Resource Allocation for Energy-Efficient Device-to-Device Communication in 4G Networks

Device-to-device (D2D) communications as an underlay of a LTE-A (4G) network can reduce the traffic load as well as power consumption in cellular networks by way of utilizing peer-to-peer links for users in proximity of each other. This would enable other cellular users to increment their traffic, and the aggregate traffic for all users can be significantly increased without requiring additional spectrum. However, D2D communications may increase interference to cellular users (CUs) and force CUs to increase their transmit power levels in order to maintain their required quality-of-service (QoS). This paper proposes an energy-efficient resource allocation scheme for D2D communications as an underlay of a fully loaded LTE-A (4G) cellular network. Simulations show that the proposed scheme allocates cellular uplink resources (transmit power and channel) to D2D pairs while maintaining the required QoS for D2D and cellular users and minimizing the total uplink transmit power for all users.Comment: 2014 7th International Symposium on Telecommunications (IST'2014

Markov-Switching GARCH Modelling of Value-at-RisK

This paper proposes an asymmetric Markov regime-switching (MS) GARCH model to estimate value-at-risk (VaR) for both long and short positions. This model improves on existing VaR methods by taking into account both regime change and skewness or leverage effects. The performance of our MS model and single-regime models is compared through an innovative backtesting procedure using daily data for UK and US market stock indices. The findings from exceptions and regulatory-based tests indicate the MS-GARCH specifications clearly outperform other models in estimating the VaR for both long and short FTSE positions and also do quite well for S&P positions. We conclude that ignoring skewness and regime changes has the effect of imposing larger than necessary conservative capital requirements

Window-based Streaming Graph Partitioning Algorithm

In the recent years, the scale of graph datasets has increased to such a degree that a single machine is not capable of efficiently processing large graphs. Thereby, efficient graph partitioning is necessary for those large graph applications. Traditional graph partitioning generally loads the whole graph data into the memory before performing partitioning; this is not only a time consuming task but it also creates memory bottlenecks. These issues of memory limitation and enormous time complexity can be resolved using stream-based graph partitioning. A streaming graph partitioning algorithm reads vertices once and assigns that vertex to a partition accordingly. This is also called an one-pass algorithm. This paper proposes an efficient window-based streaming graph partitioning algorithm called WStream. The WStream algorithm is an edge-cut partitioning algorithm, which distributes a vertex among the partitions. Our results suggest that the WStream algorithm is able to partition large graph data efficiently while keeping the load balanced across different partitions, and communication to a minimum. Evaluation results with real workloads also prove the effectiveness of our proposed algorithm, and it achieves a significant reduction in load imbalance and edge-cut with different ranges of dataset

Energy Audit in Wastewater Aeration System

To evaluate the energy consumption air to aeration basins in wastewater treatment aeration system and to compare the standard computations of oxygen demand and blower power requirements with the actual plant data

Poverty, inflation and economic growth: empirical evidence from Pakistan

This study aims to investigate the role of economic growth and inflation in explaining the prevalence of poverty in Pakistan. ARDL bound testing approach to co-integration confirms the existence of long run relationship among the variables of poverty, economic growth, inflation, investment and trade openness over the period of 1972-2008. Empirical results show that economic growth and investment have negative and inflation has positive impact on poverty. The effect of trade openness on poverty is insignificant in this study. The short run analysis reveals that economic growth has negative and inflation has positive impact on poverty whereas the role of investment and trade openness in poverty reduction in short run is not significant.Poverty, Inflation, Economic Grovvth, Pakistan, Macroeconomic Policy, Welfare, Trade Openness

Hardware-Accelerated SAR Simulation with NVIDIA-RTX Technology

Synthetic Aperture Radar (SAR) is a critical sensing technology that is notably independent of the sensor-to-target distance and has numerous cross-cutting applications, e.g., target recognition, mapping, surveillance, oceanography, geology, forestry (biomass, deforestation), disaster monitoring (volcano eruptions, oil spills, flooding), and infrastructure tracking (urban growth, structure mapping). SAR uses a high-power antenna to illuminate target locations with electromagnetic radiation, e.g., 10GHz radio waves, and illuminated surface backscatter is sensed by the antenna which is then used to generate images of structures. Real SAR data is difficult and costly to produce and, for research, lacks a reliable source ground truth. This article proposes a open source SAR simulator to compute phase histories for arbitrary 3D scenes using newly available ray-tracing hardware made available commercially through the NVIDIA's RTX graphics cards series. The OptiX GPU ray tracing library for NVIDIA GPUs is used to calculate SAR phase histories at unprecedented computational speeds. The simulation results are validated against existing SAR simulation code for spotlight SAR illumination of point targets. The computational performance of this approach provides orders of magnitude speed increases over CPU simulation. An additional order of magnitude of GPU acceleration when simulations are run on RTX GPUs which include hardware specifically to accelerate OptiX ray tracing. The article describes the OptiX simulator structure, processing framework and calculations that afford execution on massively parallel GPU computation device. The shortcoming of the OptiX library's restriction to single precision float representation is discussed and modifications of sensitive calculations are proposed to reduce truncation error thereby increasing the simulation accuracy under this constraint.Comment: 17 pages, 7 figures, Algorithms for Synthetic Aperture Radar Imagery XXVII, SPIE Defense + Commercial Sensing 202

The carbon footprint associated with water management policy options in the Las Vegas Valley, Nevada

A system dynamics model was developed to estimate the carbon dioxide (CO2) emissions associated with conveyance of water from the water source to the distribution laterals of the Las Vegas Valley. In addition, the impact of several water management policies, including water conservation, reuse, and population growth rate change was evaluated. The results show that, at present, nearly 0.53 million metric tons of CO2 emissions per year are released due to energy use for water conveyance in distribution laterals of the Valley from Lake Mead, located 32.2 km (20 miles) southeast of the Las Vegas at an elevation of nearly 366 m (1200 ft) below the Valley. The results show that the reduction in per capita water demand to 753 lpcd by 2035 can lower the CO2 emissions by approximately 16.5%. The increase in reuse of treated wastewater effluent within the valley to 77 million cubic meters by 2020 results in the decrease of CO2 emissions by 3.6%. Similarly, change in population growth rate by ±0.5% can result in CO2 emissions reduction of nearly 12.8% by 2035 when compared to the current status

Energy Consumption in Large Wastewater Treatment Plants as a Function of Wastewater Strength

Wastewater treatment (WWT) is an energy-intensive process. Strict standards for discharge often require energy intensive advanced treatment technologies. As a result, the number of plants using advanced treatment has increased (Figure 1). Rising energy costs and concerns about greenhouse gas generation present a major incentive for tracking energy usage of WWT. Energy usage in plant, for instance, typically represents 18 to 30% of the operational budget. Water efficient fixtures are also increasing loadings of organic matter to plants while lowering or maintaining overall liquid flow. The increased loadings have a significant impact on energy consumption. Previous work has focused primarily on aeration consumption for activated sludge rather than a plant as whole. There are very few studies that show energy requirements on a plant-wide scale with the Water Environment Federation (WEF) being one major source. This research presents a general methodology for tracking energy usage in a plant with regards to wastewater strength. It is anticipated that this research will provide a tool for designers and owners who wish to predict their energy impact before construction of a new plant or before implementing a new process on an existing plant

CuSCN Nanowires as Electrodes for p-Type Quantum Dot Sensitized Solar Cells: Charge Transfer Dynamics and Alumina Passivation

Quantum dot sensitized solar cells (QDSSCs) are a promising photovoltaic technology due to their low cost and simplicity of fabrication. Most QDSSCs have an n-type configuration with electron injection from QDs into TiO2, which generally leads to unbalanced charge transport (slower hole transfer rate) limiting their efficiency and stability. We have previously demonstrated that p-type (inverted) QD sensitized cells have the potential to solve this problem. Here we show for the first time that electrodeposited CuSCN nanowires can be used as a p-type nanostructured electrode for p-QDSSCs. We demonstrate their efficient sensitization by heavy metal free CuInSxSe2-x quantum dots. Photophysical studies show efficient and fast hole injection from the excited QDs into the CuSCN nanowires. The transfer rate is strongly time dependent but the average rate of 2.5 × 109 s–1 is much faster than in previously studied sensitized systems based on NiO. Moreover, we have developed an original experiment allowing us to calculate independently the rates of charge injection and QD regeneration by the electrolyte and thus to determine which of these processes occurs first. The average QD regeneration rate (1.3 × 109 s–1) is in the same range as the hole injection rate, resulting in an overall balanced charge separation process. To reduce recombination in the sensitized systems and improve their stability, the CuSCN nanowires were coated with thin conformal layers of Al2O3 using atomic layer deposition (ALD) and fully characterized by XPS and EDX. We demonstrate that the alumina layer protects the surface of CuSCN nanowires, reduces charge recombination, and increases the overall charge transfer rate up to 1.5 times depending on the thickness of the deposited Al2O3 layer