Preparation and characterization of poly(vinyl alcohol)/gum tragacanth/cellulose nanocomposite film

The effects of gum tragacanth obtained from two species of Astragalus Gossypinus (GT-G) and A. Parrowianus (GT-P) at two levels of 10% and 30% combined with cellulose nanofibers (CNF; 5%) on the physico-mechanical and structural properties of polyvinyl alcohol (PVA) nanocomposite film were investigated in this study. The water solubility and water vapor permeability of the films decreased with increasing the content of both gums, especially in the film containing 30% GT-P. The highest values of the tensile strength (39.3 MPa) and elongation at break (445%) belonged to the treatment containing 10% GT-P (90/10P/0). The FTIR and DSC analyses confirmed good interactions between GT and PVA in the 90/10P/0 treatment. SEM images indicated the dense structure of this film as the optimum treatment. Although the presence of CNF in the films containing GT-G improved some properties, especially the Young modulus, it impaired all the functional properties of nanocomposite GT-P film.     

Quantifying nonclassicality of correlations based on the concept of nondisruptive local state identification

A bipartite state is classical with respect to party A if and only if party A can perform nondisruptive local state identification (NDLID) by a projective measurement. Motivated by this we introduce a class of quantum correlation measures for an arbitrary bipartite state. The measures utilize the general Schatten p-norm to quantify the amount of departure from the necessary and sufficient condition of classicality of correlations provided by the concept of NDLID. We show that for the case of Hilbert–Schmidt norm, i.e., \(p=2\), a closed formula is available for an arbitrary bipartite state. The reliability of the proposed measures is checked from the information-theoretic perspective. Also, the monotonicity behavior of these measures under LOCC is exemplified. The results reveal that for the general pure bipartite states these measures have an upper bound which is an entanglement monotone in its own right. This enables us to introduce a new measure of entanglement, for a general bipartite state, by convex roof construction. Some examples and comparison with other quantum correlation measures are also provided.     

Using mobile node speed changes for movement direction change prediction in a realistic category of mobility models

In order to evaluate performance of protocols for ad hoc networks, the protocols have to be tested under realistic conditions. These conditions may include a reasonable transmission range, a limited buffer size, and realistic movement of mobile users (mobility models). In this paper, we propose a new and realistic type of random mobility models in which the mobile node has to decelerate to reach the point of direction change and accelerates with a defined acceleration to reach its intended speed. This realistic mobility model is proposed based on random mobility models. In reality, mobile objects tend to change their speed when they are going to change their direction, i.e. decelerate when approaching a direction change point and accelerate when they start their movement in a new direction. Therefore, in this paper, we implement this behavior in random mobility models which lack such specification. In fact, this paper represents our effort to use this accelerated movement to anticipate a probable direction change of a mobile node with reasonable confidence. The simulation type of this paper is based on traces produced by a mobility trace generator tool. We use a data mining concept called association rule mining to find any possible correlations between accelerated movement of mobile node and the probability that mobile node wants to change its direction. We calculate confidence and lift parameters for this matter, and simulate this mobility model based on random mobility models. These simulations show a meaningful correlation between occurrence of an accelerated movement and event of mobile node's direction change.     

Efficient iterative solutions to general coupled matrix equations

Linear matrix equations are encountered in many systems and control applications.In this paper,we consider the general coupled matrix equations（including the generalized coupled Sylvester matrix equations as a special case）l t=1EstYtFst = Gs,s = 1,2,···,l over the generalized reflexive matrix group（Y1,Y2,···,Yl）.We derive an efcient gradient-iterative（GI） algorithm for fnding the generalized reflexive solution group of the general coupled matrix equations.Convergence analysis indicates that the algorithm always converges to the generalized reflexive solution group for any initial generalized reflexive matrix group（Y1（1）,Y2（1）,···,Yl（1））.Finally,numerical results are presented to test and illustrate the performance of the algorithm in terms of convergence,accuracy as well as the efciency.     

Transparent autonomization in CORBA

Increasingly, software systems are constructed by integrating and composing multiple existing applications. The resulting complexity increases the need for self-management of the system. However, adding autonomic behavior to composite systems is difficult, especially when the constituent components are heterogeneous and they were not originally designed to support such interactions. Moreover, entangling the code for self-management with the code for the business logic of the original applications may actually increase the complexity of the systems, counter to the desired goal. In this paper, we address autonomization of composite systems that use CORBA, one of the first widely used middleware platforms introduced more than 17 years ago that is still commonly used in numerous systems. We propose a model, called Adaptive CORBA Template (ACT), that enables autonomic behavior to be added to CORBA applications automatically and transparently, that is, without requiring any modifications to the code implementing the business logic of the original applications. To do so, ACT uses “generic” interceptors, which are added to CORBA applications at startup time and enable autonomic behavior to be introduced later at runtime. We have developed ACT/J, a prototype of ACT in Java. We describe a case study in which ACT/J is used to introduce three types of autonomic behavior (self-healing, self-optimization, and self-configuration) to a distributed surveillance application.     

Particle Swarm Optimization for Sorted Adapted Gaussian Mixture Models

Recently, we introduced the sorted Gaussian mixture models (SGMMs) algorithm providing the means to tradeoff performance for operational speed and thus permitting the speed-up of GMM-based classification schemes. The performance of the SGMM algorithm depends on the proper choice of the sorting function, and the proper adjustment of its parameters. In the present work, we employ particle swarm optimization (PSO) and an appropriate fitness function to find the most advantageous parameters of the sorting function. We evaluate the practical significance of our approach on the text-independent speaker verification task utilizing the NIST 2002 speaker recognition evaluation (SRE) database while following the NIST SRE experimental protocol. The experimental results demonstrate a superior performance of the SGMM algorithm using PSO when compared to the original SGMM. For comprehensiveness we also compared these results with those from a baseline Gaussian mixture model-universal background model (GMM-UBM) system. The experimental results suggest that the performance loss due to speed-up is partially mitigated using PSO-derived weights in a sorted GMM-based scheme.     

Multidisciplinary design optimization of a small solid propellant launch vehicle using system sensitivity analysis

Multidisciplinary design optimization approaches have significant effects on aerospace vehicle design methodology. In designing next generation of space launch systems, MDO processes will face new and greater challenges. This study develops a system sensitivity analysis method to optimize multidisciplinary design of a two-stage small solid propellant launch vehicle. Suitable design variables, technological, and functional constraints are considered. Appropriate combinations of disciplines such as propulsion, weight, geometry, and trajectory simulation are used. A generalized sensitivity equation is developed and solved. These results are basis for optimization. Comparison of the developed approach with gradient optimization methods reveals that developed approach requires less computation time.     

Wide band resonant ultrasound spectroscopy of spheroidal modes for high accuracy estimation of Poisson coefficient of balls

An original inversion method specifically adapted to the estimation of Poisson coefficient of balls by using their resonance spectra is described. From the study of their elastic vibrations, it is possible to accurately characterize the balls. The proposed methodology can create both spheroidal modes in the balls and detect such vibrations over a large frequency range. Experimentally, by using both an ultrasonic probe for the emission (piezoelectric transducer) and a heterodyne optic probe for the reception (interferometer), it was possible to take spectroscopic measurements of spheroidal vibrations over a large frequency range (100 kHz-45 MHz) in a continuous regime. This method, which uses ratios between wave resonance frequencies, allows the Poisson coefficient to be determined independently of Young's modulus and the ball's radius and density. This has the advantage of providing highly accurate estimations of Poisson coefficient (+/-4.3 x 10(-4)) over a wide frequency range.     

Highly Efficient Quasi 2D Blue Perovskite Electroluminescence Leveraging a Dual Ligand Composition

Perovskite light-emitting diodes (PeLEDs) are advancing because of their superior external quantum efficiencies (EQEs) and color purity. Still, additional work is needed for blue PeLEDs to achieve the same benchmarks as the other visible colors. This study demonstrates an extremely efficient blue PeLED with a 488 nm peak emission, a maximum luminance of 8600 cd m⁻², and a maximum EQE of 12.2% by incorporating the double-sided ethane-1,2-diammonium bromide (EDBr₂) ligand salt along with the long-chain ligand methylphenylammonium chloride (MeCl). The EDBr₂ successfully improves the interaction between 2D perovskite layers by reducing the weak van der Waals interaction and creating a Dion–Jacobson (DJ) structure. Whereas the pristine sample (without EDBr₂) is inhibited by small stacking number (n) 2D phases with nonradiative recombination regions that diminish the PeLED performance, adding EDBr₂ successfully enables better energy transfer from small n phases to larger n phases. As evidenced by photoluminescence (PL), scanning electron microscopy (SEM), and atomic force microscopy (AFM) characterization, EDBr₂ improves the morphology by reduction of pinholes and passivation of defects, subsequently improving the efficiencies and operational lifetimes of quasi-2D blue PeLEDs.     

A Fuzzy Logic-Based Method for Replica Placement in the Peer to Peer Cloud Using an Optimization Algorithm

The Peer to Peer-Cloud (P2P-Cloud) is a suitable alternative to distributed cloud-based or peer-to-peer (P2P)-based content on a large scale. The P2P-Cloud is used in many applications such as IPTV, Video-On-Demand, and so on. In the P2P-Cloud network, overload is a common problem during overcrowds. If a node receives many requests simultaneously, the node may not be able to respond quickly to user requests, and this access latency in P2P-Cloud networks is a major problem for their users. The replication method in P2P-Cloud environments reduces the time to access and uses network bandwidth by making multiple data copies in diverse locations. The replication improves access to the information and increases the reliability of the system. The data replication's main problem is identifying the best possible placement of replica data nodes based on user requests for data access time and an NP-hard optimization problem. This paper proposes a new replica replacement to improve average access time and replica cost using fuzzy logic and Ant Colony Optimization algorithm. Ants can find the shortest path to discover the optimal node to place the duplicate file with the least access time latency. The fuzzy module evaluates the historical information of each node to analyze the pheromone value per iteration. The fuzzy membership function is also used to determine each node's degree based on the four characteristics. The simulation results showed that the access time and replica cost are improved compared to other replica replacement algorithms.