Developing architectural platforms: a disciplined approach

The Mescal project brings a formalized, disciplined methodology to the design of programmable platform-based systems, enabling the exploration of a wide array of architectures and a correct-by-construction path to implementation.     

A k-step predictive scheme for speed control of dieseldriven power plants

An adaptive speed control scheme for diesel prime movers is presented. Diesel prime movers are characterized by nonlinear, time-varying parameters including a nonlinear input dead-time variation that introduces an unknown delay between the injection of fuel and the production of engine torque. Such plants are difficult to control by conventional proportional-integral (PI) controllers. It is shown that by assuming the existence of an additional system time constant, an explicit estimate of the plant parameters and dead-time may be obtained. The algorithm converges rapidly. The resulting predictor can be used to set up a k-step ahead predictive controller. Studies that compare the performance of the adaptive scheme to that of a fixed, tuned, PI controller are presented. The algorithm is shown to be flexible enough to operate under a wide range of droop settings and is equally applicable to various operating conditions     

Water-Energy Nexus in Resource-poor Economies: The Indian Experience

The paper examines the nature of water-energy interactions at the level of end users in an economy where the demand for both water and energy exceeds the available supplies of these resources. The paper attempts an assessment of the nature of coping strategies adopted by individuals to deal with shortages/uncertainties/unreliability in the availability of water and energy per se and in inter-linked activities, and to provide indicative estimates of the cost of the prevailing supply scenario. The paper also examines the nature of policy interventions that could help in moving towards bridging the gap between the demand and supply of water and energy, especially in inter-linked activities. The scope of the paper is confined to the agricultural/irrigation and urban water supply sectors. Attempts at bridging the gap between demand and supply of both the resources call for both short-run and long-run solutions. A favourable policy environment, improved management of utilities, better organization and methods of existing infrastructure, metering of consumption, charging of rational tariffs for these services, larger investments in the creation of new capacities and a more active role of the private sector could to a large extent help in narrowing the gap and making the water and energy sectors more sustainable in the long run.     

Cross-entropy optimisation of multiple-input multiple-output capacity by transmit antenna selection

Radio channel capacity can be increased dramatically using a multiple-input multiple-output (MIMO) scheme, but at the expense of hardware complexity. An efficient approach for complexity reduction is antenna subset selection at the transmitter and/or receiver. A novel transmit antenna selection algorithm is presented using the cross-entropy optimisation method to maximise channel capacity. In contrast with the existing work, the proposed algorithm guarantees a result to within 99% of the true optimum (i.e. the maximal capacity with selected transmit antennas) with substantially low complexity. The simulation results indicate that the proposed algorithm is independent of the relationship between the selected transmit array size and receive array size. The proposed scheme has the potential to make practical MIMO systems with high performance simpler to implement.     

Structural and Electrical Properties of Ni-Co Nanoferrites Prepared by Co-precipitation Route

A series of Ni_1?x Co _x Fe₂O₄ (x=0.1, 0.2, 0.3, 0.4, 0.5) spinel ferrites have been synthesized successfully using the chemical co-precipitation route. The materials were characterized by X-rays powder diffractometry (XRD) and the electrical properties. The obtained crystallite size variation was within 15 to 33 nm using the Scherrer formula. The dc electrical resistivity was measured as a function of temperature. It is noticed that ?? _dc increases with a rise in temperature. The dielectric measurements were carried out at room temperature as a function of frequency and composition (x). The dielectric constant (????) and dielectric loss tangent (tan???) showed a decreasing trend with increasing field frequency. The ac electrical conductivity is calculated from the dielectric measurements; it increases with the rise in frequency.     

Nanostructured titanium/diamond-like carbon multilayer films: deposition, characterization, and applications

Titanium/diamond-like carbon multilayer (TDML) films were deposited using a hybrid system combining radio frequency (RF)-sputtering and RF-plasma enhanced chemical vapor deposition (PECVD) techniques under a varied number of Ti/diamond-like carbon (DLC) bilayers from 1 to 4, at high base pressure of 1 × 10(-3) Torr. The multilayer approach was used to create unique structures such as nanospheres and nanorods in TDML films, which is confirmed by scanning electron microscopy (SEM) analysis and explained by a hypothetical model. Surface composition was evaluated by X-ray photoelectron spectroscopy (XPS), whereas energy dispersive X-ray analysis (EDAX) and time-of-flight secondary ion mass spectrometer (ToF-SIMS) measurements were performed to investigate the bulk composition. X-ray diffraction (XRD) was used to evaluate the phase and crystallinity of the deposited TDML films. Residual stress in these films was found to be significantly low. These TDML films were found to have excellent nanomechanical properties with maximum hardness of 41.2 GPa. In addition, various nanomechanical parameters were calculated and correlated with each other. Owing to metallic interfacial layer of Ti in multilayer films, the optical properties, electrical properties, and photoluminescence were improved significantly. Due to versatile nanomechanical properties and biocompatibility of DLC and DLC based films, these TDML films may also find applications in biomedical science.     

Variation in structural,optical and magnetic properties of Zn1−xCrxO (x = 0.0, 0.10, 0.15, and 0.20) nanoparticles: Role of dopant concentration on non-saturation of magnetization

Cr-doped ZnO, i.e. Zn_1−xCr_xO (x = 0.00, 0.05, 0.10, 0.15 and 0.20) nanoparticles were synthesized by sol–gel route. The structural and morphological properties of these nanoparticles were investigated by high resolution transmission electron microscope (HRTEM). The average particle size of Zn_1−xCr_xO nanoparticles decreases from 75 to 40 nm with the increase in x from 0.00 to 0.20. The rings observed in selected area diffraction pattern revealed that up to x = 0.10 these nanoparticles have single phase ZnO. However, a secondary spinel phase of ZnCr₂O₄ was observed for higher Cr doping (x ≥ 0.15). The optical band gap calculated using UV–visible absorption was decreased from 3.27 to 2.27 eV with the increase in Cr-doping from 0.00 to 0.20 in ZnO nanoparticles. The undoped ZnO (Zn_1−xCr_xO; x = 0.00) nanoparticles did not show any hysteresis loop at room temperature, however, clear loops were obtained for x = 0.05–0.20. Additionally, magnetization (M) vs. applied magnetic field (H) loops for lower Cr-concentration (x = 0.05) saturate at 5 kOe, and while those with higher Cr concentration (x > 0.05) do not show saturation even at 10 kOe. This may be attributed to increase in the defects at higher Cr-doping into ZnO. The value of saturation magnetization was found to decrease from 4.24 emu g⁻¹ to 1.96 emu g⁻¹ with the increase in Cr doping from x = 0.05 to 0.20 in ZnO and may be due to the secondary ZnCr₂O₄ phase.     

An artificial neural network based adaptive power system stabilizer

An artificial neural network (ANN)-based power system stabilizer (PSS) and its application to power systems are presented. The ANN-based PSS combines the advantages of self-optimizing pole shifting adaptive control strategy and the quick response of ANN to introduce a new generation PSS. A popular type of ANN, the multilayer perceptron with error backpropagation training method, is used in this PSS. The ANN was trained by the training data group generated by the adaptive power system stabilizer (APSS). During the training, the ANN was required to memorize and simulate the control strategy of APSS until the differences were within the specified criteria. Results show that the proposed ANN-based PSS can provide good damping of the power system over a wide operating range and significantly improve the dynamic performance of the system