Multi-step ahead direct prediction for the machine condition prognosis using regression trees and neuro-fuzzy systems

This paper presents an approach to predict the operating conditions of machine based on classification and regression trees (CART) and adaptive neuro-fuzzy inference system (ANFIS) in association with direct prediction strategy for multi-step ahead prediction of time series techniques. In this study, the number of available observations and the number of predicted steps are initially determined by using false nearest neighbor method and auto mutual information technique, respectively. These values are subsequently utilized as inputs for prediction models to forecast the future values of the machines’ operating conditions. The performance of the proposed approach is then evaluated by using real trending data of low methane compressor. A comparative study of the predicted results obtained from CART and ANFIS models is also carried out to appraise the prediction capability of these models. The results show that the ANFIS prediction model can track the change in machine conditions and has the potential for using as a tool to machine fault prognosis.

Convenient Synthesis of Ferrocene Conjugates Mediated by Benzyltriethylammonium Tetrathiomolybdate in a Multi-Step Tandem Process

The synthesis of a wide range of ferrocene-derived sulfur-linked mono- and disubstituted Michael adducts and conjugates mediated by benzyltriethylammonium tetrathiomolybdate (1) in a tandem process is reported. New route to access acryloylferrocene (4) and 1,1'-diacryloylferrocene (5) is discussed. Conjugation of amino acids to ferrocene is established via their N and C termini and also via side chains employing conjugate addition as key step to furnish mono-and divalent conjugates. This methodology has also been extended to access several ferrocene-carbohydrate conjugates. The electrochemical behavior of some selected ferrocene conjugates was studied by cyclic voltammetry.

Single and multi-step phase transformation in CuZr nanowire under compressive/tensile loading

A novel stress induced martenistic phase transformation is reported in an initial B2-CuZr nanowire of cross-sectional dimensions in the range of 19.44 x 19.44-38.88 x 38.88 angstrom(2) and temperature in the range of 10-400 K under both tensile and compressive loading. Extensive Molecular Dynamic simulations are performed using an inter-atomic potential of type Finnis and Sinclair. The nanowire shows a phase transformation from an initial B2 phase to BCT (body-centered-tetragonal) phase with failure strain of similar to 40% in tension, whereas in compression, comparatively a small B2 -> BCT phase transformation is observed with failure strain of similar to 25%. Size and temperature dependent deformation mechanisms which control ultimately the B2 -> BCT phase transformation are found to be completely different for tensile and compressive loadings. Under tensile loading, small cross-sectional nanowire shows a single step phase transformation, i.e. B2 -> BCT via twinning along {100} plane, whereas nanowires with larger cross-sectional area show a two step phase transformation, i.e. B2 -> R phase -> BCT along with intermediate hardening. In the first step, nanowire shows phase transformation from B2 -> R phase via twinning along {100} plane, afterwards the nanowire deforms via twinning along {110} plane which cause further transformation from R phase -> BCT phase. Under compressive loading, the nanowire shows crushing along {100} plane after a single step phase transformation from B2 -> BCT. Proper tailoring of such size and temperature dependent phase transformation can be useful in designing nanowire for high strength applications with corrosion and fatigue resistance. (C) 2009 Elsevier Ltd. All rights reserved.

Engineering multi-step electron tunneling systems in proteins

Multi-step electron tunneling, or “hopping,” has become a fast-developing research field with studies ranging from theoretical modeling systems, inorganic complexes, to biological systems. In particular, the field is exploring hopping mechanisms in new proteins and protein complexes, as well as further understanding the classical biological hopping systems such as ribonuclease reductase, DNA photolyases, and photosystem II. Despite the plethora of natural systems, only a few biologically engineered systems exist. Engineered hopping systems can provide valuable information on key structural and electronic features, just like other kinds of biological model systems. Also, engineered systems can harness common biologic processes and utilize them for alternative reactions. In this thesis, two new hopping systems are engineered and characterized.

The protein Pseudomonas aeruginosa azurin is used as a building block to create the two new hopping systems. Besides being well studied and amenable to mutation, azurin already has been used to successfully engineer a hopping system. The two hopping systems presented in this thesis have a histidine-attached high potential rhenium 4,7-dimethyl-1,10-phenanthroline tricarbonyl [Re(dmp)(CO)3] + label which, when excited, acts as the initial electron acceptor. The metal donor is the type I copper of the azurin protein. The hopping intermediates are all tryptophan, an amino acid mutated into the azurin at select sites between the photoactive metal label and the protein metal site. One system exhibits an inter-molecular hopping through a protein dimer interface; the other system undergoes intra-molecular multi-hopping utilizing a tryptophan “wire.” The electron transfer reactions are triggered by excitation of the rhenium label and monitored by UV-Visible transient absorption, luminescence decays measurements, and time-resolved Infrared spectroscopy (TRIR). Both systems were structurally characterized by protein X-ray crystallography.

Formation of total-dose-radiation hardened materials by sequential oxygen and nitrogen implantation and multi-step annealing

Separation by implantation of oxygen and nitrogen (SIMON) silicon-on-insulator (SOI) materials were fabricated by sequential oxygen and nitrogen implantation with annealing after each implantation. Analyses of SIMS, XTEM and HRTEM were performed. The results show that superior buried insulating multi-layers were well formed and the possible mechanism is discussed. The remarkable total-dose irradiation tolerance of SIMON materials was confirmed by few shifts of drain leakage current-gate source voltage (I-V) curves of PMOS transistors fabricated on SIMON materials before and after irradiation.

The structure and current-voltage characteristics of multi-sheet InGaN quantum dots grown by a new multi-step method

Multi-sheet InGaN/GaN quantum dots (QDs) were grown successfully by surface passivation processing and low-temperature growth in metalorganic chemical vapor deposition. This method based on the principle of increasing the energy barrier of adatom hopping by surface passivation and low-temperature growth, is quite different from present methods. The InGaN quantum dots in the first layer of about 40-nm-wide and 15-nm-high grown by this method were revealed by atomic force microscopy. The InGaN QDs in upper layer grew bigger. To our knowledge, the current-voltage characteristics of multi-sheet InGaN/GaN QDs were measured for the fist time. Two kinds of resonance-tunneling-current features were observed which were attributed to the low-dimensional localization effect. Some current peaks only appeared in positive voltage for sample due to the non-uniformity of the QDs in the structure. (C) 2002 Elsevier Science B.V. All rights reserved.

Very low-pressure VLP-CVD growth of high quality gamma-Al2O3 films on silicon by multi-step process

gamma-Al2O3 films were grown on Si (10 0) substrates using the sources of TMA (AI(CH3)(3)) and O-2 by very low-pressure chemical vapor deposition. The effects of temperature control on the crystalline quality, surface morphology, uniformity and dielectricity were investigated. It has been found that the,gamma-Al2O3 film prepared at a temperature of 1000degreesC has a good crystalline quality, but the surface morphology, uniformity and dielectricity were poor due to the etching reaction between 0, and Si substrate in the initial growth stage. However, under a temperature-varied multi-step process the properties Of gamma-Al2O3 film were improved. The films have a mirror-like surface and the dielectricity was superior to that grown under a single-step process. The uniformity of gamma-Al2O3 films for 2-in epi-wafer was <5%, it is better than that disclosed elsewhere. In order to improve the crystalline quality, the gamma-Al2O3 films were annealed for I h in O-2 atmosphere. (C) 2002 Elsevier Science B.V. All rights reserved.

Recruitment of class I hydrophobins to the air : water interface initiates a multi-step process of functional amyloid formation

Class I fungal hydrophobins form amphipathic monolayers composed of amyloid rodlets. This is a remarkable case of functional amyloid formation in that a hydrophobic:hydrophilic interface is required to trigger the self-assembly of the proteins. The mechanism of rodlet formation and the role of the interface in this process have not been well understood. Here, we have studied the effect of a range of additives, including ionic liquids, alcohols, and detergents, on rodlet formation by two class I hydrophobins, EAS and DewA. Although the conformation of the hydrophobins in these different solutions is not altered, we observe that the rate of rodlet formation is slowed as the surface tension of the solution is decreased, regardless of the nature of the additive. These results suggest that interface properties are of critical importance for the recruitment, alignment, and structural rearrangement of the amphipathic hydrophobin monomers. This work gives insight into the forces that drive macromolecular assembly of this unique family of proteins and allows us to propose a three-stage model for the interface-driven formation of rodlets.

Multi-step adhesive cementation versus one-step adhesive cementation: push-out bond strength between fiber post and root dentin before and after mechanical cycling

This study evaluated the effects of mechanical cycling on resin push-out bond strength to root dentin, using two strategies for fiber post cementation. Forty bovine roots were embedded in acrylic resin after root canal preparation using a custom drill of the fiber post system. The fiber posts were cemented into root canals using two different strategies (N = 20): a conventional adhesive approach using a three-step etch-and-rinse adhesive system combined with a conventional resin cement (ScotchBond Multi Purpose Plus + RelyX ARC ), or a simplified adhesive approach using a self-adhesive resin cement (RelyX U100). The core was built up with composite resin and half of the specimens from each cementation strategy were submitted to mechanical cycling (45 degree angle; 37 degrees C; 88 N; 4 Hz; 700,000 cycles). Each specimen was cross-sectioned and the disk specimens were pushed-out. The means from every group (n = 10) were statistically analyzed using a two-way ANOVA and a Tukey test (P = 0.05). The cementation strategy affected the push-out results (P < 0.001), while mechanical cycling did not (P = 0.3716). The simplified approach (a self-adhesive resin cement) had better bond performance despite the conditioning. The self-adhesive resin cement appears to be a good option for post cementation. Further trials are needed to confirm these results.

Multi-objective mission flight planning in civil unmanned aerial systems

Unmanned Aerial Vehicles (UAVs) are emerging as an ideal platform for a wide range of civil applications such as disaster monitoring, atmospheric observation and outback delivery. However, the operation of UAVs is currently restricted to specially segregated regions of airspace outside of the National Airspace System (NAS). Mission Flight Planning (MFP) is an integral part of UAV operation that addresses some of the requirements (such as safety and the rules of the air) of integrating UAVs in the NAS. Automated MFP is a key enabler for a number of UAV operating scenarios as it aids in increasing the level of onboard autonomy. For example, onboard MFP is required to ensure continued conformance with the NAS integration requirements when there is an outage in the communications link. MFP is a motion planning task concerned with finding a path between a designated start waypoint and goal waypoint. This path is described with a sequence of 4 Dimensional (4D) waypoints (three spatial and one time dimension) or equivalently with a sequence of trajectory segments (or tracks). It is necessary to consider the time dimension as the UAV operates in a dynamic environment. Existing methods for generic motion planning, UAV motion planning and general vehicle motion planning cannot adequately address the requirements of MFP. The flight plan needs to optimise for multiple decision objectives including mission safety objectives, the rules of the air and mission efficiency objectives. Online (in-flight) replanning capability is needed as the UAV operates in a large, dynamic and uncertain outdoor environment. This thesis derives a multi-objective 4D search algorithm entitled Multi- Step A* (MSA*) based on the seminal A* search algorithm. MSA* is proven to find the optimal (least cost) path given a variable successor operator (which enables arbitrary track angle and track velocity resolution). Furthermore, it is shown to be of comparable complexity to multi-objective, vector neighbourhood based A* (Vector A*, an extension of A*). A variable successor operator enables the imposition of a multi-resolution lattice structure on the search space (which results in fewer search nodes). Unlike cell decomposition based methods, soundness is guaranteed with multi-resolution MSA*. MSA* is demonstrated through Monte Carlo simulations to be computationally efficient. It is shown that multi-resolution, lattice based MSA* finds paths of equivalent cost (less than 0.5% difference) to Vector A* (the benchmark) in a third of the computation time (on average). This is the first contribution of the research. The second contribution is the discovery of the additive consistency property for planning with multiple decision objectives. Additive consistency ensures that the planner is not biased (which results in a suboptimal path) by ensuring that the cost of traversing a track using one step equals that of traversing the same track using multiple steps. MSA* mitigates uncertainty through online replanning, Multi-Criteria Decision Making (MCDM) and tolerance. Each trajectory segment is modeled with a cell sequence that completely encloses the trajectory segment. The tolerance, measured as the minimum distance between the track and cell boundaries, is the third major contribution. Even though MSA* is demonstrated for UAV MFP, it is extensible to other 4D vehicle motion planning applications. Finally, the research proposes a self-scheduling replanning architecture for MFP. This architecture replicates the decision strategies of human experts to meet the time constraints of online replanning. Based on a feedback loop, the proposed architecture switches between fast, near-optimal planning and optimal planning to minimise the need for hold manoeuvres. The derived MFP framework is original and shown, through extensive verification and validation, to satisfy the requirements of UAV MFP. As MFP is an enabling factor for operation of UAVs in the NAS, the presented work is both original and significant.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.

One-pot two-step mechanochemical synthesis: ligand and complex preparation without isolating intermediates

Although the use of ball milling to induce reactions between solids (mechanochemical synthesis) can provide lower-waste routes to chemical products by avoiding solvent during the reaction, there are further potential advantages in using one-pot multistep syntheses to avoid the use of bulk solvents for the purification of intermediates. We report here two-step syntheses involving formation of salen-type ligands from diamines and hydroxyaldehydes followed directly by reactions with metal salts to provide the corresponding metal complexes. Five salen-type ligands 2,2'-[1,2-ethanediylbis[(E)-nitrilomethylidyne]] bisphenol, ` salenH2', 1; 2,2'-[(+/-)-1,2-cyclohexanediylbis-[(E)-nitrilomethylidyne]] bis-phenol, 2; 2,2'-[1,2-phenylenebis( nitrilomethylidyne)]-bis-phenol, ` salphenH2' 3; 2-[[(2-aminophenyl) imino] methyl]-phenol, 4; 2,2'-[(+/-)-1,2-cyclohexanediylbis[(E)-nitrilomethylidyne]]-bis[4,6-bis(1,1-dimethylethyl)]-phenol, ` Jacobsen ligand', 5) were found to form readily in a shaker-type ball mill at 0.5 to 3 g scale from their corresponding diamine and aldehyde precursors. Although in some cases both starting materials were liquids, ball milling was still necessary to drive those reactions to completion because precipitation of the product and or intermediates rapidly gave in thick pastes which could not be stirred conventionally. The only ligand which required the addition of solvent was the Jacobsen ligand 5 which required 1.75 mol equivalents of methanol to go to completion. Ligands 1-5 were thus obtained directly in 30-60 minutes in their hydrated forms, due to the presence of water by-product, as free-flowing yellow powders which could be dried by heating to give analytically pure products. The one-armed salphen ligand 4 could also be obtained selectively by changing the reaction stoichiometry to 1 : 1. SalenH(2) 1 was explored for the onepot two-step synthesis of metal complexes. In particular, after in situ formation of the ligand by ball milling, metal salts (ZnO, Ni(OAc)2 center dot 4H(2)O or Cu(OAc)(2)center dot H2O) were added directly to the jar and milling continued for a further 30 minutes. Small amounts of methanol (0.4-1.1 mol equivalents) were needed for these reactions to run to completion. The corresponding metal complexes [M(salen)] (M = Zn, 6; Ni, 7; or Cu, 8) were thus obtained quantitatively after 30 minutes in hydrated form, and could be heated briefly to give analytically pure dehydrated products. The all-at-once ` tandem' synthesis of [Zn(salen)] 6 was also explored by milling ZnO, ethylene diamine and salicylaldehyde together in the appropriate mole ratio for 60 minutes. This approach also gave the target complex selectively with no solvent needing to be added. Overall, these syntheses were found to be highly efficient in terms of time and the in avoidance of bulk solvent both during the reaction and for the isolation of intermediates. The work demonstrates the applicability of mechanochemical synthesis to one-pot multi-step strategies.

Previsão multi-passos a frente do preço de energia elétrica de curto prazo no mercado brasileiro

A predição do preço da energia elétrica é uma questão importante para todos os participantes do mercado, para que decidam as estratégias mais adequadas e estabeleçam os contratos bilaterais que maximizem seus lucros e minimizem os seus riscos. O preço da energia tipicamente exibe sazonalidade, alta volatilidade e picos. Além disso, o preço da energia é influenciado por muitos fatores, tais como: demanda de energia, clima e preço de combustíveis. Este trabalho propõe uma nova abordagem híbrida para a predição de preços de energia no mercado de curto prazo. Tal abordagem combina os filtros autorregressivos integrados de médias móveis (ARIMA) e modelos de Redes Neurais (RNA) numa estrutura em cascata e utiliza variáveis explanatórias. Um processo em dois passos é aplicado. Na primeira etapa, as variáveis explanatórias são preditas. Na segunda etapa, os preços de energia são preditos usando os valores futuros das variáveis exploratórias. O modelo proposto considera uma predição de 12 passos (semanas) a frente e é aplicada ao mercado brasileiro, que possui características únicas de comportamento e adota o despacho centralizado baseado em custo. Os resultados mostram uma boa capacidade de predição de picos de preço e uma exatidão satisfatória de acordo com as medidas de erro e testes de perda de cauda quando comparado com técnicas tradicionais. Em caráter complementar, é proposto um modelo classificador composto de árvores de decisão e RNA, com objetivo de explicitar as regras de formação de preços e, em conjunto com o modelo preditor, atuar como uma ferramenta atrativa para mitigar os riscos da comercialização de energia.