Minimizing Circulating Current in Parallel-Connected Photovoltaic Inverters

Parallel-connected photovoltaic inverters are required in large solar plants where it is not economically or technically reasonable to use a single inverter. Currently, parallel inverters require individual isolating transformers to cut the path for the circulating current. In this doctoral dissertation, the problem is approached by attempting to minimize the generated circulating current. The circulating current is a function of the generated common-mode voltages of the parallel inverters and can be minimized by synchronizing the inverters. The synchronization has previously been achieved by a communication link. However, in photovoltaic systems the inverters may be located far apart from each other. Thus, a control free of communication is desired. It is shown in this doctoral dissertation that the circulating current can also be obtained by a common-mode voltage measurement. A control method based on a short-time switching frequency transition is developed and tested with an actual photovoltaic environment of two parallel inverters connected to two 5 kW solar arrays. Controls based on the measurement of the circulating current and the common-mode voltage are generated and tested. A communication-free method of controlling the circulating current between parallelconnected inverters is developed and verified.

The use of protein structure/activity relationships in the rational design of stable particulate delivery systems

The recombinant heat shock protein (18 kDa-hsp) from Mycobacterium leprae was studied as a T-epitope model for vaccine development. We present a structural analysis of the stability of recombinant 18 kDa-hsp during different processing steps. Circular dichroism and ELISA were used to monitor protein structure after thermal stress, lyophilization and chemical modification. We observed that the 18 kDa-hsp is extremely resistant to a wide range of temperatures (60% of activity is retained at 80ºC for 20 min). N-Acylation increased its ordered structure by 4% and decreased its ß-T1 structure by 2%. ELISA demonstrated that the native conformation of the 18 kDa-hsp was preserved after hydrophobic modification by acylation. The recombinant 18 kDa-hsp resists to a wide range of temperatures and chemical modifications without loss of its main characteristic, which is to be a source of T epitopes. This resistance is probably directly related to its lack of organization at the level of tertiary and secondary structures.

Local Binary Patterns in Focal-Plane Processing. Analysis and Applications

Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

Stability and properties of cellulose-sodium hydroxide solution systems

Since cellulose is a linear macromolecule it can be used as a material for regenerated cellulose fiber products e.g. in textile fibers or film manufacturing. Cellulose is not thermoformable, thus the manufacturing of these regenerated fibers is mainly possible through dissolution processes preceding the regeneration process. However, the dissolution of cellulose in common solvents is hindered due to inter- and intra-molecular hydrogen bonds in the cellulose chains, and relatively high crystallinity. Interestingly at subzero temperatures relatively dilute sodium hydroxide solutions can be used to dissolve cellulose to a certain extent. The objective of this work was to investigate the possible factors that govern the solubility of cellulose in aqueous NaOH and the solution stability. Cellulose-NaOH solutions have the tendency to form a gel over time and at elevated temperature, which creates challenges for further processing. The main target of this work was to achieve high solubility of cellulose in aqueous NaOH without excessively compromising the solution stability. In the literature survey an overview of the cellulose dissolution is given and possible factors contributing to the solubility and solution properties of cellulose in aqueous NaOH are reviewed. Furthermore, the concept of solution rheology is discussed. In the experimental part the focus was on the characterization of the used materials and properties of the prepared solutions mainly concentrating on cellulose solubility and solution stability.

Load balancing in P2P smartphone based distributed IoT systems

With the new age of Internet of Things (IoT), object of everyday such as mobile smart devices start to be equipped with cheap sensors and low energy wireless communication capability. Nowadays mobile smart devices (phones, tablets) have become an ubiquitous device with everyone having access to at least one device. There is an opportunity to build innovative applications and services by exploiting these devices’ untapped rechargeable energy, sensing and processing capabilities. In this thesis, we propose, develop, implement and evaluate LoadIoT a peer-to-peer load balancing scheme that can distribute tasks among plethora of mobile smart devices in the IoT world. We develop and demonstrate an android-based proof of concept load-balancing application. We also present a model of the system which is used to validate the efficiency of the load balancing approach under varying application scenarios. Load balancing concepts can be apply to IoT scenario linked to smart devices. It is able to reduce the traffic send to the Cloud and the energy consumption of the devices. The data acquired from the experimental outcomes enable us to determine the feasibility and cost-effectiveness of a load balanced P2P smart phone-based applications.

Phenolic content and antioxidant capacity in organically and conventionally grown eggplant (Solanum melongena) fruits following thermal processing

AbstractThermal processing and production practices used in vegetables can cause changes in their phytochemical contents. Eggplant is characterized by its high antioxidant content. The objective of this work was to determine levels of anthocyanins, polyphenols, and flavonoids and antioxidant capacity in organically and conventionally grown eggplant prepared fresh or subjected to one of three thermal preparation methods: boiling, baking or steaming. The soluble and hydrolyzable polyphenols and flavonoids content were quantified by Folin-Ciocalteu and Aluminum chloride methods, respectively. Anthocyanins were quantified according to the pH differential method. Antioxidant capacity was determined by DPPH and ORAC methods. The results showed differences between organic and conventional eggplant for some variables although cultivation method did not have a consistent effect. Hydrolysable polyphenol content was greater, and soluble and hydrolysable antioxidant capacities were higher in organically grown eggplant, while anthocyanin content was greater in conventionally grown eggplant. Fresh eggplant produced under conventional cultivation had a much greater content of anthocyanins compared to that of other cultivation method-thermal treatment combination. In general, steamed eggplant contained higher total polyphenol and flavonoid levels as well as greater antioxidant capacity. Steamed eggplant from both conventional and organic systems also had high amounts of anthocyanins compared to other thermal treatments.

Energy aware software for many-core systems

Many-core systems provide a great potential in application performance with the massively parallel structure. Such systems are currently being integrated into most parts of daily life from high-end server farms to desktop systems, laptops and mobile devices. Yet, these systems are facing increasing challenges such as high temperature causing physical damage, high electrical bills both for servers and individual users, unpleasant noise levels due to active cooling and unrealistic battery drainage in mobile devices; factors caused directly by poor energy efficiency. Power management has traditionally been an area of research providing hardware solutions or runtime power management in the operating system in form of frequency governors. Energy awareness in application software is currently non-existent. This means that applications are not involved in the power management decisions, nor does any interface between the applications and the runtime system to provide such facilities exist. Power management in the operating system is therefore performed purely based on indirect implications of software execution, usually referred to as the workload. It often results in over-allocation of resources, hence power waste. This thesis discusses power management strategies in many-core systems in the form of increasing application software awareness of energy efficiency. The presented approach allows meta-data descriptions in the applications and is manifested in two design recommendations: 1) Energy-aware mapping 2) Energy-aware execution which allow the applications to directly influence the power management decisions. The recommendations eliminate over-allocation of resources and increase the energy efficiency of the computing system. Both recommendations are fully supported in a provided interface in combination with a novel power management runtime system called Bricktop. The work presented in this thesis allows both new- and legacy software to execute with the most energy efficient mapping on a many-core CPU and with the most energy efficient performance level. A set of case study examples demonstrate realworld energy savings in a wide range of applications without performance degradation.

Electrophysiological investigations of the timing of face processing

As important social stimuli, faces playa critical role in our lives. Much of our interaction with other people depends on our ability to recognize faces accurately. It has been proposed that face processing consists of different stages and interacts with other systems (Bruce & Young, 1986). At a perceptual level, the initial two stages, namely structural encoding and face recognition, are particularly relevant and are the focus of this dissertation. Event-related potentials (ERPs) are averaged EEG signals time-locked to a particular event (such as the presentation of a face). With their excellent temporal resolution, ERPs can provide important timing information about neural processes. Previous research has identified several ERP components that are especially related to face processing, including the N 170, the P2 and the N250. Their nature with respect to the stages of face processing is still unclear, and is examined in Studies 1 and 2. In Study 1, participants made gender decisions on a large set of female faces interspersed with a few male faces. The ERP responses to facial characteristics of the female faces indicated that the N 170 amplitude from each side of the head was affected by information from eye region and by facial layout: the right N 170 was affected by eye color and by face width, while the left N 170 was affected by eye size and by the relation between the sizes of the top and bottom parts of a face. In contrast, the P100 and the N250 components were largely unaffected by facial characteristics. These results thus provided direct evidence for the link between the N 170 and structural encoding of faces. In Study 2, focusing on the face recognition stage, we manipulated face identity strength by morphing individual faces to an "average" face. Participants performed a face identification task. The effect of face identity strength was found on the late P2 and the N250 components: as identity strength decreased from an individual face to the "average" face, the late P2 increased and the N250 decreased. In contrast, the P100, the N170 and the early P2 components were not affected by face identity strength. These results suggest that face recognition occurs after 200 ms, but not earlier. Finally, because faces are often associated with social information, we investigated in Study 3 how group membership might affect ERP responses to faces. After participants learned in- and out-group memberships of the face stimuli based on arbitrarily assigned nationality and university affiliation, we found that the N170 latency differentiated in-group and out-group faces, taking longer to process the latter. In comparison, without group memberships, there was no difference in N170 latency among the faces. This dissertation provides evidence that at a neural level, structural encoding of faces, indexed by the N170, occurs within 200 ms. Face recognition, indexed by the late P2 and the N250, occurs shortly afterwards between 200 and 300 ms. Social cognitive factors can also influence face processing. The effect is already evident as early as 130-200 ms at the structural encoding stage.

Approche systémique pour la composition d’œuvres acousmatiques, mixtes, vidéomusicales et pluridisciplinaires

Cette thèse est une exploration de mon processus compositionnel. En tentant de comprendre comment s’organise ma pensée créatrice, j’ai dégagé trois observations : l’organicisme du processus et des œuvres, la notion de mouvement et la relation récursive entre la matière et le compositeur. Ces thèmes m’ont amené à établir un lien épistémologique entre la composition musicale et l’étude des systèmes complexes. Dans ce cadre systémique, j’ai établi que les informations qui motivent mes prises de décision artistiques ont entre elles des ramifications opérationnelles et structurelles qui évoquent une arborescence rhizomatique plutôt qu’une hiérarchie linéaire. La transdisciplinarité propre à la systémique m’a également permis d’introduire des notions provenant d’autres champs de recherche. S’articulant d’emblée avec mon processus compositionnel, ces notions m’ont procuré une vision holistique de ma démarche artistique. Conséquemment, je considère l’acte de composer comme une interaction entre ma conscience et tout ce qui peut émaner de la matière sonore, les deux s’informant l’une et l’autre dans une boucle récursive que je nomme action⟳perception. L’œuvre ainsi produite n’est pas exclusivement tributaire de ma propre volition puisque, au fil du processus, mes décisions opératoires et artistiques sont en grande partie guidées par les propriétés invariantes et les propriétés morphogéniques inhérentes au matériau sonore. Cette approche dynamique n’est possible que si l’interaction avec le compositeur se fait en temps réel, ce que permet la lutherie numérique. Les résultats de mes recherches m’ont guidé dans la composition d’œuvres choisies, autant acousmatiques, mixtes, vidéomusicales que pluridisciplinaires.

Logiciel de génération de nombres aléatoires dans OpenCL

clRNG et clProbdist sont deux interfaces de programmation (APIs) que nous avons développées pour la génération de nombres aléatoires uniformes et non uniformes sur des dispositifs de calculs parallèles en utilisant l’environnement OpenCL. La première interface permet de créer au niveau d’un ordinateur central (hôte) des objets de type stream considérés comme des générateurs virtuels parallèles qui peuvent être utilisés aussi bien sur l’hôte que sur les dispositifs parallèles (unités de traitement graphique, CPU multinoyaux, etc.) pour la génération de séquences de nombres aléatoires. La seconde interface permet aussi de générer au niveau de ces unités des variables aléatoires selon différentes lois de probabilité continues et discrètes. Dans ce mémoire, nous allons rappeler des notions de base sur les générateurs de nombres aléatoires, décrire les systèmes hétérogènes ainsi que les techniques de génération parallèle de nombres aléatoires. Nous présenterons aussi les différents modèles composant l’architecture de l’environnement OpenCL et détaillerons les structures des APIs développées. Nous distinguons pour clRNG les fonctions qui permettent la création des streams, les fonctions qui génèrent les variables aléatoires uniformes ainsi que celles qui manipulent les états des streams. clProbDist contient les fonctions de génération de variables aléatoires non uniformes selon la technique d’inversion ainsi que les fonctions qui permettent de retourner différentes statistiques des lois de distribution implémentées. Nous évaluerons ces interfaces de programmation avec deux simulations qui implémentent un exemple simplifié d’un modèle d’inventaire et un exemple d’une option financière. Enfin, nous fournirons les résultats d’expérimentation sur les performances des générateurs implémentés.

PSWT Based Linear Predictive Coding and Development of a Parallel Multiple Subsequence Structure for DWT Computation

During 1990's the Wavelet Transform emerged as an important signal processing tool with potential applications in time-frequency analysis and non-stationary signal processing.Wavelets have gained popularity in broad range of disciplines like signal/image compression, medical diagnostics, boundary value problems, geophysical signal processing, statistical signal processing,pattern recognition,underwater acoustics etc.In 1993, G. Evangelista introduced the Pitch- synchronous Wavelet Transform, which is particularly suited for pseudo-periodic signal processing.The work presented in this thesis mainly concentrates on two interrelated topics in signal processing,viz. the Wavelet Transform based signal compression and the computation of Discrete Wavelet Transform. A new compression scheme is described in which the Pitch-Synchronous Wavelet Transform technique is combined with the popular linear Predictive Coding method for pseudo-periodic signal processing. Subsequently,A novel Parallel Multiple Subsequence structure is presented for the efficient computation of Wavelet Transform. Case studies also presented to highlight the potential applications.

Information Discovery in Distributed Systems-A Novel Concept Based on Modelling of Information Elements

Sharing of information with those in need of it has always been an idealistic goal of networked environments. With the proliferation of computer networks, information is so widely distributed among systems, that it is imperative to have well-organized schemes for retrieval and also discovery. This thesis attempts to investigate the problems associated with such schemes and suggests a software architecture, which is aimed towards achieving a meaningful discovery. Usage of information elements as a modelling base for efficient information discovery in distributed systems is demonstrated with the aid of a novel conceptual entity called infotron.The investigations are focused on distributed systems and their associated problems. The study was directed towards identifying suitable software architecture and incorporating the same in an environment where information growth is phenomenal and a proper mechanism for carrying out information discovery becomes feasible. An empirical study undertaken with the aid of an election database of constituencies distributed geographically, provided the insights required. This is manifested in the Election Counting and Reporting Software (ECRS) System. ECRS system is a software system, which is essentially distributed in nature designed to prepare reports to district administrators about the election counting process and to generate other miscellaneous statutory reports.Most of the distributed systems of the nature of ECRS normally will possess a "fragile architecture" which would make them amenable to collapse, with the occurrence of minor faults. This is resolved with the help of the penta-tier architecture proposed, that contained five different technologies at different tiers of the architecture.The results of experiment conducted and its analysis show that such an architecture would help to maintain different components of the software intact in an impermeable manner from any internal or external faults. The architecture thus evolved needed a mechanism to support information processing and discovery. This necessitated the introduction of the noveI concept of infotrons. Further, when a computing machine has to perform any meaningful extraction of information, it is guided by what is termed an infotron dictionary.The other empirical study was to find out which of the two prominent markup languages namely HTML and XML, is best suited for the incorporation of infotrons. A comparative study of 200 documents in HTML and XML was undertaken. The result was in favor ofXML.The concept of infotron and that of infotron dictionary, which were developed, was applied to implement an Information Discovery System (IDS). IDS is essentially, a system, that starts with the infotron(s) supplied as clue(s), and results in brewing the information required to satisfy the need of the information discoverer by utilizing the documents available at its disposal (as information space). The various components of the system and their interaction follows the penta-tier architectural model and therefore can be considered fault-tolerant. IDS is generic in nature and therefore the characteristics and the specifications were drawn up accordingly. Many subsystems interacted with multiple infotron dictionaries that were maintained in the system.In order to demonstrate the working of the IDS and to discover the information without modification of a typical Library Information System (LIS), an Information Discovery in Library Information System (lDLIS) application was developed. IDLIS is essentially a wrapper for the LIS, which maintains all the databases of the library. The purpose was to demonstrate that the functionality of a legacy system could be enhanced with the augmentation of IDS leading to information discovery service. IDLIS demonstrates IDS in action. IDLIS proves that any legacy system could be augmented with IDS effectively to provide the additional functionality of information discovery service.Possible applications of IDS and scope for further research in the field are covered.

Design and Development of Instrumentation Systems to determine the Dry Rubber Content in Natural Rubber Latex

Hevea latex is a natural biological liquid of very complex composition .Besides rubber hydrocarbons,it contains many proteinous and resinous substances,carbohydrates,inorganic matter,water,and others.The Dry Rubber Content (DRC) of latex varies according to season, tapping system,weather,soil conditions ,clone,age of the tree etc. The true DRC of the latex must be determined to ensure fair prices for the latex during commercial exchange.The DRC of Hevea latex is a very familiar term to all in the rubber industry.It has been the basis for incentive payments to tappers who bring in more than the daily agreed poundage of latex.It is an important parameter for rubber and latex processing industries for automation and verious decesion making processes.This thesis embodies the efforts made by me to determine the DRC of rubber latex following different analytical tools such as MIR absorption,thermal analysis.dielectric spectroscopy and NIR reflectance.The rubber industry is still Looking for a compact instrument that is accurate economical,easy to use and environment friendly.I hope the results presented in this thesis will help to realise this goal in the near future.

Market Orientation in Indian Seafood Processing Firms

This thesis studied the impact of market orietnation on business performance, in the seafood industry, which is a unique situation wherein the firms were all 100% export oriented. The study was able to prove that in the context of the seafood indsutry, implementation of market orientation principles will lead to increase in business performance. The business performance variables were measured under two heads, namely economic performance and non-economic performance. Market orientation in Indian seafood firms was significantly and postiively related to both the performance measures. Under the non-economic performance, were the customer and employee consequences.Again market orientation was positively and significantly related to both the consequences.Thus, the implication arising from the study is this: market orientation in Indian seafood processing firms increases their business performance. The implementation of market orientation will help the seafood firms in gaining competitve advantages in exporting. This in turn will result in increased exports and the position of Indian seafood in the global market will be strengthened. It will thus become a leading player in the global fish trade. Next, the focus was on the effect of the antecedents on the market orientation of a firm. It was seen that several factors were antecedents to the adoption of market orientation principles. They include top management emphasis, conflict, centralization and reward system. It is noted that top management emphasis and support is vital to the market orientation programme. The top management needs to adopt market oriented behaviour and reinforce the need for being market oriented, for it to percolate down the line.Interdepartmental conflict is seen to affect market orientation positively. A large percent of the Indian seafood firms are traditionally family-owned companies, rather than professionally managed firms. This would result in promulgation of old ideas of management whereby, conflict was seen as a healthy exercise, which helped to build up each department's efficiency. But, this view in the long run proves to be detrimental to the firm's performance and must therefore be kept to a bare minimum, if any.Decentralisation of decision making facilitates the participation of the lower level employees and builds up their motivational levels and commitment to the firm. Thus employees are encouraged to make their own decisions, so that they can deal with customers faster and more efficiently. Reward systems help improve an employee's morale, provide encouragement and helps inculcate commitment and loyalty. It improves the employee's self worth and fulfills his need for achievement. A satisfied employee works better, produces more output and needs less supervision, and is happy, thereby reducing costs to the company for replacement and retraining, if the employee quits.Competitive intensity plays a moderating role on the market orientation business performance. Thus in times of greater competition, the relationship between market orientation and business performance grows stronger. Thus, this thesis was successful in investigating a positive relationship between business performance and market orientation.

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.