Spatial distribution of aerosol black carbon over India during pre-monsoon season

Aerosol black carbon (BC) mass concentrations ([BC]), measured continuously during a multi-platform field experiment, Integrated Campaign for Aerosols gases and Radiation Budget (ICARB, March-May 2006), from a network of eight observatories spread over geographically distinct environments of India, (which included five mainland stations, one highland station, and two island stations (one each ill Arabian Sea and Bay of Bengal)) are examined for their spatio-temporal characteristics. During the period of study, [BC] showed large variations across the country, with values ranging from 27 mu g m(3) over industrial/urban locations to as low as 0.065 mu g m(-3) over the Arabian Sea. For all mainland stations, [BC] remained high compared to highland as well as island stations. Among the island stations, Port Blair (PBR) had higher concentration of BC, compared to Minicoy (MCY), implying more absorbing nature of Bay of Bengal aerosols than Arabian Sea. The highland station Nainital (NTL), in the central Himalayas, showed low values of [BC], comparable or even lower than that of the island station PBR, indicating the prevalence of cleaner environment over there. An examination of the changes in the mean temporal features, as the season advances from winter (December-February) to pre-monsoon (March-May), revealed that: (a) Diurnal variations were pronounced over all the mainland stations, with all afternoon low and a nighttime high: (b) At the islands, the diurnal variations, though resembled those over the mainlands, were less pronounced; and (c) In contrast to this, highland station showed an opposite pattern with an afternoon high and a late night or early morning low. The diurnal variations at all stations are mainly caused by the dynamics of local Atmospheric Boundary Layer (ABL), At the entire mainland as well as island stations (except HYD and DEL), [BC] showed a decreasing trend from January to May, This is attributed to the increased convective mixing and to the resulting enhanced vertical dispersal of species in the ABL. In addition, large short-period modulations were observed at DEL and HYD, which appeared to be episodic, An examination of this in the light of the MODIS-derived fire count data over India along with the back-trajectory analysis revealed that advection of BC from extensive forest fires and biomass-burning regions upwind were largely responsible for this episodic enhancement in BC at HYD and DEL.

Oxygen transport in a three-dimensional microvascular network incorporated with early tumour growth and preexisting vessel cooption: Numerical simulation study

We propose a dynamic mathematical model of tissue oxygen transport by a preexisting three-dimensional microvascular network which provides nutrients for an in situ cancer at the very early stage of primary microtumour growth. The expanding tumour consumes oxygen during its invasion to the surrounding tissues and cooption of host vessels. The preexisting vessel cooption, remodelling and collapse are modelled by the changes of haemodynamic conditions due to the growing tumour. A detailed computational model of oxygen transport in tumour tissue is developed by considering (a) the time-varying oxygen advection diffusion equation within the microvessel segments, (b) the oxygen flux across the vessel walls, and (c) the oxygen diffusion and consumption with in the tumour and surrounding healthy tissue. The results show the oxygen concentration distribution at different time points of early tumour growth. In addition, the influence of preexisting vessel density on the oxygen transport has been discussed. The proposed model not only provides a quantitative approach for investigating the interactions between tumour growth and oxygen delivery, but also is extendable to model other molecules or chemotherapeutic drug transport in the future study.

Development of innovative robust stability enhancement algorithms for distribution systems containing distributed generators

This project was a step forward in improving the voltage profile of traditional low voltage distribution networks with high photovoltaic generation or high peak demand. As a practical and economical solution, the developed methods use a Dynamic Voltage Restorer or DVR, which is a series voltage compensator, for continuous and communication-less power quality enhancement. The placement of DVR in the network is optimised in order to minimise its power rating and cost. In addition, new approaches were developed for grid synchronisation and control of DVR which are integrated with the voltage quality improvement algorithm for stable operation.

Effects of increasing neuromuscular electrical stimulation current intensity on cortical sensorimotor network activation: A time domain fNIRS study

Neuroimaging studies have shown neuromuscular electrical stimulation (NMES)-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and secondary somatosensory area (S2), as well as regions of the prefrontal cortex (PFC) known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI), and with reference to voluntary (VOL) wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O₂Hb) and deoxygenated (HHb) hemoglobin concentrations were estimated. The O₂Hb and HHb maps obtained using the General Linear Model (NIRS-SPM) analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O₂Hb and corresponding decrease in HHb) in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2). However, the level and area of contralateral sensorimotor network (including PFC) activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Single network adaptive critic design for power system stabilisers

The recently developed single network adaptive critic (SNAC) design has been used in this study to design a power system stabiliser (PSS) for enhancing the small-signal stability of power systems over a wide range of operating conditions. PSS design is formulated as a discrete non-linear quadratic regulator problem. SNAC is then used to solve the resulting discrete-time optimal control problem. SNAC uses only a single critic neural network instead of the action-critic dual network architecture of typical adaptive critic designs. SNAC eliminates the iterative training loops between the action and critic networks and greatly simplifies the training procedure. The performance of the proposed PSS has been tested on a single machine infinite bus test system for various system and loading conditions. The proposed stabiliser, which is relatively easier to synthesise, consistently outperformed stabilisers based on conventional lead-lag and linear quadratic regulator designs.

Location of concentrators in a computer communication network: a stochastic automation search method

The following problem is considered. Given the locations of the Central Processing Unit (ar;the terminals which have to communicate with it, to determine the number and locations of the concentrators and to assign the terminals to the concentrators in such a way that the total cost is minimized. There is alao a fixed cost associated with each concentrator. There is ail upper limit to the number of terminals which can be connected to a concentrator. The terminals can be connected directly to the CPU also In this paper it is assumed that the concentrators can bo located anywhere in the area A containing the CPU and the terminals. Then this becomes a multimodal optimization problem. In the proposed algorithm a stochastic automaton is used as a search device to locate the minimum of the multimodal cost function . The proposed algorithm involves the following. The area A containing the CPU and the terminals is divided into an arbitrary number of regions (say K). An approximate value for the number of concentrators is assumed (say m). The optimum number is determined by iteration later The m concentrators can be assigned to the K regions in (mk) ways (m > K) or (km) ways (K>m).(All possible assignments are feasible, i.e. a region can contain 0,1,…, to concentrators). Each possible assignment is assumed to represent a state of the stochastic variable structure automaton. To start with, all the states are assigned equal probabilities. At each stage of the search the automaton visits a state according to the current probability distribution. At each visit the automaton selects a 'point' inside that state with uniform probability. The cost associated with that point is calculated and the average cost of that state is updated. Then the probabilities of all the states are updated. The probabilities are taken to bo inversely proportional to the average cost of the states After a certain number of searches the search probabilities become stationary and the automaton visits a particular state again and again. Then the automaton is said to have converged to that state Then by conducting a local gradient search within that state the exact locations of the concentrators are determined This algorithm was applied to a set of test problems and the results were compared with those given by Cooper's (1964, 1967) EAC algorithm and on the average it was found that the proposed algorithm performs better.

Where and how to conserve: Extending the scope of spatial reserve network design

Ongoing habitat loss and fragmentation threaten much of the biodiversity that we know today. As such, conservation efforts are required if we want to protect biodiversity. Conservation budgets are typically tight, making the cost-effective selection of protected areas difficult. Therefore, reserve design methods have been developed to identify sets of sites, that together represent the species of conservation interest in a cost-effective manner. To be able to select reserve networks, data on species distributions is needed. Such data is often incomplete, but species habitat distribution models (SHDMs) can be used to link the occurrence of the species at the surveyed sites to the environmental conditions at these locations (e.g. climatic, vegetation and soil conditions). The probability of the species occurring at unvisited location is next predicted by the model, based on the environmental conditions of those sites. The spatial configuration of reserve networks is important, because habitat loss around reserves can influence the persistence of species inside the network. Since species differ in their requirements for network configuration, the spatial cohesion of networks needs to be species-specific. A way to account for species-specific requirements is to use spatial variables in SHDMs. Spatial SHDMs allow the evaluation of the effect of reserve network configuration on the probability of occurrence of the species inside the network. Even though reserves are important for conservation, they are not the only option available to conservation planners. To enhance or maintain habitat quality, restoration or maintenance measures are sometimes required. As a result, the number of conservation options per site increases. Currently available reserve selection tools do however not offer the ability to handle multiple, alternative options per site. This thesis extends the existing methodology for reserve design, by offering methods to identify cost-effective conservation planning solutions when multiple, alternative conservation options are available per site. Although restoration and maintenance measures are beneficial to certain species, they can be harmful to other species with different requirements. This introduces trade-offs between species when identifying which conservation action is best applied to which site. The thesis describes how the strength of such trade-offs can be identified, which is useful for assessing consequences of conservation decisions regarding species priorities and budget. Furthermore, the results of the thesis indicate that spatial SHDMs can be successfully used to account for species-specific requirements for spatial cohesion - in the reserve selection (single-option) context as well as in the multi-option context. Accounting for the spatial requirements of multiple species and allowing for several conservation options is however complicated, due to trade-offs in species requirements. It is also shown that spatial SHDMs can be successfully used for gaining information on factors that drive a species spatial distribution. Such information is valuable to conservation planning, as better knowledge on species requirements facilitates the design of networks for species persistence. This methods and results described in this thesis aim to improve species probabilities of persistence, by taking better account of species habitat and spatial requirements. Many real-world conservation planning problems are characterised by a variety of conservation options related to protection, restoration and maintenance of habitat. Planning tools therefore need to be able to incorporate multiple conservation options per site, in order to continue the search for cost-effective conservation planning solutions. Simultaneously, the spatial requirements of species need to be considered. The methods described in this thesis offer a starting point for combining these two relevant aspects of conservation planning.

Relative electrical distance concept for evaluation of network reactive power and loss contributions in a deregulated system

With the liberalisation of electricity market it has become very important to determine the participants making use of the transmission network.Transmission line usage computation requires information of generator to load contributions and the path used by various generators to meet loads and losses. In this study relative electrical distance (RED) concept is used to compute reactive power contributions from various sources like generators, switchable volt-amperes reactive(VAR) sources and line charging susceptances that are scattered throughout the network, to meet the system demands. The transmission line charge susceptances contribution to the system reactive flows and its aid extended in reducing the reactive generation at the generator buses are discussed in this paper. Reactive power transmission cost evaluation is carried out in this study. The proposed approach is also compared with other approaches viz.,proportional sharing and modified Y-bus.Detailed case studies with base case and optimised results are carried out on a sample 8-bus system. IEEE 39-bus system and a practical 72-bus system, an equivalent of Indian Southern grid are also considered for illustration and results are discussed.

Modelling heterogeneity of concrete using 2D lattice network for concrete fracture and comparison with AE study

In this paper, numerical modelling of fracture in concrete using two-dimensional lattice model is presented and also a few issues related to lattice modelling technique applicable to concrete fracture are reviewed. A comparison is made with acoustic emission (AE) events with the number of fractured elements. To implement the heterogeneity of the plain concrete, two methods namely, by generating grain structure of the concrete using Fuller's distribution and the concrete material properties are randomly distributed following Gaussian distribution are used. In the first method, the modelling of the concrete at meso level is carried out following the existing methods available in literature. The shape of the aggregates present in the concrete are assumed as perfect spheres and shape of the same in two-dimensional lattice network is circular. A three-point bend (TPB) specimen is tested in the experiment under crack mouth opening displacement (CMOD) control at a rate of 0.0004 mm/sec and the fracture process in the same TPB specimen is modelled using regular triangular 2D lattice network. Load versus crack mouth opening isplacement (CMOD) plots thus obtained by using both the methods are compared with experimental results. It was observed that the number of fractured elements increases near the peak load and beyond the peak load. That is once the crack starts to propagate. AE hits also increase rapidly beyond the peak load. It is compulsory here to mention that although the lattice modelling of concrete fracture used in this present study is very similar to those already available in literature, the present work brings out certain finer details which are not available explicitly in the earlier works.

Delay Optimal Scheduling in a Two-Hop Vehicular Relay Network

We study a scheduling problem in a wireless network where vehicles are used as store-and-forward relays, a situation that might arise, for example, in practical rural communication networks. A fixed source node wants to transfer a file to a fixed destination node, located beyond its communication range. In the absence of any infrastructure connecting the two nodes, we consider the possibility of communication using vehicles passing by. Vehicles arrive at the source node at renewal instants and are known to travel towards the destination node with average speed v sampled from a given probability distribution. Th source node communicates data packets (or fragments) of the file to the destination node using these vehicles as relays. We assume that the vehicles communicate with the source node and the destination node only, and hence, every packet communication involves two hops. In this setup, we study the source node's sequential decision problem of transferring packets of the file to vehicles as they pass by, with the objective of minimizing delay in the network. We study both the finite file size case and the infinite file size case. In the finite file size case, we aim to minimize the expected file transfer delay, i.e. expected value of the maximum of the packet sojourn times. In the infinite file size case, we study the average packet delay minimization problem as well as the optimal tradeoff achievable between the average queueing delay at the source node buffer and the average transit delay in the relay vehicle.

Deterministic schemes for key distribution in wireless sensor networks

In this paper, we propose a new security metric for measuring resilience of a symmetric key distribution scheme in wireless sensor network. A polynomial-based and a novel complete connectivity schemes are proposed and an analytical comparison, in terms of security and connectivity, between the schemes is shown. Motivated by the schemes, we derive general expressions for security and connectivity. A number of conclusions are made using these general expressions.

Jointly optimal power control and routing for a single cell, dense, ad hoc wireless network

We consider a dense, ad hoc wireless network confined to a small region, such that direct communication is possible between any pair of nodes. The physical communication model is that a receiver decodes the signal from a single transmitter, while treating all other signals as interference. Data packets are sent between source-destination pairs by multihop relaying. We assume that nodes self-organise into a multihop network such that all hops are of length d meters, where d is a design parameter. There is a contention based multiaccess scheme, and it is assumed that every node always has data to send, either originated from it or a transit packet (saturation assumption). In this scenario, we seek to maximize a measure of the transport capacity of the network (measured in bit-meters per second) over power controls (in a fading environment) and over the hop distance d, subject to an average power constraint. We first argue that for a dense collection of nodes confined to a small region, single cell operation is efficient for single user decoding transceivers. Then, operating the dense ad hoc network (described above) as a single cell, we study the optimal hop length and power control that maximizes the transport capacity for a given network power constraint. More specifically, for a fading channel and for a fixed transmission time strategy (akin to the IEEE 802.11 TXOP), we find that there exists an intrinsic aggregate bit rate (Theta(opt) bits per second, depending on the contention mechanism and the channel fading characteristics) carried by the network, when operating at the optimal hop length and power control. The optimal transport capacity is of the form d(opt)((P) over bar (t)) x Theta(opt) with d(opt) scaling as (P) over bar (1/eta)(t), where (P) over bar (t) is the available time average transmit power and eta is the path loss exponent. Under certain conditions on the fading distribution, we then provide a simple characterisation of the optimal operating point.

A neural network based CBIR system using STI features and relevance feedback

Multimedia mining primarily involves, information analysis and retrieval based on implicit knowledge. The ever increasing digital image databases on the Internet has created a need for using multimedia mining on these databases for effective and efficient retrieval of images. Contents of an image can be expressed in different features such as Shape, Texture and Intensity-distribution(STI). Content Based Image Retrieval(CBIR) is an efficient retrieval of relevant images from large databases based on features extracted from the image. Most of the existing systems either concentrate on a single representation of all features or linear combination of these features. The paper proposes a CBIR System named STIRF (Shape, Texture, Intensity-distribution with Relevance Feedback) that uses a neural network for nonlinear combination of the heterogenous STI features. Further the system is self-adaptable to different applications and users based upon relevance feedback. Prior to retrieval of relevant images, each feature is first clustered independent of the other in its own space and this helps in matching of similar images. Testing the system on a database of images with varied contents and intensive backgrounds showed good results with most relevant images being retrieved for a image query. The system showed better and more robust performance compared to existing CBIR systems

Distribution of ionic charge carriers and migration barriers in binary alkali silicate glasses

Likely spatial distributions of network-modifying (and mobile) cations in (oxide) glasses are discussed here. At very low modifier concentrations, the ions form dipoles with non-bridging oxygen centres while, at higher levels of modification, the cations tend to order as a result of Coulombic interactions. Activation energies for cation migration are calculated, assuming that the ions occupy (face-sharing) octahedral sites. It is found that conductivity activation energy decreases markedly with increasing modifier content, in agreement with experiment.