Evaluation of natural gas hydrates as a future methane source

In recent years, attention has been given to obtaining methane gas from natural gas hydrates (NGHs) sediment; but its production, economics, and safety are still far away from being commercially viable for many years, and so more research is needed. NGHs are nonstoichiometric crystalline solid compounds that form from mixtures of water molecules and light weight natural gases such as methane, ethane, propane, and carbon dioxide. They are formed in specific thermodynamic conditions, low temperatures (5–15°C) and high pressures (2–3 MPa), and are found in (a) onshore polar regions beneath permafrost and (b) offshore deep-sea sediments. Methane, NG, is the cleanest fossil fuel and its huge amounts in NGHs have carbon quantities more than double of all fossil fuels. The methods that have been proposed for NG extraction from NGHs include: (a) depressurization, (b) thermal stimulation, and (c) chemical inhibitor injections. The authors review the potential of methane gas from NGHs as an unconventional source of future energy. The formation of NGHs as well as extraction of methane from NGHs coupled with technical and environmental challenges are also addressed.     

Effective harvesting,detection, and conversion of IR radiation due to quantum dots with built-in charge

We analyze the effect of doping on photoelectron kinetics in quantum dot [QD] structures and find two strong effects of the built-in-dot charge. First, the built-in-dot charge enhances the infrared [IR] transitions in QD structures. This effect significantly increases electron coupling to IR radiation and improves harvesting of the IR power in QD solar cells. Second, the built-in charge creates potential barriers around dots, and these barriers strongly suppress capture processes for photocarriers of the same sign as the built-in-dot charge. The second effect exponentially increases the photoelectron lifetime in unipolar devices, such as IR photodetectors. In bipolar devices, such as solar cells, the solar radiation creates the built-in-dot charge that equates the electron and hole capture rates. By providing additional charge to QDs, the appropriate doping can significantly suppress the capture and recombination processes via QDs. These improvements of IR absorption and photocarrier kinetics radically increase the responsivity of IR photodetectors and photovoltaic efficiency of QD solar cells.     

Forecasting electric energy consumption using neural networks

An artificial neural network model is developed to relate the electric energy consumption in the Eastern Province of Saudi Arabia to the weather data (temperature and humidity), global solar radiation and population. A two layered feedforward neural network is used for the modelling. The inputs to the neural network are the independent variables and the output is the electric energy consumption. Seven years' of data are used for model building and validation. Model adequacy is established by a visual inspection technique and the chi-square test. Model validation, which reflects the suitability of the model for future predictions is performed by comparing the predictions of the model with future data that was not used for model building. Comparison with a regression model shows that the neural network model performs better for predictions.     

Heavy oil upgrading: Unlocking the future fuel supply

Currently, more than half of the oil reserves (53.3%) in the world are in the form of restorable oils such as heavy oil, extra heavy oil, oil sand, tar sands, oil shale, and bitumen. Heavy oil is one of the petroleum oil varieties that contain long chain hydrocarbons. All types of heavy oils contain asphaltenes and thus are considered very dense substances. The asphaltenes are one of the most complex and heavy organic compounds present in the heavy oil. The heavy oil is defined as one having an American Petroleum Institute scale index equal or smaller than 20°. In conventional refining procedures, heavy oil poses many challenges. Recycling and re-refining are applied techniques for the processing of petroleum based heavy oils into reusable light oils such as gasoline and diesel fuel. In this regard, catalytic pyrolysis and thermal cracking are promising technologies for light oil production. The authors review the heavy oil upgrading processes and their associated challenges with ambition to find cost-effective ways to ensure a constant future fuel supply.     

Strong enhancement of solar cell efficiency due to quantum dots with built-in charge

We report a 50% increase in the power conversion efficiency of InAs/GaAs quantum dot solar cells due to n-doping of the interdot space. The n-doped device was compared with GaAs reference cell, undoped, and p-doped devices. We found that the quantum dots with built-in charge (Q-BIC) enhance electron intersubband quantum dot transitions, suppress fast electron capture processes, and preclude deterioration of the open circuit voltage in the n-doped structures. These factors lead to enhanced harvesting and efficient conversion of IR energy in the Q-BIC solar cells.     

Impact of visual saliency on multi-distorted blind image quality assessment using deep neural architecture

Multimedia Tools and Applications - No-referenceimage quality assessment (NR-IQA) techniques try to assess the quality of images without anyinformation regarding the pristine version of the image....     

Effect of thermal, chemical and thermo-chemical pre-treatments to enhance methane production

The rise in oil price triggered the exploration and enhancement of various renewable energy sources. Producing biogas from organic waste is not only providing a clean sustainable indigenous fuel to the number of on-farm digesters in Europe, but also reducing the ecological and environmental deterioration. The lignocellulosic substrates are not completely biodegraded in anaerobic digesters operating at commercial scale due to their complex physical and chemical structure, which result in meager energy recovery in terms of methane yield. The focus of this study is to investigate the effect of pre-treatments: thermal, thermo-chemical and chemical pre-treatments on the biogas and methane potential of dewatered pig manure. A laboratory scale batch digester is used for these pre-treatments at different temperature range (25 °C-150 °C). Results showed that thermo-chemical pretreatment has high effect on biogas and methane potential in the temperature range (25–100 °C). Maximum enhancement is observed at 70 °C with increase of 78% biogas and 60% methane production. Thermal pretreatment also showed enhancement in the temperature range (50–10 °C), with maximum enhancement at 100 °C having 28% biogas and 25% methane increase.     

Integrating E-Commerce and Games

This paper investigates how many users of commercial interactive systems are not properly agents within the interactive narrative, largely due to the dynamics of branding in cyberspace. Parallels are drawn between the dynamic personalization of e-CRM engines and context aware computing systems. Several seminal games are discussed as examples of systems in which very different relationships exist between users and the system. Arguments are made for designing e-commerce interactive systems that install into games, inside the game narrative. Correspondence to: Ms N. Cummins, Preject Brand Communications Consultancy, Unit P, Carlton Works Studios, Asylum Road, London SE15 2SB, UK. Email: nizami@preject.com     

Multiply distorted image quality assessment based on feature level fusion and optimal feature selection

No reference image quality assessment (NR-IQA) has received considerable importance in the last decade due to a rise in the use of multimedia content in our daily lives. Due to limitations in technology, multiple distortions may be introduced in the images that need to be assessed. Recently feature selection has shown promising results for single distorted NR-IQA and their effectiveness on multiple distorted images still need to be addressed. In this paper, impact of feature level fusion and feature selection on multiple distorted image quality assessment is presented. To this end features are extracted from multiple distorted images using six NR-IQA techniques (BLIINDS-II, BRISQUE, CurveletQA, DIIVINE, GM-LOG, SSEQ) that extract features in different (discrete cosine transform, spatial, curvelet transform, wavelet transform, spatial and gradient, spatial and spectral) domains. The extracted features from different domains are fused to generate a single feature vector. All combinations of feature-level fusion from six different techniques have been evaluated. Three different feature selection algorithms (genetic search, linear forward search, particle swarm optimization) are then applied to select optimum features for NR-IQA. The selected features are then used by the support vector regression model to predict the quality score. The performance of the proposed methodology is evaluated for two multiple distorted IQA databases (LIVE multiple distorted image dataset (LIVEMD), multiply distorted image database (MDID2017)), two singly synthetically distorted IQA databases (Tampere image database (TID2013), Computational and subjective image quality database (CSIQ)), and one screen content IQA database (Screen content image quality database (SIQAD)). Experimental results show that the fusion of features from different domains gives better performance in comparison to existing multiple-distorted NR-IQA techniques with SROCC scores of 0.9555, 0.9587, 0.6892, 0.9452, and 0.7682 on the LIVEMD, MDID, TID2013, CSIQ, and SIQAD databases respectively. Moreover, the performance is further improved when the genetic search feature selection algorithm is applied to fused features to remove the redundant and irrelevant features. The SROCC scores are improved to 0.9691, 0.9723, and 0.6897 for LIVEMD, MDID, and TID2013 databases respectively.

     

Non-Stationary response of a vehicle obtained from a series of stationary responses

Ride characteristics of a vehicle moving on a rough ground with changing travel velocity are analyzed in this paper. The solution is difficult due to the non-stationary characteristics of the problem. Hence a new technique has been proposed to overcome this difficulty. This new technique is employed in the analysis of ride characteristics of a vehicle with changing velocity in the time/frequency domain. It is found that the proposed technique gives successful results in modelling non-stationary responses in terms of a series of stationary responses.