A Multi-Mode Sigma-Delta ADC for GSM/WCDMA/ WLAN Applications

The demand for new telecommunication services requiring higher capacities, data rates and different operating modes have motivated the development of new generation multi-standard wireless transceivers. In multistandard design, sigma-delta based ADC is one of the most popular choices. To this end, in this paper we present cascaded 2-2-2 reconfigurable sigma-delta modulator that can handle GSM, WCDMA and WLAN standards. The modulator makes use of a low-distortion swing suppression topology which is highly suitable for wide band applications. In GSM mode, only the first stage (2nd order Σ-Δ ADC) is used to achieve a peak SNDR of 88dB with oversampling ratio of 160 for a bandwidth of 200KHz and for WCDMA mode a 2-2 cascaded structure (4th order) is turned on with 1-bit in the first stage and 2-bit in the second stage to achieve 74 dB peak SNDR with over-sampling ratio of 16 for a bandwidth of 2MHz. Finally, a 2-2-2 cascaded MASH architecture with 4-bit in the last stage is proposed to achieve a peak SNDR of 58dB for WLAN for a bandwidth of 20MHz. The novelty lies in the fact that unused blocks of second and third stages can be made inactive to achieve low power consumption. The modulator is designed in TSMC 0.18um CMOS technology and operates at 1.8 supply voltage

A Multi-Objective Antenna Placement Genetic Algorithm for Matched Array Synthesis on Complex Platforms

A Multi-Objective Antenna Placement Genetic Algorithm (MO-APGA) has been proposed for the synthesis of matched antenna arrays on complex platforms. The total number of antennas required, their position on the platform, location of loads, loading circuit parameters, decoupling and matching network topology, matching network parameters and feed network parameters are optimized simultaneously. The optimization goal was to provide a given minimum gain, specific gain discrimination between the main and back lobes and broadband performance. This algorithm is developed based on the non-dominated sorting genetic algorithm (NSGA-II) and Minimum Spanning Tree (MST) technique for producing diverse solutions when the number of objectives is increased beyond two. The proposed method is validated through the design of a wideband airborne SAR

Interactive comment on “Experimental study using coir geotextiles in watershed management

This paper presents the results of a field experiment conducted in Kerala, South India, to test the effectiveness of coir geotextiles for embankment protection. The results reveal that treatment with geotextile in combination with grass is an effective eco-hydrological measure to protect steep slopes from erosion. In the context of sustainable watershed management, coir is a cheap and locally available material that can be used to strengthen traditional earthen bunds or protect the banks of village ponds from erosion. Particularly in developing countries, where coir is abundantly available and textiles can be produced by small-scale industry, this is an attractive alternative for conventional methods. The paper analyses the performance of different treatments with regard to soil moisture content, protection against erosion and biomass production

Systematic multi-configuration calculations on structures and properties of complex atoms

Die relativistische Multikonfigurations Dirac-Fock (MCDF) Methode ist gegenwärtig eines der am häufigsten benutzten Verfahren zur Berechnung der elektronischen Struktur und der Eigenschaften freier Atome. In diesem Verfahren werden die Wellenfunktionen ausgewählter atomarer Zustände als eine Linearkombination von sogenannten Konfigurationszuständen (CSF - Configuration State Functions) konstruiert, die in einem Teilraum des N-Elektronen Hilbert-Raumes eine (Vielteilchen-)Basis aufspannen. Die konkrete Konstruktion dieser Basis entscheidet letzlich über die Güte der Wellenfunktionen, die üblicherweise mit Hilfe einer Variation des Erwartungswertes zum no-pair Dirac-Coulomb Hamiltonoperators gewonnen werden. Mit Hilfe von MCDF Wellenfunktionen können die dominanten relativistischen und Korrelationseffekte in freien Atomen allgemein recht gut erfaßt und verstanden werden. Außer der instantanen Coulombabstoßung zwischen allen Elektronenpaaren werden dabei auch die relativistischen Korrekturen zur Elektron-Elektron Wechselwirkung, d.h. die magnetischen und Retardierungsbeiträge in der Wechselwirkung der Elektronen untereinander, die Ankopplung der Elektronen an das Strahlungsfeld sowie der Einfluß eines ausgedehnten Kernmodells erfaßt. Im Vergleich mit früheren MCDF Rechnungen werden in den in dieser Arbeit diskutierten Fallstudien Wellenfunktionsentwicklungen verwendet, die um 1-2 Größenordnungen aufwendiger sind und daher systematische Untersuchungen inzwischen auch an Atomen mit offenen d- und f-Schalen erlauben. Eine spontane Emission oder Absorption von Photonen kann bei freien Atomen theoretisch am einfachsten mit Hilfe von Übergangswahrscheinlichkeiten erfaßt werden. Solche Daten werden heute in vielen Forschungsbereichen benötigt, wobei neben den traditionellen Gebieten der Fusionsforschung und Astrophysik zunehmend auch neue Forschungsrichtungen (z.B. Nanostrukturforschung und Röntgenlithographie) zunehmend ins Blickfeld rücken. Um die Zuverlässigkeit unserer theoretischen Vorhersagen zu erhöhen, wurde in dieser Arbeit insbesondere die Relaxation der gebundenen Elektronendichte, die rechentechnisch einen deutlich größeren Aufwand erfordert, detailliert untersucht. Eine Berücksichtigung dieser Relaxationseffekte führt oftmals auch zu einer deutlich besseren Übereinstimmung mit experimentellen Werten, insbesondere für dn=1 Übergänge sowie für schwache und Interkombinationslinien, die innerhalb einer Hauptschale (dn=0) vorkommen. Unsere in den vergangenen Jahren verbesserten Rechnungen zu den Wellenfunktionen und Übergangswahrscheinlichkeiten zeigen deutlich den Fortschritt bei der Behandlung komplexer Atome. Gleichzeitig kann dieses neue Herangehen künftig aber auch auf (i) kompliziertere Schalensstrukturen, (ii) die Untersuchung von Zwei-Elektronen-ein-Photon (TEOP) Übergängen sowie (iii) auf eine Reihe weiterer atomarer Eigenschaften übertragen werden, die bekanntermaßen empflindlich von der Relaxation der Elektronendichte abhängen. Dies sind bspw. Augerzerfälle, die atomare Photoionisation oder auch strahlende und dielektronische Rekombinationsprozesse, die theoretisch bisher nur selten überhaupt in der Dirac-Fock Näherung betrachtet wurden.

Multi-site time-trend analysis of soil fertility management effects on crop production in sub-Saharan West Africa

Soil fertility constraints to crop production have been recognized widely as a major obstacle to food security and agro-ecosystem sustainability in sub-Saharan West Africa. As such, they have led to a multitude of research projects and policy debates on how best they should be overcome. Conclusions, based on long-term multi-site experiments, are lacking with respect to a regional assessment of phosphorus and nitrogen fertilizer effects, surface mulched crop residues, and legume rotations on total dry matter of cereals in this region. A mixed model time-trend analysis was used to investigate the effects of four nitrogen and phosphorus rates, annually applied crop residue dry matter at 500 and 2000 kg ha^-1, and cereal-legume rotation versus continuous cereal cropping on the total dry matter of cereals and legumes. The multi-factorial experiment was conducted over four years at eight locations, with annual rainfall ranging from 510 to 1300 mm, in Niger, Burkina Faso, and Togo. With the exception of phosphorus, treatment effects on legume growth were marginal. At most locations, except for typical Sudanian sites with very low base saturation and high rainfall, phosphorus effects on cereal total dry matter were much lower with rock phosphate than with soluble phosphorus, unless the rock phosphate was combined with an annual seed-placement of 4 kg ha^-1 phosphorus. Across all other treatments, nitrogen effects were negligible at 500 mm annual rainfall but at 900 mm, the highest nitrogen rate led to total dry matter increases of up to 77% and, at 1300 mm, to 183%. Mulch-induced increases in cereal total dry matter were larger with lower base saturation, reaching 45% on typical acid sandy Sahelian soils. Legume rotation effects tended to increase over time but were strongly species-dependent.

Management approaches in organic potato and tomato production

The presented thesis considered three different system approach topics to ensure yield and plant health in organically grown potatoes and tomatoes. The first topic describes interactions between late blight (Phytophthora infestans) incidence and soil nitrogen supply on yield in organic potato farming focussing in detail on the yield loss relationship of late blight based on results of several field trials. The interactive effects of soil N-supply, climatic conditions and late blight on the yield were studied in the presence and absence of copper fungicides from 2002-2004 for the potato cultivar Nicola. Under conditions of central Germany the use of copper significantly reduced late blight in almost all cases (15-30 %). However, the reductions in disease through copper application did not result in statistically significant yield increases (+0 – +10 %). Subsequently, only 30 % of the variation in yield could be attributed to disease reductions. A multiple regression model (R²Max), however, including disease reduction, growth duration and temperature sum from planting until 60 % disease severity was reached and soil mineral N contents 10 days after emergence could explain 75 % of the observed variations in yield. The second topic describes the effect of some selected organic fertilisers and biostimulant products on nitrogen-mineralization and efficiency, yield and diseases in organic potato and tomato trials. The organic fertilisers Biofeed Basis (BFB, plant derived, AgroBioProducts, Wageningen, Netherlands) and BioIlsa 12,5 Export (physically hydrolysed leather shavings, hair and skin of animals; ILSA, Arizignano, Italy) and two biostimulant products BioFeed Quality (BFQ, multi-compound seaweed extract, AgroBioProducts) and AUSMA (aqueous pine and spruce needle extract, A/S BIOLAT, Latvia), were tested. Both fertilisers supplied considerable amounts of nitrogen during the main uptake phases of the crops and reached yields as high or higher as compared to the control with horn meal fertilisation. The N-efficiency of the tested fertilisers in potatoes ranged from 90 to 159 kg yield*kg-1 N – input. Most effective with tomatoes were the combined treatments of fertiliser BFB and the biostimulants AUSMA and BFQ. Both biostimulants significantly increased the share of healthy fruit and/or the number of fruits. BFQ significantly increased potato yields (+6 %) in one out of two years and reduced R. solani-infestation in the potatoes. This suggests that the biostimulants had effects on plant metabolism and resistance properties. However, no effects of biostimulants on potato late blight could be observed in the fields. The third topic focused on the effect of suppressive composts and seed tuber health on the saprophytic pathogen Rhizoctonia solani in organic potato systems. In the present study 5t ha-1 DM of a yard and bio-waste (60/40) compost produced in a 5 month composting process and a 15 month old 100 % yard waste compost were used to assess the effects on potato infection with R. solani when applying composts within the limits allowed. Across the differences in initial seed tuber infestation and 12 cultivars 5t DM ha-1 of high quality composts, applied in the seed tuber area, reduced the infestation of harvested potatoes with black scurf, tuber malformations and dry core tubers by 20 to 84 %, 20 to 49 % and 38 to 54 %, respectively, while marketable yields were increased by 5 to 25 % due to lower rates of wastes after sorting (marketable yield is gross yield minus malformed tubers, tubers with dry core, tubers with black scurf > 15% infested skin). The rate of initial black scurf infection of the seed tubers also affected tuber number, health and quality significantly. Compared to healthy seed tubers initial black scurf sclerotia infestation of 2-5 and >10 % of tuber surface led in untreated plots to a decrease in marketable yields by 14-19 and 44-66 %, a increase of black scurf severity by 8-40 and 34-86 % and also increased the amount of malformed and dry core tubers by 32-57 and 109-214 %.

Development of thermo-analytical prediction and classification models for food in thermal devices using a multi sensor system and artificial neural networks

Die thermische Verarbeitung von Lebensmitteln beeinflusst deren Qualität und ernährungsphysiologischen Eigenschaften. Im Haushalt ist die Überwachung der Temperatur innerhalb des Lebensmittels sehr schwierig. Zudem ist das Wissen über optimale Temperatur- und Zeitparameter für die verschiedenen Speisen oft unzureichend. Die optimale Steuerung der thermischen Zubereitung ist maßgeblich abhängig von der Art des Lebensmittels und der äußeren und inneren Temperatureinwirkung während des Garvorgangs. Das Ziel der Arbeiten war die Entwicklung eines automatischen Backofens, der in der Lage ist, die Art des Lebensmittels zu erkennen und die Temperatur im Inneren des Lebensmittels während des Backens zu errechnen. Die für die Temperaturberechnung benötigten Daten wurden mit mehreren Sensoren erfasst. Hierzu kam ein Infrarotthermometer, ein Infrarotabstandssensor, eine Kamera, ein Temperatursensor und ein Lambdasonde innerhalb des Ofens zum Einsatz. Ferner wurden eine Wägezelle, ein Strom- sowie Spannungs-Sensor und ein Temperatursensor außerhalb des Ofens genutzt. Die während der Aufheizphase aufgenommen Datensätze ermöglichten das Training mehrerer künstlicher neuronaler Netze, die die verschiedenen Lebensmittel in die entsprechenden Kategorien einordnen konnten, um so das optimale Backprogram auszuwählen. Zur Abschätzung der thermische Diffusivität der Nahrung, die von der Zusammensetzung (Kohlenhydrate, Fett, Protein, Wasser) abhängt, wurden mehrere künstliche neuronale Netze trainiert. Mit Ausnahme des Fettanteils der Lebensmittel konnten alle Komponenten durch verschiedene KNNs mit einem Maximum von 8 versteckten Neuronen ausreichend genau abgeschätzt werden um auf deren Grundlage die Temperatur im inneren des Lebensmittels zu berechnen. Die durchgeführte Arbeit zeigt, dass mit Hilfe verschiedenster Sensoren zur direkten beziehungsweise indirekten Messung der äußeren Eigenschaften der Lebensmittel sowie KNNs für die Kategorisierung und Abschätzung der Lebensmittelzusammensetzung die automatische Erkennung und Berechnung der inneren Temperatur von verschiedensten Lebensmitteln möglich ist.

Multi-Robot Task Allocation for Inspection Problems with Cooperative Tasks Using Hybrid Genetic Algorithms

In dieser Dissertation werden Methoden zur optimalen Aufgabenverteilung in Multirobotersystemen (engl. Multi-Robot Task Allocation – MRTA) zur Inspektion von Industrieanlagen untersucht. MRTA umfasst die Verteilung und Ablaufplanung von Aufgaben für eine Gruppe von Robotern unter Berücksichtigung von operativen Randbedingungen mit dem Ziel, die Gesamteinsatzkosten zu minimieren. Dank zunehmendem technischen Fortschritt und sinkenden Technologiekosten ist das Interesse an mobilen Robotern für den Industrieeinsatz in den letzten Jahren stark gestiegen. Viele Arbeiten konzentrieren sich auf Probleme der Mobilität wie Selbstlokalisierung und Kartierung, aber nur wenige Arbeiten untersuchen die optimale Aufgabenverteilung. Da sich mit einer guten Aufgabenverteilung eine effizientere Planung erreichen lässt (z. B. niedrigere Kosten, kürzere Ausführungszeit), ist das Ziel dieser Arbeit die Entwicklung von Lösungsmethoden für das aus Inspektionsaufgaben mit Einzel- und Zweiroboteraufgaben folgende Such-/Optimierungsproblem. Ein neuartiger hybrider Genetischer Algorithmus wird vorgestellt, der einen teilbevölkerungbasierten Genetischen Algorithmus zur globalen Optimierung mit lokalen Suchheuristiken kombiniert. Zur Beschleunigung dieses Algorithmus werden auf die fittesten Individuen einer Generation lokale Suchoperatoren angewendet. Der vorgestellte Algorithmus verteilt die Aufgaben nicht nur einfach und legt den Ablauf fest, sondern er bildet auch temporäre Roboterverbünde für Zweiroboteraufgaben, wodurch räumliche und zeitliche Randbedingungen entstehen. Vier alternative Kodierungsstrategien werden für den vorgestellten Algorithmus entworfen: Teilaufgabenbasierte Kodierung: Hierdurch werden alle möglichen Lösungen abgedeckt, allerdings ist der Suchraum sehr groß. Aufgabenbasierte Kodierung: Zwei Möglichkeiten zur Zuweisung von Zweiroboteraufgaben wurden implementiert, um die Effizienz des Algorithmus zu steigern. Gruppierungsbasierte Kodierung: Zeitliche Randbedingungen zur Gruppierung von Aufgaben werden vorgestellt, um gute Lösungen innerhalb einer kleinen Anzahl von Generationen zu erhalten. Zwei Umsetzungsvarianten werden vorgestellt. Dekompositionsbasierte Kodierung: Drei geometrische Zerlegungen wurden entworfen, die Informationen über die räumliche Anordnung ausnutzen, um Probleme zu lösen, die Inspektionsgebiete mit rechteckigen Geometrien aufweisen. In Simulationsstudien wird die Leistungsfähigkeit der verschiedenen hybriden Genetischen Algorithmen untersucht. Dazu wurde die Inspektion von Tanklagern einer Erdölraffinerie mit einer Gruppe homogener Inspektionsroboter als Anwendungsfall gewählt. Die Simulationen zeigen, dass Kodierungsstrategien, die auf der geometrischen Zerlegung basieren, bei einer kleinen Anzahl an Generationen eine bessere Lösung finden können als die anderen untersuchten Strategien. Diese Arbeit beschäftigt sich mit Einzel- und Zweiroboteraufgaben, die entweder von einem einzelnen mobilen Roboter erledigt werden können oder die Zusammenarbeit von zwei Robotern erfordern. Eine Erweiterung des entwickelten Algorithmus zur Behandlung von Aufgaben, die mehr als zwei Roboter erfordern, ist möglich, würde aber die Komplexität der Optimierungsaufgabe deutlich vergrößern.

Growing through Connections – A Multi-Case Study of Two Alternative Food Networks in Cluj-Napoca, Romania

In a context of urgent global socio-ecological challenges, the aim of this paper has been to explore the potential of localised and socially connected food systems. More specifically, through a multi-case study of two alternative food networks in the city of Cluj-Napoca, Romania, their contribution to a sustainable food paradigm has been explored. An important synergy within the networks is how good food is equated with peasant produce, but issues regarding quantity, delivery arrangement, power relations and inclusiveness constitute potential conflicts. Although challenged by unfavourable trends on national and EU levels, the networks are becoming more embedded horizontally, through an intrinsic focus on community in one case and through quality food stimulating good relations in the other case. The networks contribute to a sustainable food paradigm by promoting agroecology, by reclaiming socio-cultural factors of food provisioning and by being part of a (re)-peasantisation process. Exploring how these kinds of initiatives can emerge, be sustained and be developed is of relevance, especially considering their potential for improving the prospects of environmentally sustainable and socially just futures in Romania and beyond.

Pi: A Parallel Architecture Interface for Multi-Model Execution

This thesis defines Pi, a parallel architecture interface that separates model and machine issues, allowing them to be addressed independently. This provides greater flexibility for both the model and machine builder. Pi addresses a set of common parallel model requirements including low latency communication, fast task switching, low cost synchronization, efficient storage management, the ability to exploit locality, and efficient support for sequential code. Since Pi provides generic parallel operations, it can efficiently support many parallel programming models including hybrids of existing models. Pi also forms a basis of comparison for architectural components.

Heterogeneous Multi-Robot Cooperation

This report addresses the problem of achieving cooperation within small- to medium- sized teams of heterogeneous mobile robots. I describe a software architecture I have developed, called ALLIANCE, that facilitates robust, fault tolerant, reliable, and adaptive cooperative control. In addition, an extended version of ALLIANCE, called L-ALLIANCE, is described, which incorporates a dynamic parameter update mechanism that allows teams of mobile robots to improve the efficiency of their mission performance through learning. A number of experimental results of implementing these architectures on both physical and simulated mobile robot teams are described. In addition, this report presents the results of studies of a number of issues in mobile robot cooperation, including fault tolerant cooperative control, adaptive action selection, distributed control, robot awareness of team member actions, improving efficiency through learning, inter-robot communication, action recognition, and local versus global control.

Design and Control of an Anthropomorphic Robotic Finger with Multi-point Tactile Sensation

The goal of this research is to develop the prototype of a tactile sensing platform for anthropomorphic manipulation research. We investigate this problem through the fabrication and simple control of a planar 2-DOF robotic finger inspired by anatomic consistency, self-containment, and adaptability. The robot is equipped with a tactile sensor array based on optical transducer technology whereby localized changes in light intensity within an illuminated foam substrate correspond to the distribution and magnitude of forces applied to the sensor surface plane. The integration of tactile perception is a key component in realizing robotic systems which organically interact with the world. Such natural behavior is characterized by compliant performance that can initiate internal, and respond to external, force application in a dynamic environment. However, most of the current manipulators that support some form of haptic feedback either solely derive proprioceptive sensation or only limit tactile sensors to the mechanical fingertips. These constraints are due to the technological challenges involved in high resolution, multi-point tactile perception. In this work, however, we take the opposite approach, emphasizing the role of full-finger tactile feedback in the refinement of manual capabilities. To this end, we propose and implement a control framework for sensorimotor coordination analogous to infant-level grasping and fixturing reflexes. This thesis details the mechanisms used to achieve these sensory, actuation, and control objectives, along with the design philosophies and biological influences behind them. The results of behavioral experiments with a simple tactilely-modulated control scheme are also described. The hope is to integrate the modular finger into an %engineered analog of the human hand with a complete haptic system.

Improving Multi-class Text Classification with Naive Bayes

There are numerous text documents available in electronic form. More and more are becoming available every day. Such documents represent a massive amount of information that is easily accessible. Seeking value in this huge collection requires organization; much of the work of organizing documents can be automated through text classification. The accuracy and our understanding of such systems greatly influences their usefulness. In this paper, we seek 1) to advance the understanding of commonly used text classification techniques, and 2) through that understanding, improve the tools that are available for text classification. We begin by clarifying the assumptions made in the derivation of Naive Bayes, noting basic properties and proposing ways for its extension and improvement. Next, we investigate the quality of Naive Bayes parameter estimates and their impact on classification. Our analysis leads to a theorem which gives an explanation for the improvements that can be found in multiclass classification with Naive Bayes using Error-Correcting Output Codes. We use experimental evidence on two commonly-used data sets to exhibit an application of the theorem. Finally, we show fundamental flaws in a commonly-used feature selection algorithm and develop a statistics-based framework for text feature selection. Greater understanding of Naive Bayes and the properties of text allows us to make better use of it in text classification.

Assembly Guidance in Augmented Reality Environments Using a Virtual Interactive Tool

The application of augmented reality (AR) technology for assembly guidance is a novel approach in the traditional manufacturing domain. In this paper, we propose an AR approach for assembly guidance using a virtual interactive tool that is intuitive and easy to use. The virtual interactive tool, termed the Virtual Interaction Panel (VirIP), involves two tasks: the design of the VirIPs and the real-time tracking of an interaction pen using a Restricted Coulomb Energy (RCE) neural network. The VirIP includes virtual buttons, which have meaningful assembly information that can be activated by an interaction pen during the assembly process. A visual assembly tree structure (VATS) is used for information management and assembly instructions retrieval in this AR environment. VATS is a hierarchical tree structure that can be easily maintained via a visual interface. This paper describes a typical scenario for assembly guidance using VirIP and VATS. The main characteristic of the proposed AR system is the intuitive way in which an assembly operator can easily step through a pre-defined assembly plan/sequence without the need of any sensor schemes or markers attached on the assembly components.