Classification of Vehicles using Magnetic Dipole Model

This paper presents an efficient approach to the modeling and classification of vehicles using the magnetic signature of the vehicle. A database was created using the magnetic signature collected over a wide range of vehicles(cars). A vehicle is modeled as an array of magnetic dipoles. The strength of the magnetic dipole and the separation between the magnetic dipoles varies for different vehicles and is dependent on the metallic composition and configuration of the vehicle. Based on the magnetic dipole data model, we present a novel method to extract a feature vector from the magnetic signature. In the classification of vehicles, a linear support vector machine configuration is used to classify the vehicles based on the obtained feature vectors.

Efficient method of moving shadow detection and vehicle classification

Moving shadow detection and removal from the extracted foreground regions of video frames, aim to limit the risk of misconsideration of moving shadows as a part of moving objects. This operation thus enhances the rate of accuracy in detection and classification of moving objects. With a similar reasoning, the present paper proposes an efficient method for the discrimination of moving object and moving shadow regions in a video sequence, with no human intervention. Also, it requires less computational burden and works effectively under dynamic traffic road conditions on highways (with and without marking lines), street ways (with and without marking lines). Further, we have used scale-invariant feature transform-based features for the classification of moving vehicles (with and without shadow regions), which enhances the effectiveness of the proposed method. The potentiality of the method is tested with various data sets collected from different road traffic scenarios, and its superiority is compared with the existing methods. (C) 2013 Elsevier GmbH. All rights reserved.

Classification of Vehicles Using Magnetic Field Angle Model

This paper presents an efficient approach to the modeling and classification of vehicles using the magnetic signature of the vehicle. A database was created using the magnetic signature collected over a wide range of vehicles(cars). A sensor dependent approach called as Magnetic Field Angle Model is proposed for modeling the obtained magnetic signature. Based on the data model, we present a novel method to extract the feature vector from the magnetic signature. In the classification of vehicles, a linear support vector machine configuration is used to classify the vehicles based on the obtained feature vectors.

Graphene Oxide-MnFe2O4 Magnetic Nanohybrids for Efficient Removal of Lead and Arsenic from Water

We show that the hybrids of single-layer graphene oxide with manganese ferrite magnetic nanoparticles have the best adsorption properties for efficient removal of Pb(II), As(III), and As(V) from contaminated water. The nanohybrids prepared by coprecipitation technique were characterized using atomic force and scanning electron microscopies, Fourier transformed infrared spectroscopy, Raman spectroscopy, X-ray diffraction, and surface area measurements. Magnetic character of the nanohybrids was ascertained by a vibrating sample magnetometer. Batch experiments were carried out to quantify the adsorption kinetics and adsorption capacities of the nanohybrids and compared with the bare nanoparticles of MnFe2O4. The adsorption data from our experiments fit the Langmuir isotherm, yielding the maximum adsorption capacity higher than the reported values so far. Temperature-dependent adsorption studies have been done to estimate the free energy and enthalpy of adsorption. Reusability, ease of magnetic separation, high removal efficiency, high surface area, and fast kinetics make these nanohybrids very attractive candidates for low-cost adsorbents for the effective coremoval of heavy metals from contaminated water.

Performance Enhancement of Piezoelectric Energy Harvesters Using Multilayer and Multistep Beam Configurations

Low-power requirements of contemporary sensing technology attract research on alternate power sources that can replace batteries. Energy harvesters absorb ambient energy and function as power sources for sensors and other low-power devices. Piezoelectric bimorphs have been demonstrating the preeminence in converting the mechanical energy in ambient vibrations into electrical energy. Improving the performance of these harvesters is pivotal as the energy in ambient vibrations is innately low. In this paper, we focus on enhancing the performance of piezoelectric harvesters through a multilayer and, in particular, a multistep configuration. Partial coverage of piezoelectric material in steps along the length of a cantilever beam results in a multistep piezoelectric energy harvester. We also discuss obtaining an approximate deformation curve for the beam with multiple steps in a computationally efficient manner. We find that the power generated by a multistep beam is almost 90% more than that by a multilayer harvester made out of the same volume of polyvinylidinefluoride ( PVDF), further corroborated experimentally. Improvements observed in the power generated prove to be a boon for weakly coupled low profile piezoelectric materials. Thus, in spite of the weak piezoelectric coupling observed in PVDF, its energy harvesting capability can be improved significantly using it in a multistep piezoelectric beam configuration.

Energy Sharing for Multiple Sensor Nodes With Finite Buffers

We consider the problem of finding optimal energy sharing policies that maximize the network performance of a system comprising of multiple sensor nodes and a single energy harvesting (EH) source. Sensor nodes periodically sense the random field and generate data, which is stored in the corresponding data queues. The EH source harnesses energy from ambient energy sources and the generated energy is stored in an energy buffer. Sensor nodes receive energy for data transmission from the EH source. The EH source has to efficiently share the stored energy among the nodes to minimize the long-run average delay in data transmission. We formulate the problem of energy sharing between the nodes in the framework of average cost infinite-horizon Markov decision processes (MDPs). We develop efficient energy sharing algorithms, namely Q-learning algorithm with exploration mechanisms based on the epsilon-greedy method as well as upper confidence bound (UCB). We extend these algorithms by incorporating state and action space aggregation to tackle state-action space explosion in the MDP. We also develop a cross entropy based method that incorporates policy parameterization to find near optimal energy sharing policies. Through simulations, we show that our algorithms yield energy sharing policies that outperform the heuristic greedy method.

Achieving Highly Efficient, Selective, and Stable CO2 Reduction on Nitrogen-Doped Carbon Nanotubes

The challenge in the electrosynthesis of fuels from CO2 is to achieve durable and active performance with cost-effective catalysts. Here, we report that carbon nanotubes (CNTs), doped with nitrogen to form resident electron-rich defects, can act as highly efficient and, more importantly, stable catalysts for the conversion of CO2 to CO. The unprecedented overpotential (-0.18 V) and selectivity (80%) observed on nitrogen-doped CNTs (NCNTs) are attributed to their unique features to facilitate the reaction, including (i) high electrical conductivity, (ii) preferable catalytic sites (pyridinic N defects), and (iii) low free energy for CO2 activation and high barrier for hydrogen evolution. Indeed, DFT calculations show a low free energy barrier for the potential-limiting step to form key intermediate COOH as well as strong binding energy of adsorbed CON and weak binding energy for the adsorbed CO. The highest selective site toward CO production is pyridinic N, and the NCNT-based electrodes exhibit no degradation over 10 h of continuous operation, suggesting the structural stability of the electrode.

A TDMA-based Energy Aware MAC (TEA-MAC) Protocol for Reliable Multicast in WSNs

Multicast in wireless sensor networks (WSNs) is an efficient way to spread the same data to multiple sensor nodes. It becomes more effective due to the broadcast nature of wireless link, where a message transmitted from one source is inherently received by all one-hop receivers, and therefore, there is no need to transmit the message one by one. Reliable multicast in WSNs is desirable for critical tasks like code updation and query based data collection. The erroneous nature of wireless medium coupled with limited resource of sensor nodes, makes the design of reliable multicast protocol a challenging task. In this work, we propose a time division multiple access (TDMA) based energy aware media access and control (TEA-MAC) protocol for reliable multicast in WSNs. The TDMA eliminates collisions, overhearing and idle listening, which are the main sources of reliability degradation and energy consumption. Furthermore, the proposed protocol is parametric in the sense that it can be used to trade-off reliability with energy and delay as per the requirement of the underlying applications. The performance of TEA-MAC has been evaluated by simulating it using Castalia network simulator. Simulation results show that TEA-MAC is able to considerably improve the performance of multicast communication in WSNs.

Efficient visible light photocatalytic activity and enhanced stability of BiOBr/Cd(OH)(2) heterostructures

Novel BioBr/Cd(OH)(2) heterostructures were synthesized by a facile chemical bath method under ambient conditions. A series of BiOBr/Cd(OH)(2) heterostructures were obtained by tuning the Bi/Cd molar ratios. The obtained heterostructures were characterized by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and energy dispersive spectroscopy (EDS). Optical properties were studied by UV-visible spectroscopy, diffuse reflectance spectroscopy and photoluminescence (PL). Photocatalytic studies on rhodamine B (RhB) under visible light irradiation showed that the heterostructures are very efficient photocatalysts in mild basic medium. Scavenger test studies confirmed that the photogenerated holes and superoxide radicals (O-2(center dot-)) are the main active species responsible for RhB degradation. Comparison of photoluminescence (PL) intensity suggested that an inhibited charge recombination is crucial for the degradation process over these photocatalysts. Moreover, relative positioning of the valence and conduction band edges of the semiconductors, O-2/O-2(center dot-) and (OH)-O-center dot/H2O redox potentials and HOMO-LUMO levels of RhB appear to be responsible for the hole-specificity of degradation. Photocatalytic recycling experiments indicated the high stability of the catalysts in the reaction medium without any significant loss of activity. This study hence concludes that the heterojunction constructed between Cd(OH)(2) and BiOBr interfaces play a crucial role in influencing the charge carrier dynamics and subsequent photocatalytic activity.

Ordered Pd2Ge Intermetallic Nanoparticles as Highly Efficient and Robust Catalyst for Ethanol Oxidation

Pd2Ge nanoparticles were synthesized by superhydride reduction of K2PdCl4 and GeCl4. The syntheses were performed using a solvothermal method in the absence of surfactants, and the size of the nanoparticles was controlled by varying the reaction time. The powder X-ray diffraction (PXRD) and transmission electron microscopy data suggest that Pd2Ge nanoparticles were formed as an ordered intermetallic phase. In the crystal structure, Pd and Ge atoms occupy two different crystallographic positions with a vacancy in one of the Ge sites, which was proved by PXRD and energy-dispersive X-ray analysis. The catalyst is highly efficient for the electrochemical oxidation of ethanol and is stable up to the 250th cycle in alkaline medium. The electrochemical active surface area and current density values obtained, 1.41 cm(2) and 4.1 mA cm(-2), respectively, are superior to those of the commercial Pd on carbon. The experimentally observed data were interpreted in terms of the combined effect of adsorption energies of CH3CO and OH radical, d-band center model, and work function of the corresponding catalyst surfaces.

Efficient Low Complexity Power Allocation Policies for Wireless Communication Systems Guaranteeing QoS

We consider near-optimal policies for a single user transmitting on a wireless channel which minimize average queue length under average power constraint. The power is consumed in transmission of data only. We consider the case when the power used in transmission is a linear function of the data transmitted. The transmission channel may experience multipath fading. Later, we also extend these results to the multiuser case. We show that our policies can be used in a system with energy harvesting sources at the transmitter. Next we consider data users which require minimum rate guarantees. Finally we consider the system which has both data and real time users. Our policies have low computational complexity, closed form expression for mean delays and require only the mean arrival rate with no queue length information.

Energy conversion in shape memory alloy heat engine - Part II: Simulation

In this paper, a theoretical model proposed in Part I (Zhu et al., 2001a) is used to simulate the behavior of a twin crank NiTi SMA spring based heat engine, which has been experimentally studied by Iwanaga et al. (1988). The simulation results are compared favorably with the measurements. It is found that (1) output torque and heat efficiency decrease as rotation speed increase; (2) both output torque and output power increase with the increase of hot water temperature; (3) at high rotation speed, higher water temperature improves the heat efficiency. On the contrary, at low rotation speed, lower water temperature is more efficient; (4) the effects of initial spring length may not be monotonic as reported. According to the simulation, output torque, output power and heat efficiency increase with the decrease of spring length only in the low rotation speed case. At high rotation speed, the result might be on the contrary.

Dealing with Energy-QoE Trade-Offs in Mobile Video

Scalable video coding allows an efficient provision of video services at different quality levels with different energy demands. According to the specific type of service and network scenario, end users and/or operators may decide to choose among different energy versus quality combinations. In order to deal with the resulting trade-off, in this paper we analyze the number of video layers that are worth to be received taking into account the energy constraints. A single-objective optimization is proposed based on dynamically selecting the number of layers, which is able to minimize the energy consumption with the constraint of a minimal quality threshold to be reached. However, this approach cannot reflect the fact that the same increment of energy consumption may result in different increments of visual quality. Thus, a multiobjective optimization is proposed and a utility function is defined in order to weight the energy consumption and the visual quality criteria. Finally, since the optimization solving mechanism is computationally expensive to be implemented in mobile devices, a heuristic algorithm is proposed. This way, significant energy consumption reduction will be achieved while keeping reasonable quality levels.

Energy transfer between silicon-oxygen-related defects and Yb3+ in transparent glass ceramics containing Ba2TiSi2O 8 nanocrystals

We report on the conversion of near-ultraviolet radiation of 250-350 nm into near-infrared emission of 970-1100 nm in Yb3+-doped transparent glass ceramics containing Ba2TiSi2O8 nanocrystals due to the energy transfer from the silicon-oxygen-related defects to Yb3+ ions. Efficient Yb3+ emission (F-2(5/2)-> F-2(7/2)) was detected under the excitation of defects absorption at 314 nm. The occurrence of energy transfer is proven by both steady state and time-resolved emission spectra, respectively, at 15 K. The Yb2O3 concentration dependent energy transfer efficiency has also been evaluated, and the maximum value is 65% for 8 mol % Yb2O3 doped glass ceramic. These materials are promising for the enhancement of photovoltaic conversion efficiency of silicon solar cells via spectra modification.

Efficient GeV ion generation by ultraintense circularly polarized laser pulse

The interaction of an ultraintense circularly polarized laser pulse and a solid target is studied by one-dimensional particle-in-cell simulations. Ions at the front of the target are reflected by a moving quasisteady electrostatic field and obtain a relativistic velocity. At a laser intensity of 10(22) W/cm(2), almost half of the laser energy is transferred to ions and GeV ions are obtained. Effects of laser polarization state and target thickness on the laser energy conversion are investigated. It is found that a circularly polarized laser pulse can accelerate ions more efficiently than a linearly polarized laser pulse at the same laser and target parameters. A monoenergetic ion bunch is obtained for the ultrathin target, which is accelerated as a single entity. (c) 2007 American Institute of Physics.