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.

     

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.     

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.     

Developing a Scaling Equation as a Function of Pressure and Temperature to Determine the Amount of Asphaltene Precipitation

A simple and applicable scaling equation as a function of pressure, temperature, molecular weight, dilution ratio (solvent), and weight percent of precipitated asphaltene has been developed. This equation can be used to determine the weight percent of precipitated asphaltene in the presence of difference precipitants (solvents) and the amount of solvent at onset point. Since increasing the pressure of crude oil decreases the amount of asphaltene precipitation, the effect of reservoir pressure has been taken into account in developing this equation. The results obtained by using this equation are substantially different and more accurate from other developed scaling equations for asphaltene precipitation. By considering the effect of reservoir pressure in developing the scaling equation and application of a genetic algorithm, the unknown parameters of the scaling equation are simultaneously and without any reservation obtained. The most important application of this unique equation is in the determination of critical point of asphaltene precipitation, known as onset point, and asphaltene precipitation in gas injection operations for enhanced oil recovery. The results predicted using the scaling equations are compared with the authors' experimental and literature precipitation data and it is shown that they are in good agreement with our experimental data. The scaling equation can be used in the design of gas-injected reservoir to prevent precipitation of the asphaltene aggregates in the reservoir.     

Modification of rheological and filtration characteristics of water‐based mud for drilling oil and gas wells using green SiO2 @ZnO@Xanthan nanocomposite

In this study, a green, simple and economical approach was used to synthesise the SiO₂ @ZnO@Xanthan nanocomposite (NC) to modify the rheological and filtration characteristics of the water‐based drilling mud. The green synthesised NCs were identified using scanning electron microscopy, energy dispersive X‐ray spectroscopy, elemental mapping, X‐ray diffraction and UV–Vis analytical techniques. Additionally, the effect of SiO₂ @ZnO@Xanthan NCs on the filtration and rheological properties of mud including apparent viscosity, plastic viscosity, yield point, gel strength, mud cake and fluid loss was investigated. The obtained results confirmed that the synthesised NCs effectively improved the rheological properties of drilling mud, and considerably decreased its fluid loss and filter cake by about 54 and 92.5%, respectively. The results highly recommend the SiO₂ @ZnO@Xanthan NC as an excellent additive to improve the rheological properties, and reduce the fluid loss and the filter cake of the drilling mud.Inspec keywords: X‐ray diffraction, scanning electron microscopy, nanofabrication, additives, nanocomposites, X‐ray chemical analysis, drilling (geotechnical), yield point, rheology, filtration, industrial economics, silicon compounds, zinc compounds, ultraviolet spectra, visible spectra, nanofluidics, gelsOther keywords: rheological properties, fluid loss, drilling mud, filtration characteristics, water‐based mud, green approach, economical approach, X‐ray spectroscopy, mud cake, apparent viscosity, oil‐gas wells, nanocomposite synthesis, scanning electron microscopy, energy dispersive X‐ray spectroscopy, elemental mapping, X‐ray diffraction, Uv–Vis spectroscopy, plastic viscosity, yield point, gel strength, additive, SiO₂ , ZnO