Hybrid Background Subtraction in Video using Bi-level CodeBook Model

Detection of Objects in Video is a highly demanding area of research. The Background Subtraction Algorithms can yield better results in Foreground Object Detection. This work presents a Hybrid CodeBook based Background Subtraction to extract the foreground ROI from the background. Codebooks are used to store compressed information by demanding lesser memory usage and high speedy processing. This Hybrid method which uses Block-Based and Pixel-Based Codebooks provide efficient detection results; the high speed processing capability of block based background subtraction as well as high Precision Rate of pixel based background subtraction are exploited to yield an efficient Background Subtraction System. The Block stage produces a coarse foreground area, which is then refined by the Pixel stage. The system’s performance is evaluated with different block sizes and with different block descriptors like 2D-DCT, FFT etc. The Experimental analysis based on statistical measurements yields precision, recall, similarity and F measure of the hybrid system as 88.74%, 91.09%, 81.66% and 89.90% respectively, and thus proves the efficiency of the novel system.

Corrosion Health Monitoring System for Steel Ship Structures

Corrosion represents one of the largest through life cost component of ships. Ship owners and operators recognize that combating corrosion significantly impacts the vessels’ reliability, availability and through life costs. Primary objective of this paper is to review various inspections, monitoring systems and life cycle management with respect to corrosion control of ships and to develop the concept of “Corrosion Health” (CH) which would quantify the extent of corrosion at any point of ships’ operational life. A system approach in which the ship structure is considered as a corrosion system and divided into several corrosion zones, with distinct characteristics, is presented. Various corrosion assessment criteria for assessment of corrosion condition are listed. A CH rating system for representation of complex corrosion condition with a numeric number along with recommendations for repair/maintenance action is also discussed

Photovoltaic hybrid systems for rural electrification in the Mekong countries

In rural areas of the Mekong Countries, the problem of electricity supplying rural communities is particularly alarming. Supplying power to these areas requires facilities that are not economically viable. However, government programs are under way to provide this product that is vital to community well being. A nation priority of Mekong Countries is to provide electrical power to people in rural areas, within normal budgetary constraints. Electricity must be introduced into rural areas in such a way that maximize the technical, economic and social benefit. Another consideration is the source of electrical generation and the effects on the natural environment. The main research purpose is to implement field tests, monitoring and evaluation of the PV-Diesel Hybrid System (PVHS) at the Energy Park of School of Renewable Energy Technology (SERT) in order to test the PVSH working under the meteorological conditions of the Mekong Countries and to develop a software simulation called RES, which studies the technical and economic performance of rural electrification options. This software must be easy to use and understand for the energy planner on rural electrification projects, to evaluate the technical and economic performance of the PVHS based on the renewable energy potential for rural electrification of the Mekong Country by using RES. Finally, this project aims to give guidance for the possible use of PVHS application in this region, particularly in regard to its technical and economic sustainability. PVHS should be promoted according to the principles of proper design and adequate follow up with maintenance, so that the number of satisfied users will be achieved. PVHS is not the only possible technology for rural electrification, but for the Mekong Countries it is one of the most proper choices. Other renewable energy options such as wind, biomass and hydro power need to be studied in future.

Autonomes Performance-Management in dienstorientierten Architekturen

Die Bedeutung des Dienstgüte-Managements (SLM) im Bereich von Unternehmensanwendungen steigt mit der zunehmenden Kritikalität von IT-gestützten Prozessen für den Erfolg einzelner Unternehmen. Traditionell werden zur Implementierung eines wirksamen SLMs Monitoringprozesse in hierarchischen Managementumgebungen etabliert, die einen Administrator bei der notwendigen Rekonfiguration von Systemen unterstützen. Auf aktuelle, hochdynamische Softwarearchitekturen sind diese hierarchischen Ansätze jedoch nur sehr eingeschränkt anwendbar. Ein Beispiel dafür sind dienstorientierte Architekturen (SOA), bei denen die Geschäftsfunktionalität durch das Zusammenspiel einzelner, voneinander unabhängiger Dienste auf Basis deskriptiver Workflow-Beschreibungen modelliert wird. Dadurch ergibt sich eine hohe Laufzeitdynamik der gesamten Architektur. Für das SLM ist insbesondere die dezentrale Struktur einer SOA mit unterschiedlichen administrativen Zuständigkeiten für einzelne Teilsysteme problematisch, da regelnde Eingriffe zum einen durch die Kapselung der Implementierung einzelner Dienste und zum anderen durch das Fehlen einer zentralen Kontrollinstanz nur sehr eingeschränkt möglich sind. Die vorliegende Arbeit definiert die Architektur eines SLM-Systems für SOA-Umgebungen, in dem autonome Management-Komponenten kooperieren, um übergeordnete Dienstgüteziele zu erfüllen: Mithilfe von Selbst-Management-Technologien wird zunächst eine Automatisierung des Dienstgüte-Managements auf Ebene einzelner Dienste erreicht. Die autonomen Management-Komponenten dieser Dienste können dann mithilfe von Selbstorganisationsmechanismen übergreifende Ziele zur Optimierung von Dienstgüteverhalten und Ressourcennutzung verfolgen. Für das SLM auf Ebene von SOA Workflows müssen temporär dienstübergreifende Kooperationen zur Erfüllung von Dienstgüteanforderungen etabliert werden, die sich damit auch über mehrere administrative Domänen erstrecken können. Eine solche zeitlich begrenzte Kooperation autonomer Teilsysteme kann sinnvoll nur dezentral erfolgen, da die jeweiligen Kooperationspartner im Vorfeld nicht bekannt sind und – je nach Lebensdauer einzelner Workflows – zur Laufzeit beteiligte Komponenten ausgetauscht werden können. In der Arbeit wird ein Verfahren zur Koordination autonomer Management-Komponenten mit dem Ziel der Optimierung von Antwortzeiten auf Workflow-Ebene entwickelt: Management-Komponenten können durch Übertragung von Antwortzeitanteilen untereinander ihre individuellen Ziele straffen oder lockern, ohne dass das Gesamtantwortzeitziel dadurch verändert wird. Die Übertragung von Antwortzeitanteilen wird mithilfe eines Auktionsverfahrens realisiert. Technische Grundlage der Kooperation bildet ein Gruppenkommunikationsmechanismus. Weiterhin werden in Bezug auf die Nutzung geteilter, virtualisierter Ressourcen konkurrierende Dienste entsprechend geschäftlicher Ziele priorisiert. Im Rahmen der praktischen Umsetzung wird die Realisierung zentraler Architekturelemente und der entwickelten Verfahren zur Selbstorganisation beispielhaft für das SLM konkreter Komponenten vorgestellt. Zur Untersuchung der Management-Kooperation in größeren Szenarien wird ein hybrider Simulationsansatz verwendet. Im Rahmen der Evaluation werden Untersuchungen zur Skalierbarkeit des Ansatzes durchgeführt. Schwerpunkt ist hierbei die Betrachtung eines Systems aus kooperierenden Management-Komponenten, insbesondere im Hinblick auf den Kommunikationsaufwand. Die Evaluation zeigt, dass ein dienstübergreifendes, autonomes Performance-Management in SOA-Umgebungen möglich ist. Die Ergebnisse legen nahe, dass der entwickelte Ansatz auch in großen Umgebungen erfolgreich angewendet werden kann.

Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers

The Support Vector (SV) machine is a novel type of learning machine, based on statistical learning theory, which contains polynomial classifiers, neural networks, and radial basis function (RBF) networks as special cases. In the RBF case, the SV algorithm automatically determines centers, weights and threshold such as to minimize an upper bound on the expected test error. The present study is devoted to an experimental comparison of these machines with a classical approach, where the centers are determined by $k$--means clustering and the weights are found using error backpropagation. We consider three machines, namely a classical RBF machine, an SV machine with Gaussian kernel, and a hybrid system with the centers determined by the SV method and the weights trained by error backpropagation. Our results show that on the US postal service database of handwritten digits, the SV machine achieves the highest test accuracy, followed by the hybrid approach. The SV approach is thus not only theoretically well--founded, but also superior in a practical application.

Modelling, control and supervision for a class of hybrid systems

The aim of this thesis is to narrow the gap between two different control techniques: the continuous control and the discrete event control techniques DES. This gap can be reduced by the study of Hybrid systems, and by interpreting as Hybrid systems the majority of large-scale systems. In particular, when looking deeply into a process, it is often possible to identify interaction between discrete and continuous signals. Hybrid systems are systems that have both continuous, and discrete signals. Continuous signals are generally supposed continuous and differentiable in time, since discrete signals are neither continuous nor differentiable in time due to their abrupt changes in time. Continuous signals often represent the measure of natural physical magnitudes such as temperature, pressure etc. The discrete signals are normally artificial signals, operated by human artefacts as current, voltage, light etc. Typical processes modelled as Hybrid systems are production systems, chemical process, or continuos production when time and continuous measures interacts with the transport, and stock inventory system. Complex systems as manufacturing lines are hybrid in a global sense. They can be decomposed into several subsystems, and their links. Another motivation for the study of Hybrid systems is the tools developed by other research domains. These tools benefit from the use of temporal logic for the analysis of several properties of Hybrid systems model, and use it to design systems and controllers, which satisfies physical or imposed restrictions. This thesis is focused in particular types of systems with discrete and continuous signals in interaction. That can be modelled hard non-linealities, such as hysteresis, jumps in the state, limit cycles, etc. and their possible non-deterministic future behaviour expressed by an interpretable model description. The Hybrid systems treated in this work are systems with several discrete states, always less than thirty states (it can arrive to NP hard problem), and continuous dynamics evolving with expression: with Ki ¡ Rn constant vectors or matrices for X components vector. In several states the continuous evolution can be several of them Ki = 0. In this formulation, the mathematics can express Time invariant linear system. By the use of this expression for a local part, the combination of several local linear models is possible to represent non-linear systems. And with the interaction with discrete events of the system the model can compose non-linear Hybrid systems. Especially multistage processes with high continuous dynamics are well represented by the proposed methodology. Sate vectors with more than two components, as third order models or higher is well approximated by the proposed approximation. Flexible belt transmission, chemical reactions with initial start-up and mobile robots with important friction are several physical systems, which profits from the benefits of proposed methodology (accuracy). The motivation of this thesis is to obtain a solution that can control and drive the Hybrid systems from the origin or starting point to the goal. How to obtain this solution, and which is the best solution in terms of one cost function subject to the physical restrictions and control actions is analysed. Hybrid systems that have several possible states, different ways to drive the system to the goal and different continuous control signals are problems that motivate this research. The requirements of the system on which we work is: a model that can represent the behaviour of the non-linear systems, and that possibilities the prediction of possible future behaviour for the model, in order to apply an supervisor which decides the optimal and secure action to drive the system toward the goal. Specific problems can be determined by the use of this kind of hybrid models are: - The unity of order. - Control the system along a reachable path. - Control the system in a safe path. - Optimise the cost function. - Modularity of control The proposed model solves the specified problems in the switching models problem, the initial condition calculus and the unity of the order models. Continuous and discrete phenomena are represented in Linear hybrid models, defined with defined eighth-tuple parameters to model different types of hybrid phenomena. Applying a transformation over the state vector : for LTI system we obtain from a two-dimensional SS a single parameter, alpha, which still maintains the dynamical information. Combining this parameter with the system output, a complete description of the system is obtained in a form of a graph in polar representation. Using Tagaki-Sugeno type III is a fuzzy model which include linear time invariant LTI models for each local model, the fuzzyfication of different LTI local model gives as a result a non-linear time invariant model. In our case the output and the alpha measure govern the membership function. Hybrid systems control is a huge task, the processes need to be guided from the Starting point to the desired End point, passing a through of different specific states and points in the trajectory. The system can be structured in different levels of abstraction and the control in three layers for the Hybrid systems from planning the process to produce the actions, these are the planning, the process and control layer. In this case the algorithms will be applied to robotics ¡V a domain where improvements are well accepted ¡V it is expected to find a simple repetitive processes for which the extra effort in complexity can be compensated by some cost reductions. It may be also interesting to implement some control optimisation to processes such as fuel injection, DC-DC converters etc. In order to apply the RW theory of discrete event systems on a Hybrid system, we must abstract the continuous signals and to project the events generated for these signals, to obtain new sets of observable and controllable events. Ramadge & Wonham¡¦s theory along with the TCT software give a Controllable Sublanguage of the legal language generated for a Discrete Event System (DES). Continuous abstraction transforms predicates over continuous variables into controllable or uncontrollable events, and modifies the set of uncontrollable, controllable observable and unobservable events. Continuous signals produce into the system virtual events, when this crosses the bound limits. If this event is deterministic, they can be projected. It is necessary to determine the controllability of this event, in order to assign this to the corresponding set, , controllable, uncontrollable, observable and unobservable set of events. Find optimal trajectories in order to minimise some cost function is the goal of the modelling procedure. Mathematical model for the system allows the user to apply mathematical techniques over this expression. These possibilities are, to minimise a specific cost function, to obtain optimal controllers and to approximate a specific trajectory. The combination of the Dynamic Programming with Bellman Principle of optimality, give us the procedure to solve the minimum time trajectory for Hybrid systems. The problem is greater when there exists interaction between adjacent states. In Hybrid systems the problem is to determine the partial set points to be applied at the local models. Optimal controller can be implemented in each local model in order to assure the minimisation of the local costs. The solution of this problem needs to give us the trajectory to follow the system. Trajectory marked by a set of set points to force the system to passing over them. Several ways are possible to drive the system from the Starting point Xi to the End point Xf. Different ways are interesting in: dynamic sense, minimum states, approximation at set points, etc. These ways need to be safe and viable and RchW. And only one of them must to be applied, normally the best, which minimises the proposed cost function. A Reachable Way, this means the controllable way and safe, will be evaluated in order to obtain which one minimises the cost function. Contribution of this work is a complete framework to work with the majority Hybrid systems, the procedures to model, control and supervise are defined and explained and its use is demonstrated. Also explained is the procedure to model the systems to be analysed for automatic verification. Great improvements were obtained by using this methodology in comparison to using other piecewise linear approximations. It is demonstrated in particular cases this methodology can provide best approximation. The most important contribution of this work, is the Alpha approximation for non-linear systems with high dynamics While this kind of process is not typical, but in this case the Alpha approximation is the best linear approximation to use, and give a compact representation.

Architecture for neuronal cell control of a mobile robot

It is usually expected that the intelligent controlling mechanism of a robot is a computer system. Research is however now ongoing in which biological neural networks are being cultured and trained to act as the brain of an interactive real world robot - thereby either completely replacing or operating in a cooperative fashion with a computer system. Studying such neural systems can give a distinct insight into biological neural structures and therefore such research has immediate medical implications. In particular, the use of rodent primary dissociated cultured neuronal networks for the control of mobile `animals' (artificial animals, a contraction of animal and materials) is a novel approach to discovering the computational capabilities of networks of biological neurones. A dissociated culture of this nature requires appropriate embodiment in some form, to enable appropriate development in a controlled environment within which appropriate stimuli may be received via sensory data but ultimate influence over motor actions retained. The principal aims of the present research are to assess the computational and learning capacity of dissociated cultured neuronal networks with a view to advancing network level processing of artificial neural networks. This will be approached by the creation of an artificial hybrid system (animal) involving closed loop control of a mobile robot by a dissociated culture of rat neurons. This 'closed loop' interaction with the environment through both sensing and effecting will enable investigation of its learning capacity This paper details the components of the overall animat closed loop system and reports on the evaluation of the results from the experiments being carried out with regard to robot behaviour.

PEGylated amyloid peptide nanocontainer delivery and release system

A micellar nanocontainer delivery and release system is designed on the basis of a peptide-polymer conjugate. The hybrid molecules self-assemble into micelles comprising a modified amyloid peptide core surrounded by a PEG corona. The modified amyloid peptide previously studied in our group forms helical ribbons based on a beta-sheet motif and contains beta-amino acids that are excluded from the beta-sheet structure, thus being potentially useful as fibrillization inhibitors. In the model peptide-PEG hybrid system studied, enzymatic degradation using alpha-chymotrypsin leads to selective cleavage close to the PEG-peptide linkage, break up of the micelles, and release of peptides in unassociated form. The release of monomeric peptide is useful because aggregation of the released peptide into beta-sheet amyloid fibrils is not observed. This concept has considerable potential in the targeted delivery of peptides for therapeutic applications.

Expert system aid for design of overload line distribution networks

The use of expert system techniques in power distribution system design is examined. The selection and siting of equipment on overhead line networks is chosen for investigation as the use of equipment such as auto-reclosers, etc., represents a substantial investment and has a significant effect on the reliability of the system. Through past experience with both equipment and network operations, most decisions in selection and siting of this equipment are made intuitively, following certain general guidelines or rules of thumb. This heuristic nature of the problem lends itself to solution using an expert system approach. A prototype has been developed and is currently under evaluation in the industry. Results so far have demonstrated both the feasibility and benefits of the expert system as a design aid.

Two-level network design with intermediate facilities: An application to electrical distribution systems

We consider the two-level network design problem with intermediate facilities. This problem consists of designing a minimum cost network respecting some requirements, usually described in terms of the network topology or in terms of a desired flow of commodities between source and destination vertices. Each selected link must receive one of two types of edge facilities and the connection of different edge facilities requires a costly and capacitated vertex facility. We propose a hybrid decomposition approach which heuristically obtains tentative solutions for the vertex facilities number and location and use these solutions to limit the computational burden of a branch-and-cut algorithm. We test our method on instances of the power system secondary distribution network design problem. The results show that the method is efficient both in terms of solution quality and computational times. (C) 2010 Elsevier Ltd. All rights reserved.

Molecular characterization of Arabidopsis thaliana PUF proteins - binding specificity and target candidates

PUF proteins regulate both stability and translation through sequence-specific binding to the 3` UTR of target mRNA transcripts. Binding is mediated by a conserved PUF domain, which contains eight repeats of approximately 36 amino acids each. Found in all eukaryotes, they have been related to several developmental processes. Analysis of the 25 Arabidopsis Pumilio (APUM) proteins presenting PUF repeats reveals that 12 (APUM-1 to APUM-12) have a PUF domain with 50-75% similarity to the Drosophila PUF domain. Through three-hybrid assays, we show that APUM-1 to APUM-6 can bind specifically to the Nanos response element sequence recognized by Drosophila Pumilio. Using an Arabidopsis RNA library in a three-hybrid screening, we were able to identify an APUM-binding consensus sequence. Computational analysis allowed us to identify the APUM-binding element within the 3` UTR in many Arabidopsis transcripts, even in important mRNAs related to shoot stem cell maintenance. We demonstrate that APUM-1 to APUM-6 are able to bind specifically to APUM-binding elements in the 3` UTR of WUSCHEL, CLAVATA-1, PINHEAD/ZWILLE and FASCIATA-2 transcripts. The results obtained in the present study indicate that the APUM proteins may act as regulators in Arabidopsis through an evolutionarily conserved mechanism, which may open up a new approach for investigating mRNA regulation in plants.

Quenching of Photoactivity in Phthalocyanine Copper(II)-Titanate Nanotube Hybrid Systems

Titanate nanotubes (TiNTs) were obtained by hydrothermal treatment of anatase powder in aqueous NaOH solution and then modified with 2,9,16,23-tertracarboxyl phthalocyanine copper(H) (CuPc). This hybrid organic inorganic nanoscopic system was characterized by X-ray diffraction, microscopy, and spectroscopy. Transmission electron microscopy (TEM) images of pure and modified TiNTs revealed multiwall structures with an average outer diameter of 9 nm and a length of several hundred nanometers. The tubular morphology of the TiNTs was covered with CuPc-film. The amount of CuPc adsorbed onto the TiNTs was quantified by electron paramagnetic resonance (EPR). Using the same technique and spin-trapping methodology, the photogeneration of reactive oxygen species (ROS) from the TiNTs was systematically investigated. A drastic quenching of photoactivity was observed in the CuPc/TiNT hybrid system. Electron transfer from excited CuPc states to the TiNT conduction band followed by electron recombination may be the cause of this quenching.

Applicatiion of Almost ideal demand system for a pharmaceutical

This thesis is an application of the Almost Ideal Demand System approach of Deaton and Muellbauer,1980, for a particular pharmaceutical, Citalopram, in which GORMAN´s (1971) multi-stage budgeting approach is applied basically since it is one of the most useful approach in estimating demand for differentiated products. Citalopram is an antidepressant drug that is used in the treatment of major depression. As for most other pharmaceuticals whose the patent has expired, there exist branded and generic versions of Citalopram. This paper is aimed to define its demand system with two stage models for the branded version and five generic versions, and to show whether generic versions are able to compete with the branded version. I calculated the own price elasticities, and it made me possible to compare and make a conclusion about the consumers’ choices over the brand and generic drugs. Even though the models need for being developed with some additional variables, estimation results of models and uncompensated price elasticities indicated that the branded version has still power in the market, and generics are able to compete with lower prices. One important point that has to be taken into consideration is that the Swedish pharmaceutical market faced a reform on October 1, 2002, that aims to make consumer better informed about the price and decrease the overall expenditures for pharmaceuticals. Since there were not significantly enough generic sales to take into calculation before the reform, my paper covers sales after the reform.

Active cooling of low-concentrating hybrid PV/Thermal collectors

A series of measurements on the performance of solar cell string modules with low-concentrating CPC reflectors with a concentration factor C ˜ 4X have been carried out. To minimise the reduction in efficiency due to high cell temperatures, the modules were cooled. Four different way of cooling were tested:1) The thermal mass of the module was increased, 2) passive air cooling was used by introducing a small air gap between the module and the reflector, 3) the PV cells were cooled by a large cooling fin, 4) the module was actively cooled by circulating cold water on the back. The best performance was given with the actively cooled PV module which gave 2,2 times the output from a reference module while for the output from the module with a cooling fin the value was 1,8.Active cooling is also interesting due to the possibility of co-generation of thermal and electrical energy which is discussed in the paper. Simulations, based on climate data from Stockholm, latitude 59.4°N, show that there are good prospects for producing useful temperatures of the cooling fluid with only a slightly reduced performance of the electrical fraction of the PV thermal hybrid system.

PV-Wind Hybrid Systems for Swedish Locations

PV-Wind-Hybrid systems for stand-alone applications have the potential to be more cost efficient compared to PV-alone systems. The two energy sources can, to some extent, compensate each others minima. The combination of solar and wind should be especially favorable for locations at high latitudes such as Sweden with a very uneven distribution of solar radiation during the year. In this article PV-Wind-Hybrid systems have been studied for 11 locations in Sweden. These systems supply the household electricity for single family houses. The aim was to evaluate the system costs, the cost of energy generated by the PV-Wind-Hybrid systems, the effect of the load size and to what extent the combination of these two energy sources can reduce the costs compared to a PV-alone system. The study has been performed with the simulation tool HOMER developed by the National Renewable Energy Laboratory (NREL) for techno-economical feasibility studies of hybrid systems. The results from HOMER show that the net present costs (NPC) for a hybrid system designed for an annual load of 6000 kWh with a capacity shortage of 10% will vary between $48,000 and $87,000. Sizing the system for a load of 1800 kWh/year will give a NPC of $17,000 for the best and $33,000 for the worst location. PV-Wind-Hybrid systems are for all locations more cost effective compared to PV-alone systems. Using a Hybrid system is reducing the NPC for Borlänge by 36% and for Lund by 64%. The cost per kWh electricity varies between $1.4 for the worst location and $0.9 for the best location if a PV-Wind-Hybrid system is used.