 and 100 kΩ; measurement results are very near by using the DC direct and ratio methods. At 100 kΩ; representation of the resistance as an equivalent series resistance is not suitable at frequencies above 10 kHz, while for 100 mΩ and 1 Ω; the equivalent parallel representation is not suitable above the same frequency. The uncertainty analysis is also studied for all the obtained results.     

Stress analysis of multi-layer electronic and mechanical systems (MEMS) under fatigue and impact loading conditions

Detailed micro electronic and mechanical systems (MEMS) for a mobile microprocessor complex shape were modeled using Finite Element (FE) processing. Fatigue and impact conditions were performed on the Ball Grid Array (BGA) Integrated Circuit (IC) using Abaqus\CAE finite element analysis software. The main objective of this research is to make sure that BGA products can endure the roughness of the daily usage, where a portable electronic product is habitually coupled with potential damage of functional failure when the device falls.     

Brain-potential evidence for the time course of access to biographical facts and names of familiar persons.

On seeing familiar persons, biographical (semantic) information is typically retrieved faster and more accurately than name information. Serial stage models explain this pattern by suggesting that access to the name follows the retrieval of semantic information. in contrast, interactive activation and competition (IAC) models hold that both processes start together but name retrieval is slower because of structural peculiarities. With a 2-choice go/no-go procedure based on a semantic and a name-related classification, the authors tested differential predictions of the 2 alternative models for reaction times (RTs) and lateralized readiness potentials (LRP). Both LRP (Experiment 1) and RT (Experiment 2) results are in line with IAC models of face identification and naming. (PsycINFO Database Record (c) 2011 APA, all rights reserved)