In-Motes EYE:a real time application for automobiles in wireless sensor networks

Wireless sensor networks have been identified as one of the key technologies for the 21st century. In order to overcome their limitations such as fault tolerance and conservation of energy, we propose a middleware solution, In-Motes. In-Motes stands as a fault tolerant platform for deploying and monitoring applications in real time offers a number of possibilities for the end user giving him in parallel the freedom to experiment with various parameters, in an effort the deployed applications to run in an energy efficient manner inside the network. The proposed scheme is evaluated through the In-Motes EYE application, aiming to test its merits under real time conditions. In-Motes EYE application which is an agent based real time In-Motes application developed for sensing acceleration variations in an environment. The application was tested in a prototype area, road alike, for a period of four months.

Design of a modular, high step-up ratio DC–DC converter for HVDC applications integrating offshore wind power

High-power and high-voltage gain dc-dc converters are key to high-voltage direct current (HVDC) power transmission for offshore wind power. This paper presents an isolated ultra-high step-up dc-dc converter in matrix transformer configuration. A flyback-forward converter is adopted as the power cell and the secondary side matrix connection is introduced to increase the power level and to improve fault tolerance. Because of the modular structure of the converter, the stress on the switching devices is decreased and so is the transformer size. The proposed topology can be operated in column interleaved modes, row interleaved modes, and hybrid working modes in order to deal with the varying energy from the wind farm. Furthermore, fault-tolerant operation is also realized in several fault scenarios. A 400-W dc-dc converter with four cells is developed and experimentally tested to validate the proposed technique, which can be applied to high-power high-voltage dc power transmission.

Structural Health Monitoring using Index Based Reasoning for Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) may develop cracks, erosion, delamination or other damages due to aging, fatigue or extreme loads. Identifying these damages is critical for the safe and reliable operation of the systems. ^ Structural Health Monitoring (SHM) is capable of determining the conditions of systems automatically and continually through processing and interpreting the data collected from a network of sensors embedded into the systems. With the desired awareness of the systems’ health conditions, SHM can greatly reduce operational cost and speed up maintenance processes. ^ The purpose of this study is to develop an effective, low-cost, flexible and fault tolerant structural health monitoring system. The proposed Index Based Reasoning (IBR) system started as a simple look-up-table based diagnostic system. Later, Fast Fourier Transformation analysis and neural network diagnosis with self-learning capabilities were added. The current version is capable of classifying different health conditions with the learned characteristic patterns, after training with the sensory data acquired from the operating system under different status. ^ The proposed IBR systems are hierarchy and distributed networks deployed into systems to monitor their health conditions. Each IBR node processes the sensory data to extract the features of the signal. Classifying tools are then used to evaluate the local conditions with health index (HI) values. The HI values will be carried to other IBR nodes in the next level of the structured network. The overall health condition of the system can be obtained by evaluating all the local health conditions. ^ The performance of IBR systems has been evaluated by both simulation and experimental studies. The IBR system has been proven successful on simulated cases of a turbojet engine, a high displacement actuator, and a quad rotor helicopter. For its application on experimental data of a four rotor helicopter, IBR also performed acceptably accurate. The proposed IBR system is a perfect fit for the low-cost UAVs to be the onboard structural health management system. It can also be a backup system for aircraft and advanced Space Utility Vehicles. ^

Error tolerance of topological codes with independent bit-flip and measurement errors

Topological quantum error correction codes are currently among the most promising candidates for efficiently dealing with the decoherence effects inherently present in quantum devices. Numerically, their theoretical error threshold can be calculated by mapping the underlying quantum problem to a related classical statistical-mechanical spin system with quenched disorder. Here, we present results for the general fault-tolerant regime, where we consider both qubit and measurement errors. However, unlike in previous studies, here we vary the strength of the different error sources independently. Our results highlight peculiar differences between toric and color codes. This study complements previous results published in New J. Phys. 13, 083006 (2011).

A solution to the three disjoint path problem on honeycomb tori

In a previous paper we solved an open problem named as the three disjoint path problem on honeycomb meshes. In this paper we extend the technique used to solve the related problem on honeycomb tori. The result gives the minimum possible length of the longest of any three disjoint paths between two given nodes in a torus. The problem has practical benefits in the fault tolerant aspects of interconnection topologies.

Approximation Algorithms for Network Design and Orienteering

This thesis presents approximation algorithms for some NP-Hard combinatorial optimization problems on graphs and networks; in particular, we study problems related to Network Design. Under the widely-believed complexity-theoretic assumption that P is not equal to NP, there are no efficient (i.e., polynomial-time) algorithms that solve these problems exactly. Hence, if one desires efficient algorithms for such problems, it is necessary to consider approximate solutions: An approximation algorithm for an NP-Hard problem is a polynomial time algorithm which, for any instance of the problem, finds a solution whose value is guaranteed to be within a multiplicative factor of the value of an optimal solution to that instance. We attempt to design algorithms for which this factor, referred to as the approximation ratio of the algorithm, is as small as possible. The field of Network Design comprises a large class of problems that deal with constructing networks of low cost and/or high capacity, routing data through existing networks, and many related issues. In this thesis, we focus chiefly on designing fault-tolerant networks. Two vertices u,v in a network are said to be k-edge-connected if deleting any set of k − 1 edges leaves u and v connected; similarly, they are k-vertex connected if deleting any set of k − 1 other vertices or edges leaves u and v connected. We focus on building networks that are highly connected, meaning that even if a small number of edges and nodes fail, the remaining nodes will still be able to communicate. A brief description of some of our results is given below. We study the problem of building 2-vertex-connected networks that are large and have low cost. Given an n-node graph with costs on its edges and any integer k, we give an O(log n log k) approximation for the problem of finding a minimum-cost 2-vertex-connected subgraph containing at least k nodes. We also give an algorithm of similar approximation ratio for maximizing the number of nodes in a 2-vertex-connected subgraph subject to a budget constraint on the total cost of its edges. Our algorithms are based on a pruning process that, given a 2-vertex-connected graph, finds a 2-vertex-connected subgraph of any desired size and of density comparable to the input graph, where the density of a graph is the ratio of its cost to the number of vertices it contains. This pruning algorithm is simple and efficient, and is likely to find additional applications. Recent breakthroughs on vertex-connectivity have made use of algorithms for element-connectivity problems. We develop an algorithm that, given a graph with some vertices marked as terminals, significantly simplifies the graph while preserving the pairwise element-connectivity of all terminals; in fact, the resulting graph is bipartite. We believe that our simplification/reduction algorithm will be a useful tool in many settings. We illustrate its applicability by giving algorithms to find many trees that each span a given terminal set, while being disjoint on edges and non-terminal vertices; such problems have applications in VLSI design and other areas. We also use this reduction algorithm to analyze simple algorithms for single-sink network design problems with high vertex-connectivity requirements; we give an O(k log n)-approximation for the problem of k-connecting a given set of terminals to a common sink. We study similar problems in which different types of links, of varying capacities and costs, can be used to connect nodes; assuming there are economies of scale, we give algorithms to construct low-cost networks with sufficient capacity or bandwidth to simultaneously support flow from each terminal to the common sink along many vertex-disjoint paths. We further investigate capacitated network design, where edges may have arbitrary costs and capacities. Given a connectivity requirement R_uv for each pair of vertices u,v, the goal is to find a low-cost network which, for each uv, can support a flow of R_uv units of traffic between u and v. We study several special cases of this problem, giving both algorithmic and hardness results. In addition to Network Design, we consider certain Traveling Salesperson-like problems, where the goal is to find short walks that visit many distinct vertices. We give a (2 + epsilon)-approximation for Orienteering in undirected graphs, achieving the best known approximation ratio, and the first approximation algorithm for Orienteering in directed graphs. We also give improved algorithms for Orienteering with time windows, in which vertices must be visited between specified release times and deadlines, and other related problems. These problems are motivated by applications in the fields of vehicle routing, delivery and transportation of goods, and robot path planning.

Generalized cluster states based on finite groups

We define generalized cluster states based on finite group algebras in analogy to the generalization of the toric code to the Kitaev quantum double models. We do this by showing a general correspondence between systems with CSS structure and finite group algebras, and applying this to the cluster states to derive their generalization. We then investigate properties of these states including their projected entangled pair state representations, global symmetries, and relationship to the Kitaev quantum double models. We also discuss possible applications of these states.

Engineering a Quantum Many-body Hamiltonian with Trapped Ions

While fault-tolerant quantum computation might still be years away, analog quantum simulators offer a way to leverage current quantum technologies to study classically intractable quantum systems. Cutting edge quantum simulators such as those utilizing ultracold atoms are beginning to study physics which surpass what is classically tractable. As the system sizes of these quantum simulators increase, there are also concurrent gains in the complexity and types of Hamiltonians which can be simulated. In this work, I describe advances toward the realization of an adaptable, tunable quantum simulator capable of surpassing classical computation. We simulate long-ranged Ising and XY spin models which can have global arbitrary transverse and longitudinal fields in addition to individual transverse fields using a linear chain of up to 24 Yb+ 171 ions confined in a linear rf Paul trap. Each qubit is encoded in the ground state hyperfine levels of an ion. Spin-spin interactions are engineered by the application of spin-dependent forces from laser fields, coupling spin to motion. Each spin can be read independently using state-dependent fluorescence. The results here add yet more tools to an ever growing quantum simulation toolbox. One of many challenges has been the coherent manipulation of individual qubits. By using a surprisingly large fourth-order Stark shifts in a clock-state qubit, we demonstrate an ability to individually manipulate spins and apply independent Hamiltonian terms, greatly increasing the range of quantum simulations which can be implemented. As quantum systems grow beyond the capability of classical numerics, a constant question is how to verify a quantum simulation. Here, I present measurements which may provide useful metrics for large system sizes and demonstrate them in a system of up to 24 ions during a classically intractable simulation. The observed values are consistent with extremely large entangled states, as much as ~95% of the system entangled. Finally, we use many of these techniques in order to generate a spin Hamiltonian which fails to thermalize during experimental time scales due to a meta-stable state which is often called prethermal. The observed prethermal state is a new form of prethermalization which arises due to long-range interactions and open boundary conditions, even in the thermodynamic limit. This prethermalization is observed in a system of up to 22 spins. We expect that system sizes can be extended up to 30 spins with only minor upgrades to the current apparatus. These results emphasize that as the technology improves, the techniques and tools developed here can potentially be used to perform simulations which will surpass the capability of even the most sophisticated classical techniques, enabling the study of a whole new regime of quantum many-body physics.

Glyphosate tolerant volunteer corn control at two development stages

The loss of grains during the harvest of glyphosate tolerant corn may generate volunteer plants, which can interfere in the conventional or glyphosate crop in succession. The current work aim to evaluate the control of the volunteer corn glyphosate tolerant under two weed stages. Aimed to evaluate the control of volunteer glyphosate tolerant corn in two stages of development. There were conducted two experiments with hybrid 2B688 HR (lepidoptera and glyphosate tolerant), the application were at V5 and V8 stage. The experiment was randomized block design with four replicates, using the treatments: haloxyfop at 25, 50 and 62 g ha-1 alone and associated with 2,4-D at 670 g ha-1 or fluroxypyr at 200 g ha-1. The standard was clethodim at 84 g ha-1 with 2,4-D and fluroxypyr at same rates. The applications of haloxyfop and clethodim both isolated or in a mixture with 2,4-D and fluroxypyr at V5 stage showed total control (100%) at 32 and 39 days after the application, except for haloxyfop + 2,4-D (25 + 670 g ha-1) mixture, which did not provided adequate control. At V8 stage, haloxyfop + 2,4-D (50 + 670 g ha-1) and haloxyfop + 2,4-D (62 + 670 g ha-1) mixtures took up to 6 and 10 days or longer to reach adequate to excellent control, when compared to haloxyfop isolated applications in the same doses, respectively. Either isolated clethodim or mixed with 2, 4-D and fluroxypyr did not show adequate control. The treatments showed efficient control on volunteer corn plants at V5 stage, except for haloxyfop + 2, 4-D (25 + 670 g ha-1) mixture. At V8 stage applications, haloxyfop either isolated or mixture with fluroxypyr demonstrated excellent control on every evaluated dose. The mixture with 2, 4-D can reduce haloxyfop efficiency at low doses. Clethodim alone or mixed with 2,4-D or furoxypyr did not provide acceptable level of control.

Classification and fault detection methods for fuel cell monitoring and quality control

In this paper, various types of fault detection methods for fuel cells are compared. For example, those that use a model based approach or a data driven approach or a combination of the two. The potential advantages and drawbacks of each method are discussed and comparisons between methods are made. In particular, classification algorithms are investigated, which separate a data set into classes or clusters based on some prior knowledge or measure of similarity. In particular, the application of classification methods to vectors of reconstructed currents by magnetic tomography or to vectors of magnetic field measurements directly is explored. Bases are simulated using the finite integration technique (FIT) and regularization techniques are employed to overcome ill-posedness. Fisher's linear discriminant is used to illustrate these concepts. Numerical experiments show that the ill-posedness of the magnetic tomography problem is a part of the classification problem on magnetic field measurements as well. This is independent of the particular working mode of the cell but influenced by the type of faulty behavior that is studied. The numerical results demonstrate the ill-posedness by the exponential decay behavior of the singular values for three examples of fault classes.

Genetic control of fruit-setting percentage of tomatoes tolerant to high temperatures

The aim of present work was to study, through means and variances of generations, the genetic control of fruit-set percentage in tomatoes, in a biparental cross between line Jab-95 (resistant to fruit-set) and 'Caribe' cultivar (susceptible to fruit-set) after being subjected to high temperatures. F1, F2, and backcross generations for both parents (P 1, P2) were produced in a greenhouse at FCAVUNESP, Jaboticabal-SP, Brazil. A randomized complete block experimental design with four replications was used to evaluate the different generations. Estimates of genetic parameters were obtained according to Mather and Jinks (1982). An additive-dominant model was fitted to explain the variation observed. The mean degree of dominance (0.54), indicated incomplete dominance in the direction of increasing fruit-set percentage at high temperatures. The genetic control of fruit-set percentage, at high temperatures, for tomato was found to be oligogenic or polygenic (3.54 genes). The heritability in a limited sense was 83.91%, suggesting that the selection of individuals based on the characteristic evaluated can be efficient.

Fast fault section estimation in distribution control centers using adaptive genetic algorithm

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Water Stress Reveals Differential Antioxidant Responses Of Tolerant And Non-tolerant Sugarcane Genotypes.

The biochemical responses of the enzymatic antioxidant system of a drought-tolerant cultivar (IACSP 94-2094) and a commercial cultivar in Brazil (IACSP 95-5000) grown under two levels of soil water restriction (70% and 30% Soil Available Water Content) were investigated. IACSP 94-2094 exhibited one additional active superoxide dismutase (Cu/Zn-SOD VI) isoenzyme in comparison to IACSP 95-5000, possibly contributing to the heightened response of IACSP 94-2094 to the induced stress. The total glutathione reductase (GR) activity increased substantially in IACSP 94-2094 under conditions of severe water stress; however, the appearance of a new GR isoenzyme and the disappearance of another isoenzyme were found not to be related to the stress response because the cultivars from both treatment groups (control and water restrictions) exhibited identical changes. Catalase (CAT) activity seems to have a more direct role in H2O2 detoxification under water stress condition and the shift in isoenzymes in the tolerant cultivar might have contributed to this response, which may be dependent upon the location where the excessive H2O2 is being produced under stress. The improved performance of IACSP 94-2094 under drought stress was associated with a more efficient antioxidant system response, particularly under conditions of mild stress.