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.     

Fabrication of a novel latex-based membrane for oily wastewater filtration: effect of degassing on the properties of membrane

Iranian Polymer Journal - Nitrile butadiene rubber latex/graphene oxide (NBR/GO) membranes were fabricated by latex compounding and curing method. This was a new method to produce membrane, thus,...     

The thermal conductivity of oils sands

Measurements have been made of the effective thermal conductivity of some samples of Athabasca oil sands using a steady state method over the temperature range 20°C – 120°C. The bitumen content of the samples was altered from its natural value by mixing with additional sand and the resulting values of the thermal conductivity were found to increase with increasing the oil content. Moreover, the effective thermal conductivity values were found to decrease with increasing temperature.     

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.     

A tabu search with an oscillation strategy for the discriminant analysis problem

This article proposes a tabu search approach to solve a mathematical programming formulation of the linear classification problem, which consists of determining an hyperplane that separates two groups of points as well as possible in ?^m. The tabu search approach proposed is based on a non-standard formulation using linear system infeasibility. The search space is the set of bases defined on the matrix that describes the linear system. The moves are performed by pivoting on a specified row and column. On real machine learning databases, our approach compares favorably with implementations based on parametric programming and irreducible infeasible constraint sets. Additional computational results for randomly generated instances confirm that our method provides a suitable alternative to the mixed integer programming formulation that is solved by a commercial code when the number of attributes m increases.     

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,...