Effect of absorption layer on interior sound field of sonar dome

Using the finite element method (FEM) and boundary element method (BEM) and considering the sound absorption layer which is covered on the backing of the sonar dome, the interior field in the dome which is excited by the incident plane wave has been studied. This method is validated by comparing numerical results with that of classic elastic theory. Then the effect of parameters of the sound absorption layer on interior sound field has been analyzed. The numerical calculation results show that uniformity of interior sound pressure is improved when the backing is covered with a sound absorption layer. The thicker the layer is, or the higher the loss factor of layer is, the more uniform the sound field is.     

Analysis and enhancement of a watermarking protocol suitable for web context

AbstractA buyer-seller watermarking protocol is a combination of traditional watermarking and fingerprinting techniques. Recently, Frattolillo proposed such a watermarking protocol suitable for web context. Frattolillo’s scheme has two problems which would make it hard to implement practically. Several possible solutions to the two problems are presented in this paper.     

Opportunistic preventive maintenance optimization for multi-unit series systems with combing multi-preventive maintenance techniques

This paper proposes a dynamic opportunistic preventive maintenance (PM) optimization policy for multi-unit series systems by integrating multi PM techniques. Two PM techniques, periodic PM and sequential PM, are considered. Whenever one of the units reaches its reliability threshold, a PM action has to be performed on that unit. At that time the whole system has to be stopped and PM opportunities arise for the other units of the system. An optimal PM practice is determined by maximizing the short-term cumulative opportunistic maintenance (OM) cost savings for the whole system. Numerical examples are given to show how this approach works. Finally, a comparison between the proposed PM policy and the other policies is given.     

On the algorithms of adaptive neural network-based speed control of switched reluctance machines

AbstractA switched reluctance machine(SRM)drive is a time-varying,strongly nonlinear system.High performance control can no longer be achieved by using linear techniques.This paper describes the back-propagation (BP)neural network-based proportional-integral-derivative(PID)speed control of the SRM.It’s the interest of this paper to explore the utilization of the prior empirical knowledge as guidance in the initializing and training of the neural networks.The purpose is to make the networks less sensitive on the initial weights.Two modified algorithms are presented and simulation experiments show some interesting findings about their control effects and their corresponding sensitivity on the initial weights of the networks.     

3D Numerical simulation of non-isothermal resin transfer molding filling process using unstructured tetrahedron mesh

We present a numerical formulation for resin flow based on the concept of quasi-steady state situation at the flow front. To be fit for complicated product shapes, we use the four-node unstructured tetrahedron mesh based on which the numerical formulation of temperature and degree of cure is developed. The validity of our method is established in the case where flexible meshes are used. The results show that the numerical procedure, tested on known data, provides numerically valid and reasonably accurate predictions.     

Remaining Useful Life Prediction of Turbofan Engine Using Hybrid Model Based on Autoencoder and Bidirectional Long Short-Term Memory

High voltage electrostatics and corona discharge are utilized for various applications in pollution and environmental control. The traditional applications have many flaws due to improper construction of electrode design and assembly that cause system failure, in particular when electrically stimulated devices are exposed to high humidity. A new innovative-patented design by Hamade, electrically stimulated catalytic converter (ESCC), eliminates such flaws and shows the wide practical applications of the new design. The new design utilized previous patented designs and work of the same inventor but retrofitted for catalytic auto exhaust emission control. The current and previous patents include: employing electrically stimulated filtration (ESF) to replace high efficiency particulate air (HEPA) filters, treatment of biological and infectious diseases, electret fabrication, and, most notably, the invention of a new electrically stimulated catalytic converter (ESCC). The electrically stimulated catalytic converter invention includes an exhaust conduit fed from the engine exhaust port with a housed corona charger apparatus. The opposite end is opened to the atmosphere outside of the vehicle or connected to a reduced-size catalytic converter. The corona charger is intrusively or non-intrusively associated with a main flow path defined by the exhaust conduit. The corona charger includes at least one electrode, which may be recessed away from, the main flow path. A plurality of corona chargers may be used in various combinations, optimally a two dimensional grid. The electrically stimulated catalytic converter is adapted to treat and eliminate auto exhaust pollution emission to air.     

Intelligent Costume Recommendation System Based on Expert System

On the basis of expert system, we design a costume recommendation system which provides customers with clothing collocation solution and more experience. We set up a costume matching knowledge base collected from experts, and represent the knowledge with production rules. By analyzing the customers’ specific physical information got through man-machine interface, the proposed system provides customers an intelligent costume recommendation strategy in accordance with blackboard model reasoning. Moreover, index adding algorithm is integrated into the traditional serial blackboard model in the system. Finally, we present experiments which show the search rate is improved significantly.     

Impacts of CaO Solid Particles in Carbon Dioxide Absorption Process from Ship Emission with NaOH Solution

CO₂ emitted from ship exhaust is one of the major sources of atmospheric pollution. In order to reduce ship CO₂ emissions, this paper comes up with the idea of recovering CO₂ from ship exhaust by NaOH solution and improves the absorption rate by adding CaO solid particles. The effect mechanism of CaO solid particles on CO₂ absorption efficiency is analyzed in detail, and the mathematical model is deduced and the CaO enhancement factor is calculated through experiments. Experiment result demonstrates that the effect of CaO solid particles on the absorption of CO₂ in alkali solution is significant. The absorption rate of pure CO₂ gas, the simulated ship exhaust gas and 6135AZG marine diesel engine emission can be increased by 10%, 15.85% and 10.30%, respectively. So it can be seen that CaO solid particles play an important role in improving the absorption efficiency of ship CO₂ emission.     

E-Shop Transshipment Selection Evaluation Based on Cloud Model

In e-commerce, a critical problem is how to transship the products between different e-shops to lessen the risk of out of stock, especially in network shopping mall of China. Most of importance is how to select the optimal one in the waiting list of e-shops to make the transshipment economical. However, many factors that influence the effect of transshipment are uncertain and fuzzy, such as customer demand, product price and inventory level. Based on the cloud model theory, a novel method for evaluation of e-shop transshipment selection in the same network shopping mall is proposed to solve the problem. The factors that influence the transshipment effect are discussed in detail. An example of selecting the optimal e-shop to transship products to the out of stock e-shop is given on the basis of the steps of our evaluation calculation. Finally, the result shows that it can effectively optimize transshipment in online shopping economically.     

Advanced Fuzzy C-Means Algorithm Based on Local Density and Distance

This paper presents an advanced fuzzy C-means (FCM) clustering algorithm to overcome the weakness of the traditional FCM algorithm, including the instability of random selecting of initial center and the limitation of the data separation or the size of clusters. The advanced FCM algorithm combines the distance with density and improves the objective function so that the performance of the algorithm can be improved. The experimental results show that the proposed FCM algorithm requires fewer iterations yet provides higher accuracy than the traditional FCM algorithm. The advanced algorithm is applied to the influence of stars’ box-office data, and the classification accuracy of the first class stars achieves 92.625%.