A survey on video content rating: taxonomy,challenges and open issues

Multimedia Tools and Applications - Rating a video based on its content is one of the most important solutions to classify videos for audience age groups. In this regard, Film content rating and TV...     

Automatic navigation of mobile robots in unknown environments

Online navigation with known target and unknown obstacles is an interesting problem in mobile robotics. This article presents a technique based on utilization of neural networks and reinforcement learning to enable a mobile robot to learn constructed environments on its own. The robot learns to generate efficient navigation rules automatically without initial settings of rules by experts. This is regarded as the main contribution of this work compared to traditional fuzzy models based on notion of artificial potential fields. The ability for generalization of rules has also been examined. The initial results qualitatively confirmed the efficiency of the model. More experiments showed at least 32 % of improvement in path planning from the first till the third path planning trial in a sample environment. Analysis of the results, limitations, and recommendations is included for future work.     

Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system

Despite the proven advantages of sampling-based motion planning algorithms, their inability to handle online navigation tasks and providing low-cost solutions make them less efficient in practice. In this paper, a novel sampling-based algorithm is proposed which is able to plan in an unknown environment and provides solutions with lower cost in terms of path length, runtime and stability of the results. First, a fuzzy controller is designed which incorporates the heuristic rules of Tabu search to enable the planner for solving online navigation tasks. Then, an adaptive neuro-fuzzy inference system (ANFIS) is proposed such that it constructs and optimizes the fuzzy controller based on a set of given input/output data. Furthermore, a heuristic dataset generator is implemented to provide enough data for the ANFIS using a randomized procedure. The performance of the proposed algorithm is evaluated through simulation in different motion planning queries. Finally, the proposed planner is compared to some of the similar motion planning algorithms to support the claim of superiority of its performance.

     

Practical evaluation of relationship between concrete resistivity,water penetration,rapid chloride penetration and compressive strength

There are several factors and test methods for evaluating the durability of concrete. In recent years a great deal of attention has been paid to research and development of relationships of these parameters for production of sustainable concretes: water penetration and Rapid Chloride Penetration Test (RCPT) methods which are most commonly used to evaluate the permeability of concrete are two of the most famous methods specified by BS EN-12390-8:2000 and ASTM C1202 respectively. Concrete surface resistivity (SR) test is also a suitable indicator for concrete penetration and chloride ion permeability. It is a non-destructive, simple, rapid and economical method that can also be used on site.The present study is an exploratory research concerned with the relationship of these methods. Based on the correlation of concrete resistivity with water penetration and Rapid Chloride Penetration Test (RCPT) results, two new models for relating these parameters are presented.     

An unusual aural presentation of Pneumocystis carinii

One case of allergic contact dermatitis caused by polyvinyl chloride identification bands is reported. Patch tests in this case were positive for three of four bands tested, resorcinol monobenzoate, and benzoyl peroxide. Manufacturers could not confirm the presence of resorcinol monobenzoate and benzoyl peroxide in their respective bands. It is concluded that the patient's reaction was allergic and due to an unknown chemical(s) in the bands. Additives may comprise a significant portion of polyvinyl chloride bands. These components may be leachable, and thus lead to contact sensitization with subsequent allergy. Although patch testing is an excellent first step in determining the offending allergen, specialized chemical analysis may be required for exact identification.     

AN ALTERNATIVE APPROACH TO FCM ACTIVATION FOR MODELING DYNAMIC SYSTEMS

Recurrent neural models such as fuzzy cognitive maps (FCM) are well established in decision modeling through progressive variations of systems’ concepts. However, existing activation functions have shortcomings, such as a lack of sensitivity to weights of initial concepts, which is due to exaggerated focus on the training of networks’ causal links. Therefore, in most cases, decision outputs converge toward lower and higher extremes and do not represent gray scales. Another disadvantage is that current models require sufficient time delay for convergence toward results. This makes FCM unable to handle transient changes in input. A new technique has been examined in this article using a real-life example to improve FCM activation in terms of fast response to dynamic stimuli. A simple expert model of hexapod locomotion is developed without focus on weight training. The system's response to stimuli is evaluated through a complete six-phase stride to validate the effectiveness of the developed activation function.     

Three‐dimensional multiphase flow model to study channel flow dynamics of PEM fuel cells

A three‐dimensional multiphase flow model has been developed to study dynamics of a water droplet on the surface of the channel of proton exchange membrane fuel cell. Results are presented based on solving full Navier–Stokes equations for Newtonian liquids. The volume‐of‐fluid method is used to numerically determine the deformation of free surfaces. Water droplet and channel fluid properties determine whether the droplet deforms and remain stationary or disintegrate. We have shown the dependency of the water flooding to the flow rate and pressure drop in the channel has been introduced as a tool to determine water flooding in the channel. Copyright © 2010 John Wiley & Sons, Ltd.     

Control valve stiction detection using Markov transition field and deep convolutional neural network

Control valve stiction is an industrial problem that often causes oscillations in process control loops. Oscillating control loops are not capable of maintaining key process variables near or at their desired values, thus yielding low-quality products, inducing economic loss, and increasing environmental impacts. Therefore, it is of vital importance to detect stiction in industrial control valves. In this regard, the present work proposes a new method based on the Markov transition field and convolutional neural network (CNN) to identify sticky control valves in industrial control loops. The Markov transition field is employed to convert process variable (PV) and controller output (OP) into two-dimensional images, which are then utilized by CNN to learn to distinguish stiction induced oscillations from oscillations brought out by a non-stiction condition. A transfer learning strategy is adopted to improve the stiction detection capability of the proposed method. Its performance is evaluated via its application to benchmark control loops taken from the chemical, paper, mining, and metal industries. Results demonstrate that the proposed method obtains the correct verdict for the majority of the control loops studied.     

A numerical investigation of various phase change models on simulation of saturated film boiling heat transfer

There is a great variety of two‐phase models in numerical simulations. The performance of each model complicates the numerical simulation of boiling. The challenge of the right choice of heat and mass transfer models makes this type of problem more complicated. In this research work, the volume of the fluid two‐phase model has been used to simulate the film boiling of saturated liquid. The geo‐reconstruction method also reconstructs the interface of two phases. The models of the sharp interface, Lee and Tanasawa have been employed among the available models for calculating the phase change rate and the source terms of the equations. The Numerical solver of the phase‐change is verified through the Stefan one‐dimensional vaporizing problem. Correct empirical coefficients used in both Lee and Tanasawa models are presented. Bubble detachment time, flow pattern, the periodic Nusselt number, and the bubble form have been investigated in all three phase change models. Two Berenson and Klimenko experimental correlations have been used for verification of Nusselt number derived from simulations. The Nusselt number shows a proper fit with the Klimenko's Nusselt number. Obtained Nusselt number demonstrates the Lee model is more precise than other phase change models in simulating of film boiling on the flat plate.     

Reactive DC magnetron sputter deposited copper nitride nano-crystalline thin films: Growth and characterization

CuN_x thin films were grown by reactive DC magnetron sputtering and their structural, morphological, optical and electrical properties were evaluated. This study provides insight into the importance of substrate temperature and nitrogen content on the characteristic of CuN_x films. Phase analysis and structural properties of these films were identified by X-ray diffraction (XRD) technique. XRD results showed that the CuN_x films were single phase and polycrystalline with mixed orientation. Nitrogen excess accommodates in vacant interstitial sites of cubic anti-ReO₃ crystal structure of CuN_x and exhibits a solid solubility. The variation of surface morphology, studied by scanning electron microscope (SEM), shows suppression of the pyramidal-like grain growth by N richness. Optical study were performed by UV-Vis-near IR transmittance spectroscopy. Film thickness, refractive index and extinction coefficient were extracted from the measured transmittance using a reversed engineering method. Absorption coefficient and electrical resistivity indicate that the CuN_x films present extrinsic semiconducting behavior with an indirect optical band gap between 1.19 and 1.44 eV. To confirm the optical band gap energy, a first principle calculation was performed and compared with the measured data.