Stochastic Models for Automatic Diacritics Generation of Arabic Names

In this paper, two new models for generating diacritics for Arabic names are proposed. The first proposed model is called N-gram model. It is a stochastic model that is based on generating a corpus database of N-grams extracted from a large database of names with their corresponding probability according to an N-gram position in a text (Bhal et al., 1983). i.e., the probability that an N-gram has happened in a position x, where x can be the first, second,... or ith position in the text. Replacing the N-grams with their patterns extends the first model to the second proposed stochastic model. It is called the Envelope model. These two proposed models are unique in being the first attempt to solve the problem in Arabic text diacritics generation using linguistic constraints stochastic approaches that are neither grammatical nor pure lexical based (Merialdo, 1991; Ney and Essen, 1991; Schukat-Talamazzini et al., 1992; Witschel and Niedermair, 1992). This methodology helps in reducing size and complexity of software implementation of the proposed models and makes it easier to update and port across different platforms.     

Identification of reflected, scaled, translated, and rotated objects from their radon projections

In this paper, we present a method for identification of binary objects from a given set of radon projections. Given a suitably regular 2-D function f, we form a new function g from f by using the operations of reflection, scaling, translation, and rotation. We show how the radon projections of g are related to those of f and devise a procedure that can be used to determine the parameters from the radon projections of f and g. We illustrate this process using a family of block images that include common 7 x 5 pixel representations for the letters A, B,....., Z.     

Dynamics of Choline-Containing Phospholipids in Traumatic Brain Injury and Associated Comorbidities

The incidences of traumatic brain injuries (TBIs) are increasing globally because of expanding population and increased dependencies on motorized vehicles and machines. This has resulted in increased socio-economic burden on the healthcare system, as TBIs are often associated with mental and physical morbidities with lifelong dependencies, and have severely limited therapeutic options. There is an emerging need to identify the molecular mechanisms orchestrating these injuries to life-long neurodegenerative disease and a therapeutic strategy to counter them. This review highlights the dynamics and role of choline-containing phospholipids during TBIs and how they can be used to evaluate the severity of injuries and later targeted to mitigate neuro-degradation, based on clinical and preclinical studies. Choline-based phospholipids are involved in maintaining the structural integrity of the neuronal/glial cell membranes and are simultaneously the essential component of various biochemical pathways, such as cholinergic neuronal transmission in the brain. Choline or its metabolite levels increase during acute and chronic phases of TBI because of excitotoxicity, ischemia and oxidative stress; this can serve as useful biomarker to predict the severity and prognosis of TBIs. Moreover, the effect of choline-replenishing agents as a post-TBI management strategy has been reviewed in clinical and preclinical studies. Overall, this review determines the theranostic potential of choline phospholipids and provides new insights in the management of TBI.     

Numerical simulation of the axial collapse of thin-walled polygonal section tubes

This paper deals with the post-buckling deformation characteristics of aluminum alloy extruded polygonal section tubes subjected to dynamic axial impacts. The explicit finite element code LS-DYNA is the primary analytical tool used in this investigation. The study focuses on investigating a post-buckling deformation phenomenon that is primarily manifested by an axial crumpling action that generates material folds as the impact energy is dissipated. The research is conducted in two phases. The first phase consists of validating the LS-DYNA model parameters and numerical results pertaining to thin-walled aluminum extruded square tubes with actual published experimental data. The post-buckling deformation characteristics of the specimens such as the overall final configuration and the various folding deformation modes (extensional, symmetric and asymmetric) resulting from the axial collapse of the member is also investigated in a subsequent phase. Based on the numerical simulation results, it is apparent that the increase in the number of walls (flanges) has a direct impact on the mean axial crushing force and permanent displacement parameters. In particular, the adoption of a hexagonal tube section as an axially loaded energy absorbing column yields an average increase of 11% in the mean axial crushing force and an average decrease of 10% in the permanent displacement. The greatest benefits are obtained in the specimens with the thinnest nominal wall thickness, where the upper bound results show an average increase of 27% in the mean axial crushing force and average decrease of 20% in the permanent displacement.     

The two-stage assembly flowshop scheduling problem with bicriteria of makespan and mean completion time

In this paper, we address the two-stage assembly flowshop scheduling problem with a weighted sum of makespan and mean completion time criteria, known as bicriteria. Since the problem is NP-hard, we propose heuristics to solve the problem. Specifically, we propose three heuristics; simulated annealing (SA), ant colony optimization (ACO), and self-adaptive differential evolution (SDE). We have conducted computational experiments to compare the performance of the proposed heuristics. It is statistically shown that both SA and SDE perform better than ACO. Moreover, the experiments reveal that SA, in general, performs better than SDE, while SA consumes less CPU time than both SDE and ACO. Therefore, SA is shown to be the best heuristic for the problem.     

Rheological and mechanical characterization of poly(lactic acid)/polypropylene polymer blends

Poly(lactic acid) (PLA) was melt blended with polypropylene (PP) with the aim of replacing commodity polymers in future applications. Since cost of PLA is quite high, it is not economically feasible to use it alone for day to day use as a packaging material without blending. This paper reports the preparation of poly(lactic acid)/polypropylene polymer blends (PLA/PP) using a laboratory scale single screw extruder. Rheological and mechanical properties of the prepared blends were determined. The rheological experiments were carried out on a capillary rheometer, the effect of shear rate, temperature and PLA content on the flow activation energy and true viscosity of the blends were described. Mechanical properties of the blends were investigated on dog bone-shaped samples obtained by injection molding; tensile tests were performed using Testometric M350-10KN. The effect of PLA content on Young’s modulus, strain at break and stress at break of the blends were described. The rheological results showed that the true viscosity of the blends is between that of the pure polymers, whereas the flow activation energy of the blends is less than that of the pure polymers. The mechanical results showed incompatibility between PLA and PP in the blend.     

Hybrid fault diagnosis for telerobotics system

Fault detection and isolation (FDI) of a class of networked control systems (NCS), applied for telerobotics system is studied in this paper. The considered NCS application is related to telerobotics system, where it is modelled with a hybrid manner, by including the continuous, discrete, uncertain, and stochastic aspects of all the system components. The main considered components of the NCS namely the network system and controlled system are completely decoupled according to their operation characteristics. The network part is taken as a discrete and stochastic system in presence of non-structured uncertainties and external faults, while the controlled part is considered as a continuous system in presence of input and output faults. Two model based fault diagnosis approaches are proposed in this paper. The first concerns a discrete and stochastic observer applied to the network system in order to detect and isolate system faults in presence of induced delay on the network part. The second is based on the analytical redundancy relations (ARR) allows detecting and isolating the input and output system’ faults. Experimental results applied on telerobotics system, show the performance and the limit of the proposed fault diagnosis approach.     

Preparation and studying properties of polybutene‐1/thermoplastic starch blends

Starch as an inexpensive and renewable source has been used as a filler for environmental friendly plastics for about two decades. In this study, glycerol was used as a plasticizer for starch to enhance the dispersion and the interfacial affinity in thermoplastic starch (TPS)/polybutene‐1(PB‐1) blend. PB‐1 was melt blended with TPS using a single screw extrusion process and molded using injection molding process to investigate the rheological and mechanical properties of these blends. Rheological properties were studied using a capillary rheometer, and the Bagley's correction was performed. Mechanical analysis (stress–strain curves) was performed using Testometric M350‐10 kN. The rheological properties showed that the melt viscosity of the blend is less than that of PB‐1, and the flow activation energy at a constant shear stress of the blend increases with increasing glycerol content in the blend. The mechanical experiments showed that both stress and strain at break of the blends are less than that of PB‐1, whereas the Young's modulus of the most blends is higher than that of PB‐1 which confirms the filling role of TPS in the blend. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012