Region-based surveillance video retrieval with effective object representation

Retrieving the most relevant video frames that contain the object specified in a given query (query-by-region) remains a challenging task. Two common challenges of region-based retrieval approaches are to accurately extract or segment object(s) and select a proper matching strategy. This paper addresses these problems by proposing a retrieval approach that uses a new region-based matching technique equipped with an effective object representation method. In the first stage, the proposed approach selects the most informative instances of each object that appeared in the video by utilizing an adapted clustering algorithm over the extracted features. In the retrieval stage, the new matching technique returns the most relevant sequences of video by mapping a given region with those identified representative instances of objects based on their similarity scores. The proposed approach is evaluated on standard datasets and the results demonstrate a 31% improvement in the retrieval performance compared to other state-of-the-art methods.     

Constellation constrained multiuser multiple‐input multiple‐output for high capacity and error performance over correlated fading channels

Channels' correlation has direct impact to degrade the capacity and reliability of multiple‐input multiple‐output (MIMO) systems considerably. In this paper, new signal constellation designs are investigated to mitigate fading correlation and maximize the capacity and error performance of multiuser MIMO (MU‐MIMO) over correlated channels, which is a major research challenge. Two methods are studied in a novel constellation constrained MU‐MIMO approach, namely, unequal power allocation and rotated constellation. Based on principles of maximizing the minimum Euclidean distance (d_min) of composite received signals, users' data can be recovered using maximum likelihood joint detection irrespective of correlation values. Compared with the identical constellation scenario in conventional MU‐MIMO, it is shown that constellation rearrangement of transmitted signals has direct impact to resolve the detection ambiguity when the channel difference is not sufficient, particularly in moderate to high correlations. Extensive analysis and simulation results demonstrate the superiority of proposed technique to capture most of the promised gains of multiantenna systems and application for future wireless communications. Copyright © 2014 John Wiley & Sons, Ltd.     

Fly ash-based geopolymer for Pb removal from aqueous solution

The aim of this work was to synthesis highly amorphous geopolymer from waste coal fly ash, to be used as an adsorbent for lead Pb(II) removal from aqueous wastewater. The effect of various parameters including geopolymer dosage, initial concentration, contact time, pH and temperature on lead adsorption were investigated. The major components of the used ash in the current study were SiO(2), Al(2)O(3) and Fe(2)O(3) representing 91.53 wt% of its mass. It was found that the synthesized geopolymer has higher removal capacity for lead ions when compared with that of raw coal fly ash. The removal efficiency increases with increasing geopolymer dosage, contact time, temperature, and the decrease of Pb(2+) initial concentration. The optimum removal efficiency was obtained at pH 5. Adsorption isotherm study indicated that Langmuir isotherm model is the best fit for the experimental data than Freundlich model. It was found also that the adsorption process is endothermic and more favorable at higher temperatures.     

Support vector regression-based model for prediction of behavior stone column parameters in soft clay under highway embankment

In order to have a proper design and analysis for the column of stone in the soft clay soil, it is essential to develop an accurate prediction model for the settlement behavior of the stone column. In the current research, to predict the behavior in the settlement of stone column a support vector machine (SVM) method is developed and examined. In addition, the proposed model has been compared with the existing reference settlement prediction model that using the monitored field data. As SVM mathematical procedure has resilient and robust generalization aptitude and ensures searching for global minima for particular training data as well. Therefore, the potential that support vector regression might perform efficiently to predict the ground soft clay settlement is relatively valuable. As a result, in this study, comparison of two different developed types of SVM method is carried out. Generally, significant reduction in the relative error (RE%) and root mean square error has been achieved. Utilizing nu-SVM-type model through tenfold cross-validation procedure could achieve outstanding performance accuracy level with RE% less than 2% and CR = 0.9987. The study demonstrates high potential for applying SVM in detecting the settlement behavior of SC prediction and ascertains that SVM could be effectively used for settlement stone columns analysis.

     

Collision Free Mobility Adaptive (CFMA) MAC for wireless sensor networks

In this paper we propose high throughput collision free, mobility adaptive and energy efficient medium access protocol (MAC) called Collision Free Mobility Adaptive (CFMA) for wireless sensor networks. CFMA ensures that transmissions incur no collisions, and allows nodes to undergo sleep mode whenever they are not transmitting or receiving. It uses delay allocation scheme based on traffic priority at each node and avoids allocating same backoff delay for more than one node unless they are in separate clusters. It also allows nodes to determine when they can switch to sleep mode during operation. CFMA for mobile nodes provides fast association between the mobile node and the cluster coordinator. The proposed MAC performs well in both static and mobile scenarios, which shows its significance over existing MAC protocols proposed for mobile applications. The performance of CFMA is evaluated through extensive simulation, analysis and comparison with other mobility aware MAC protocols. The results show that CFMA outperforms significantly the existing CSMA/CA, Sensor Mac (S-MAC), Mobile MAC (MOB-MAC), Adaptive Mobility MAC (AM-MAC), Mobility Sensor MAC (MS-MAC), Mobility aware Delay sensitive MAC (MD-MAC) and Dynamic Sensor MAC (DS-MAC) protocols including throughput, latency and energy consumption.     

RBF-NN-based model for prediction of weld bead geometry in Shielded Metal Arc Welding (SMAW)

Welding processes are considered as an essential component in most of industrial manufacturing and for structural applications. Among the most widely used welding processes is the shielded metal arc welding (SMAW) due to its versatility and simplicity. In fact, the welding process is predominant procedure in the maintenance and repair industry, construction of steel structures and also industrial fabrication. The most important physical characteristics of the weldment are the bead geometry which includes bead height and width and the penetration. Different methods and approaches have been developed to achieve the acceptable values of bead geometry parameters. This study presents artificial intelligence techniques (AIT): For example, radial basis function neural network (RBF-NN) and multilayer perceptron neural network (MLP-NN) models were developed to predict the weld bead geometry. A number of 33 plates of mild steel specimens that have undergone SMAW process are analyzed for their weld bead geometry. The input parameters of the SMAW consist of welding current (A), arc length (mm), welding speed (mm/min), diameter of electrode (mm) and welding gap (mm). The outputs of the AIT models include property parameters, namely penetration, bead width and reinforcement. The results showed outstanding level of accuracy utilizing RBF-NN in simulating the weld geometry and very satisfactorily to predict all parameters in comparison with the MLP-NN model.

     

Hydrocracking of waste lubricant into gasoline fraction over CoMo catalyst supported on mesoporous carbon from bovine bone gelatin

The hydrocracking of waste lubricant into gasoline fraction was carried out using CoMo catalyst supported on mesoporous carbon. The carbon was synthesized using bovine bone gelatin and SBA-15 as a template. The metals were loaded onto the carbon by wet impregnation method. The total metal content of catalyst was prepared into two different amounts which were labelled as CoMo/MCG1 and CoMo/MCG2. Catalytic activity and selectivity were evaluated in hydrocracking of waste lubricant at 450, 475, and 500 °C, and lubricant/catalyst weight ratio of 50, 100, 200, 300, and 400. The result revealed that acidity and specific surface area of the catalyst played an important role in determining the catalytic performance in the hydrocracking of waste lubricant. The highest percentage of gasoline fraction was 58.09%, produced by hydrocracking of waste lubricant at 475 °C and lubricant/catalyst weight ratio of 300 using CoMo/MCG2 catalyst.     

Synthesis and Characterization of SnO2 on Porous Silicon for Photoconversion

Silicon - A photoconversion device was fabricated based on SnO2 film prepared by a chemical spray pyrolysis technique. The SnO2 nanofilms were grown on the porous silicon (PS) nanosurface. Various...     

Beam injection methods for characterizing thin‐film solar cells

II–VI and I–III–VI solar cells are promising for future thin‐film photovoltaics. In this paper, the roles of electron‐beam‐induced current (EBIC) and cathodoluminescence in evaluating the influence of interfaces on those solar cells are reviewed. CdTe and Cu(In,Ga)Se₂ (CIGS) are the absorbers of the cells investigated. For CdTe/CdS solar cells, a detailed study has been conducted of the effects of grain boundaries and the Te/CdTe or ZnTe:Cu/CdTe interfaces for back‐contacting. For CIGS solar cells, we have investigated different buffer layer schemes, showing that these interfaces are critical in the definition of the mechanisms for carrier collection. Copyright © 2002 John Wiley & Sons, Ltd.     

Modeling and investigation start-up procedures of a combined cycle power plant

This study describes the particular development and investigation of a static and dynamic simulation model and its application to improve the start-up process of a combined cycle power plant. Generally, the power plant system and control design mean highly complex interactivities. The dynamic simulation models using powerful computers are effective tools for studying and understanding the operating characteristics of power plants to meet and improve the design, control strategy and operational requirements. The heat recovery steam generator (HRSG) is modeled by using commercial simulation software named advanced process simulation software (APROS). The HRSG model includes an advanced control philosophy and turbine bypass systems to have a high level of accuracy, especially during hard transients. The comparison between the simulation results and measured data is documented. The received results proved and embodied that the simulation is both very reliable to estimate the real HRSG dynamic behaviour and capable to predict the operational processes. Through a parametric study, the start-up time will be reduced while keeping the life-time consumption of critically stressed components under control.