Molecular weight distributions and size fractionations of H-coal liquids

This Paper deals with a comparative study on the use of gel permeation chromatography (g.p.c.) and vapour pressure osmometry (v.p.o.) to obtain molecular weight data for the hexane-soluble fractions of three H-coal liquids. The use of two types of column packing materials, polyvinylacetate and styrene-divinylbenzene copolymer gels, is described. A successful, preparative use of the polyvinylacetate gel to fractionate the hexane-soluble fraction of H-coal liquid, atmospheric still overhead (ASO), has been established. Molecular weight data obtained by v.p.o. for the benzene-soluble fraction and the pyridine-soluble fraction of the three H-coal liquids are reported. Solvent extraction has been utilized also to find the amount of oil, asphaltenes and asphaltols in the three H-coal liquids.     

Cure kinetics of an epoxy/liquid aromatic diamine modified with poly(ether imide)

The cure kinetics and mechanisms of an epoxy oligomer based on diglycidyl ether of bisphenol A (DGEBA), polymerized with a liquid aromatic diamine based on diethyl toluene diamine (DETDA 80), and its blends with poly(ether imide) (PEI) at concentrations of 0–15 wt % were studied with differential scanning calorimetry under dynamic and isothermal conditions. The kinetic analyses were performed with a phenomenological approach. The reaction mechanism of the blends remained the same as that of the neat epoxy. However, the addition of PEI had a marked effect on the cure kinetics in the DGEBA/DETDA 80 system. The rate of reaction decreased with an increase in the thermoplastic content. Diffusion control was incorporated to describe the cure behavior of the blends in the latter stages. Greater diffusion control was observed as the PEI concentration increased and the cure temperature decreased. Polymer blends based on this epoxy/liquid aromatic diamine had not been previously studied from a kinetic viewpoint. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 96: 660–672, 2005     

Preparation,characterization and in vitro drug release properties of polytrimethylene carbonate/polyadipic anhydride blend microspheres

Polyadipic anhydride (PAA), an aliphatic polyanhydride, and polytrimethylene carbonate (PTMC), an aliphatic polycarbonate, were synthesized via ring opening polymerization of oxepan‐2,7‐dione and melt‐condensation of trimethylene carbonate (1,3 dioxan‐2‐one), respectively. PTMC–PAA blend microspheres containing different ratios of buprenorphine HCl (2, 5, and 10%) were prepared by an oil‐in‐oil emulsion solvent removal method. Microspheres with different ratios of PTMC–PAA (85/15, 70/30, and 55/45) containing 5% buprenorphine HCl were prepared. Microspheres were spherical with visible cracks and pores on the surface. The average particle size of microspheres was around 200 μm for all microspheres. Drug loading efficiency of PTMC–PAA microspheres (85/15, 70/30, and 55/45) was 97.2, 95.2, and 70.2%, respectively. With the increase in the PTMC ratio, the melting point and the enthalpy of melting were both decreased. The mechanism for drug release from PTMC–PAA blend microspheres were generally a combination of drug diffusion through polymers and biodegradation of the polymers. In first three days, the release from microspheres followed zero order kinetics and was dependent on the PAA content. After three days the drug release from microspheres followed first order kinetics. In conclusion it was demonstrated that buprenorphine HCl release from microspheres could be successfully controlled by using different ratios of PTMC–PAA blends. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 2377–2383, 2006     

A secure and improved multi server authentication protocol using fuzzy commitment

Multimedia Tools and Applications - The advancement in communication and computation technologies has paved a way for connecting large number of heterogeneous devices to offer specified services....     

Recognizing arabic handwritten characters using deep learning and genetic algorithms

Automated techniques for Arabic content recognition are at a beginning period contrasted with their partners for the Latin and Chinese contents recognition. There is a bulk of handwritten Arabic archives available in libraries, data centers, historical centers, and workplaces. Digitization of these documents facilitates (1) to preserve and transfer the country’s history electronically, (2) to save the physical storage space, (3) to proper handling of the documents, and (4) to enhance the retrieval of information through the Internet and other mediums. Arabic handwritten character recognition (AHCR) systems face several challenges including the unlimited variations in human handwriting and the leakage of large and public databases. In the current study, the segmentation and recognition phases are addressed. The text segmentation challenges and a set of solutions for each challenge are presented. The convolutional neural network (CNN), deep learning approach, is used in the recognition phase. The usage of CNN leads to significant improvements across different machine learning classification algorithms. It facilitates the automatic feature extraction of images. 14 different native CNN architectures are proposed after a set of try-and-error trials. They are trained and tested on the HMBD database that contains 54,115 of the handwritten Arabic characters. Experiments are performed on the native CNN architectures and the best-reported testing accuracy is 91.96%. A transfer learning (TF) and genetic algorithm (GA) approach named “HMB-AHCR-DLGA” is suggested to optimize the training parameters and hyperparameters in the recognition phase. The pre-trained CNN models (VGG16, VGG19, and MobileNetV2) are used in the later approach. Five optimization experiments are performed and the best combinations are reported. The highest reported testing accuracy is 92.88%.

     

Effect of expandable graphite and ammonium polyphosphate on the thermal degradation and weathering of intumescent fire-retardant coating

This research aims to study the effect of ammonium polyphosphate and expandable graphite on the intumescent coating formulations (ICF). The coating presented in this research article is based on carbon source expandable graphite (EG), blowing agent melamine, acid source ammonium polyphosphate (APP), epoxy resin as a binder with polyamide amine. The stability of the developed coating was verified at 950°C for 1-hour fire test. The results showed that the coating is stable and well bond with the steel substrate. The char was characterized by using FESEM, XRD, FTIR, DTA, TGA, XPS, Py-GCMS and Weathering Test. The morphology of the char was studied by SEM of the coating after furnace fire test. XRD and FTIR show the presence of graphite, borophosphate; boron oxide and sassolite in the residual char. TGA and DTG disclosed that EG improved the residual mass of coating. XPS analysis showed the char residue of IF5-APP-EG contains carbon and oxygen contents 47.50 and 40.70, respectively. Py-GCMS analysis described that the IF5-APP-EG released less gaseous compounds. The weathering test illustrated that's the char expansion of coatings samples was decreased due to the presence of a humid environment and UV light. The IF5-APP-EG showed the maximum char expansion, lower substrate temperature and high residual weight among the studied formulations.     

Crack growth angle prediction of an internal crack under mixed mode load for unfilled elastomer using the strain energy density factor

This article investigates the prediction of the crack growth angle of an existing internal crack under mixed mode loading at the crack tip for an unfilled ethylene propylene diene terpolymer rubber (EPDM). For the realization of mixed mode loading, the cracks of the uniaxial loaded specimens were oriented with different angles to the loading direction. The energy density factor was used as a potential criterion for determining the crack growth angle. The determination of the strain energy density factor was carried out simulatively in Abaqus. The second-order Ogden model was used to describe the rubber-like material behavior. The relative local minimum of the strain energy density factor provides the possible growth angle. The experimental investigations show that the initial cracks grow orthogonally to the loading direction for the different crack orientation angles. For the crack orientation angle parallel to the load direction, the crack growth was observed because the strong stretching of the specimen caused strong necking in the crack region. The crack growth for the remaining crack orientation angles were induced due to shear loading at the crack tip. The predictive angle of different crack orientation angles shows very good accordance to the measured crack growth angles.     

Plasticizing effect of biodegradable dipropylene glycol bibenzoate and epoxidized linseed oil on diglycidyl ether of bisphenol A based epoxy resin

Major limitation for use of epoxy thermosets in engineering applications is its sudden brittle failure. In the present study dipropylene glycol dibenzoate (DPGDB) based plasticizer is used to modify diglycidyl ether of bisphenol A (DEGEBA) based epoxy resin system via simple blending technique. Bio-based epoxidized linseed oil was also used to modify epoxy resin system and compared with DPGDB modified resin. For DPGDB modified resin storage modulus and loss modulus of the epoxy system modified with 10% plasticizer increased by 7.54% and 12.24%, respectively. The primary mechanism responsible for such behavior is improved crosslinking density. With 5% plasticizer loading, flexural strength increased by 21%. There was an improvement of 312.74% in strain at failure for 10% plasticizer loading, while preserving its mechanical strength. It was found that DPGDB based modification was better than epoxidized linseed oil modification.     

Semantic indexing of Arabic texts for information retrieval system

As part of information retrieval systems (IRS) and in the context of the use of ontologies for documents and queries indexing, we propose and evaluate in this paper the contribution of this approach applied to Arabic texts. To do this we indexed a corpus of Arabic text using Arabic WordNet. The disambiguation of words was performed by applying the Lesk algorithm. The results obtained by our experiment allowed us to deduct the contribution of this approach in IRS for Arabic texts.     

Constrained model predictive control for time-varying delay systems: Application to an active car suspension

This study investigates the problem of robust model predictive control (RMPC) for active suspension systems with time-varying delays and input constraints. The uncertainty is of convex polytopic type. Based on the Lyapunov-Krasovskii functional method, sufficient stability conditions of the time-varying delays systems are derived by linear matrix inequalities (LMIs) terms. At each time set, a feasible state feedback is obtained by minimizing an upper bound of the ‘worst-case’ quadratic objective function over an infinite horizon subject to constraints on inputs. Finally, a quarter-vehicle model is exploited to demonstrate the effectiveness of the proposed method.