Improved Multilevel Hysteresis Current Regulation and Capacitor Voltage Balancing Schemes for Flying Capacitor Multilevel Inverter

This paper focuses on the development of multilevel hysteresis current regulation strategies. Two such strategies have been discussed and some modifications in their control tasks have been proposed to achieve more reliable and improved performance. In general, the multiband concept has been used while making the proposals. The hysteresis band size considerations have also been presented by taking into account the desired and existing system conditions. The proposed modulation schemes have been applied to a five-level flying-capacitor inverter, whose operation under hysteresis current control mode is much less established. A new method of flying-capacitor voltage balancing is proposed which ensures balanced flying-capacitor voltages and, at the same time, maintains the desired current profile. It uses a time-based approach for controlling the capacitor voltages and achieves appreciable voltage spectrum under wide range of load power factor conditions. The performance of the proposed strategies is confirmed through both simulation and experimental investigations.     

Attack Resilient and Efficient Protocol based on Greedy Perimeter Coordinator Routing—Mobility Awareness for Preventing the Attack in the VANET

Wireless Personal Communications - A Greedy Perimeter Coordinator Routing and Mobility Awareness (GPCR-MA) vehicular routing is a widely accepted routing protocol for VANET (Vehicular Ad hoc...     

An Adaptive Non Reference Anchor Array Framework for Audio Retrieval in Teleconferencing Environment

In this paper, an adaptive framework for audio retrieval in live teleconferencing environments with multiple participants is proposed. The framework uses a non reference anchor array (NRA) to capture the interfering speech sources, in addition to the primary array that captures the speech source of interest (SOI). A linearly constrained-minimum variance (LC-MV) beamformer is used herein such that the signal coming from the look direction is preserved while interferences coming from the non look direction are nulled. Additionally, the reverberant component of the speech acquired by this framework is removed by a novel method that uses the linear prediction (LP) residual cepstrum. This method does not require the computation of the acoustic impulse response (AIR) of the teleconferencing room and hence is computationally efficient. The NRA framework is therefore able to remove correlated noise coming from the direction of the SOI and also dereverberating the noise free signal. The performance of the proposed framework is evaluated by conducting experiments on clean speech acquisition from distant microphone arrays. Experiments on distant speech recognition are also conducted using the TIMIT and MONC databases. Experimental results obtained from the proposed framework indicate a reasonable improvement over correlation, subspace and standard minimum variance beamforming methods. The application of the framework in audio retrieval in a live teleconferencing environment with multiple participants is also discussed.     

Baselines for carbon emissions in the Indian and Chinese power sectors: Implications for international carbon trading

The study examines the dynamics of carbon emissions baselines of electricity generation in Indian states and Chinese provinces in the backdrop of ongoing electricity sector reforms in these countries. Two Indian states—Gujarat and Andhra Pradesh, and three Chinese provinces–Guangdong, Liaoning and Hubei have been chosen for detailed analysis to bring out regional variations that are not captured in aggregate country studies. The study finds that fuel mix is the main driver behind the trends exhibited by the carbon baselines in these five cases. The cases confirm that opportunities exist in the Indian and Chinese electricity sectors to lower carbon intensity mainly in the substitution of other fuels for coal and, to a lesser extent, adoption of more efficient and advanced coal-fired generation technology. Overall, the findings suggest that the electricity sectors in India and China are becoming friendlier to the global environment. Disaggregated analysis, detailed and careful industry analysis is essential to establishing a power sector carbon emissions baseline as a reference for CDM crediting. However, considering all the difficulties associated with the baseline issue, our case studies demonstrate that there is merit in examining alternate approaches that rely on more aggregated baselines.     

Analysis and design of optimum interleaver for iterative receivers in IDMA scheme

In this paper, we propose a new tree based interleaver (TBI) to generate different chip‐level interleaving sequences for different users in an interleave division multiple access (IDMA) system, which reduces computational complexity. This method of generation also solves the memory cost problem and reduces the amount of information exchange between mobile stations (MSs) and base stations (BSs) required to specify the interleaver. Simulation results are presented to show that the proposed interleavers perform well as compared to random interleavers in an IDMA system. Copyright © 2008 John Wiley & Sons, Ltd.     

MCF: A Metamodeling-Based Component Composition Framework—Composing SystemC IPs for Executable System Models

Reusing Intellectual Property (IP)-cores accompanied by automated generation of the glue-logic, and automated composability checks can help designers to create efficient system-level models quickly and correctly for fast design space exploration. Furthermore, with the rise of multiple transaction level and register-transfer level abstractions, constructing models with mixed abstraction levels is also important. A framework that allows designers to: 1) describe the structure of components, their interfaces, and their interactions, with a semantically rich visual frontend; 2) automatically select IPs from a component library-based on sound-type theoretic principles; and 3) perform constraint based checks for composability, is highly desirable in this context. A metamodel based framework brings forth further advantages. It helps in: 1) providing rigorous semantics to the visual models; 2) imposing restrictions on the model and on interactions between components through constraints expressed in a constraint language; and 3) enabling type-checking and inference-based facilities. Furthermore, using XML-based schemas to store and process meta-information about the IPs as well as the schematic visual model, allows for an IP selection and integration methodology using existing XML processing tools. With these in mind, we present MCF, a metamodeling-based component composition framework for SystemC-based IP core composition at multiple and mixed abstraction levels, with all the advantages stated above.     

SML-Sys: a functional framework with multiple models of computation for modeling heterogeneous system

System-on-Chip and other complex distributed hardware/software systems contain heterogeneous components. High-level modeling of such systems require frameworks that provide designers with the ability to express concepts of models of computation (MoC)s as modeling constructs. Many system-level modeling frameworks and corresponding modeling notations such as Ptolemy II and SystemC-H facilitate multi-MoC modeling but are based on imperative programming languages (C++, Java, etc). In such frameworks, the computation and communication aspects between the components of models get intertwined thereby hindering its amenability to formal analysis. In this work, we illustrate function-based semantic definitions of MoCs, which are formulated in a functional framework called SML-Sys. We illustrate through a number of examples how to create system models using this functional programming paradigm.     

Rate-distortion optimized tree-structured compression algorithms for piecewise polynomial images.

This paper presents novel coding algorithms based on tree-structured segmentation, which achieve the correct asymptotic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise polynomials, by using an R-D based prune and join scheme. For the one-dimensional case, our scheme is based on binary-tree segmentation of the signal. This scheme approximates the signal segments using polynomial models and utilizes an R-D optimal bit allocation strategy among the different signal segments. The scheme further encodes similar neighbors jointly to achieve the correct exponentially decaying R-D behavior (D(R) - c(o)2(-c1R)), thus improving over classic wavelet schemes. We also prove that the computational complexity of the scheme is of O(N log N). We then show the extension of this scheme to the two-dimensional case using a quadtree. This quadtree-coding scheme also achieves an exponentially decaying R-D behavior, for the polygonal image model composed of a white polygon-shaped object against a uniform black background, with low computational cost of O(N log N). Again, the key is an R-D optimized prune and join strategy. Finally, we conclude with numerical results, which show that the proposed quadtree-coding scheme outperforms JPEG2000 by about 1 dB for real images, like cameraman, at low rates of around 0.15 bpp.     

Improved low energy adaptive clustering hierarchy and its optimum cluster head selection

ABSTRACT

Wireless sensor networks (WSNs) play a vital role in present-day world, which are being used in different types of applications and occupy an important part in networking domain. The main objective of WSNs is to sense and collect the information from a given area of interest and provide the gathered data to the sink. WSN comprises of number of sensor nodes with batteries of limited energy for communication and computational activities, which are not possible to recharge the batteries after their deployment in the region of interest. Therefore, saving battery energy and utilising the limited power to the optimum level for extending network lifetime became the main factor of WSN. Hence, optimum cluster head (CH) selection will make the network to support longer lifetime and balanced energy consumption during its lifetime. Our proposed protocol selects the optimum CH and found out to be more efficient than the existing low energy adaptive clustering hierarchy. The simulated output shows better network lifetime and in some other performance metric.     

Light Amplification and Efficient Electroluminescence from a Solution-Processable Diketopyrrolopyrrole Derivative via Triplet-to-Singlet Upconversion

Over the years, achieving efficient electroluminescence (EL) while simultaneously having low light amplification thresholds under optical excitation has been the key to progression toward the long-thought objective of electrically pumped organic lasers. While significant progress in this regard has been made for organic semiconductors emitting in the blue–green region of the visible spectrum, organic laser dyes with low-energy emission (>600 nm) still suffer from high amplified spontaneous emission (ASE) thresholds and low external quantum efficiencies (EQEs) in devices. Herein, low ASE thresholds and efficient EL are reported from a solution-processable organic laser dye dithiophenyl diketopyrrolopyrrole (DT-DPP). The ASE threshold of 4 µJ cm⁻² at the wavelength of 620 nm is obtained while making constructive use of triplet excitons by doping DT-DPP in a green-emitting host matrix, which exhibits thermally activated delayed fluorescence (TADF). The organic light-emitting diode fabricated from this system gives a high EQE of 7.9% due to the efficient utilization of triplet excitons. Transient EL studies further show that a high reverse intersystem crossing rate is crucial in achieving lasing under electrical pumping from such TADF-assisted fluorescent systems.