Light weight model for intra mode selection in HEVC

Multimedia Tools and Applications - The High Efficiency Video Coding (HEVC) efficiently reduces the size of the multimedia contents, but at the cost of high computation complexity. In order to make...     

Synthesis and characterization of eugenol-based silicone modified waterborne polyurethane with excellent properties

A eugenol-based silicone-containing monomer 4,4′-(1,1,3,3-tetramethyldisiloxane-1,3-dipropyl)bis-2-methoxyphenol(EUSi) was synthesized from eugenol and 1,1,3,3-tetramethyldisiloxane via the hydrosilylation reaction. And waterborne polyurethane (WPU) with excellent properties was obtained by using EUSi as a type of diol chain extender. The unique combination of rigidity and flexibility in the chemical structure of EUSi greatly facilitated the mechanical properties, thermal properties, and water resistance of WPU. With only a 3% dosage of EUSi, the maximum tensile strength was increased from 6.2 to 22.4 MPa, while the water absorption was decreased from 31.3% to a surprisingly 7.6%. Our work provides a new convenient strategy for the preparation of organosilicon-modified WPU with improved performance.     

Adaptive infill sampling criterion for multi-fidelity optimization based on Gappy-POD

This paper presents a reformulation of the “Gappy Proper Orthogonal Decomposition” (Gappy-POD) multi-fidelity modeling approach and proposes an enrichment criterion associated with an adaptive infill algorithm. The latter is here applied to the study of the flight domain of the RAE-2822 transonic airfoil at two different levels of accuracy to demonstrate its ability to detect areas in a two-dimensional design space where the surrogate model needs improvement to better drive the optimization process.     

Evaluating Six Sigma failure rate for inverse Gaussian cycle times

Six Sigma is a quality philosophy and methodology that aims to achieve operational excellence and delighted customers. The cost of poor quality depends on the sigma quality level and its corresponding failure rate. Six Sigma provides a well-defined target of 3.4 defects per million. This failure rate is commonly evaluated under the assumption that the process is normally distributed and its specifications are two-sided. However, these assumptions may lead to implementation of quality-improvement strategies that are based on inaccurate evaluations of quality costs and profits. This paper defines the relationship between failure rate and sigma quality level for inverse Gaussian processes. The inverse Gaussian distribution has considerable applications in describing cycle times, product life, employee service times, and so on. We show that for these processes attaining Six Sigma target failure rate requires higher quality efforts than for normal processes. A generic model is presented to characterise cycle times in manufacturing systems. In this model, the asymptotic production is described by a drifted Brownian motion, and the cycle time is evaluated by using the first passage time theory of a Wiener process to a boundary. The proposed method estimates the right efforts required to reach Six Sigma goals.     

Tracking and Analysis of Pedestrian’s Behavior in Public Places

Crowd management becomes a global concern due to increased population in urban areas. Better management of pedestrians leads to improved use of public places. Behavior of pedestrian’s is a major factor of crowd management in public places. There are multiple applications available in this area but the challenge is open due to complexity of crowd and depends on the environment. In this paper, we have proposed a new method for pedestrian’s behavior detection. Kalman filter has been used to detect pedestrian’s using movement based approach. Next, we have performed occlusion detection and removal using region shrinking method to isolate occluded humans. Human verification is performed on each human silhouette and wavelet analysis and particle gradient motion are extracted for each silhouettes. Gray Wolf Optimizer (GWO) has been utilized to optimize feature set and then behavior classification has been performed using the Extreme Gradient (XG) Boost classifier. Performance has been evaluated using pedestrian’s data from avenue and UBI-Fight datasets, where both have different environment. The mean achieved accuracies are 91.3% and 85.14% over the Avenue and UBI-Fight datasets, respectively. These results are more accurate as compared to other existing methods.     

A Framework of Deep Optimal Features Selection for Apple Leaf Diseases Recognition

Identifying fruit disease manually is time-consuming, expert-required, and expensive; thus, a computer-based automated system is widely required. Fruit diseases affect not only the quality but also the quantity. As a result, it is possible to detect the disease early on and cure the fruits using computer-based techniques. However, computer-based methods face several challenges, including low contrast, a lack of dataset for training a model, and inappropriate feature extraction for final classification. In this paper, we proposed an automated framework for detecting apple fruit leaf diseases using CNN and a hybrid optimization algorithm. Data augmentation is performed initially to balance the selected apple dataset. After that, two pre-trained deep models are fine-tuning and trained using transfer learning. Then, a fusion technique is proposed named Parallel Correlation Threshold (PCT). The fused feature vector is optimized in the next step using a hybrid optimization algorithm. The selected features are finally classified using machine learning algorithms. Four different experiments have been carried out on the augmented Plant Village dataset and yielded the best accuracy of 99.8%. The accuracy of the proposed framework is also compared to that of several neural nets, and it outperforms them all.     

Sulphur dioxide loadings over megacity Lahore (Pakistan) and adjoining region of Indo-Gangetic Basin

This article presents spatial and temporal variations of planetary boundary layer (PBL) sulphur dioxide (SO₂) over megacity Lahore and adjoining region, a typical representative area in the Indo-Gangetic Basin (IGB) largely influenced by transported volcanic SO₂ from Africa, Middle East, and southern Europe, by using data retrieved from satellite-based Ozone Monitoring Instrument (OMI) during October 2004–September 2015. We find a positive trend of 2.4% per year (slope 0.01 ± 0.005 with y-intercept 0.35 ± 0.03 Dobson Unit (DU), correlation coefficient r = 0.55 and 2-tailed p-value at 0.1) of OMI-SO₂ column with the average value of 0.4 ± 0.05 DU. Strong seasonality of OMI-SO₂ column is observed over the region linked with local meteorology, patterns of anthropogenic emissions, crop residue burning, and vegetation cover. There exists a seasonal high value in winter 0.56 ± 0.24 DU with a peak in December 0.67 ± 0.26 DU. The seasonal lowest value is observed to be 0.29 ± 0.11 DU in wet summer with minimum value in July 0.25 ± 0.06 DU. High growth rates of OMI-SO₂ column over the study region have been observed in January, June, October, and December ranging from 5.7% to 11.6% per year. Satellite data show elevated OMI-SO₂ columns in 2007, 2008, 2011, and 2012 largely contributed by trans-boundary volcanic SO₂. A detailed analysis of volcanic SO₂ transported from Africa and Middle East (Jabal Al-Tair, Dalaffilla, and Nabro volcanoes) over the study area is presented. Air mass trajectories suggest the presence of long-range transported volcanic SO₂ at high altitude levels over Lahore and IGB region during the volcanic episodes. The SO₂ enhancements in PBL during winter season are generally due to significant vertical downdraft of high-altitude volcanic SO₂. For the first time, we present significant influence of volcanic SO₂ from southern Europe (Mt. Etna volcano) reaching over the study area. Daily mean OMI-SO₂ levels up to 21.4, 10.0, 5.6, and 2.4 DU have been noticed due to the eruptions from Dalaffilla, Mt. Etna, Nabro, and Jabal Al-Tair volcanoes, respectively.     

Détermination du facteur de multiplication M pour un fonctionnement optimal des photodétecteurs à avalanche

The purpose of this paper is relative to the determination of the multiplication factor Mfor an optimum behaviour of the avalanche photodetector. Two types of avalanche photodetector s are compared: a silicon structure n ⁺ πpπp ⁺ Read diode and a GaAlAs heterostructure. Calculating the Noise Equivalent Power (nep)of the whole system, the law S_i(f) =2q I_phoM_x is used, where the parameter x is determined experimentally in both avalanche photodetectors. The exponent x (between 2 and 4) dominates in the nep expression and the ideal nep for the avalanche photodetector system is obtained when x equals 2.     

Three Dimensional Conceptualisation of Hydrogeological Environment to Underpin Groundwater Management in Irrigation Area

Australian irrigated agriculture utilises about 70?% of all water used in the country, 21?% of which is derived from groundwater. Sustainability for irrigated agriculture also depends on keeping the watertables at a safe level below the rootzone to avoid salinisation and reduction in crop yields. There is a vital need to understand groundwater and aquifer systems and their roles in the sustainability of irrigated agriculture in order to manage groundwater properly. This study builds on the previous hydrogeological and groundwater investigations of the Coleambally Irrigation Area (CIA) in New South Wales of Australia. It presents a new approach which systematically characterises regional hydrogeological environment using a three-dimensional (3-D) conceptual framework developed in ArcGIS. The 3-D hydrological conceptualisation of the CIA has integrated disparate sources of data into a coherent knowledge base for a better visualisation of hydrogeological characteristics and a comprehensive analysis of groundwater flow and aquifers. As an application example, the model was used to develop cross-sectional models of the area and to estimate regional-scale net recharge. The results have provided a basis for the numerical modelling and added values to procedures which underpin irrigation system management investment decisions through improving the understanding of hydrogeology underlying the area and creating an action-oriented dialogue among stakeholders.