Fault tolerant synchronization of chaotic heavy symmetric gyroscope systems versus external disturbances via Lyapunov rule-based fuzzy control

In this paper, fault tolerant synchronization of chaotic gyroscope systems versus external disturbances via Lyapunov rule-based fuzzy control is investigated. Taking the general nature of faults in the slave system into account, a new synchronization scheme, namely, fault tolerant synchronization, is proposed, by which the synchronization can be achieved no matter whether the faults and disturbances occur or not. By making use of a slave observer and a Lyapunov rule-based fuzzy control, fault tolerant synchronization can be achieved. Two techniques are considered as control methods: classic Lyapunov-based control and Lyapunov rule-based fuzzy control. On the basis of Lyapunov stability theory and fuzzy rules, the nonlinear controller and some generic sufficient conditions for global asymptotic synchronization are obtained. The fuzzy rules are directly constructed subject to a common Lyapunov function such that the error dynamics of two identical chaotic motions of symmetric gyros satisfy stability in the Lyapunov sense. Two proposed methods are compared. The Lyapunov rule-based fuzzy control can compensate for the actuator faults and disturbances occurring in the slave system. Numerical simulation results demonstrate the validity and feasibility of the proposed method for fault tolerant synchronization.     

A new hybrid denoising model based on PDEs

In this paper, a novel denoising algorithm based on the denoising methods of partial differential equations is presented. The proposed algorithm is obtained by using a stochastic algorithm for combining two denoising methods based on partial differential equations. The model provides a new approach for solving the contradiction in the image restoration. The new hybrid model has more ability to restore the image in terms of peak signal to noise ratio, blind/referenceless image spatial quality evaluator and visual quality, compared with each of denoising methods separately used. Experimental results show that our approach is more efficient in image denoising than the used denoising methods.     

Query expansion using pseudo relevance feedback on wikipedia

One of the major challenges in Web search pertains to the correct interpretation of users’ intent. Query Expansion is one of the well-known approaches for determining the intent of the user by addressing the vocabulary mismatch problem. A limitation of the current query expansion approaches is that the relations between the query terms and the expanded terms is limited. In this paper, we capture users’ intent through query expansion. We build on earlier work in the area by adopting a pseudo-relevance feedback approach; however, we advance the state of the art by proposing an approach for feature learning within the process of query expansion. In our work, we specifically consider the Wikipedia corpus as the feedback collection space and identify the best features within this context for term selection in two supervised and unsupervised models. We compare our work with state of the art query expansion techniques, the results of which show promising robustness and improved precision.     

A procedure with stepsize control for solving n one-dimensional IVPs

Finite precision computations may affect the stability of algorithms and the accuracy of computed solutions. In this paper we first obtain a relation for computing the number of common significant digits between the exact solution and a computed solution of a one-dimensional initial-value problem obtained by using a single-step or multi-step method. In fact, by using the approximate solutions obtained with stepsizes h and h /2, the number of common significant digits between approximate solution with stepsize h and exact solution is estimated. Then by using the stochastic arithmetic, the CESTAC method, and the CADNA library we propose an algorithm to control the round-off error effect on the computed solution. This method can easily apply to a system of n one-dimensional initial-value problems. Finally some numerical examples are given to show the efficiency of the method.     

Dynamic decision models for staged software product line configuration

Software product line engineering practices offer desirable characteristics such as rapid product development, reduced time-to-market, and more affordable development costs as a result of systematic representation of the variabilities of a domain of discourse that leads to methodical reuse of software assets. The development lifecycle of a product line consists of two main phases: domain engineering, which deals with the understanding and formally modeling of the target domain, and application engineering that is concerned with the configuration of a product line into one concrete product based on the preferences and requirements of the stakeholders. The work presented in this paper focuses on the application engineering phase and builds both the theoretical and technological tools to assist the stakeholders in (a) understanding the complex interactions of the features of a product line; (b) eliciting the utility of each feature for the stakeholders and hence exposing the stakeholders’ otherwise implicit preferences in a way that they can more easily make decisions; and (c) dynamically building a decision model through interaction with the stakeholders and by considering the structural characteristics of software product line feature models, which will guide the stakeholders through the product configuration process. Initial exploratory empirical experiments that we have performed show that our proposed approach for helping stakeholders understand their feature preferences and its associated staged feature model configuration process is able to positively impact the quality of the end results of the application engineering process within the context of the limited number of participants. In addition, it has been observed that the offered tooling support is able to ease the staged feature model configuration process.     

Development of cloud point extraction for simultaneous extraction and determination of gold and palladium using ICP-OES

Cloud point method was applied for the simultaneous extraction and preconcentration of trace amounts of gold and palladium. The extraction of analytes was performed in the presence of 1,8-diamino-4,5-dihydroxy anthraquinone as chelating agent and Triton X-114 as a non-ionic surfactant. After phase separation, the surfactant-rich phase was diluted with concentrated HNO(3) (65%, w/w) and the analytes concentrations were determined by inductively coupled plasma-optical emission spectrometry (ICP-OES). The variables affecting the complexation and extraction conditions were optimized and under the optimum conditions (i.e. pH 6.5, 2.2 x 10(-4) mol l(-1) chelating agent, 0.15% (w/v) of Triton X-114, equilibration temperature 55 degrees C, centrifuge at 3500 rpm), quantitative extraction of Au(III) and Pd(II) from 100 ml of the aqueous solution was performed. The calibration curves were linear in the range of 0.5-1000 microg l(-1) with detection limits of 0.5 and 0.3 microg l(-1) and the enrichment factors were 8.6 and 20.2 for Au and Pd, respectively. Also the precision (%RSD) for eight replicate determinations of the analytes was better than 5%. Finally, the proposed method was successfully applied for the determination of Au and Pd in mine stones and standard reference materials (SRM).     

Impregnated of C6CoFeN6 nanoparticles in poly-1-naphthol for uptake of Cs(I) from aqueous waste

To carry out our research, C₆CoFeN₆@poly-1-naphthol nanoparticles were synthesized and characterized by SEM, X-ray diffraction, Fourier transform infrared, thermogravimetric analysis and Brunauer–Emmett–Teller (BET) analyses. The SEM images indicate that the average particle sizes are about 60 nm in diameter. The BET result provides a clear evidence for the high surface area of the sample 180.6 m²/g. Cs(I) ions removed from the aqueous solution in a batch mode using CoHCF@poly-1-nanphtol as an adsorbent. The adsorption effecting parameters such as the solution pH, initial Cs(I) concentration, contact time and temperature were studied. Maximum sorption capacity for the nanocomposite was found to be 200.5 mg/g at 1000 mg/g, pH = 5 and 298 K. The time-adsorption dependence studies indicated that the maximum Cs(I) uptake was within the initial 40 min contact time and the adsorption mechanism was governed by the double exponential model. The equilibrium sorption data fitted well to the Freudlich model with n ? 1 indicating a stronger interaction and high affinity of C₆CoFeN₆@poly-1-naphthol for Cs(I) ions. The thermodynamic parameters, including changes in Gibbs free energy, entropy and enthalpy, were determined. The results indicated that CoHCF–poly-1-nanphtol could be a potential adsorbent for the uptake of Cs(I) ions from an aqueous solution.     

Fusion Rules Effects on Lifetime Maximization of Multi-channel Cooperative Spectrum Sensing

Cooperative spectrum sensing (CSS) is an efficient method to detect the reliability of the free spectrum, however, with great overhead and energy consumption. In this paper, we study a much broader application of CSS, where the sensors are used to sense multiple channels. On the one hand, since the tiny and low-cost sensors do not have high-speed analog-to-digital-convertors, they cannot simultaneously sense more than one channel. Therefore, the simultaneous multi-channel CSS is an important issue in a cognitive sensor network (CSN). On the other hand, these tiny sensors do not have high-power batteries, which makes the network lifetime as an important metric. In this paper, node selection is proposed for the multi-channel CSS to maximize the lifetime of a CSN under some detection constraints with lower overhead than cooperative sensing by all the sensors simultaneously. We analyze the problem for the OR and the AND rules, which can be implemented at the fusion center. The problem is solved by using convex optimization methods where assignment indices for every sensor are assumed. We provide a performance analysis through simulations using MATLAB, which shows that the sensor selection scheme provides a significant long lifetime for a CSN compared to the case where sensors are selected randomly and where all sensors are just classified to sense the channels simultaneously.

     

Introduction of a Novel Hybrid Weighted Exponential Logarithm-Maximum Throughput (HWEL-MT) Scheduler for QoS Improvement of LTE/4G Cellular Networks

The real-time broadcast of multimedia contents such as VoIP and video traffics in recent cellular networks is increasingly becoming common. In this regard, LTE networks with the objective of providing high speed data along with QoS assurance have been introduced. To perform this, schedulers in order to allocate of the resources to the traffics are used as channel-aware/QoS-aware. The most important and effective schedulers are EXP RULE and E2M RULE for this type of networks but still requires improving of QoS parameters to reach an optimal level of performance. In this paper aims to improve the packet loss rate (PLR), latency and throughput parameters especially and improve the other QoS parameters generally in the downlink LTE networks, a new scheduler called Hybrid Weighted Exponential Logarithm-Maximum Throughput (HWEL-MT) RULE method has been proposed. By performing simulations and comparisons between output results of EXP-Rule, E2M RULE and HWEL-MT RULE schedulers for VoIP, video and best effort traffics, we have totally concluded that the proposed HWEL-MT scheduler is able to improve PLR, delay, throughput, fairness and spectral efficiency more than two other examined methods. The results have been presented and compared by implementing a LTE network included 5–70 mobile users in open source LTE-Sim software.