Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.

A Dynamic Migration Model for Self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

Matkalla marginaalista valtavirtaan? : Huumeiden käytön lopettaneiden elämäntapa ja toipuminen

On a journey from marginal to mainstream? The lifestyle and recovery of former drug users This thesis studies the lifestyle and recovery of former users of illicit drugs through their experiences. The study describes the life of people with drug problems both during the time they used drugs regularly and after they stopped the use entirely. The focus is on the development of the lifestyle of 32 persons who no longer use drugs. They may have stopped using drugs independently or with the help of a treatment. In this study, persons who have given up drug use with the help of a psychosocially oriented treatment are called non-medicinally treated former users (n=19) whereas opioid addicts who have stopped using drugs through substitution treatment are referred to as substitution treatment patients (n=13). The research material was gathered from theme interviews. The criteria for the focus group of the study included the following: a) the interviewees had had a serious drug problem in their past; b) they had not used drugs for at least one year prior to the interview; c) they were not in an institutional care at the time of the study. This thesis is basically a lifestyle study in which the aspects of lifestyle are used to describe the everyday life of former drug users. The study reviews the whole spectrum of everyday routines, especially the social interaction and subjective experiences of people. The second concept used in this study is recovery, which is described as a process that starts from the abstinence from substances and adoption of the recovery culture and continues as a comprehensive change of the lifestyle, identity and values of an individual. Disengaging from a drug-oriented lifestyle and connected social network as well as finding an individual frame of reference is a demanding process. Years of drug use have often caused complex health and social disadvantages as well as problems with work, education, livelihood, accommodation and human relationships. The effect of the past on the present arises at all levels. The interviews revealed a recovery culture maintaining the lifestyle as well as an adaptive and optimistic approach to the future among those participating in the study. The study shows that an adequate distance from acute substance use is a precondition for the beginning of the recovery process, yet abstinence in itself tells nothing about the actual recovery. The study describes how some recovering users find a meaning in life easily whereas others have to work actively for their recovery. Detaching oneself from the feeling of adopted abnormality connected with substance addiction forms an important basis for satisfying abstinence. Peer groups support the development of counter-cultures and abstinence or the support is received from the community formed in the substitution treatment clinic.

An agent based adaptive bandwidth allocation scheme for multimedia applications

Bandwidth allocation for multimedia applications in case of network congestion and failure poses technical challenges due to bursty and delay sensitive nature of the applications. The growth of multimedia services on Internet and the development of agent technology have made us to investigate new techniques for resolving the bandwidth issues in multimedia communications. Agent technology is emerging as a flexible promising solution for network resource management and QoS (Quality of Service) control in a distributed environment. In this paper, we propose an adaptive bandwidth allocation scheme for multimedia applications by deploying the static and mobile agents. It is a run-time allocation scheme that functions at the network nodes. This technique adaptively finds an alternate patchup route for every congested/failed link and reallocates the bandwidth for the affected multimedia applications. The designed method has been tested (analytical and simulation)with various network sizes and conditions. The results are presented to assess the performance and effectiveness of the approach. This work also demonstrates some of the benefits of the agent based schemes in providing flexibility, adaptability, software reusability, and maintainability. (C) 2004 Elsevier Inc. All rights reserved.

A Dynamic Migration Model for self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

Mahanadi streamflow: climate change impact assessment and adaptive strategies

Impacts of climate change on hydrology are assessed by downscaling large scale general circulation model (GCM) outputs of climate variables to local scale hydrologic variables. This modelling approach is characterized by uncertainties resulting from the use of different models, different scenarios, etc. Modelling uncertainty in climate change impact assessment includes assigning weights to GCMs and scenarios, based on their performances, and providing weighted mean projection for the future. This projection is further used for water resources planning and adaptation to combat the adverse impacts of climate change. The present article summarizes the recent published work of the authors on uncertainty modelling and development of adaptation strategies to climate change for the Mahanadi river in India.

Some observations on the behaviour of colchicine-treated cells during recovery in Allium CEPA

The accidental discovery of a cell with haploid number of diplochromosomes in squashes of colchicine-treated root tips led to a search for haploid anaphases in treated roots allowed to recover in water. No haploid anaphases were seen. Apart from the divisional stages of diploid and tetraploid nuclei, cells with two pro-, meta- and ana-phases were observed. The formation of distinct cell boundaries by each nucleus of an originally multinucleate cell indicates their potentialities in this direction.

High performance VLSI architecture design for H.264 CAVLC decoder

H.264 video standard achieves high quality video along with high data compression when compared to other existing video standards. H.264 uses context-based adaptive variable length coding (CAVLC) to code residual data in Baseline profile. In this paper we describe a novel architecture for CAVLC decoder including coeff-token decoder, level decoder total-zeros decoder and run-before decoder UMC library in 0.13 mu CMOS technology is used to synthesize the proposed design. The proposed design reduces chip area and improves critical path performance of CAVLC decoder in comparison with [1]. Macroblock level (including luma and chroma) pipeline processing for CAVLC is implemented with an average of 141 cycles (including pipeline buffering) per macroblock at 250MHz clock frequency. To compare our results with [1] clock frequency is constrained to 125MHz. The area required for the proposed architecture is 17586 gates, which is 22.1% improvement in comparison to [1]. We obtain a throughput of 1.73 * 10(6) macroblocks/second, which is 28% higher than that reported in [1]. The proposed design meets the processing requirement of 1080HD [5] video at 30frames/seconds.

An efficient and scalable checkpointing and recovery algorithm for distributed systems

In this paper, we describe an efficient coordinated-checkpointing and recovery algorithm which can work even when the channels are assumed to be non-FIFO, and messages may be lost. Nodes are assumed to be autonomous, and they do not block while taking checkpoints. Based on the local conditions, any process can request the previous coordinator for the 'permission' to initiate a new checkpoint. Allowing multiple initiators of checkpoints avoids the bottleneck associated with a single initiator, but the algorithm permits only a single instance of checkpointing process at any given time, thus reducing much of the overhead associated with multiple initiators of distributed algorithms.

Effective treatment of infectious diseases: A nonlinear adaptive control theoretic approach

A nonlinear adaptive system theoretic approach is presented in this paper for effective treatment of infectious diseases that affect various organs of the human body. The generic model used does not represent any specific disease. However, it mimics the generic immunological dynamics of the human body under pathological attack, including the response to external drugs. From a system theoretic point of view, drugs can be interpreted as control inputs. Assuming a set of nominal parameters in the mathematical model, first a nonlinear controller is designed based on the principle of dynamic inversion. This treatment strategy was found to be effective in completely curing "nominal patients". However, in some cases it is ineffective in curing "realistic patients". This leads to serious (sometimes fatal) damage to the affected organ. To make the drug dosage design more effective, a model-following neuro-adaptive control design is carried out using neural networks, which are trained (adapted) online. From simulation studies, this adaptive controller is found to be effective in killing the invading microbes and healing the damaged organ even in the presence of parameter uncertainties and continuing pathogen attack.

A neuro-adaptive augmented optimal dynamic inversion approach for effective and efficient treatment of chronic myelogenous leukemia

Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an efficient technique is presented for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used for the control (medication) synthesis. First, taking a set of nominal parameters, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat nominal patients (patients having same nominal parameters as used for the control design) effectively. However, since the parameters of an actual patient can be different from that of the ideal patient, to make the treatment strategy more effective and efficient, a model-following neuro-adaptive controller is augmented to the nominal controller. In this approach, a neural network trained online (based on Lyapunov stability theory) facilitates a new adaptive controller, computed online. From the simulation studies, this adaptive control design approach (treatment strategy) is found to be very effective to treat the CML disease for actual patients. Sufficient generality is retained in the theoretical developments in this paper, so that the techniques presented can be applied to other similar problem as well. Note that the technique presented is computationally non-intensive and all computations can be carried out online.

Adaptive load control of the central processor in a distributed system with a star topology

The author presents adaptive control techniques for controlling the flow of real-time jobs from the peripheral processors (PPs) to the central processor (CP) of a distributed system with a star topology. He considers two classes of flow control mechanisms: (1) proportional control, where a certain proportion of the load offered to each PP is sent to the CP, and (2) threshold control, where there is a maximum rate at which each PP can send jobs to the CP. The problem is to obtain good algorithms for dynamically adjusting the control level at each PP in order to prevent overload of the CP, when the load offered by the PPs is unknown and varying. The author formulates the problem approximately as a standard system control problem in which the system has unknown parameters that are subject to change. Using well-known techniques (e.g., naive-feedback-controller and stochastic approximation techniques), he derives adaptive controls for the system control problem. He demonstrates the efficacy of these controls in the original problem by using the control algorithms in simulations of a queuing model of the CP and the load controls.

Optimal Blood Glucose Regulation using Single Network Adaptive Critics

Diabetes is a serious disease during which the body's production and use of insulin is impaired, causing glucose concentration level toincrease in the bloodstream. Regulating blood glucose levels as close to normal as possible, leads to a substantial decrease in long term complications of diabetes. In this paper, an intelligent neural network on-line optimal feedback treatment strategy based on nonlinear optimal control theory is presented for the disease using subcutaneous treatment strategy. A simple mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system is considered based on the Bergman's minimal model. A glucose infusion term representing the effect of glucose intake resulting from a meal is introduced into the model equations. The efficiency of the proposed controllers is shown taking random parameters and random initial conditions in presence of physical disturbances like food intake. A comparison study with linear quadratic regulator theory brings Out the advantages of the nonlinear control synthesis approach. Simulation results show that unlike linear optimal control, the proposed on-line continuous infusion strategy never leads to severe hypoglycemia problems.

A novel fiber-coated strong base-type anion exchanger with superfast kinetics. Removal and recovery of silver thiosulfate from aqueous solutions

A commercial acrylic fiber with 92% (w/w) acrylonitrile content was partially hydrolyzed converting a fraction of the nitrile (-CN) groups to carboxylic acid (-COOH) groups, to coat the fiber with polyethylenimine (PEI) resin, which was then crosslinked with glutaraldehyde and further quaternized with ethyl chloroacetate to produce a novel strong-base anionic exchanger in the form of fiber. Designated as PAN(QPEI.XG)(Cl-), the fibrous sorbent was compared with a commercial bead-form resin Amberlite IRA-458(Cl-) in respect of sorption capacity, selectivity, and kinetics for removal of silver thiosulfate complexes from aqueous solutions. Though the saturation level of [Ag(S2O3)(2)](3-) on PAN(QPEI.XG)(Cl-) is considerably less than that on IRA-458(Cl-), the gel-coated fibrous sorbent exhibits, as compared to the bead-form sorbent, a significantly higher sorption selectivity for the silver thiosulfate complex in the presence of excess of other anions Such as S2O32-, SO42-, and Cl-, and a remarkably faster rate of both sorption and stripping. The initial uptake of the sorbate by the fibrous sorbent is nearly instantaneous, reaching up to similar to 80% of the saturation capacity within 10 s, as compared to only similar to 12% on the bead-form sorbent. The high initial rate of uptake fits a shell-core kinetic model for sorption on fiber of cylindrical geometry. With 4M HCl, the stripping of the sorbed silver complex from the fibrous sorbent is clean and nearly instantaneous, while, in contrast, a much slower rate of stripping on the bead-form sorbent leads to its fouling due to a slow decomposition of the silver thiosulfate complex in the acidic medium.