Demo: Using RapidMiner for Text Mining

In this demo the basic text mining technologies by using RapidMining have been reviewed. RapidMining basic characteristics and operators of text mining have been described. Text mining example by using Navie Bayes algorithm and process modeling have been revealed.

Digital Libraries as a Social Media

This paper presents an innovative approach for enhancing digital libraries functionalities. An innovative distributed architecture involving digital libraries for effective and efficient knowledge sharing was developed. In the frame of this architecture semantic services were implemented, offering multi language and multi culture support, adaptability and knowledge resources recommendation, based on the use of ontologies, metadata and user modeling. New methods for teacher education using digital libraries and knowledge sharing were developed. These new methods were successfully applied in more than 15 pilot experiments in seven European countries, with more than 3000 teachers trained.

Advances in decision support systems on the endeavour for supply chain optimality

Industry practitioners are seeking to create optimal logistics networks through more efficient decision-making leading to a shift of power from a centralized position to a more decentralized approach. This has led to researchers, exploring with vigor, the application of agent based modeling (ABM) in supply chains and more recently, its impact on decision-making. This paper investigates reasons for the shift to decentralized decision-making and the impact on supply chains. Effective decentralization of decision-making with ABM and hybrid modeling is investigated, observing the methods and potential of achieving optimality.

Origin of the Grande Ronde Formation flows, Columbia River flood basalt group

Lavas belonging to the Grande Ronde Formation (GRB) constitute about 63% of the Columbia River Basalt Group (CRBG), a flood basalt province in the NW United States. A puzzling feature is the lack of phenocrysts (< 5%) in these chemically evolved lavas. Based mainly on this observation it has been hypothesized that GRB lavas were nearly primary melts generated by large-scale melting of eclogite. Another recent hypothesis holds that GRB magmas were extremely hydrous and rose rapidly from the mantle such that the dissolved water kept the magmas close to their liquidi. I present new textural and chemical evidence to show that GRB lavas were neither primary nor hydrous melts but were derived from other melts via efficient fractional crystallization and mixing in shallow intrusive systems. Texture and chemical features further suggest that the melt mixing process may have been exothermic, which forced variable melting of some of the existing phenocrysts. ^ Finally, reported here are the results of efforts to simulate the higher pressure histories of GRB using COMAGMAT and MELTS softwares. The intent was to evaluate (1) whether such melts could be derived from primary melts formed by partial melting of a peridotite source as an alternative to the eclogite model, or if bulk melting of eclogite is required; and (2) at what pressure such primary melts could have been in equilibrium with the mantle. I carried out both forward and inverse modeling. The best fit forward model indicates that most primitive parent melts related to GRB could have been multiply saturated at ∼1.5--2.0 GPa. I interpret this result to indicate that the parental melts last equilibrated with a peridotitic mantle at 1.5--2.0 GPa and such partial melts rose to ∼0.2 GPa where they underwent efficient mixing and fractionation before erupting. These models suggest that the source rock was not eclogitic but a fertile spinel lherzolite, and that the melts had ∼0.5% water. ^

Role of carbon nanotube dispersion in fracture toughening of plasma sprayed aluminum oxide-carbon nanotube nanocomposite coating

Aluminum oxide (Al2O3, or alumina) is a conventional ceramic known for applications such as wear resistant coatings, thermal liners, heaters, crucibles, dielectric systems, etc. However applications of Al 2O3 are limited owing to its inherent brittleness. Due to its excellent mechanical properties and bending strength, carbon nanotubes (CNT) is an ideal reinforcement for Al2O3 matrix to improve its fracture toughness. The role of CNT dispersion in the fracture toughening of the plasma sprayed Al2O3-CNT nanocomposite coating is discussed in the current work. Pretreatment of powder feedstock is required for dispersing CNTs in the matrix. Four coatings namely spray dried Al2O 3 (A-SD), Al2O3 blended with 4wt.% CNT (A4C-B), composite spray dried Al2O3-4wt.% CNT (A4C-SD) and composite spray dried A1203-8wt.% CNT (A8C-SD), are synthesized by plasma spraying. Owing to extreme temperatures and velocities involved in the plasma spraying of ceramics, retention of CNTs in the resulting coatings necessitates optimizing plasma processing parameters using an inflight particle diagnostic sensor. A bimodal microstructure was obtained in the matrix that consists of fully melted and resolidified structure and solid state sintered structure. CNTs are retained both in the fully melted region and solid-state sintered regions of processed coatings. Fracture toughness of A-SD, A4C-B, A4C-SD and A8C-SD coatings was 3.22, 3.86, 4.60 and 5.04 MPa m1/2 respectively. This affirms the improvement of fracture toughness from 20% (in A4C-B coating) to 43% (in A4C-SD coating) when compared to the A-SD coating because of the CNT dispersion. Fracture toughness improvement from 43% (in A4C-SD) to 57% (in A8C-SD) coating is evinced because of the CNT content. Reinforcement by CNTs is described by its bridging, anchoring, hook formation, impact alignment, fusion with splat, and mesh formation. The Al2O3/CNT interface is critical in assisting the stress transfer and utilizing excellent mechanical properties of CNTs. Mathematical and computational modeling using ab-initio principle is applied to understand the wetting behavior at the Al2O 3/CNT interface. Contrasting storage modulus was obtained by nanoindentation (∼210, 250, 250-350 and 325-420 GPa in A-SD, A4C-B, A4C-SD, and A8C-SD coatings respectively) depicting the toughening associated with CNT content and dispersion.

Optimization of transit transfer times: A system-wide approach

This dissertation presents a system-wide approach, based on genetic algorithms, for the optimization of transfer times for an entire bus transit system. Optimization of transfer times in a transit system is a complicated problem because of the large set of binary and discrete values involved. The combinatorial nature of the problem imposes a computational burden and makes it difficult to solve by classical mathematical programming methods. ^ The genetic algorithm proposed in this research attempts to find an optimal solution for the transfer time optimization problem by searching for a combination of adjustments to the timetable for all the routes in the system. It makes use of existing scheduled timetables, ridership demand at all transfer locations, and takes into consideration the randomness of bus arrivals. ^ Data from Broward County Transit are used to compute total transfer times. The proposed genetic algorithm-based approach proves to be capable of producing substantial time savings compared to the existing transfer times in a reasonable amount of time. ^ The dissertation also addresses the issues related to spatial and temporal modeling, variability in bus arrival and departure times, walking time, as well as the integration of scheduling and ridership data. ^

Groundwater-surface water interactions on tree islands in the Everglades, south Florida

The marked decline in tree island cover across the Everglades over the last century, has been attributed to landscape-scale hydrologic degradation. To preserve and restore Everglades tree islands, a clear understanding of tree island groundwater-surface water interactions is needed, as these interactions strongly influence the chemistry of shallow groundwater and the location and patterns of vegetation in many wetlands. The goal of this work was to define the relationship between groundwater-surface water interactions, plant-water uptake, and the groundwater geochemical condition of tree islands. Groundwater and surface water levels, temperature, and chemistry were monitored on eight constructed and one natural tree island in the Everglades from 2007–2010. Sap flow, diurnal water table fluctuations and stable oxygen isotopes of stem, ground and soil water were used to determine the effect of plant-water uptake on groundwater-surface water interactions. Hydrologic and geochemical modeling was used to further explore the effect of plant-groundwater-surface water interactions on ion concentrations and potential mineral formation.^

The nature of microvariability in blazar 0716+714

We organized an international campaign to observe the blazar 0716+714 in the optical band. The observations took place from February 24, 2009 to February 26, 2009. The global campaign was carried out by observers from more that sixteen countries and resulted in an extended light curve nearly seventy-eight hours long. The analysis and the modeling of this light curve form the main work of this dissertation project. In the first part of this work, we present the time series and noise analyses of the data. The time series analysis utilizes discrete Fourier transform and wavelet analysis routines to search for periods in the light curve. We then present results of the noise analysis which is based on the idea that each microvariability curve is the realization of the same underlying stochastic noise processes in the blazar jet. ^ Neither reoccuring periods nor random noise can successfully explain the observed optical fluctuations. Hence in the second part, we propose and develop a new model to account for the microvariability we see in blazar 0716+714. We propose that the microvariability is due to the emission from turbulent regions in the jet that are energized by the passage of relativistic shocks. Emission from each turbulent cell forms a pulse of emission, and when convolved with other pulses, yields the observed light curve. We use the model to obtain estimates of the physical parameters of the emission regions in the jet.^

Improving resource management in virtualized data centers using application performance models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^

Covalent protein adduction by drugs of abuse

Recreational abuse of the drugs cocaine, methamphetamine, and morphine continues to be prevalent in the United States of America and around the world. While numerous methods of detection exist for each drug, they are generally limited by the lifetime of the parent drug and its metabolites in the body. However, the covalent modification of endogenous proteins by these drugs of abuse may act as biomarkers of exposure and allow for extension of detection windows for these drugs beyond the lifetime of parent molecules or metabolites in the free fraction. Additionally, existence of covalently bound molecules arising from drug ingestion can offer insight into downstream toxicities associated with each of these drugs. This research investigated the metabolism of cocaine, methamphetamine, and morphine in common in vitro assay systems, specifically focusing on the generation of reactive intermediates and metabolites that have the potential to form covalent protein adducts. Results demonstrated the formation of covalent adduction products between biological cysteine thiols and reactive moieties on cocaine and morphine metabolites. Rigorous mass spectrometric analysis in conjunction with in vitro metabolic activation, pharmacogenetic reaction phenotyping, and computational modeling were utilized to characterize structures and mechanisms of formation for each resultant thiol adduction product. For cocaine, data collected demonstrated the formation of adduction products from a reactive arene epoxide intermediate, designating a novel metabolic pathway for cocaine. In the case of morphine, data expanded on known adduct-forming pathways using sensitive and selective analysis techniques, following the known reactive metabolite, morphinone, and a proposed novel metabolite, morphine quinone methide. Data collected in this study describe novel metabolic events for multiple important drugs of abuse, culminating in detection methods and mechanistic descriptors useful to both medical and forensic investigators when examining the toxicology associated with cocaine, methamphetamine, and morphine.

Dynamic image precompensation for improving visual performance of computer users with ocular aberrations

With the progress of computer technology, computers are expected to be more intelligent in the interaction with humans, presenting information according to the user's psychological and physiological characteristics. However, computer users with visual problems may encounter difficulties on the perception of icons, menus, and other graphical information displayed on the screen, limiting the efficiency of their interaction with computers. In this dissertation, a personalized and dynamic image precompensation method was developed to improve the visual performance of the computer users with ocular aberrations. The precompensation was applied on the graphical targets before presenting them on the screen, aiming to counteract the visual blurring caused by the ocular aberration of the user's eye. A complete and systematic modeling approach to describe the retinal image formation of the computer user was presented, taking advantage of modeling tools, such as Zernike polynomials, wavefront aberration, Point Spread Function and Modulation Transfer Function. The ocular aberration of the computer user was originally measured by a wavefront aberrometer, as a reference for the precompensation model. The dynamic precompensation was generated based on the resized aberration, with the real-time pupil diameter monitored. The potential visual benefit of the dynamic precompensation method was explored through software simulation, with the aberration data from a real human subject. An "artificial eye'' experiment was conducted by simulating the human eye with a high-definition camera, providing objective evaluation to the image quality after precompensation. In addition, an empirical evaluation with 20 human participants was also designed and implemented, involving image recognition tests performed under a more realistic viewing environment of computer use. The statistical analysis results of the empirical experiment confirmed the effectiveness of the dynamic precompensation method, by showing significant improvement on the recognition accuracy. The merit and necessity of the dynamic precompensation were also substantiated by comparing it with the static precompensation. The visual benefit of the dynamic precompensation was further confirmed by the subjective assessments collected from the evaluation participants.

A geochemical study of crustal plutonic rocks from the southern Mariana Trench forearc: Relationship to volcanic rocks erupted during subduction initiation

Two suites of intermediate-felsic plutonic rocks were recovered by dredges RD63 and RD64 (R/V KK81-06-26) from the northern wall of the Mariana trench near Guam, which is located in the southern part of the Izu-Bonin-Mariana (IBM) island arc system. The locations of the dredges are significant as the area contains volcanic rocks (forearc basalts and boninites) that have been pivotal in explaining processes that occur when one lithospheric plate initially begins to subduct beneath another. The plutonic rocks have been classified based on petrologic and geochemical analyses, which provides insight to their origin and evolution in context of the surrounding Mariana trench. Based on whole rock geochemistry, these rocks (SiO2: 49-78 wt%) have island arc trace element signatures (Ba, Sr, Rb enrichment, Nb-Ta negative anomalies, U/Th enrichment), consistent with the adjacent IBM volcanics. Depletion of rare earth elements (REEs) relative to primitive mantle and excess Zr and Hf compared to the middle REEs indicate that the source of the plutonic rocks is similar to boninites and transitional boninites. Early IBM volcanic rocks define isotopic fields (Sr, Pb, Nd and Hf-isotopes) that represent different aspects of the subduction process (e.g., sediment influence, mantle provenance). The southern Mariana plutonic rocks overlap these fields, but show a clear distinction between RD63 and RD64. Modeling of the REEs, Zr and Hf shows that the plutonic suites formed via melting of boninite crust or by crystallization from a boninite-like magma rather than other sources that are found in the IBM system. The data presented support the hypothesis that the plutonic rocks from RD63 and RD64 are products of subduction initiation and are likely pieces of middle crust in the forearc exposed at the surface by faulting and serpentine mudvolcanoes. Their existence shows that intermediate-felsic crust may form very early in the history of an intra-oceanic island arc system. Plutonic rocks with similar formation histories may exist in obducted suprasubduction zone ophiolites and would be evidence that felsic-intermediate forearc plutonics are eventually accreted to the continents.

Role of carbon nanotube dispersion in fracture toughening of plasma sprayed aluminum oxide - carbon nanotube nanocomposite coating

Aluminum oxide (A1203, or alumina) is a conventional ceramic known for applications such as wear resistant coatings, thermal liners, heaters, crucibles, dielectric systems, etc. However applications of A1203 are limited owing to its inherent brittleness. Due to its excellent mechanical properties and bending strength, carbon nanotubes (CNT) is an ideal reinforcement for A1203 matrix to improve its fracture toughness. The role of CNT dispersion in the fracture toughening of the plasma sprayed A1203-CNT nanocomposite coating is discussed in the current work. Pretreatment of powder feedstock is required for dispersing CNTs in the matrix. Four coatings namely spray dried A1203 (A-SD), A1203 blended with 4wt.% CNT (A4C-B), composite spray dried A1203-4wt.% CNT (A4C-SD) and composite spray dried A1203-8wt.% CNT (A8CSD), are synthesized by plasma spraying. Owing to extreme temperatures and velocities involved in the plasma spraying of ceramics, retention of CNTs in the resulting coatings necessitates optimizing plasma processing parameters using an inflight particle diagnostic sensor. A bimodal microstructure was obtained in the matrix that consists of fully melted and resolidified structure and solid state sintered structure. CNTs are retained both in the fully melted region and solid-state sintered regions of processed coatings. Fracture toughness of A-SD, A4C-B, A4C-SD and A8C-SD coatings was 3.22, 3.86, 4.60 and 5.04 MPa m1/2 respectively. This affirms the improvement of fracture toughness from 20 % (in A4C-B coating) to 43% (in A4C-SD coating) when compared to the A-SD coating because of the CNT dispersion. Fracture toughness improvement from 43 % (in A4C-SD) to 57% (in A8C-SD) coating is evinced because of the CNT content. Reinforcement by CNTs is described by its bridging, anchoring, hook formation, impact alignment, fusion with splat, and mesh formation. The A1203/CNT interface is critical in assisting the stress transfer and utilizing excellent mechanical properties of CNTs. Mathematical and computational modeling using ab-initio principle is applied to understand the wetting behavior at the A1203/CNTinterface. Contrasting storage modulus was obtained by nanoindentation (~ 210, 250, 250-350 and 325-420 GPa in A-SD, A4C-B, A4C-SD, and A8C-SD coatings respectively) depicting the toughening associated with CNT content and dispersion.

Modelagem computacional para avaliação da interação entre painéis de alvenaria e estrutura de suporte em concreto armado

The developed study proposes a new computer modeling efficient and easy to apply in usual project situations to evaluate the interaction between masonry panels and support structure. The proposed model simulates the behavior of the wall exclusively using frame finite elements, thus compounding an equivalent frame. The validation was performed in two ways: firstly, through the analysis of various panels of generic plans, comparing the results obtained from equivalent frame model with the ones from a reference model, which uses shell finite elements in discretization of the walls; and in a second step, comparing with the results of the experimental model of Rosenhaupt. The analyzes considered the linear elastic behavior for materials and consisted basically in the evaluation of vertical displacements and efforts in support beams, and tensions at the base of walls. Was also evaluated, from flat and threedimensional modeling of some walls from a real project, important aspects of the wall-beam interaction, e.g.: the presence of openings of doors and windows, arranged in any position; conditions of support and linking of beams; interference of moorings between walls; and consideration of wind action. The analysis of the achieved results demonstrated the efficiency of the proposed modeling, since they have very similar aspects in the distribution of stresses and efforts, always with intensities slightly larger than those of the reference and experimental models.

Modelagem do consumo de energia de redes de sensores sem fio usando SystemC-AMS e stateflow

This work aims at modeling power consumption at the nodes of a Wireless Sensor Network (WSN). For doing so, a finite state machine was implemented by means of SystemC-AMS and Stateflow modeling and simulation tools. In order to achieve this goal, communication data in a WSN were collected. Based on the collected data, a simulation environment for power consumption characterization, which aimed at describing the network operation, was developed. Other than performing power consumption simulation, this environment also takes into account a discharging model as to analyze the battery charge level at any given moment. Such analysis result in a graph illustrating the battery voltage variations as well as its state of charge (SOC). Finally, a case study of the WSN power consumption aims to analyze the acquisition mode and network data communication. With this analysis, it is possible make adjustments in node-sensors to reduce the total power consumption of the network.