Using a structural approach to identify relationships between soil and erosion in a semi-humid forested area, South India

Biogeochemical and hydrological cycles are currently studied on a small experimental forested watershed (4.5 km(2)) in the semi-humid South India. This paper presents one of the first data referring to the distribution and dynamics of a widespread red soil (Ferralsols and Chromic Luvisols) and black soil (Vertisols and Vertic intergrades) cover, and its possible relationship with the recent development of the erosion process. The soil map was established from the observation of isolated soil profiles and toposequences, and surveys of soil electromagnetic conductivity (EM31, Geonics Ltd), lithology and vegetation. The distribution of the different parts of the soil cover in relation to each other was used to establish the dynamics and chronological order of formation. Results indicate that both topography and lithology (gneiss and amphibolite) have influenced the distribution of the soils. At the downslope, the following parts of the soil covers were distinguished: i) red soil system, ii) black soil system, iii) bleached horizon at the top of the black soil and iv) bleached sandy saprolite at the base of the black soil. The red soil is currently transforming into black soil and the transformation front is moving upslope. In the bottom part of the slope, the chronology appears to be the following: black soil > bleached horizon at the top of the black soil > streambed > bleached horizon below the black soil. It appears that the development of the drainage network is a recent process, which was guided by the presence of thin black soil with a vertic horizon less than 2 in deep. Three distinctive types of erosional landforms have been identified: 1. rotational slips (Type 1); 2. a seepage erosion (Type 2) at the top of the black soil profile; 3. A combination of earthflow and sliding in the non-cohesive saprolite of the gneiss occurs at midslope (Type 3). Types 1 and 2 erosion are mainly occurring downslope and are always located at the intersection between the streambed and the red soil-black soil contact. Neutron probe monitoring, along an area vulnerable to erosion types 1 and 2, indicates that rotational slips are caused by a temporary watertable at the base of the black soil and within the sandy bleached saprolite, which behaves as a plane of weakness. The watertable is induced by the ephemeral watercourse. Erosion type 2 is caused by seepage of a perched watertable, which occurs after swelling and closing of the cracks of the vertic clay horizon and within a light textured and bleached horizon at the top of black soil. Type 3 erosion is not related to the red soil-black soil system but is caused by the seasonal seepage of saturated throughflow in the sandy saprolite of the gneiss occurring at midslope. (c) 2006 Elsevier B.V. All rights reserved.

Data mining approaches to software fault diagnosis

Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior and the use of appropriate data mining techniques on the chosen representation. In this paper, we use the sequence of system calls to characterize program execution. The data mining tasks addressed are learning to map system call streams to fault labels and automatic identification of fault causes. Spectrum kernels and SVM are used for the former while latent semantic analysis is used for the latter The techniques are demonstrated for the intrusion dataset containing system call traces. The results show that kernel techniques are as accurate as the best available results but are faster by orders of magnitude. We also show that latent semantic indexing is capable of revealing fault-specific features.

S-matrix for magnons in the D1-D5 system

We show that integrability and symmetries of the near horizon geometry of the D1-D5 system determine the S-matrix for the scattering of magnons with polarizations in AdS(3) x S-3 completely up to a phase. Using semi-classical methods we evaluate the phase to the leading and to the one-loop approximation in the strong coupling expansion. We then show that the phase obeys the unitarity constraint implied by the crossing relations to the one-loop order. We also verify that the dispersion relation obeyed by these magnons is one-loop exact at strong coupling which is consistent with their BPS nature.

Concepts of Static Var System Control For Enhancing Power Transfer in Long Transmission Lines

This paper is concerned with the influence of different levels of complexity in modelling various constituent subsystems on the dynamic stability of power systems compensated by static var systems (SVS) operating on pure voltage control. The system components investigated include thyristor controlled reactor (TCR) transients, SVS delays, network transients, the synchronous generator and automatic voltage regulator (AVR). An overall model is proposed which adequately describes the system performance for small signal perturbations. The SVS performance is validated through detailed nonlinear simulation on a physical simulator.

Automatic verification of distributed logic specifications

Formal specification is vital to the development of distributed real-time systems as these systems are inherently complex and safety-critical. It is widely acknowledged that formal specification and automatic analysis of specifications can significantly increase system reliability. Although a number of specification techniques for real-time systems have been reported in the literature, most of these formalisms do not adequately address to the constraints that the aspects of 'distribution' and 'real-time' impose on specifications. Further, an automatic verification tool is necessary to reduce human errors in the reasoning process. In this regard, this paper is an attempt towards the development of a novel executable specification language for distributed real-time systems. First, we give a precise characterization of the syntax and semantics of DL. Subsequently, we discuss the problems of model checking, automatic verification of satisfiability of DL specifications, and testing conformance of event traces with DL specifications. Effective solutions to these problems are presented as extensions to the classical first-order tableau algorithm. The use of the proposed framework is illustrated by specifying a sample problem.

Towards building an intelligent decision support system for project management

Management of large projects, especially the ones in which a major component of R&D is involved and those requiring knowledge from diverse specialised and sophisticated fields, may be classified as semi-structured problems. In these problems, there is some knowledge about the nature of the work involved, but there are also uncertainties associated with emerging technologies. In order to draw up a plan and schedule of activities of such a large and complex project, the project manager is faced with a host of complex decisions that he has to take, such as, when to start an activity, for how long the activity is likely to continue, etc. An Intelligent Decision Support System (IDSS) which aids the manager in decision making and drawing up a feasible schedule of activities while taking into consideration the constraints of resources and time, will have a considerable impact on the efficient management of the project. This report discusses the design of an IDSS that helps in project planning phase through the scheduling phase. The IDSS uses a new project scheduling tool, the Project Influence Graph (PIG).

A reinforcement learning approach to automatic generation control

This paper formulates the automatic generation control (AGC) problem as a stochastic multistage decision problem. A strategy for solving this new AGC problem formulation is presented by using a reinforcement learning (RL) approach This method of obtaining an AGC controller does not depend on any knowledge of the system model and more importantly it admits considerable flexibility in defining the control objective. Two specific RL based AGC algorithms are presented. The first algorithm uses the traditional control objective of limiting area control error (ACE) excursions, where as, in the second algorithm, the controller can restore the load-generation balance by only monitoring deviation in tie line flows and system frequency and it does not need to know or estimate the composite ACE signal as is done by all current approaches. The effectiveness and versatility of the approaches has been demonstrated using a two area AGC model. (C) 2002 Elsevier Science B.V. All rights reserved.

Continuous-time Single Network Adaptive Critic for Regulator Design of Nonlinear Control Affine Systems

An optimal control law for a general nonlinear system can be obtained by solving Hamilton-Jacobi-Bellman equation. However, it is difficult to obtain an analytical solution of this equation even for a moderately complex system. In this paper, we propose a continuoustime single network adaptive critic scheme for nonlinear control affine systems where the optimal cost-to-go function is approximated using a parametric positive semi-definite function. Unlike earlier approaches, a continuous-time weight update law is derived from the HJB equation. The stability of the system is analysed during the evolution of weights using Lyapunov theory. The effectiveness of the scheme is demonstrated through simulation examples.

Recent Advances in Low CTE and High Density System-on-a-Package (SOP) Substrate with Thin Film Component Integration

The Packaging Research Center has been developing next generation system-on-a-package (SOP) technology with digital, RF, optical, and sensor functions integrated in a single package/module. The goal of this effort is to develop a platform substrate technology providing very high wiring density and embedded thin film passive and active components using PWB compatible materials and processes. The latest SOP baseline process test vehicle has been fabricated on novel Si-matched CTE, high modulus C-SiC composite core substrates using 10mum thick BCB dielectric films with loss tangent of 0.0008 and dielectric constant of 2.65. A semi-additive plating process has been developed for multilayer microvia build-up using BCB without the use of any vacuum deposition or polishing/CMP processes. PWB and package substrate compatible processes such as plasma surface treatment/desmear and electroless/electrolytic pulse reverse plating was used. The smallest line width and space demonstrated in this paper is 6mum with microvia diameters in the 15-30mum range. This build-up process has also been developed on medium CTE organic laminates including MCL-E-679F from Hitachi Chemical and PTFE laminates with Cu-Invar-Cu core. Embedded decoupling capacitors with capacitance density of >500nF/cm2 have been integrated into the build-up layers using sol-gel synthesized BaTiO3 thin films (200-300nm film thickness) deposited on copper foils and integrated using vacuum lamination and subtractive etch processes. Thin metal alloy resistor films have been integrated into the SOP substrate using two methods: (a) NiCrAlSi thin films (25ohms per square) deposited on copper foils (Gould Electronics) laminated on the build-up layers and two step etch process for resistor definition, and (b) electroless plated Ni-W-P thin films (70 ohms to few Kohms per square) on the BCB dielectric by plasma surface treatment and activation. The electrical design and build-up layer structure along- - with key materials and processes used in the fabrication of the SOP4 test vehicle were presented in this paper. Initial results from the high density wiring and embedded thin film components were also presented. The focus of this paper is on integration of materials, processes and structures in a single package substrate for system-on-a-package (SOP) implementation

Effect of gas injection on drag and surface heat transfer rates for a 30 degrees semi-apex angle blunt body flying at Mach 5.75

Effect of coolant gas injection in the stagnation region on the surface heat transfer rates and aerodynamic drag for a large angle blunt body flying at hypersonic Mach number is reported for two stagnation enthalpies. A 60° apex-angle blunt cone model is employed for this purpose with air injection at the nose through a hole of 2mm diameter. The convective surface heating rates and aerodynamic drag are measured simultaneously using surface mounted platinum thin film sensors and internally mounted accelerometer balance system, respectively. About 35–40% reduction in surface heating rates is observed in the vicinity of stagnation region whereas 15–25% reduction in surface heating rates is felt beyond the stagnation region at stagnation enthalpy of 1.6MJ/kg. The aerodynamic drag expressed in terms of drag coefficient is found to increase by 20% due to the air injection.

A neural network based automatic generation control design through reinforcement learning

This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.

Reinforcement learning controllers for automatic generation control in power systems having re-heat units with GRC and dead-band

A new automatic generation controller (AGC) design approach, adopting reinforcement learning (RL) techniques, was recently pro- posed [1]. In this paper we demonstrate the design and performance of controllers based on this RL approach for automatic generation control of systems consisting of units having complex dynamics—the reheat type of thermal units. For such systems, we also assess the capabilities of RL approach in handling realistic system features such as network changes, parameter variations, generation rate constraint (GRC), and governor deadband.

Semi empirical models for selectivity of supercritical carbon dioxide for solid mixtures

Selectivity of the particular solvent to separate a mixture is essential for the optimal design of a separation process. Supercritical carbon dioxide (SCCO2) is widely used as a solvent in the extraction, purification and separation of specialty chemicals. The effect of the temperature and pressure on selectivity is complicated and varies from system to system. The effect of temperature and pressure on selectivity of SCCO2 for different solid mixtures available in literature was analyzed. In this work, we have developed two model equations to correlate the selectivity in terms of temperature and pressure. The model equations have correlated the selectivity of SCCO2 satisfactorily for 18 solid mixtures with an average absolute relative deviation (AARD) of around 5%. (C) 2012 Elsevier B.V. All rights reserved.

On-Chip Memory Architecture Exploration Framework for DSP Processor-Based Embedded System on Chip

Today's SoCs are complex designs with multiple embedded processors, memory subsystems, and application specific peripherals. The memory architecture of embedded SoCs strongly influences the power and performance of the entire system. Further, the memory subsystem constitutes a major part (typically up to 70%) of the silicon area for the current day SoC. In this article, we address the on-chip memory architecture exploration for DSP processors which are organized as multiple memory banks, where banks can be single/dual ported with non-uniform bank sizes. In this paper we propose two different methods for physical memory architecture exploration and identify the strengths and applicability of these methods in a systematic way. Both methods address the memory architecture exploration for a given target application by considering the application's data access characteristics and generates a set of Pareto-optimal design points that are interesting from a power, performance and VLSI area perspective. To the best of our knowledge, this is the first comprehensive work on memory space exploration at physical memory level that integrates data layout and memory exploration to address the system objectives from both hardware design and application software development perspective. Further we propose an automatic framework that explores the design space identifying 100's of Pareto-optimal design points within a few hours of running on a standard desktop configuration.

Ship-Mounted Real-Time Surface Observational System on board Indian Vessels for Validation and Refinement of Model Forcing Fields

A network of ship-mounted real-time Automatic Weather Stations integrated with Indian geosynchronous satellites Indian National Satellites (INSATs)] 3A and 3C, named Indian National Centre for Ocean Information Services Real-Time Automatic Weather Stations (I-RAWS), is established. The purpose of I-RAWS is to measure the surface meteorological-ocean parameters and transmit the data in real time in order to validate and refine the forcing parameters (obtained from different meteorological agencies) of the Indian Ocean Forecasting System (INDOFOS). Preliminary validation and intercomparison of analyzed products obtained from the National Centre for Medium Range Weather Forecasting and the European Centre for Medium-Range Weather Forecasts using the data collected from I-RAWS were carried out. This I-RAWS was mounted on board oceanographic research vessel Sagar Nidhi during a cruise across three oceanic regimes, namely, the tropical Indian Ocean, the extratropical Indian Ocean, and the Southern Ocean. The results obtained from such a validation and intercomparison, and its implications with special reference to the usage of atmospheric model data for forcing ocean model, are discussed in detail. It is noticed that the performance of analysis products from both atmospheric models is similar and good; however, European Centre for Medium-Range Weather Forecasts air temperature over the extratropical Indian Ocean and wind speed in the Southern Ocean are marginally better.