994 resultados para Block energy


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As a significant milestone in the data dissemination of wireless sensor networks (WSNs), the comb-needle (CN) model was developed to dynamically balance the sensor data pushing and pulling during hybrid data dissemination. Unfortunately, the hybrid push-pull data dissemination strategy may overload some sensor nodes and form the hotspots that consume energy significantly. This usually leads to the collapse of the network at a very early stage. In the past decade, although many energy-aware dynamic data dissemination methods have been proposed to alleviate the hotspots issue, the block characteristic of sensor nodes has been overlooked and how to offload traffic from hot blocks with low energy through long-distance hybrid dissemination remains an open problem. In this paper, we developed a block-aware data dissemination model to balance the inter-block energy and eliminate the spreading of intra-block hotspots. Through the clustering mechanism based on geography and energy, "similar" large-scale sensor nodes can be efficiently grouped into specific blocks to form the global block information (GBI). Based on GBI, the long-distance block-cross hybrid algorithms are further developed by effectively aggregating inter-block and intra-block data disseminations. Extensive experimental results demonstrate the capability and the efficiency of the proposed approach. © 2014 Elsevier Ltd.

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A series of block copolymers containing nonconjugated spacer and 3D pi-pi stacking structure with simultaneous blue-, green-, and yellow-emitting units has been synthesized and characterized. The dependence of the energy transfer and electroluminescence (EL) properties of these block copolymers on the contents of oligo(phenylenevinylene)s has been investigated. The block copolymer (GEO8-BEO-YEO4) with 98.8% blue-emitting oligomer (BEO), 0.8% green-emitting oligomer (GEO), and 0.4% yellow-emitting oligomer (YEO) showed the best electroluminescent performance, exhibiting a maximum luminance of 2309 cd/m(2) and efficiency of 0.34 cd/A. The single-layer-polymer light-emitting diodes device based on GEO2-BEO-YEO4 emitted greenish white light with the CIE coordinates of (0.26, 0.37) at 10 V. The synergetic effect of the efficient energy transfer and 3D pi-pi stack of these block copolymers on the photoiuminescent and electroluminescent properties are investigated.

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Energy efficiency is an essential requirement for all contemporary computing systems. We thus need tools to measure the energy consumption of computing systems and to understand how workloads affect it. Significant recent research effort has targeted direct power measurements on production computing systems using on-board sensors or external instruments. These direct methods have in turn guided studies of software techniques to reduce energy consumption via workload allocation and scaling. Unfortunately, direct energy measurements are hampered by the low power sampling frequency of power sensors. The coarse granularity of power sensing limits our understanding of how power is allocated in systems and our ability to optimize energy efficiency via workload allocation.
We present ALEA, a tool to measure power and energy consumption at the granularity of basic blocks, using a probabilistic approach. ALEA provides fine-grained energy profiling via sta- tistical sampling, which overcomes the limitations of power sens- ing instruments. Compared to state-of-the-art energy measurement tools, ALEA provides finer granularity without sacrificing accuracy. ALEA achieves low overhead energy measurements with mean error rates between 1.4% and 3.5% in 14 sequential and paral- lel benchmarks tested on both Intel and ARM platforms. The sampling method caps execution time overhead at approximately 1%. ALEA is thus suitable for online energy monitoring and optimization. Finally, ALEA is a user-space tool with a portable, machine-independent sampling method. We demonstrate two use cases of ALEA, where we reduce the energy consumption of a k-means computational kernel by 37% and an ocean modelling code by 33%, compared to high-performance execution baselines, by varying the power optimization strategy between basic blocks.

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This thesis reports the synthesis and/or applications of three types of block copolymers that each bear a low-surface-energy block. First, poly(dimethylsiloxane)-block-poly(2-cinnamoyloxyethyl acrylate) (PDMS-b-PCEA) was synthesized and characterized. Cotton coating using a micellar solution of this block copolymer yielded superhydrophobic cotton fabrics. X-ray photoelectron spectroscopy (XPS) and surface property analyses indicated that the PDMS block topped the polymer coating. Photocuring the cotton swatches crosslinked the underlying PCEA layer and yielded permanent coatings. More interestingly, hydrophilically patterned superhydrophobic cotton fabrics were produced using photolithography that allowed the crosslinking of the coating around irradiated fibers but the removal, by solvent extraction, of the coating on fibers that were not irradiated. Since water-based ink only permeated the uncoated regions, such patterned fabric was further used to print ink patterns onto substrates such as fabrics, cardboard, paper, wood, and aluminum foil. Then, another PDMS-based diblock copolymer poly(dimethylsiloxane)-block-poly(glycidyl methacrylate) (PDMS-b-PGMA) was prepared. Different from PCEA that photocrosslinked around cotton fibers, PGMA reacted with hydroxyl groups on cotton fiber surfaces to get covalently attached. Further, different PGMA chains crosslinked with each other. PDMS-b-PGMA-coated cotton fabrics have been used for oil-water separations. In addition, polymeric nanoparticles were grafted onto cotton fiber surface before PDMS-b-PGMA was used to cover the surfaces of the grafted spheres and the residual surfaces of the cotton fibers. These two types of fabrics, coated by the block copolymer alone or by the polymer nanospheres and then the copolymer, were characterized by scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FT-IR), and water repellency analyses. A comprehensive comparative study was made of their performances in oil-water separation. Finally, a fluorinated ABC triblock copolymer poly(acrylic acid)-block-poly(2-cinnamoyloxyethyl methacrylate)-block-poly(2-perfluorooctylethyl methacrylate) (PAA-b-PCEMA-b-PFOEMA) was used to iii encapsulate air nanobubbles. The produced air nanobubbles were thermodynamically stable in water and were some 100 times more stable than commercially available perfluorocarbon-filled microbubbles under ultrasound. These nanobubbles, due to their small sizes and thus ability to permeate the capillary networks of organs and to reach tumors, may expand the applications of microbubbles in diagnostic ultrasonography and find new applications in ultrasound-regulated drug delivery.

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The concept of moving block signallings (MBS) has been adopted in a few mass transit railway systems. When a dense queue of trains begins to move from a complete stop, the trains can re-start in very close succession under MBS. The feeding substations nearby are likely to be overloaded and the service will inevitably be disturbed unless substations of higher power rating are used. By introducing starting time delays among the trains or limiting the trains’ acceleration rate to a certain extent, the peak energy demand can be contained. However, delay is introduced and quality of service is degraded. An expert system approach is presented to provide a supervisory tool for the operators. As the knowledge base is vital for the quality of decisions to be made, the study focuses on its formulation with a balance between delay and peak power demand.

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A high peak power demand at substations will result under Moving Block Signalling (MBS) when a dense queue of trains begins to start from a complete stop at the same time in an electrified railway system. This may cause the power supply interruption and in turn affect the train service substantially. In a recent study, measures of Starting Time Delay (STD) and Acceleration Rate Limit (ARL) are the possible approaches to reduce the peak power demand on the supply system under MBS. Nevertheless, there is no well-defined relationship between the two measures and peak power demand reduction (PDR). In order to attain a lower peak demand at substations on different traffic conditions and system requirements, an expert system is one of the possible approaches to procure the appropriate use of peak demand reduction measures. The main objective of this paper is to study the effect of the train re-starting strategies on the power demand at substations and the time delay suffered by the trains with the aid of computer simulation. An expert system is a useful tool to select various adoptions of STD and ARL under different operational conditions and system requirements.

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In recent years, development of Unmanned Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This thesis presents an investigation of methods for increasing the energy efficiency on UAVs. One method is via the development of a Mission Waypoint Optimisation (MWO) procedure for a small fixed-wing UAV, focusing on improving the onboard fuel economy. MWO deals with a pre-specified set of waypoints by modifying the given waypoints within certain limits to achieve its optimisation objectives of minimising/maximising specific parameters. A simulation model of a UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. This simulation model was separately integrated with a multi-objective Evolutionary Algorithm (MOEA) optimiser and a Sequential Quadratic Programming (SQP) solver to perform single-objective and multi-objective optimisation procedures of a set of real-world waypoints in order to minimise the onboard fuel consumption. The results of both procedures show potential in reducing fuel consumption on a UAV in a ight mission. Additionally, a parallel Hybrid-Electric Propulsion System (HEPS) on a small fixedwing UAV incorporating an Ideal Operating Line (IOL) control strategy was developed. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine was determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

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A large part of the rural people of developing countries use traditional biomass stoves to meet their cooking and heating energy demands. These stoves possess very low thermal efficiency; besides, most of them cannot handle agricultural wastes. Thus, there is a need to develop an alternate cooking contrivance which is simple, efficient and can handle a range of biomass including agricultural wastes. In this reported work, a highly densified solid fuel block using a range of low cost agro residues has been developed to meet the cooking and heating needs. A strategy was adopted to determine the best suitable raw materials, which was optimized in terms of cost and performance. Several experiments were conducted using solid fuel block which was manufactured using various raw materials in different proportions; it was found that fuel block composed of 40% biomass, 40% charcoal powder, 15% binder and 5% oxidizer fulfilled the requirement. Based on this finding, fuel blocks of two different configurations viz. cylindrical shape with single and multi-holes (3, 6, 9 and 13) were constructed and its performance was evaluated. For instance, the 13 hole solid fuel block met the requirement of domestic cooking; the mean thermal power was 1.6 kWth with a burn time of 1.5 h. Furthermore, the maximum thermal efficiency recorded for this particular design was 58%. Whereas, the power level of single hole solid fuel block was found to be lower but adequate for barbecue cooking application.

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In this paper, we present dynamic voltage and frequency Managed 256 x 64 SRAM block in 65 nm technology, for frequency ranging from 100 MHz to 1 GHz. The total energy is minimized for any operating frequency in the above range and leakage energy is minimized during standby mode. Since noise margin of SRAM cell deteriorates at low voltages, we propose static noise margin improvement circuitry, which symmetrizes the SRAM cell by controlling the body bias of pull down NMOS transistor. We used a 9T SRAM cell that isolates Read and hold noise margin and has less leakage. We have implemented an efficient technique of pushing address decoder into zigzag- super-cut-off in stand-by mode without affecting its performance in active mode of operation. The read bit line (RBL) voltage drop is controlled and pre-charge of bit lines is done only when needed for reducing power wastage.

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In this paper analytical expressions for optimal Vdd and Vth to minimize energy for a given speed constraint are derived. These expressions are based on the EKV model for transistors and are valid in both strong inversion and sub threshold regions. The effect of gate leakage on the optimal Vdd and Vth is analyzed. A new gradient based algorithm for controlling Vdd and Vth based on delay and power monitoring results is proposed. A Vdd-Vth controller which uses the algorithm to dynamically control the supply and threshold voltage of a representative logic block (sum of absolute difference computation of an MPEG decoder) is designed. Simulation results using 65 nm predictive technology models are given.

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This paper describes a dynamic voltage frequency control scheme for a 256 X 64 SRAM block for reducing the energy in active mode and stand-by mode. The DVFM control system monitors the external clock and changes the supply voltage and the body bias so as to achieve a significant reduction in energy. The behavioral model of the proposed DVFM control system algorithm is described and simulated in HDL using delay and energy parameters obtained through SPICE simulation. The frequency range dictated by an external controller is 100 MHz to I GHz. The supply voltage of the complete memory system is varied in steps of 50 mV over the range of 500 mV to IV. The threshold voltage range of operation is plusmn100 mV around the nominal value, achieving 83.4% energy reduction in the active mode and 86.7% in the stand-by mode. This paper also proposes a energy replica that is used in the energy monitor subsystem of the DVFM system.

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Perfect space-time block codes (STBCs) are based on four design criteria-full-rateness, nonvanishing determinant, cubic shaping, and uniform average transmitted energy per antenna per time slot. Cubic shaping and transmission at uniform average energy per antenna per time slot are important from the perspective of energy efficiency of STBCs. The shaping criterion demands that the generator matrix of the lattice from which each layer of the perfect STBC is carved be unitary. In this paper, it is shown that unitariness is not a necessary requirement for energy efficiency in the context of space-time coding with finite input constellations, and an alternative criterion is provided that enables one to obtain full-rate (rate of complex symbols per channel use for an transmit antenna system) STBCs with larger normalized minimum determinants than the perfect STBCs. Further, two such STBCs, one each for 4 and 6 transmit antennas, are presented and they are shown to have larger normalized minimum determinants than the comparable perfect STBCs which hitherto had the best-known normalized minimum determinants.