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.     

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...     

Rapid Determination of Free Fatty Acid in Extra Virgin Olive Oil by Raman Spectroscopy and Multivariate Analysis

We introduce a visible Raman spectroscopic method for determining the free fatty acid (FFA) content of extra virgin olive oil with the aid of multivariate analysis. Oleic acid was used to increase the FFA content in extra virgin olive oil up to 0.80% in order to extend the calibration span. For calibration purposes, titration was carried out to determine the concentration of FFA for the investigated oil samples. As calibration model for the FFA content (FFA%), a partial least squares (PLS) regression was applied. The accuracy of the Raman calibration model was estimated using the root mean square error (RMSE) of calibration and validation and the correlation coefficient (R ²) between actual and predicted values. The calibration curve of actual FFA% obtained by titration versus predicted values based on Raman spectra was established for different spectral regions. The spectral window (945–1600 cm⁻¹), which includes carotenoid bands, was found to be a useful fingerprint region being statistically significant for the prediction of the FFA%. High R ² and small RMSE values for calibration and validation could be obtained, respectively.     

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.     

Ultra-high performance concrete and fiber reinforced concrete: achieving strength and ductility without heat curing

Ultra-high performance concrete (UHPC) and ultra-high performance fiber reinforced concrete (UHP-FRC) were introduced in the mid 1990s. Special treatment, such as heat curing, pressure and/or extensive vibration, is often required in order to achieve compressive strengths in excess of 150 MPa (22 ksi). This study focuses on the development of UHP-FRCs without any special treatment and utilizing materials that are commercially available on the US market. Enhanced performance was accomplished by optimizing the packing density of the cementitious matrix, using very high strength steel fibers, tailoring the geometry of the fibers and optimizing the matrix-fiber interface properties. It is shown that addition of 1.5% deformed fibers by volume results in a direct tensile strength of 13 MPa, which is 60% higher than comparable UHP-FRC with smooth steel fibers, and a tensile strain at peak stress of 0.6%, which is about three times that for UHP-FRC with smooth fibers. Compressive strength up to 292 MPa (42 ksi), tensile strength up to 37 MPa (5.4 ksi) and strain at peak stress up to 1.1% were also attained 28 days after casting by using up to 8% volume fraction of high strength steel fibers and infiltrating them with the UHPC matrix.     

Hybrid wavelet measurement matrices for improving compressive imaging

Compressive sensing principle claims that a compressible signal can be recovered from a small number of random linear measurements. However, the design of efficient measurement basis in compressive imaging remains as a challenging problem. In this paper, a new set of hybrid wavelet measurement matrices is proposed to improve the quality of the compressive imaging, increase the compression ratio and reduce the processing time. The performance of these hybrid wavelet matrices for image modeling and reconstruction is evaluated and compared with other traditional measurement matrices such as the random measurement matrices, Walsh and DCT matrices. The compressive imaging approach chosen in this study is the block compressive sensing with smoothed projected Landweber reconstruction technique. The simulation results indicate that the imaging performance of the proposed hybrid wavelet measurement matrices is approximately 2–3 dB better than that obtained using Gaussian matrix especially at higher compression ratios.     

Evaluation of Augmented Reality for Rapid Assessment of Earthquake-Induced Building Damage

This paper discusses the feasibility of using augmented reality (AR) to evaluate earthquake-induced building damage. In the proposed approach, previously stored building information is superimposed onto a real structure in AR. Structural damage can then be quantified by measuring and interpreting key differences between the real and augmented views of the facility. Proof-of-concept experiments were performed in conjunction with large-scale cyclic shear wall tests. In these, CAD images of the walls were superimposed onto the wall specimens. Then, as the wall specimens were deformed under applied loading, the horizontal drifts between the walls and the augmented images were computed using two different techniques and compared with actual wall drifts. The obtained results highlight the potential of using AR for rapid damage detection and indicate that the accuracy of structural displacements measured using AR is a direct function of the accuracy with which augmented images can be registered with the real world. The limitations of the technology, considerations for field implementation, and the potential for other related applications of AR are also discussed.     

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.