A complete VARMA modelling methodology based on scalar components

Abstract. This article proposes an extension to scalar component methodology for the identification and estimation of VARMA models. The complete methodology determines the exact positions of all free parameters in any VARMA model with a predetermined embedded scalar component structure. This leads to an exactly identified system of equations that is estimated using full information maximum likelihood.     

An efficient compressed domain video indexing method

Video indexing is employed to represent the features of video sequences. Motion vectors derived from compressed video are preferred for video indexing because they can be accessed by partial decoding; thus, they are used extensively in various video analysis and indexing applications. In this study, we introduce an efficient compressed domain video indexing method and implement it on the H.264/AVC coded videos. The video retrieval experimental evaluations indicate that the video retrieval based on the proposed indexing method outperforms motion vector based video retrieval in 74 % of queries with little increase in computation time. Furthermore, we compared our method with a pixel level video indexing method which employs both temporal and spatial features. Experimental evaluation results indicate that our method outperforms the pixel level method both in performance and speed. Hence considering the speed and precision characteristics of indexing methods, the proposed method is an efficient indexing method which can be used in various video indexing and retrieval applications.     

A new feature selection algorithm and composite neural network for electricity price forecasting

In a competitive electricity market, the forecasting of energy prices is an important activity for all the market participants either for developing bidding strategies or for making investment decisions. In this paper, a new forecast strategy is proposed for day ahead prediction of electricity price, which is a complex signal with nonlinear, volatile and time dependent behavior. Our forecast strategy includes a new two stage feature selection algorithm, a composite neural network (CNN) and a few auxiliary predictors. The feature selection algorithm has two filtering stages to remove irrelevant and redundant candidate inputs, respectively. This algorithm is based on mutual information (MI) criterion and selects the input variables of the CNN among a large set of candidate inputs. The CNN is composed of a few neural networks (NN) with a new data flow among its building blocks. The CNN is the forecast engine of the proposed strategy. A kind of cross-validation technique is also presented to fine-tune the adjustable parameters of the feature selection algorithm and CNN. Moreover, the proposed price forecast strategy is equipped with a few auxiliary predictors to enrich the candidate set of inputs of the forecast engine. The whole proposed strategy is examined on the PJM, Spanish and Californian electricity markets and compared with some of the most recent price forecast methods.     

Quantitative characterization of carrier injection across metal–organic interfaces using Bardeen theory

We have investigated the contact between a metal and an organic/polymeric (o/p) material and we have introduced a relation for carrier injection using Bardeen theory. A series of narrow barriers is considered in the semiconductor side to account for the localized nature of the carriers in the o/p material. As an application of the model, we have calculated the hopping rate of carriers in terms of the contact parameters. Also, we have discussed the hopping of carriers deep into the organic dielectric. Finally, we have explored the hopping rate in practical contacts between polyfluorene-based polymers and different electrodes.     

Thermosensitive folic acid-targeted poly (ethylene-<Emphasis Type="Italic">co</Emphasis>-vinyl alcohol) hemisuccinate polymeric nanoparticles for delivery of epirubicin to breast cancer cells

A novel thermosensitive folic acid (FA)-targeted succinylated poly (ethylene-co-vinyl alcohol) (EVOH) (EVOHS-FA) nanocarrier was synthesized for the specific delivery of epirubicin (EPI) to MCF-7 breast cancer cell line. Three different ratios of synthesized EVOH-Suc were reacted with FA. The structure of the desired products (EVOHS₄₀-FA, EVOHS₆₀-FA and EVOHS₈₀-FA) was confirmed by ¹H NMR and FTIR techniques. Nanoparticles were obtained by nano-precipitation procedure using DMSO/H₂O as solvent/anti-solvent. The particle size, zeta potential, entrapment efficacy and in vitro release profile of the final formulations in different temperatures were measured. The optimized nanoparticles had the particle size of 214 ± 8.5 nm, zeta potential of ?29.6 mV, PDI of 0.198 ± 0.04, and a high encapsulation efficiency that released the drug efficiently within 450 h at the temperature of 40 °C compared to 37 °C. The morphology of nanoparticles was studied by scanning electron microscopy. The in vitro cytotoxicity was evaluated using the MTT assay on MCF-7 cell lines in response to temperatures of 37 and 40 °C. The MTT assay indicated that the targeted nanoparticles carrying EPI were significantly more cytotoxic than the non-targeted nanoparticles and the free drug at 40 °C.     

Effects of cooling channel blockage on fuel plate temperature in Tehran Research Reactor

In this study, the variation of the temperature distribution of the fuel plate in Tehran Research Reactor core was studied in case of coolant channels blockage. While the experimental method is not possible, both the analytical and simulation methods were used to obtain the more reliable data. The results show that one channel blockage will increase the fuel temperature to about 100%, but it does not lead to clad melt down still. With further calculation and simulation it is understood that if the coolant velocity drops to 90% of its nominal value, it may causes the clad melt-ing down. At least two channels with complete blockage even at the positions far from the core center can also melt down the clad.     

Using 1H‐NMR spectroscopy for the kinetic study of the in situ solution free‐radical copolymerization of styrene and ethyl acrylate

The free‐radical copolymerization of styrene and ethyl acrylate in benzene‐d₆ as the solvent in the presence of benzoyl peroxide as an initiator at 70°C was studied by online ¹H‐NMR spectroscopy. The chemical composition of the copolymer at different reaction times was calculated from the conversion of the monomers to the copolymer, and then the reactivity ratios of styrene and ethyl acrylate were determined at both low and high conversions. Data for the overall monomer conversion versus the time were used to estimate the ratio k_pk_t^?0.5 for different compositions of the initial feed (k_p is the propagation rate constant, and k_t is the termination rate constant). k_pk increased with an increasing molar fraction of ethyl acrylate in the initial feed. The monomer mixture and copolymer compositions versus the overall monomer conversion were calculated with the data of ¹H‐NMR spectra. The incorporation of the styrene monomer into the copolymer structure was more favored than that of the ethyl acrylate monomer. Reducing the molar fraction of styrene in the initial feed intensified this. Drawing the molar fraction of styrene (or ethyl acrylate) in the copolymer chains versus that in the initial feed showed a tendency of the system toward random copolymerization. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007     

Synthesis and characterization of novel biodegradable water dispersed poly(ether-urethane)s and their MWCNT-AS nanocomposites functionalized with aspartic acid as dispersing agent

New biodegradable poly(ether-urethane)s (PEU)s were synthesized via the reaction of L-leucine anhydride cyclo-peptide, polyethylene glycol-1000 and hexamethylene diisocyanate. Then, they were end-functionalized with aspartic acid (AS) as a dispersing agent and were dispersed in water. MWCNTs were also functionalized by AS under microwave irradiation. Polymer/MWCNT-AS composites and polymer/MWCNT-AS water dispersed composites were prepared through an ultrasound-assisted method. We have designed these PEUs with two different structural architectures (PA1and PA2) which can be readily dispersed in water (PA1-D and PA2-D). The structure and properties of the polymers, MWCNTs-AS and PEUs/MWCNTs-AS composites were investigated by FTIR and NMR spectroscopy methods and FE-SEM, TEM and TGA techniques. The particle sizes of the resulting PA1-D and PA2-D dispersions were in the range of 200–300 nm. The results showed that by increasing MWCNT-AS loading, the degradation rate and particle sizes of the dispersed composites decreased, while thermal stability and dispersion stability of the composite systems increased. The degradation tests of polymers and their composites in PBS at 37 °C after 10 days showed weight losses ranging from 23 to 44 and 17–37%, respectively. The cytotoxicity study of polymers using the direct-contact test on L929 mouse fibroblast cell line showed no toxicity. Other properties such as thermal stability, dispersion’s particle size, degradation rate and morphology of the composites were studied, and the effect of simultaneous dispersion of MWCNTs-AS and PEUs in water on the properties of the resulting mixtures was studied. We suggest that these polymers have tunable properties which may potentially be considered for drug carriers’ studies.     

A new compression based approach for reconfiguration overhead reduction in virtex based RTR systems

The advantage of RTR systems usually comes with some costs. The required time to map some areas of a program to an FPGA is considerable and affects the performance of RTR systems. Several methods have been developed to speed up the configuration process in these systems. Configuration compression can reduce the total number of write operations to load a configuration and it has been proven to be an efficient technique for dealing with the configuration overhead. In this paper, we have developed a new approach for reconfiguration overhead reduction in Virtex Based RTR Systems by using a compression technique based on Lempel-Ziv (LZ) algorithm. Since the order of the sequence of configuration frames affects the compression rate, we have proposed an algorithm based on Genetic Algorithm for finding the optimal configuration sequence of frames. The proposed algorithm will be applied to the input configuration file in a batch (offline) manner, and its time complexity is tolerable considering the overhead reduction obtained by having the optimal sequence of frames in run-time configuration decompression. Also, corresponding to our approach, a hardware model has been designed for configuration decompression.     

Upper Limb Robot Mediated Stroke Therapy—GENTLE/s Approach

Stroke is a leading cause of disability in particular affecting older people. Although the causes of stroke are well known and it is possible to reduce these risks, there is still a need to improve rehabilitation techniques. Early studies in the literature suggest that early intensive therapies can enhance a patient's recovery. According to physiotherapy literature, attention and motivation are key factors for motor relearning following stroke. Machine mediated therapy offers the potential to improve the outcome of stroke patients engaged on rehabilitation for upper limb motor impairment. Haptic interfaces are a particular group of robots that are attractive due to their ability to safely interact with humans. They can enhance traditional therapy tools, provide therapy on demand and can present accurate objective measurements of a patient's progression. Our recent studies suggest the use of tele-presence and VR-based systems can potentially motivate patients to exercise for longer periods of time. The creation of human-like trajectories is essential for retraining upper limb movements of people that have lost manipulation functions following stroke. By coupling models for human arm movement with haptic interfaces and VR technology it is possible to create a new class of robot mediated neuro rehabilitation tools. This paper provides an overview on different approaches to robot mediated therapy and describes a system based on haptics and virtual reality visualisation techniques, where particular emphasis is given to different control strategies for interaction derived from minimum jerk theory and the aid of virtual and mixed reality based exercises.