A bayesian artificial neural network method to characterise laminar defects using dynamic measurements

This paper reports on the development of an artificial neural network (ANN) method to detect laminar defects following the pattern matching approach utilizing dynamic measurement. Although structural health monitoring (SHM) using ANN has attracted much attention in the last decade, the problem of how to select the optimal class of ANN models has not been investigated in great depth. It turns out that the lack of a rigorous ANN design methodology is one of the main reasons for the delay in the successful application of the promising technique in SHM. In this paper, a Bayesian method is applied in the selection of the optimal class of ANN models for a given set of input/target training data. The ANN design method is demonstrated for the case of the detection and characterisation of laminar defects in carbon fibre-reinforced beams using flexural vibration data for beams with and without non-symmetric delamination damage.

Modelling and improving maintenance decisions:Having foresight with simulation and artificial intelligence

Machine breakdowns are one of the main sources of disruption and throughput fluctuation in highly automated production facilities. One element in reducing this disruption is ensuring that the maintenance team responds correctly to machine failures. It is, however, difficult to determine the current practice employed by the maintenance team, let alone suggest improvements to it. 'Knowledge based improvement' is a methodology that aims to address this issue, by (a) eliciting knowledge on current practice, (b) evaluating that practice and (c) looking for improvements. The methodology, based on visual interactive simulation and artificial intelligence methods, and its application to a Ford engine assembly facility are described. Copyright © 2002 Society of Automotive Engineers, Inc.

Application of Artificial Intelligence Methods to Computer Design of Inorganic Compounds

In this paper the main problems for computer design of materials, which would have predefined properties, with the use of artificial intelligence methods are presented. The DB on inorganic compound properties and the system of DBs on materials for electronics with completely assessed information: phase diagram DB of material systems with semiconducting phases and DB on acousto-optical, electro-optical, and nonlinear optical properties are considered. These DBs are a source of information for data analysis. Using the DBs and artificial intelligence methods we have predicted thousands of new compounds in ternary, quaternary and more complicated chemical systems and estimated some of their properties (crystal structure type, melting point, homogeneity region etc.). The comparison of our predictions with experimental data, obtained later, showed that the average reliability of predicted inorganic compounds exceeds 80%. The perspectives of computational material design with the use of artificial intelligence methods are considered.

About the Journal of RAAI ”News of Artificial Intelligence”

Beginning from 1991, Russian (initially Soviet) Association for Artificial Intelligence (RAAI) publishes the own journal ‘News of Artificial Intelligence’. The journal is founded on the initiative of the famous specialist in the field of Artificial Intelligence (AI), the first president of Soviet Association for Artificial Intelligence, the academician of Russian Academy of Natural Science (RANS), doctor of technical sciences (d.t.s.), professor D.A. Pospelov, which from 1991 up to 2001 was its main editor.

Investigations of artificial sediments from two deep-sea in situ recolonization experiments deployed for one year at the central HAUSGARTEN station IV during ARK-XIX/3c

Commercial exploitation and abrupt changes of the natural conditions may have severe impacts on the Arctic deep-sea ecosystem. The present recolonisation experiment mimicked a situation after a catastrophic disturbance (e.g. by turbidites caused by destabilized continental slopes after methane hydrate decomposition) and investigated if the recolonisation of a deep-sea habitat by meiobenthic organisms is fostered by variations innutrition and/or sediment structure. Two "Sediment Tray Free Vehicles" were deployed for one year in summer 2003 at 2500 m water depth in the Arctic deep-sea in the eastern Fram Strait. The recolonisation trays were filled with different artificial and natural sediment types (glass beads, sand, sediment mixture, pure deep-sea sediment) and were enriched with various types of food (algae, yeast, fish). After one year, meiobenthos abundances and various sediment related environmental parameters were investigated. Foraminifera were generally the most successful group: they dominated all treatments and accounted for about 87% of the total meiobenthos. Colonizing meiobenthos specimens were generally smaller compared to those in the surrounding deep-sea sediment, suggesting an active recolonisation by juveniles. Although experimental treatments with fine-grained, algae-enriched sediment showed abundances closest to natural conditions, the results suggest that food availability was the main determining factor for a successful recolonisation by meiobenthos and the structure of recolonised sediments was shown to have a subordinate influence.

Experimental study about the impact of artificial lighting on loggerhead female nesting in Cape Verde.

[EN] Artificial illumination of nesting beaches is one of the main threats to endangered sea turtle populations. Nocturnal lighting can impair female nest site selection and nesting success, as well as behavior and hatchling survival in their way from the nest surface to the seashore. The island of Boavista (Cape Verde) hosts the third largest loggerhead nesting aggregation in the world and the only relevant population in the Eastern Atlantic coast. Several threats such as fishing by-catch and female slaughter during nesting are severely threatening its conservation.

Ambiente computacional paradesenvolvimento de aplicações de controladores lógicos programáveis baseado em linguagens SFC e ST

This work proposes an environment for programming programmable logic controllers applied to oil wells with BCP type method of artificially lifting. The environment will have an editor based in the diagram of sequential functions for programming of PLCs. This language was chosen due to the fact of being high-level and accepted by the international standard IEC 61131-3. The use of these control programs in real PLC will be possible with the use of an intermediate level of language based on XML specification PLCopen T6 XML. For the testing and validation of the control programs, an area should be available for viewing variables obtained through communication with a real PLC. Thus, the main contribution of this work is to develop a computational environment that allows: modeling, testing and validating the controls represented in SFC and applied in oil wells with BCP type method of artificially lifting

Sistema de sensoriamento eletromagnético utilizado para detecção da contaminação do óleo isolante do motor no método de elevação artificial do tipo bombeio centrífugo submerso

In the artificial lift method by Electrical Submersible Pump (ESP), the energy is transmitted for the well´s deep through a flat electric handle, where it is converted into mechanical energy through an engine of sub-surface, which is connected to a centrifugal pump. This transmits energy to the fluid under the pressure form, bringing it to the surface In this method the subsurface equipment is basically divided into: pump, seal and motor. The main function of the seal is the protect the motor, avoiding the motor´s oil be contaminated by oil production and the consequent burning of it. Over time, the seal will be wearing and initiates a contamination of motor oil, causing it to lose its insulating characteristics. This work presents a design of a magnetic sensor capable of detecting contamination of insulating oil used in the artificial lift method of oil-type Electrical Submersible Pump (ESP). The objective of this sensor is to generate alarm signal just the moment when the contamination in the isolated oil is present, enabling the implementation of a predictive maintenance. The prototype was designed to work in harsh conditions to reach a depth of 2000m and temperatures up to 150°C. It was used a simulator software to defined the mechanical and electromagnetic variables. Results of field experiments were performed to validate the prototype. The final results performed in an ESP system with a 62HP motor showed a good reliability and fast response of the prototype.

VERIFYING SUCCESS OF ARTIFICIAL REEFS IN THE HURON-ERIE CORRIDOR FOR LAKE STURGEON

Lake sturgeon (Acipenser fulvescens) were historically abundant in the Huron-Erie Corridor (HEC), a 160 km river/channel network composed of the St. Clair River, Lake St. Clair, and the Detroit River that connects Lake Huron to Lake Erie. In the HEC, most natural lake sturgeon spawning substrates have been eliminated or degraded as a result of channelization and dredging. To address significant habitat loss in HEC, multi-agency restoration efforts are underway to restore spawning substrate by constructing artificial spawning reefs. The main objective of this study was to conduct post-construction monitoring of lake sturgeon egg deposition and larval emergence near two of these artificial reef projects; Fighting Island Reef in the Detroit River, and Middle Channel Spawning Reef in the lower St. Clair River. We also investigated seasonal and nightly timing of larval emergence, growth, and vertical distribution in the water column at these sites, and an additional site in the St. Clair River where lake sturgeon are known to spawn on a bed of ~100 year old coal clinkers. From 2010-12, we collected viable eggs and larvae at all three sites indicating that these artificial reefs are creating conditions suitable for egg deposition, fertilization, incubation, and larval emergence. The construction methods and materials, and physical site conditions present in HEC artificial reef projects can be used to inform future spawning habitat restoration or enhancement efforts. The results from this study have also identified the likelihood of additional uncharacterized natural spawning sites in the St. Clair River. In addition to the field study, we conducted a laboratory experiment involving actual substrate materials that have been used in artificial reef construction in this system. Although coal clinkers are chemically inert, some trace elements can be reincorporated with the clinker material during the combustion process. Since lake sturgeon eggs and larvae are developing in close proximity to this material, it is important to measure the concentration of potentially toxic trace elements. This study focused on arsenic, which occurs naturally in coal and can be toxic to fishes. Total arsenic concentration was measured in samples taken from four substrate treatments submerged in distilled water; limestone cobble, rinsed limestone cobble, coal clinker, and rinsed coal clinker. Samples were taken at three time intervals: 24 hours, 11 days, and 21 days. ICP-MS analysis showed that concentrations of total arsenic were below the EPA drinking water standard (10 ppb) for all samples. However, at the 24 hour sampling interval, a two way repeated measures ANOVA with a Holm-Sidak post hoc analysis (α= 0.05) showed that the mean arsenic concentration was significantly higher in the coal clinker substrate treatment then in the rinsed coal clinker treatment (p=0.006), the limestone cobble treatment (p

Digital soil mapping using reference area and artificial neural networks.

Digital soil mapping is an alternative for the recognition of soil classes in areas where pedological surveys are not available. The main aim of this study was to obtain a digital soil map using artificial neural networks (ANN) and environmental variables that express soillandscape relationships. This study was carried out in an area of 11,072 ha located in the Barra Bonita municipality, state of São Paulo, Brazil. A soil survey was obtained from a reference area of approximately 500 ha located in the center of the area studied. With the mapping units identified together with the environmental variables elevation, slope, slope plan, slope profile, convergence index, geology and geomorphic surfaces, a supervised classification by ANN was implemented. The neural network simulator used was the Java NNS with the learning algorithm "back propagation." Reference points were collected for evaluating the performance of the digital map produced. The occurrence of soils in the landscape obtained in the reference area was observed in the following digital classification: medium-textured soils at the highest positions of the landscape, originating from sandstone, and clayey loam soils in the end thirds of the hillsides due to the greater presence of basalt. The variables elevation and slope were the most important factors for discriminating soil class through the ANN. An accuracy level of 82% between the reference points and the digital classification was observed. The methodology proposed allowed for a preliminary soil classification of an area not previously mapped using mapping units obtained in a reference area

High friction and acoustic surface for pavements: development of artificial engineered aggregates from recycled powders

There is a constant need to improve the infrastructure's quality and build new infrastructure with better designs. The risk of accidents and noise can be reduced by improving the surface properties of the pavement. The amount of raw material used in road construction is worrisome, as it is finite and due the waste produced. Environmentally-friendly roads construction, recycling might be the main way. Projects must be more environmentally-friendly, safer, and quieter. Is it possible to develop a safer, quieter and environmentally-friendly pavement surfaces? The hypothesis is: is it possible to create an Artificial Engineered Aggregate (AEA) using waste materials and providing it with a specific shape that can help to reduce the noise and increase the friction? The thesis presents the development of an AEA and its application as a partial replacement in microsurfacing samples. The 1st introduces the topic and provides the aim and objectives of the thesis. The 2nd chapter – presents a pavement solution to noise and friction review. The 3rd chapter - developing a mix design for a geopolymer mortar that used basalt powder. The 4th chapter is presented the physical-mechanical evaluation of the AEA. The 5th chapter evaluates the use of this aggregate in microsurfacing regarding the texture parameters. The 6th chapter, those parameter are used as an input to SPERoN® model, simulating their noise behavior of these solutions. The findings from this thesis are presented as partial conclusions in each chapter, to be closed in a final chapter. The main findings are: the DoE provided the tool to select the appropriate geopolymer mortar mix design; AEA had interesting results regarding the physical-mechanical tests; AEA in partial replacement of the natural aggregates in microsurfacing mixture proved feasible. The texture parameters and noise levels obtained in AEA samples demonstrate that it can serve as a HIFASP

Design and testing of innovative, artificial intelligence-based techniques to model and control the combustion process and to reduce the Co2 emissions in modern, high-performance, gasoline direct injection engines

This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.

The Effect Of Soy Dietary Supplement And Low Dose Of Hormone Therapy On Main Cardiovascular Health Biomarkers: A Randomized Controlled Trial.

To assess the effects of a soy dietary supplement on the main biomarkers of cardiovascular health in postmenopausal women compared with the effects of low-dose hormone therapy (HT) and placebo. Double-blind, randomized and controlled intention-to-treat trial. Sixty healthy postmenopausal women, aged 40-60 years, 4.1 years mean time since menopause were recruited and randomly assigned to 3 groups: a soy dietary supplement group (isoflavone 90mg), a low-dose HT group (estradiol 1 mg plus noretisterone 0.5 mg) and a placebo group. Lipid profile, glucose level, body mass index, blood pressure and abdominal/hip ratio were evaluated in all the participants at baseline and after 16 weeks. Statistical analyses were performed using the χ2 test, Fisher's exact test, Kruskal-Wallis non-parametric test, analysis of variance (ANOVA), paired Student's t-test and Wilcoxon test. After a 16-week intervention period, total cholesterol decreased 11.3% and LDL-cholesterol decreased 18.6% in the HT group, but both did not change in the soy dietary supplement and placebo groups. Values for triglycerides, HDL-cholesterol, glucose level, body mass index, blood pressure and abdominal/hip ratio did not change over time in any of the three groups. The use of dietary soy supplement did not show any significant favorable effect on cardiovascular health biomarkers compared with HT. The trial is registered at the Brazilian Clinical Trials Registry (Registro Brasileiro de Ensaios Clínicos - ReBEC), number RBR-76mm75.

Update On Ultraviolet A And B Radiation Generated By The Sun And Artificial Lamps And Their Effects On Skin.

Solar radiation, especially ultraviolet A (UVA) and ultraviolet B (UVB), can cause damage to the human body, and exposure to the radiation may vary according to the geographical location, time of year and other factors. The effects of UVA and UVB radiation on organisms range from erythema formation, through tanning and reduced synthesis of macromolecules such as collagen and elastin, to carcinogenic DNA mutations. Some studies suggest that, in addition to the radiation emitted by the sun, artificial sources of radiation, such as commercial lamps, can also generate small amounts of UVA and UVB radiation. Depending on the source intensity and on the distance from the source, this radiation can be harmful to photosensitive individuals. In healthy subjects, the evidence on the danger of this radiation is still far from conclusive.

Artificial Gait In Complete Spinal Cord Injured Subjects: How To Assess Clinical Performance.

Objective Adapt the 6 minutes walking test (6MWT) to artificial gait in complete spinal cord injured (SCI) patients aided by neuromuscular electrical stimulation. Method Nine male individuals with paraplegia (AIS A) participated in this study. Lesion levels varied between T4 and T12 and time post injured from 4 to 13 years. Patients performed 6MWT 1 and 6MWT 2. They used neuromuscular electrical stimulation, and were aided by a walker. The differences between two 6MWT were assessed by using a paired t test. Multiple r-squared was also calculated. Results The 6MWT 1 and 6MWT 2 were not statistically different for heart rate, distance, mean speed and blood pressure. Multiple r-squared (r2 = 0.96) explained 96% of the variation in the distance walked. Conclusion The use of 6MWT in artificial gait towards assessing exercise walking capacity is reproducible and easy to apply. It can be used to assess SCI artificial gait clinical performance.