Intelligent mapping of stresses in a hydraulic crane

Continuous loading and unloading can cause breakdown of cranes. In seeking solution to this problem, the use of an intelligent control system for improving the fatigue life of cranes in the control of mechatronics has been under study since 1994. This research focuses on the use of neural networks as possibilities of developing algorithm to map stresses on a crane. The intelligent algorithm was designed to be a part of the system of a crane, the design process started with solid works, ANSYS and co-simulation using MSc Adams software which was incorporated in MATLAB-Simulink and finally MATLAB neural network (NN) for the optimization process. The flexibility of the boom accounted for the accuracy of the maximum stress results in the ADAMS model. The flexibility created in ANSYS produced more accurate results compared to the flexibility model in ADAMS/View using discrete link. The compatibility between.ADAMS and ANSYS softwares was paramount in the efficiency and the accuracy of the results. Von Mises stresses analysis was more suitable for this thesis work because the hydraulic boom was made from construction steel FE-510 of steel grade S355 with yield strength of 355MPa. Von Mises theory was good for further analysis due to ductility of the material and the repeated tensile and shear loading. Neural network predictions for the maximum stresses were then compared with the co-simulation results for accuracy, and the comparison showed that the results obtained from neural network model were sufficiently accurate in predicting the maximum stresses on the boom than co-simulation.

Mapping cancer, cardiovascular and malaria research in Brazil

This paper presents performance indicators for the Brazilian cancer, cardiovascular and malaria research areas from 1981 to 1995. The data show an increasing number of papers since 1981 and author numbers indicate a continuous growth of the scientific community and suggest an expected impact of scientific activity on biomedical education. The data also characterize cardiovascular research as a well-established area and cancer research as a faster growing consolidating field. The 1989-1994 share of Brazilian articles among world publications shows a growing trend for the cancer (1.61) and cardiovascular (1.59) areas, and a decrease for the malaria area (0.89). The burden of the three diseases on society is contrasted by the small number of consolidated Brazilian research groups, and a questionable balance of thematic activity, especially with regard to malaria. Brazilian periodicals play an important role in increasing the international visibility of science produced in the country. Cancer and cardiovascular research is strongly concentrated in the Southeastern and in Southern regions of Brazil, especially in São Paulo (at least one address from São Paulo in 64.5% of the 962 cancer articles and in 66.9% of the 2250 cardiovascular articles, the second state being Rio de Janeiro with at least one address in 14.1 and 11% of those articles, respectively). Malaria research (468 articles) is more evenly distributed across the country, following the pattern of the endemic distribution of the disease. Surveying these national indicator trends can be useful to establish policies in the decision process about health sciences, medical education and public health.

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

Balancing the quotation process by LEAN methods

This thesis studies the possibility to use lean tools and methods in a quotation process which is carried out in an office environment. The aim of the study was to find out and test the relevant lean tools and methods which can help to balance and standardize the quotation process, and reduce the variance in quotation lead times and in quality. Seminal works, researches and guide books related to the topic were used as the basis for the theory development. Based on the literature review and the case company’s own lean experience, the applicable lean tools and methods were selected to be tested by a sales support team. Leveling production, by product categorization and value stream mapping, was a key method to be used to balance the quotation process. 5S method was started concurrently for standardizing the work. Results of the testing period showed that lean tools and methods are applicable in office process and selected tools and methods helped to balance and standardize the quotation process. Case company’s sales support team decided to implement new lean based quotation process model.

A systematic mapping study on technical debt definition

The goal of this study was to explore and understand the definition of technical debt. Technical debt refers to situation in a software development, where shortcuts or workarounds are taken in technical decision. However, the original definition has been applied to other parts of software development and it is currently difficult to define technical debt. We used mapping study process as a research methodology to collect literature related to the research topic. We collected 159 papers that referred to original definition of technical debt, which were retrieved from scientific literature databases to conduct the search process. We retrieved 107 definitions that were split into keywords. The keyword map is one of the main results of this work. Apart from that, resulting synonyms and different types of technical debt were analyzed and added to the map as branches. Overall, 33 keywords or phrases, 6 synonyms and 17 types of technical debt were distinguished.

A systematic mapping study on open data

This thesis presented the overview of Open Data research area, quantity of evidence and establishes the research evidence based on the Systematic Mapping Study (SMS). There are 621 such publications were identified published between years 2005 and 2014, but only 243 were selected in the review process. This thesis highlights the implications of Open Data principals’ proliferation in the emerging era of the accessibility, reusability and sustainability of data transparency. The findings of mapping study are described in quantitative and qualitative measurement based on the organization affiliation, countries, year of publications, research method, star rating and units of analysis identified. Furthermore, units of analysis were categorized by development lifecycle, linked open data, type of data, technical platforms, organizations, ontology and semantic, adoption and awareness, intermediaries, security and privacy and supply of data which are important component to provide a quality open data applications and services. The results of the mapping study help the organizations (such as academia, government and industries), re-searchers and software developers to understand the existing trend of open data, latest research development and the demand of future research. In addition, the proposed conceptual framework of Open Data research can be adopted and expanded to strengthen and improved current open data applications.

Systematic mapping study on integration of B2B customers in ERP

Business-to-business terminology is relatively new as a business concept, so is the enterprise resource planning system in information technology. Research, implementation and integration of these two concept has been observed for last two decades in this paper. One of the major success point for growth in business-to-business environment is the availability of internal and partner data. Enterprise resource planning system facilitates storing, analysis of such data and enables different business process automation, forecasting and numerous value creating activity. In order to achieve such functionality for B2B customers, integrating them within ERP is very useful. This paper aims at understanding and suggesting such integration through investigating related documentation of similar integration scenarios, infrastructure, models and architectures. The investigation of the topic of this paper has been made using systematic mapping study of related papers and listing and suggesting necessary ingredients that enables such integration. Furthermore, this paper also suggests possibilities to overcome challenges integration experts might face during the integration phase and opens doors to future research scope in the related fields.

Mapping one university's response to internationalization : a case study

This study explored one university's response to the internationalization of higher education. Case study methodology was employed through a review of current and archival documents and interviews with key actors in the international spheres of the university. The historical, current, and future contexts were considered to situate the case study on a time line. Data analysis revealed that there were several points of division among the university community related to the response to internationalization, but also a major point of coherence in the centrality of inter-cultural understanding in efforts to internationalize. Other key findings included strengths, areas for improvement, and future directions of the university's response to internationalization. All of these findings were contextualized in findings related to the history of the university. In addition to these major findings, three themes in relation to the vision for internationalization at the institution were revealed: ( a) intercultural understanding, (b) the comprehensive status of the university, and (c) the financial benefits of internationalization. Recommendations are made for practice at the university in order to clarify this vision to develop a clear foundation from which to further build a response to internationalization that is solidly based on inter-cultural understanding, and recommendations for future research into the process of internationalization at the institutional level in Canada are suggested.

Architecture and other Architectures: Mapping the Production of Insular Space in the Pearl River Delta (China) and Jakarta (Indonesia)

Globalization is widely regarded as the rise of the borderless world. However in practice, true globalization points rather to a “spatial logic” by which globalization is manifested locally in the shape of insular space. Globalization in this sense is not merely about the creation of physical fragmentation of space but also the creation of social disintegration. This study tries to proof that global processes also create various forms of insular space leading also to specific social implications. In order to examine the problem this study looks at two cases: China’s Pearl River Delta (PRD) and Jakarta in Indonesia. The PRD case reveals three forms of insular space namely the modular, concealed and the hierarchical. The modular points to the form of enclosed factories where workers are vulnerable for human-right violations due to the absent of public control. The concealed refers to the production of insular space by subtle discrimination against certain social groups in urban space. And the hierarchical points to a production of insular space that is formed by an imbalanced population flow. The Jakarta case attempts to show more types of insularity in relation to the complexity of a mega-city which is shaped by a culture of exclusion. Those are dormant and hollow insularity. The dormant refers to the genesis of insular– radical – community from a culture of resistance. The last type, the hollow, points to the process of making a “pseudo community” where sense of community is not really developed as well as weak social relationship with its surrounding. Although global process creates various expressions of territorial insularization, however, this study finds that the “line of flight” is always present, where the border of insularity is crossed. The PRD’s produces vernacular modernization done by peasants which is less likely to be controlled by the politics of insularization. In Jakarta, the culture of insularization causes urban informalities that have no space, neither spatially nor socially; hence their state of ephemerality continues as a tactic of place-making. This study argues that these crossings possess the potential for reconciling venue to defuse the power of insularity.

Efficient topology estimation for large scale optical mapping

Large scale image mosaicing methods are in great demand among scientists who study different aspects of the seabed, and have been fostered by impressive advances in the capabilities of underwater robots in gathering optical data from the seafloor. Cost and weight constraints mean that lowcost Remotely operated vehicles (ROVs) usually have a very limited number of sensors. When a low-cost robot carries out a seafloor survey using a down-looking camera, it usually follows a predetermined trajectory that provides several non time-consecutive overlapping image pairs. Finding these pairs (a process known as topology estimation) is indispensable to obtaining globally consistent mosaics and accurate trajectory estimates, which are necessary for a global view of the surveyed area, especially when optical sensors are the only data source. This thesis presents a set of consistent methods aimed at creating large area image mosaics from optical data obtained during surveys with low-cost underwater vehicles. First, a global alignment method developed within a Feature-based image mosaicing (FIM) framework, where nonlinear minimisation is substituted by two linear steps, is discussed. Then, a simple four-point mosaic rectifying method is proposed to reduce distortions that might occur due to lens distortions, error accumulation and the difficulties of optical imaging in an underwater medium. The topology estimation problem is addressed by means of an augmented state and extended Kalman filter combined framework, aimed at minimising the total number of matching attempts and simultaneously obtaining the best possible trajectory. Potential image pairs are predicted by taking into account the uncertainty in the trajectory. The contribution of matching an image pair is investigated using information theory principles. Lastly, a different solution to the topology estimation problem is proposed in a bundle adjustment framework. Innovative aspects include the use of fast image similarity criterion combined with a Minimum spanning tree (MST) solution, to obtain a tentative topology. This topology is improved by attempting image matching with the pairs for which there is the most overlap evidence. Unlike previous approaches for large-area mosaicing, our framework is able to deal naturally with cases where time-consecutive images cannot be matched successfully, such as completely unordered sets. Finally, the efficiency of the proposed methods is discussed and a comparison made with other state-of-the-art approaches, using a series of challenging datasets in underwater scenarios

Análisis de la aplicabilidad de la técnica Value Stream Mapping en el rediseño de sistemas productivos

Los sistemas productivos de las empresas han de adaptarse a las exigencias de los mercados. El Value Stream Mapping (VSM) es una técnica desarrollada por la Producción Ajustada y orientada al rediseño de dichos sistemas productivos. Si bien existe divulgación teórica sobre la técnica así como publicaciones de casos prácticos exitosos, se detecta la carencia de un análisis que explore en profundidad la aplicabilidad de la técnica en entornos productivos relacionados con las lineas de flujo desconectadas. Así, el objetivo de la tesis es la evaluación de la aplicabilidad del VSM en dichos entornos. El método de investigación adoptado ha consistido en un estudio de casos múltiple sobre seis empresas. Los resultados confirman la validez práctica del VSM para el rediseño de sistemas productivos. No obstante, también se fijan aspectos de mejora y desarrollo para que la técnica pueda convertirse en la referencia base.

Determining feature relevance for the grouping of motor unit action potentials through generative topographic mapping

The study of motor unit action potential (MUAP) activity from electrornyographic signals is an important stage on neurological investigations that aim to understand the state of the neuromuscular system. In this context, the identification and clustering of MUAPs that exhibit common characteristics, and the assessment of which data features are most relevant for the definition of such cluster structure are central issues. In this paper, we propose the application of an unsupervised Feature Relevance Determination (FRD) method to the analysis of experimental MUAPs obtained from healthy human subjects. In contrast to approaches that require the knowledge of a priori information from the data, this FRD method is embedded on a constrained mixture model, known as Generative Topographic Mapping, which simultaneously performs clustering and visualization of MUAPs. The experimental results of the analysis of a data set consisting of MUAPs measured from the surface of the First Dorsal Interosseous, a hand muscle, indicate that the MUAP features corresponding to the hyperpolarization period in the physisiological process of generation of muscle fibre action potentials are consistently estimated as the most relevant and, therefore, as those that should be paid preferential attention for the interpretation of the MUAP groupings.

Proof of concept of automated mapping of weeds in arable fields

The project investigated whether it would be possible to remove the main technical hindrance to precision application of herbicides to arable crops in the UK, namely creating geo-referenced weed maps for each field. The ultimate goal is an information system so that agronomists and farmers can plan precision weed control and create spraying maps. The project focussed on black-grass in wheat, but research was also carried out on barley and beans and on wild-oats, barren brome, rye-grass, cleavers and thistles which form stable patches in arable fields. Farmers may also make special efforts to control them. Using cameras mounted on farm machinery, the project explored the feasibility of automating the process of mapping black-grass in fields. Geo-referenced images were captured from June to December 2009, using sprayers, a tractor, combine harvesters and on foot. Cameras were mounted on the sprayer boom, on windows or on top of tractor and combine cabs and images were captured with a range of vibration levels and at speeds up to 20 km h-1. For acceptability to farmers, it was important that every image containing black-grass was classified as containing black-grass; false negatives are highly undesirable. The software algorithms recorded no false negatives in sample images analysed to date, although some black-grass heads were unclassified and there were also false positives. The density of black-grass heads per unit area estimated by machine vision increased as a linear function of the actual density with a mean detection rate of 47% of black-grass heads in sample images at T3 within a density range of 13 to 1230 heads m-2. A final part of the project was to create geo-referenced weed maps using software written in previous HGCA-funded projects and two examples show that geo-location by machine vision compares well with manually-mapped weed patches. The consortium therefore demonstrated for the first time the feasibility of using a GPS-linked computer-controlled camera system mounted on farm machinery (tractor, sprayer or combine) to geo-reference black-grass in winter wheat between black-grass head emergence and seed shedding.

Final report on research project PS2010, proof of concept of automated mapping of weeds in arable fields

Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).

Multiple PID mapping using neural networks in a MIMO steam generator system

A neural network was used to map three PID operating regions for a two-input two-output steam generator system. The network was used in stand alone feedforward operation to control the whole operating range of the process, after being trained from the PID controllers corresponding to each control region. The network inputs are the plant error signals, their integral, their derivative and a 4-error delay train.