Support vector machine applied to settlement of shallow foundations on cohesionless soils

The determination of settlement of shallow foundations on cohesionless soil is an important task in geotechnical engineering. Available methods for the determination of settlement are not reliable. In this study, the support vector machine (SVM), a novel type of learning algorithm based on statistical theory, has been used to predict the settlement of shallow foundations on cohesionless soil. SVM uses a regression technique by introducing an ε – insensitive loss function. A thorough sensitive analysis has been made to ascertain which parameters are having maximum influence on settlement. The study shows that SVM has the potential to be a useful and practical tool for prediction of settlement of shallow foundation on cohesionless soil.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Is it the economy, stupid? The role of social versus economic factors in people’s support for hosting the Olympic Games: Evidence from 12 democratic countries

Public referenda have gained momentum as a democratic tool to legitimize public mega projects such as hosting the Olympic Games. Interest groups in favour of hosting the Olympics therefore try to influence voters through public campaigns that primarily focus on economic benefits. However, recent studies find no or hardly any economic impact of hosting the Olympics, instead providing evidence for a positive social impact. This raises the question whether citizens consider economic or social factors when deciding on hosting the Olympics. Based on representative survey data from 12 countries, our results suggest that economic factors can influence voting behaviour, although the influence of social factors is stronger.

Size-dependent magnetic properties of iron carbide nanoparticles embedded in a carbon matrix

Here we report on the magnetic properties of iron carbide nanoparticles embedded in a carbon matrix. Granular distributions of nanoparticles in an inert matrix, of potential use in various applications, were prepared by pyrolysis of organic precursors using the thermally assisted chemical vapour deposition method. By varying the precursor concentration and preparation temperature, compositions with varying iron concentration and nanoparticle sizes were made. Powder x-ray diffraction, transmission electron microscopy and Mossbauer spectroscopy studies revealed the nanocrystalline iron carbide (Fe3C) presence in the partially graphitized matrix. The dependence of the magnetic properties on the particle size and temperature (10 K < T < 300 K) were studied using superconducting quantum interference device magnetometry. Based on the affect of surrounding carbon spins, the observed magnetic behaviour of the nanoparticle compositions, such as the temperature dependence of magnetization and coercivity, can be explained.

Modified density matrix renormalization group algorithm for the zigzag spin-1/2 chain with frustrated antiferromagnetic exchange: Comparison with field theory at large J(2)/J(1)

A modified density matrix renormalization group (DMRG) algorithm is applied to the zigzag spin-1/2 chain with frustrated antiferromagnetic exchange J(1) and J(2) between first and second neighbors. The modified algorithm yields accurate results up to J(2)/J(1) approximate to 4 for the magnetic gap Delta to the lowest triplet state, the amplitude B of the bond order wave phase, the wavelength lambda of the spiral phase, and the spin correlation length xi. The J(2)/J(1) dependences of Delta, B, lambda, and xi provide multiple comparisons to field theories of the zigzag chain. The twist angle of the spiral phase and the spin structure factor yield additional comparisons between DMRG and field theory. Attention is given to the numerical accuracy required to obtain exponentially small gaps or exponentially long correlations near a quantum phase transition.

Radiation effects in supported nanoparticles

Nanotechnology applications are entering the market in increasing numbers, nanoparticles being among the main classes of materials used. Particles can be used, e.g., for catalysing chemical reactions, such as is done in car exhaust catalysts today. They can also modify the optical and electronic properties of materials or be used as building blocks for thin film coatings on a variety of surfaces. To develop materials for specific applications, an intricate control of the particle properties, structure, size and shape is required. All these depend on a multitude of factors from methods of synthesis and deposition to post-processing. This thesis addresses the control of nanoparticle structure by low-energy cluster beam deposition and post-synthesis ion irradiation. Cluster deposition in high vacuum offers a method for obtaining precisely controlled cluster-assembled materials with minimal contamination. Due to the clusters small size, however, the cluster-surface interaction may drastically change the cluster properties on deposition. In this thesis, the deposition process of metal and alloy clusters on metallic surfaces is modelled using molecular dynamics simulations, and the mechanisms influencing cluster structure are identified. Two mechanisms, mechanical melting upon deposition and thermally activated dislocation motion, are shown to determine whether a deposited cluster will align epitaxially with its support. The semiconductor industry has used ion irradiation as a tool to modify material properties for decades. Irradiation can be used for doping, patterning surfaces, and inducing chemical ordering in alloys, just to give a few examples. The irradiation response of nanoparticles has, however, remained an almost uncharted territory. Although irradiation effects in nanoparticles embedded inside solid matrices have been studied, almost no work has been done on supported particles. In this thesis, the response of supported nanoparticles is studied systematically for heavy and light ion irradiation. The processes leading to damage production are identified and models are developed for both types of irradiation. In recent experiments, helium irradiation has been shown to induce a phase transformation from multiply twinned to single-crystalline nanoparticles in bimetallic alloys, but the nature of the transition has remained unknown. The alloys for which the effect has been observed are CuAu and FePt. It is shown in this thesis that transient amorphization leads to the observed transition and that while CuAu and FePt do not amorphize upon irradiation in bulk or as thin films, they readily do so as nanoparticles. This is the first time such an effect is demonstrated with supported particles, not embedded in a matrix where mixing is always an issue. An understanding of the above physical processes is essential, if nanoparticles are to be used in applications in an optimal way. This thesis clarifies the mechanisms which control particle morphology, and paves way for the synthesis of nanostructured materials tailored for specific applications.

Mixed pixel analysis for flood mapping using extended support vector machine

This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

Teacher peer support in social network sites

This paper describes the types of support that teachers are accessing through the Social Network Site (SNS) 'Facebook'. It describes six ways in which teachers support one another within online groups. It presents evidence from a study of a large, open group of teachers online over a twelve week period, repeated with multiple groups a year later over a one week period. The findings suggest that large open groups in SNSs can be a useful source of pragmatic advice for teachers but that these groups are rarely a place for reflection on or feedback about teaching practice.

Non-resident workers: A comparison of family support services for resource, health, and defence communities

Non-resident workforces experience high labour turnover, which has an impact on organisational operations and affects worker satisfaction and, in turn, partners’ ability to cope with work-related absences. Research suggests that partner satisfaction may be increased by providing a range of support services, which include professional, practical, and social support. A search was conducted to identify support available for resources and health-industry non-resident workers. These were compared to the supports available to families of deployed defence personnel. They were used to compare and contrast the spread available for each industry. The resources industry primarily provided social support, and lacked an inclusion of professional and practical supports. Health-professional support services were largely directed towards extended locum support, rather than to Fly-In Fly-Out workers. Improving sources of support which parallel support provided to the Australian Defence Force is suggested as a way to increase partner satisfaction. The implications are to understand the level of uptake, perceived importance, and utilisation of such support services.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Kantoaalto koulutuksesta työyhteisön viestintäosaamiseen : lyhytkestoisen viestintäkoulutuksen vaikuttavuuden avaintekijät

The purpose of this research is to examine whether short-term communication training can have an impact on the improvement of communication capacity of working communities, and what are prerequisites for the creation of such capacity. Subjects of this research were short-term communication trainings aimed at the managerial and expert levels of enterprises and communities. The research endeavors to find out how communication trainings with an impact should be devised and implemented, and what this requires from the client and provider of the training service. The research data is mostly comprised of quantitative feed-back collected at the end of a training day, as well as delayed interviews. The evaluations have been based on a stakeholder approach, and those concerned were participants to the trainings, clients having commissioned the trainings and communication trainers. The principal method of the qualitative analysis is that of a data-driven content analysis. Two research instruments have been constructed for the analysis and for the presentation of the results: an evaluation circle for the purposes of a holistic evaluation and a development matrix for the structuring of an effective training. The core concept of the matrix is a carrier wave effect, which is needed to carry the abstractions from the training into concrete functions in the everyday life. The relevance of the results has been tested in a pilot organization. The immediate assessment and delayed evaluations gave a very differing picture of the trainings. The immediate feedback was of nearly commendable level, but the effects carried forward into the everyday situations of the working community were small and that the learning rarely was applied into practice. A training session that receives good feedback does not automatically result in the development of individual competence, let alone that of the community. The results show that even short-term communication training can promote communication competence that eventually changes the working culture on an organizational level, provided that the training is designed into a process and that the connections into the participants’ work are ensured. It is essential that all eight elements of the carrier wave effect are taken into account. The entire purchaser-provider -process must function while not omitting the contribution of the participants themselves. The research illustrates the so called bow tie -model of an effective communication training based on the carrier wave effect. Testing the results in pilot trainings showed that a rather small change in the training approach may have a signi¬ficant effect on the outcome of the training as well as those effects that are carried on into the working community. The evaluation circle proved to be a useful tool, which can be used while planning, executing and evaluating training in practice. The development matrix works as a tool for those producing the training service, those using the service as well as those deciding on the purchase of the service in planning and evaluating training that sustainably improves communication capacity. Thus the evaluation circle also works to support and ensure the long-term effects of short-term trainings. In addition to communication trainings, the tools developed for this research are useable for many such needs, where an organization is looking to improve its operations and profitability through training.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.

Mixed pixel analysis and assessment for flood mapping

The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.

Quality of support for multicasting over mobile ad-hoc networks

An ad hoc network is composed of mobile nodes without any infrastructure. Recent trends in applications of mobile ad hoc networks rely on increased group oriented services. Hence multicast support is critical for ad hoc networks. We also need to provide service differentiation schemes for different group of users. An efficient application layer multicast (APPMULTICAST) solution suitable for low mobility applications in MANET environment has been proposed in [10]. In this paper, we present an improved application layer multicast solution suitable for medium mobility applications in MANET environment. We define multicast groups with low priority and high priority and incorporate a two level service differentiation scheme. We use network layer support to build the overlay topology closer to the actual network topology. We try to maximize Packet Delivery Ratio. Through simulations we show that the control overhead for our algorithm is within acceptable limit and it achieves acceptable Packet Delivery Ratio for medium mobility applications.

Support vector machine approach for the switching transient peak overvoltages during line energization

At the time of restoration transmission line switching is one of the major causes, which creates transient overvoltages. Though detailed Electro Magnetic Transient studies are carried out extensively for the planning and design of transmission systems, such studies are not common in a day-today operation of power systems. However it is important for the operator to ensure during restoration of supply that peak overvoltages resulting from the switching operations are well within safe limits. This paper presents a support vector machine approach to classify the various cases of line energization in the category of safe or unsafe based upon the peak value of overvoltage at the receiving end of line. Operator can define the threshold value of voltage to assign the data pattern in either of the class. For illustration of proposed approach the power system used for switching transient peak overvoltages tests is a 400 kV equivalent system of an Indian southern gri