Joint Computing and Network Resource Scheduling in a Lambda Grid Network

Data-intensive Grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth lightpath is called a Lambda Grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on Lambda Grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a Lambda Grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a Lambda Grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

Joint Computing and Network Resource Scheduling in a Lambda Grid Network

Data-intensive Grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth lightpath is called a Lambda Grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on Lambda Grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a Lambda Grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a Lambda Grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

Fatores que Influenciam a flexibilidade da produção de veículos comerciais

Pós-graduação em Engenharia de Produção - FEG

A comparison of CA125, HE4, risk ovarian malignancy algorithm (ROMA), and risk malignancy index (RMI) for the classification of ovarian masses

OBJECTIVE: Differentiation between benign and malignant ovarian neoplasms is essential for creating a system for patient referrals. Therefore, the contributions of the tumor markers CA125 and human epididymis protein 4 (HE4) as well as the risk ovarian malignancy algorithm (ROMA) and risk malignancy index (RMI) values were considered individually and in combination to evaluate their utility for establishing this type of patient referral system. METHODS: Patients who had been diagnosed with ovarian masses through imaging analyses (n = 128) were assessed for their expression of the tumor markers CA125 and HE4. The ROMA and RMI values were also determined. The sensitivity and specificity of each parameter were calculated using receiver operating characteristic curves according to the area under the curve (AUC) for each method. RESULTS: The sensitivities associated with the ability of CA125, HE4, ROMA, or RMI to distinguish between malignant versus benign ovarian masses were 70.4%, 79.6%, 74.1%, and 63%, respectively. Among carcinomas, the sensitivities of CA125, HE4, ROMA (pre-and post-menopausal), and RMI were 93.5%, 87.1%, 80%, 95.2%, and 87.1%, respectively. The most accurate numerical values were obtained with RMI, although the four parameters were shown to be statistically equivalent. CONCLUSION: There were no differences in accuracy between CA125, HE4, ROMA, and RMI for differentiating between types of ovarian masses. RMI had the lowest sensitivity but was the most numerically accurate method. HE4 demonstrated the best overall sensitivity for the evaluation of malignant ovarian tumors and the differential diagnosis of endometriosis. All of the parameters demonstrated increased sensitivity when tumors with low malignancy potential were considered low-risk, which may be used as an acceptable assessment method for referring patients to reference centers.

Does videothoracoscopy improve clinical outcomes when implemented as part of a pleural empyema treatment algorithm?

OBJECTIVE: We aimed to evaluate whether the inclusion of videothoracoscopy in a pleural empyema treatment algorithm would change the clinical outcome of such patients. METHODS: This study performed quality-improvement research. We conducted a retrospective review of patients who underwent pleural decortication for pleural empyema at our institution from 2002 to 2008. With the old algorithm (January 2002 to September 2005), open decortication was the procedure of choice, and videothoracoscopy was only performed in certain sporadic mid-stage cases. With the new algorithm (October 2005 to December 2008), videothoracoscopy became the first-line treatment option, whereas open decortication was only performed in patients with a thick pleural peel (>2 cm) observed by chest scan. The patients were divided into an old algorithm (n = 93) and new algorithm (n = 113) group and compared. The main outcome variables assessed included treatment failure (pleural space reintervention or death up to 60 days after medical discharge) and the occurrence of complications. RESULTS: Videothoracoscopy and open decortication were performed in 13 and 80 patients from the old algorithm group and in 81 and 32 patients from the new algorithm group, respectively (p < 0.01). The patients in the new algorithm group were older (41 +/- 1 vs. 46.3 +/- 16.7 years, p=0.014) and had higher Charlson Comorbidity Index scores [0(0-3) vs. 2(0-4), p = 0.032]. The occurrence of treatment failure was similar in both groups (19.35% vs. 24.77%, p= 0.35), although the complication rate was lower in the new algorithm group (48.3% vs. 33.6%, p = 0.04). CONCLUSIONS: The wider use of videothoracoscopy in pleural empyema treatment was associated with fewer complications and unaltered rates of mortality and reoperation even though more severely ill patients were subjected to videothoracoscopic surgery.

Risk Factor Analysis of Late Survival After Heart Transplantation According to Donor Profile: A Multi-Institutional Retrospective Study of 512 Transplants

Introduction. Patients with terminal heart failure have increased more than the available organs leading to a high mortality rate on the waiting list. Use of Marginal and expanded criteria donors has increased due to the heart shortage. Objective. We analyzed all heart transplantations (HTx) in Sao Paulo state over 8 years for donor profile and recipient risk factors. Method. This multi-institutional review collected HTx data from all institutions in the state of Sao Paulo, Brazil. From 2002 to 2008 (6 years), only 512 (28.8%) of 1777 available heart donors were accepted for transplantation. All medical records were analyzed retrospectively; none of the used donors was excluded, even those considered to be nonstandard. Results. The hospital mortality rate was 27.9% (n = 143) and the average follow-up time was 29.4 +/- 28.4 months. The survival rate was 55.5% (n = 285) at 6 years after HTx. Univariate analysis showed the following factors to impact survival: age (P = .0004), arterial hypertension (P = .4620), norepinephrine (P = .0450), cardiac arrest (P = .8500), diabetes mellitus (P = .5120), infection (P = .1470), CKMB (creatine kinase MB) (P = .8694), creatinine (P = .7225), and Na+ (P = .3273). On multivariate analysis, only age showed significance; logistic regression showed a significant cut-off at 40 years: organs from donors older than 40 years showed a lower late survival rates (P = .0032). Conclusions. Donor age older than 40 years represents an important risk factor for survival after HTx. Neither donor gender nor norepinephrine use negatively affected early survival.

Multi-criteria analysis in the strategic environmental assessment of the sugar and alcohol sector

The Strategic Environmental Assessment (SEA) of the sugar and alcohol sector guides a territorial and sectoral planning that benefits most of the local society and supports this economic activity in all its stages. In this way, the present work aims to determine an index of aggregation of the indicators generated in the baseline of the SEA process, called Index of Sustainability of Expansion of the Sugar and Alcohol Sector (IScana). For this, it was used the normalization of the indicators of each city by the fuzzy logic and attribution of weights by the Analytic Hierarchy Process (AHP). Then, the IScana values had been spatialized in the region of 'Grande Dourados'-Mato Grosso do Sul State. The northern portion concentrated the highest values of IScana, 0.48 and 0.55, referring to the cities of Nova Alvorada do Sul and Rio Brilhante, while, in the central portion, the city of Dourados presented the lowest value, 0.10. The selection of the set of indicators forming the IScana, and their relative importance, was satisfactory for the application of fuzzy logic and AHP techniques. The IScana index supplies objective information regarding the diagnosis of the region for the application of SEA.

A three-pronged approach to social business: a Brazilian multi-case analysis

Social businesses present a new paradigm to capitalism, in which private companies, non-profit organizations and civil society create a new type of business with the main objective of solving social problems with financial sustainability and efficiency through market mechanisms. As any new phenomenon, different authors conceptualize social businesses with distinct views. This article aims to present and characterize three different perspectives of social business definitions: the European, the American and that of the emerging countries. Each one of these views was illustrated by a different Brazilian case. We conclude with the idea that all the cases have similar characteristics, but also relevant differences that are more than merely geographical. The perspectives analyzed in this paper provide an analytical framework for understanding the field of social businesses. Moreover, the cases demonstrate that in the Brazilian context the field of social business is under construction and that as such it draws on different conceptual influences to deal with a complex and challenging reality.

Programmable logic design of a compact Genetic Algorithm for phasor estimation in real-time

The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).

Probabilistic approaches in civil engineering: generation of random fields and structural identification with genetic algorithms

The inherent stochastic character of most of the physical quantities involved in engineering models has led to an always increasing interest for probabilistic analysis. Many approaches to stochastic analysis have been proposed. However, it is widely acknowledged that the only universal method available to solve accurately any kind of stochastic mechanics problem is Monte Carlo Simulation. One of the key parts in the implementation of this technique is the accurate and efficient generation of samples of the random processes and fields involved in the problem at hand. In the present thesis an original method for the simulation of homogeneous, multi-dimensional, multi-variate, non-Gaussian random fields is proposed. The algorithm has proved to be very accurate in matching both the target spectrum and the marginal probability. The computational efficiency and robustness are very good too, even when dealing with strongly non-Gaussian distributions. What is more, the resulting samples posses all the relevant, welldefined and desired properties of “translation fields”, including crossing rates and distributions of extremes. The topic of the second part of the thesis lies in the field of non-destructive parametric structural identification. Its objective is to evaluate the mechanical characteristics of constituent bars in existing truss structures, using static loads and strain measurements. In the cases of missing data and of damages that interest only a small portion of the bar, Genetic Algorithm have proved to be an effective tool to solve the problem.

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

Modulation Techniques for Multi-Phase Converters and Control Strategies for Multi-Phase Electric Drives

The ever-increasing spread of automation in industry puts the electrical engineer in a central role as a promoter of technological development in a sector such as the use of electricity, which is the basis of all the machinery and productive processes. Moreover the spread of drives for motor control and static converters with structures ever more complex, places the electrical engineer to face new challenges whose solution has as critical elements in the implementation of digital control techniques with the requirements of inexpensiveness and efficiency of the final product. The successfully application of solutions using non-conventional static converters awake an increasing interest in science and industry due to the promising opportunities. However, in the same time, new problems emerge whose solution is still under study and debate in the scientific community During the Ph.D. course several themes have been developed that, while obtaining the recent and growing interest of scientific community, have much space for the development of research activity and for industrial applications. The first area of research is related to the control of three phase induction motors with high dynamic performance and the sensorless control in the high speed range. The management of the operation of induction machine without position or speed sensors awakes interest in the industrial world due to the increased reliability and robustness of this solution combined with a lower cost of production and purchase of this technology compared to the others available in the market. During this dissertation control techniques will be proposed which are able to exploit the total dc link voltage and at the same time capable to exploit the maximum torque capability in whole speed range with good dynamic performance. The proposed solution preserves the simplicity of tuning of the regulators. Furthermore, in order to validate the effectiveness of presented solution, it is assessed in terms of performance and complexity and compared to two other algorithm presented in literature. The feasibility of the proposed algorithm is also tested on induction motor drive fed by a matrix converter. Another important research area is connected to the development of technology for vehicular applications. In this field the dynamic performances and the low power consumption is one of most important goals for an effective algorithm. Towards this direction, a control scheme for induction motor that integrates within a coherent solution some of the features that are commonly required to an electric vehicle drive is presented. The main features of the proposed control scheme are the capability to exploit the maximum torque in the whole speed range, a weak dependence on the motor parameters, a good robustness against the variations of the dc-link voltage and, whenever possible, the maximum efficiency. The second part of this dissertation is dedicated to the multi-phase systems. This technology, in fact, is characterized by a number of issues worthy of investigation that make it competitive with other technologies already on the market. Multiphase systems, allow to redistribute power at a higher number of phases, thus making possible the construction of electronic converters which otherwise would be very difficult to achieve due to the limits of present power electronics. Multiphase drives have an intrinsic reliability given by the possibility that a fault of a phase, caused by the possible failure of a component of the converter, can be solved without inefficiency of the machine or application of a pulsating torque. The control of the magnetic field spatial harmonics in the air-gap with order higher than one allows to reduce torque noise and to obtain high torque density motor and multi-motor applications. In one of the next chapters a control scheme able to increase the motor torque by adding a third harmonic component to the air-gap magnetic field will be presented. Above the base speed the control system reduces the motor flux in such a way to ensure the maximum torque capability. The presented analysis considers the drive constrains and shows how these limits modify the motor performance. The multi-motor applications are described by a well-defined number of multiphase machines, having series connected stator windings, with an opportune permutation of the phases these machines can be independently controlled with a single multi-phase inverter. In this dissertation this solution will be presented and an electric drive consisting of two five-phase PM tubular actuators fed by a single five-phase inverter will be presented. Finally the modulation strategies for a multi-phase inverter will be illustrated. The problem of the space vector modulation of multiphase inverters with an odd number of phases is solved in different way. An algorithmic approach and a look-up table solution will be proposed. The inverter output voltage capability will be investigated, showing that the proposed modulation strategy is able to fully exploit the dc input voltage either in sinusoidal or non-sinusoidal operating conditions. All this aspects are considered in the next chapters. In particular, Chapter 1 summarizes the mathematical model of induction motor. The Chapter 2 is a brief state of art on three-phase inverter. Chapter 3 proposes a stator flux vector control for a three- phase induction machine and compares this solution with two other algorithms presented in literature. Furthermore, in the same chapter, a complete electric drive based on matrix converter is presented. In Chapter 4 a control strategy suitable for electric vehicles is illustrated. Chapter 5 describes the mathematical model of multi-phase induction machines whereas chapter 6 analyzes the multi-phase inverter and its modulation strategies. Chapter 7 discusses the minimization of the power losses in IGBT multi-phase inverters with carrier-based pulse width modulation. In Chapter 8 an extended stator flux vector control for a seven-phase induction motor is presented. Chapter 9 concerns the high torque density applications and in Chapter 10 different fault tolerant control strategies are analyzed. Finally, the last chapter presents a positioning multi-motor drive consisting of two PM tubular five-phase actuators fed by a single five-phase inverter.

Exact Algorithms for Different Classes of Vehicle Routing Problems

We deal with five problems arising in the field of logistics: the Asymmetric TSP (ATSP), the TSP with Time Windows (TSPTW), the VRP with Time Windows (VRPTW), the Multi-Trip VRP (MTVRP), and the Two-Echelon Capacitated VRP (2E-CVRP). The ATSP requires finding a lest-cost Hamiltonian tour in a digraph. We survey models and classical relaxations, and describe the most effective exact algorithms from the literature. A survey and analysis of the polynomial formulations is provided. The considered algorithms and formulations are experimentally compared on benchmark instances. The TSPTW requires finding, in a weighted digraph, a least-cost Hamiltonian tour visiting each vertex within a given time window. We propose a new exact method, based on new tour relaxations and dynamic programming. Computational results on benchmark instances show that the proposed algorithm outperforms the state-of-the-art exact methods. In the VRPTW, a fleet of identical capacitated vehicles located at a depot must be optimally routed to supply customers with known demands and time window constraints. Different column generation bounding procedures and an exact algorithm are developed. The new exact method closed four of the five open Solomon instances. The MTVRP is the problem of optimally routing capacitated vehicles located at a depot to supply customers without exceeding maximum driving time constraints. Two set-partitioning-like formulations of the problem are introduced. Lower bounds are derived and embedded into an exact solution method, that can solve benchmark instances with up to 120 customers. The 2E-CVRP requires designing the optimal routing plan to deliver goods from a depot to customers by using intermediate depots. The objective is to minimize the sum of routing and handling costs. A new mathematical formulation is introduced. Valid lower bounds and an exact method are derived. Computational results on benchmark instances show that the new exact algorithm outperforms the state-of-the-art exact methods.

Nonlinear Control Strategies for Cooperative Control of Multi-Robot Systems

This thesis deals with distributed control strategies for cooperative control of multi-robot systems. Specifically, distributed coordination strategies are presented for groups of mobile robots. The formation control problem is initially solved exploiting artificial potential fields. The purpose of the presented formation control algorithm is to drive a group of mobile robots to create a completely arbitrarily shaped formation. Robots are initially controlled to create a regular polygon formation. A bijective coordinate transformation is then exploited to extend the scope of this strategy, to obtain arbitrarily shaped formations. For this purpose, artificial potential fields are specifically designed, and robots are driven to follow their negative gradient. Artificial potential fields are then subsequently exploited to solve the coordinated path tracking problem, thus making the robots autonomously spread along predefined paths, and move along them in a coordinated way. Formation control problem is then solved exploiting a consensus based approach. Specifically, weighted graphs are used both to define the desired formation, and to implement collision avoidance. As expected for consensus based algorithms, this control strategy is experimentally shown to be robust to the presence of communication delays. The global connectivity maintenance issue is then considered. Specifically, an estimation procedure is introduced to allow each agent to compute its own estimate of the algebraic connectivity of the communication graph, in a distributed manner. This estimate is then exploited to develop a gradient based control strategy that ensures that the communication graph remains connected, as the system evolves. The proposed control strategy is developed initially for single-integrator kinematic agents, and is then extended to Lagrangian dynamical systems.

Content extraction: Identifying the main content in HTML documents

Except the article forming the main content most HTML documents on the WWW contain additional contents such as navigation menus, design elements or commercial banners. In the context of several applications it is necessary to draw the distinction between main and additional content automatically. Content extraction and template detection are the two approaches to solve this task. This thesis gives an extensive overview of existing algorithms from both areas. It contributes an objective way to measure and evaluate the performance of content extraction algorithms under different aspects. These evaluation measures allow to draw the first objective comparison of existing extraction solutions. The newly introduced content code blurring algorithm overcomes several drawbacks of previous approaches and proves to be the best content extraction algorithm at the moment. An analysis of methods to cluster web documents according to their underlying templates is the third major contribution of this thesis. In combination with a localised crawling process this clustering analysis can be used to automatically create sets of training documents for template detection algorithms. As the whole process can be automated it allows to perform template detection on a single document, thereby combining the advantages of single and multi document algorithms.