Effect of Grid Resolution and Terrain Characteristics on Data from DTM

Previous work in digital terrain modeling (DTM) has shown that if regular gridded-data sets are used in the construction of the model, both the resolution of the gridded-data set and the characteristics of the terrain being modeled have an effect on the accuracy of digital terrain models. The main objective of this study is to test the hypothesis that both the resolution of the gridded-data set and the characteristics of the terrain being modeled have an effect on the accuracy of any derived data. To test this hypothesis, the terrain was classified in terms of its roughness. Various forms of data were derived from the terrain model; these include volumes, surface area, contours, and cross sections. The accuracy for each of these quantities was calculated by comparing them with values obtained from a control model. This research concluded that by both increasing the resolution of the regular gridded-data sets and varying the characeristics of the terrain, the accuracy of any derived data is affected.     

Interpreting the hydrogen adsorption on organic groups functionalized MOF-5s by statistical physics model

The hydrogen adsorption isotherms at equilibrium on four adsorbents (MOF-5 and three modified MOF-5s named, CH₃-MOF-5, Br-MOF-5 and Cl-MOF-5) were studied using a monolayer model with four adsorption sites energies. The analytical expression of this model was developed using the grand canonical ensemble in statistical physics by taking some working hypotheses involving some physicochemical parameters which can describe the adsorption process. These parameters are: four numbers of hydrogen adsorbed molecules per site (n₁, n₂, n₃ and n₄), four receptor site densities (N_M1, N_M2, N_M3 and N_M4), four saturation adsorbed quantities (Q₁, Q₂, Q₃ and Q₄) and four adsorption energies (??₁, ??₂, ??₃ and ??₄). The evolutions of these parameters in relation with temperature were discussed to understand and interpret the adsorption process at different temperatures. Fitting results revealed that the adsorption of hydrogen on MOF-5 is an exothermic physisorption process. The adsorption surface is inhomogeneous with many site energies. The fitting of the adsorption site is achieved by an aggregate of hydrogen molecules. The adopted model expression is used to derive the thermodynamic potential functions which govern the sorption mechanism such as entropy S_a, free enthalpy of Gibbs G and internal energy E_int.     

Species identification by oligonucleotide hybridisation: the influence of processing of meat products

We have evaluated the influence of meat processing on the results obtained with a species identification test by DNA oligonucleotide hybridisation. Freezing and thawing of meat did not cause a substantial reduction in the hybridisation signal. Heating of meat at 100°C or 120°C, however, led to signal reduction caused by DNA degradation, but identification was still possible. The signal is highly influenced by the kind of tissues processed. Four extensively processed products with 50 g kg⁻¹ species admixtures were tested. Admixtures could be detected in three products but no hybridisation signal was observed with corned beef. We conclude that the quantification of admixtures by hybridisation is not better than with most alternative methods of species identification, as the strength of the signal depends on factors such as tissue origin and sample processing. © 1999 Society of Chemical Industry     

Q2ABR: QoE‐aware adaptive video bit rate solution

In this paper, we propose a new adaptive bit rate (ABR) streaming method. This method is based on estimating and monitoring users' video streaming experience, their quality of experience (QoE). This ensures a good user QoE and optimises bandwidth utilisation by monitoring video buffer fill rate to ensure minimal data traffic. First, we achieve a QoE evaluation model based on network bandwidth, video segment representation, and dropped video frame rate parameters. Second, following our QoE evaluation model, we formulate an ABR method using the reinforcement learning (RL) paradigm to select video representations and using a breakpoint detection mechanism to monitor end‐user QoE variation. The proposed ABR method is called “QoE‐aware adaptive bit rate (Q2ABR)” and is composed of three individual modules, one for QoE estimation using machine learning methods, one for QoE variation monitoring using the breakpoint detection mechanism, and one for video representation selection using reinforcement learning. The design objective of Q2ABR is to ensure the overall QoE of these users while maintaining a minimum variation in the standard deviation of the users' QoE values. Third, the performance of the Q2ABR method is evaluated and compared with several existing ABR approaches in the literature using real traces that we collect on different transport scenarios (such as bus and train, among others). Since this method considers the user's perception of video quality as a regulator for optimising the overall video distribution network, good results are ensured in terms of the user's experience and buffer fill rate.     

Decomposing global solar radiation into its diffuse and direct normal radiation

ABSTRACT

This work presents a model based on Radial Basis Function (RBF) to estimate the diffused solar radiation (DSR) and direct normal radiation (DNR) fractions of solar radiation from global solar radiation in a semiarid area in Algeria based on a database measured between 2013 and 2015. The data has been collected at Applied Research Unit for Renewable Energies, (URAER) at Ghardaia city situated in the south of Algeria. The experimental results show that RBF model estimates DNR and DSR with high performance. The difference between the measured and the predicted values show a normalised Root Mean Square Error (nRMSE) of 0.033 and 0.065 for DNR and DSR, respectively. The obtained values of Determination Coefficient (R²) and Correlation Coefficient (R) are: 97.3%, 98.60%, respectively for DNR and 88.89%, 91.12% For DSR.

However, the obtained results are very plausible and showed that RBF model estimates the DSR and DNR with good accuracy.