Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Generating artificial chromosomes with probability control in genetic algorithm for machine scheduling problems

In this paper, a novel genetic algorithm is developed by generating artificial chromosomes with probability control to solve the machine scheduling problems. Generating artificial chromosomes for Genetic Algorithm (ACGA) is closely related to Evolutionary Algorithms Based on Probabilistic Models (EAPM). The artificial chromosomes are generated by a probability model that extracts the gene information from current population. ACGA is considered as a hybrid algorithm because both the conventional genetic operators and a probability model are integrated. The ACGA proposed in this paper, further employs the ``evaporation concept'' applied in Ant Colony Optimization (ACO) to solve the permutation flowshop problem. The ``evaporation concept'' is used to reduce the effect of past experience and to explore new alternative solutions. In this paper, we propose three different methods for the probability of evaporation. This probability of evaporation is applied as soon as a job is assigned to a position in the permutation flowshop problem. Experimental results show that our ACGA with the evaporation concept gives better performance than some algorithms in the literature.

Nonlinear measures of respiration: Respiratory irregularity and increased chaos of respiration in patients with panic disorder

Background. Respiratory irregularity has been previously reported in patients with panic disorder using time domain measures. However, the respiratory signal is not entirely linear and a few previous studies used approximate entropy (APEN), a measure of regularity of time series. We have been studying APEN and other nonlinear measures including a measure of chaos, the largest Lyapunov exponent (LLE) of heart rate time series, in some detail. In this study, we used these measures of respiration to compare normal controls (n = 18) and patients with panic disorder (n = 22) in addition to the traditional time domain measures of respiratory rate and tidal volume. Methods: Respiratory signal was obtained by the Respitrace system using a thoracic and an abdominal belt, which was digitized at 500 Hz. Later, the time series were constructed at 4 Hz, as the highest frequency in this signal is limited to 0.5 Hz. We used 256 s of data (1,024 points) during supine and standing postures under normal breathing and controlled breathing at 12 breaths/min. Results: APEN was significantly higher in patients in standing posture during normal as well as controlled breathing (p = 0.002 and 0.02, respectively). LLE was also significantly higher in standing posture during normal breathing (p = 0.009). Similarly, the time domain measures of standard deviations and the coefficient of variation (COV) of tidal volume (TV) were significantly higher in the patient group (p = 0.02 and 0.004, respectively). The frequency of sighs was also higher in the patient group in standing posture (p = 0.02). In standing posture, LLE (p < 0.05) as well as APEN (p < 0.01) contributed significantly toward the separation of the two groups over and beyond the linear measure, i.e. the COV of TV. Conclusion: These findings support the previously described respiratory irregularity in patients with panic disorder and also illustrate the utility of nonlinear measures such as APEN and LLE as additional measures toward a better understanding of the abnormalities of respiratory physiology in similar patient populations as the correlation between LLE, APEN and some of the time domain measures only explained up to 50-60% of the variation. Copyright (C) 2002 S. Karger AG, Basel.

Volume Change behaviour in Calcitic Soil influenced with Sulphuric Acid using Artificial Neural Networks

This paper elucidates the methodology of applying artificial neural network model (ANNM) to predict the percent swell of calcitic soil in sulphuric acid solutions, a complex phenomenon involving many parameters. Swell data required for modelling is experimentally obtained using conventional oedometer tests under nominal surcharge. The phases in ANN include optimal design of architecture, operation and training of architecture. The designed optimal neural model (3-5-1) is a fully connected three layer feed forward network with symmetric sigmoid activation function and trained by the back propagation algorithm to minimize a quadratic error criterion.The used model requires parameters such as duration of interaction, calcite mineral content and acid concentration for prediction of swell. The observed strong correlation coefficient (R2 = 0.9979) between the values determined by the experiment and predicted using the developed model demonstrates that the network can provide answers to complex problems in geotechnical engineering.

Stress-Strain Prediction of Jointed Rocks using Artificial Neural Networks

The applicability of Artificial Neural Networks for predicting the stress-strain response of jointed rocks at varied confining pressures, strength properties and joint properties (frequency, orientation and strength of joints) has been studied in the present paper. The database is formed from the triaxial compression tests on different jointed rocks with different confining pressures and different joint properties reported by various researchers. This input data covers a wide range of rock strengths, varying from very soft to very hard. The network was trained using a 3 layered network with feed forward back propagation algorithm. About 85% of the data was used for training and remaining15% for testing the predicting capabilities of the network. Results from the analyses were very encouraging and demonstrated that the neural network approach is efficient in capturing the complex stress-strain behaviour of jointed rocks. A single neural network is demonstrated to be capable of predicting the stress-strain response of different rocks, whose intact strength vary from 11.32 MPa to 123 MPa and spacing of joints vary from 10 cm to 100 cm for confining pressures ranging from 0 to 13.8 MPa.

Cascaded walks in protein sequence space: use of artificial sequences in remote homology detection between natural proteins

Over the past two decades, many ingenious efforts have been made in protein remote homology detection. Because homologous proteins often diversify extensively in sequence, it is challenging to demonstrate such relatedness through entirely sequence-driven searches. Here, we describe a computational method for the generation of `protein-like' sequences that serves to bridge gaps in protein sequence space. Sequence profile information, as embodied in a position-specific scoring matrix of multiply aligned sequences of bona fide family members, serves as the starting point in this algorithm. The observed amino acid propensity and the selection of a random number dictate the selection of a residue for each position in the sequence. In a systematic manner, and by applying a `roulette-wheel' selection approach at each position, we generate parent family-like sequences and thus facilitate an enlargement of sequence space around the family. When generated for a large number of families, we demonstrate that they expand the utility of natural intermediately related sequences in linking distant proteins. In 91% of the assessed examples, inclusion of designed sequences improved fold coverage by 5-10% over searches made in their absence. Furthermore, with several examples from proteins adopting folds such as TIM, globin, lipocalin and others, we demonstrate that the success of including designed sequences in a database positively sensitized methods such as PSI-BLAST and Cascade PSI-BLAST and is a promising opportunity for enormously improved remote homology recognition using sequence information alone.

Stabilized SPH-based simulations of impact dynamics using acceleration-corrected artificial viscosity

Artificial viscosity in SPH-based computations of impact dynamics is a numerical artifice that helps stabilize spurious oscillations near the shock fronts and requires certain user-defined parameters. Improper choice of these parameters may lead to spurious entropy generation within the discretized system and make it over-dissipative. This is of particular concern in impact mechanics problems wherein the transient structural response may depend sensitively on the transfer of momentum and kinetic energy due to impact. In order to address this difficulty, an acceleration correction algorithm was proposed in Shaw and Reid (''Heuristic acceleration correction algorithm for use in SPH computations in impact mechanics'', Comput. Methods Appl. Mech. Engrg., 198, 3962-3974) and further rationalized in Shaw et al. (An Optimally Corrected Form of Acceleration Correction Algorithm within SPH-based Simulations of Solid Mechanics, submitted to Comput. Methods Appl. Mech. Engrg). It was shown that the acceleration correction algorithm removes spurious high frequency oscillations in the computed response whilst retaining the stabilizing characteristics of the artificial viscosity in the presence of shocks and layers with sharp gradients. In this paper, we aim at gathering further insights into the acceleration correction algorithm by further exploring its application to problems related to impact dynamics. The numerical evidence in this work thus establishes that, together with the acceleration correction algorithm, SPH can be used as an accurate and efficient tool in dynamic, inelastic structural mechanics. (C) 2011 Elsevier Ltd. All rights reserved.

Stimulation discomfort comparison of asynchronous and synchronous methods with multi-field electrodes

Functional Electrical Stimulation (FES) is a technique that consists on applying electrical current pulses to artificially activate motor nerve fibers and produce muscle contractions to achieve functional movements. The main applications of FES are within the rehabilitation field, in which this technique is used to aid recovery or to restore lost motor functions. People that benefit of FES are usually patients with neurological disorders which result in motor dysfunctions; most common patients include stroke and spinal cord injury (SCI). Neuroprosthesis are devices that have their basis in FES technique, and their aim is to bridge interrupted or damaged neural paths between the brain and upper or lower limbs. One of the aims of neuroprosthesis is to artificially generate muscle contractions that produce functional movements, and therefore, assist impaired people by making them able to perform activities of daily living (ADL). FES applies current pulses and stimulates nerve fibers by means of electrodes, which can be either implanted or surface electrodes. Both of them have advantages and disadvantages. Implanted electrodes need open surgery to place them next to the nerve root, so these electrodes carry many disadvantages that are produced by the use of invasive techniques. In return, as the electrodes are attached to the nerve, they make it easier to achieve selective functional movements. On the contrary, surface electrodes are not invasive and are easily attached or detached on the skin. Main disadvantages of surface electrodes are the difficulty of selectively stimulating nerve fibers and uncomfortable feeling perceived by users due to sensory nerves located in the skin. Electrical stimulation surface electrode technology has improved significantly through the years and recently, multi-field electrodes have been suggested. This multi-field or matrix electrode approach brings many advantages to FES; among them it is the possibility of easily applying different stimulation methods and techniques. The main goal of this thesis is therefore, to test two stimulation methods, which are asynchronous and synchronous stimulation, in the upper limb with multi-field electrodes. To this end, a purpose-built wrist torque measuring system and a graphic user interface were developed to measure wrist torque produced with each of the methods and to efficiently carry out the experiments. Then, both methods were tested on 15 healthy subjects and sensitivity results were analyzed for different cases. Results show that there are significant differences between methods regarding sensation in some cases, which can affect effectiveness or success of FES.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Controles da produção primária em um Córrego de Mata Atlântica

Esta dissertação consiste de dois capítulos, cada um correspondendo a um estudo realizado de modo independente. Em um córrego de Mata Atlântica, Rio de Janeiro, Brasil, foram estudados efeitos de herbívoros e de controles ambientais no perifíton. No primeiro trabalho foram testados os efeitos do camarão Potimirim glabra, um engenheiro do ecossistema, nos parâmetros metabólicos de comunidades perifíticas (Produção, Respiração, Metabolismo Líquido da Comunidade e razão Produção:Respiração). O tratamento de inclusão de Potimirim produziu resultados inversos aos esperados, com aumento da clorofila e massa seca das comunidades perifíticas, levantando dúvida com relação à eficácia dos tratamentos. Nenhuma das variáveis metabólicas esteve relacionada aos tratamentos. Considera-se que efeitos artefato da gaiola utilizada na inclusão dos camarões podem ter prejudicado o efeito esperado de remoção de material pelos camarões. Os resultados podem indicar, entretanto, que para o efeito de herbívoros os parâmetros clorofila e massa seca sejam mais sensíveis e variáveis que os metabólicos para as comunidades estudadas. São recomendados futuros trabalhos com metodologias que reduzam os efeitos artefato, tais como exclusão de herbívoros com cercas elétricas. No segundo trabalho, foram estudados os estoques, a distribuição e os controles da biomassa perifítica para o córrego. Entre os substratos estudados, a areia apresentou os maiores estoques, com 5 vezes mais clorofila e 20 vezes mais massa seca que os substratos pedra e folha. Diferenças entre trechos com diferentes densidades do camarão herbívoro Potimirim glabra revelaram para o substrato pedra menores valores de massa seca para os locais onde o camarão é mais numeroso. Entre as variáveis ambientais, apenas a profundidade esteve relacionada aos dados de biomassa nos substratos pedra e areia. A comparação dos dados deste estudo com trabalhos anteriores pode indicar que distúrbios provocados por enchentes podem alterar os estoques e os padrões de distribuição para este córrego.

Salmon stocking by the Lancashire River Authority: investigations into the requirements and methods best suited to the area

All species of fish are able to propagate and maintain their numbers provided that no adverse influence occurs to change the compatible environment, the salmon is no exception. Propagation of fish by artificial means has long been a subject of discussion amongst fishery workers and views have been expressed (both favourable and unfavourable) on the merits of the various methods employed. In an attempt to discover whether artificial propagation was necessary and also to find the best methods of propagation to adopt in the various rivers, a phased programme of investigation into natural spawning efficiency and the results obtained by various methods of artificial propagation was started in the Lancashire River Board area during 1957. The object being to seek information on: (1) The survival of ova from natural spawnings to the eyed and alevin stages. (2) The population density of feeding fry (from natural spawnings) at various intervals of development. (3) The viability of green ova and eyed ova- when planted artificially. (4a) The survival to 0+ parr from implants of eyed ova unfed fry and fed fry. (4b) Populations per unit area of 0+ parr from various planting densities of eyed ova, unfed fry and fed fry. Sampling stations were selected on the Rivers Ribble, Lune and Wyre watersheds for the purpose of marking and examination of natural salmon redds.

Artificial Habitats for Fisheries Enhancement in the Australian Region

This paper outlines developments over about 20 years in the construction of and ecological research on artificial reefs, fish aggregation devices (FAD's), and other artificial habitats designed to enhance fish populations and fisheries in the Australian region (including New Zealand and Papua New Guinea). Work was initially carried out on multicomponent reefs using a variety of waste materials, as well as some specially constructed concrete and steel structures. Later studies concentrated on single-component reefs, again mainly using waste materials. Although no definitive conclusions were reached on the relative effectiveness of the different materials used, waste motor vehicle tires and derelict ships were generally judged to be the best all-around materials for single-component reef construction in sheltered estuarine and offshore marine environments, respectively, in this region. FAD's comprising polyvinylchloride pipe sparbuoys (or in some areas polyurethane foam floats) attached to railroad car wheel anchors by polyethylene rope and chain, and supporting attractor drapes of synthetic mesh webbing, also provedtobegenerallysuccessfulin thisarea. Overall conclusions for the Australian region include the predominant use of waste materials in artificial reef construction, which has been primarily aimed at recreational fisheries enhancement; the successful use of FAD's for both recreational and commercial fisheries enhancement; the need for further and better planned research into and monitoring of the effectiveness of both of these enhancement methods; and the need for future research into the effectiveness of unfished "artificial habitat reserves" in enhancing fisheries production from surrounding fished areas.

Self-assembled artificial pinning centres in thick YBCO superconducting films

Strong, artificial pinning centres are required in superconducting films of large thickness for power applications in high magnetic fields. One of the methods for the introduction of pinning centres in such films is substrate decoration, i.e., growing nanoscale islands of certain materials on the substrate prior to the deposition of the superconducting film. Two other methods are building up a layered distribution of a second phase and homogeneous incorporation of second phase inclusions from a compositional target. In this paper, we compare the effectiveness of these methods in terms of the type of the self-assembly of nanoparticles. The comparison is made over a large set of YBa2Cu3O7 films of thickness up to 6.6 μm deposited with Au, Ag, Pd, LaNiO3, PrBa2Cu 3O7, YBCO, BaZrO3 and Gd2Ba 4CuWOy nanoparticles. It is found that substrate-decoration self-assembly is able to provide higher critical current in low magnetic field than the incorporation of homogeneous second phase in the sample microstructure. By specific modification of substrate decoration we achieved the self-field critical current per centimetre of width of 896 A/cm at 77.3 K and 1620 A/cm at 65 K in a film of thickness of 4.8 μm. © 2010 IOP Publishing Ltd.

Plankton Community Succession in Artificial Systems Subjected to Cyanobacterial Blooms Removal using Chitosan-Modified Soils

Using artificial systems to simulate natural lake environments with cyanobacterial blooms, we investigated plankton community succession by polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) fingerprinting and morphological method. With this approach, we explored potential ecological effects of a newly developed cyanobacterial blooms removal method using chitosan-modified soils. Results of PCR-DGGE and morphological identification showed that plankton communities in the four test systems were nearly identical at the beginning of the experiment. After applying the newly developed and standard removal methods, there was a shift in community composition, but neither chemical conditions nor plankton succession were significantly affected by the cyanobacteria removal process. The planted Vallisneria natans successfully recovered after cyanobacteria removal, whereas that in the box without removal process did not. Additionally, canonical correspondence analysis indicated that other than for zooplankton abundance, total phosphorus was the most important environmental predictor of planktonic composition. The present study and others suggest that dealing with cyanobacteria removal using chitosan-modified soils can play an important role in controlling cyanobacterial blooms in eutrophicated freshwater systems.

Embodied artificial intelligence: Trends and challenges

The field of Artificial Intelligence, which started roughly half a century ago, has a turbulent history. In the 1980s there has been a major paradigm shift towards embodiment. While embodied artificial intelligence is still highly diverse, changing, and far from "theoretically stable", a certain consensus about the important issues and methods has been achieved or is rapidly emerging. In this non-technical paper we briefly characterize the field, summarize its achievements, and identify important issues for future research. One of the fundamental unresolved problems has been and still is how thinking emerges from an embodied system. Provocatively speaking, the central issue could be captured by the question "How does walking relate to thinking?" © Springer-Verlag Berlin Heidelberg 2004.