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.

Dual light barrier method for six degrees of freedom tool center point calibration of an industrial robot

Tool center point calibration is a known problem in industrial robotics. The major focus of academic research is to enhance the accuracy and repeatability of next generation robots. However, operators of currently available robots are working within the limits of the robot´s repeatability and require calibration methods suitable for these basic applications. This study was conducted in association with Stresstech Oy, which provides solutions for manufacturing quality control. Their sensor, based on the Barkhausen noise effect, requires accurate positioning. The accuracy requirement admits a tool center point calibration problem if measurements are executed with an industrial robot. Multiple possibilities are available in the market for automatic tool center point calibration. Manufacturers provide customized calibrators to most robot types and tools. With the handmade sensors and multiple robot types that Stresstech uses, this would require great deal of labor. This thesis introduces a calibration method that is suitable for all robots which have two digital input ports free. It functions with the traditional method of using a light barrier to detect the tool in the robot coordinate system. However, this method utilizes two parallel light barriers to simultaneously measure and detect the center axis of the tool. Rotations about two axes are defined with the center axis. The last rotation about the Z-axis is calculated for tools that have different width of X- and Y-axes. The results indicate that this method is suitable for calibrating the geometric tool center point of a Barkhausen noise sensor. In the repeatability tests, a standard deviation inside robot repeatability was acquired. The Barkhausen noise signal was also evaluated after recalibration and the results indicate correct calibration. However, future studies should be conducted using a more accurate manipulator, since the method employs the robot itself as a measuring device.

Mapping of a novel viviparous unstable mutant of maize (vp 12)

A new viviparous mutant of maize (Zea mays L.), associated with genetic instability and designated viviparous-12 (vp12), was identified in a synthetic Tuxpeño adapted to tropical regions. In the present work, the linkage group of this new locus was determined. Progenies of inbred line L477 segregating for the vp12 mutant were crossed with waxy-marked reciprocal translocation stocks. The phenotypic frequencies of the wx and vp12 mutants were analyzed in F2 progenies. The results demonstrated that the Viviparous-12 locus of maize is located on the long arm of chromosome 6.

Chromosomal evolution and comparative gene mapping in the Drosophila repleta species group

A review of our recent work on the cromosomal evolution of the Drosophila repleta species group is presented. Most studies have focused on the buzzatii species complex, a monophyletic set of 12 species which inhabit the deserts of South America and the West Indies. A statistical analysis of the length and breakpoint distribution of the 86 paracentric inversions observed in this complex has shown that inversion length is a selected trait. Rare inversions are usually small while evolutionary successful inversions, fixed and polymorphic, are predominantly of medium size. There is also a negative correlation between length and number of inversions per species. Finally, the distribution of inversion breakpoints along chromosome 2 is non-random, with chromosomal regions which accumulate up to 8 breakpoints (putative "hot spots"). Comparative gene mapping has also been used to investigate the molecular organization and evolution of chromosomes. Using in situ hybridization, 26 genes have been precisely located on the salivary gland chromosomes of D. repleta and D. buzzatii; another nine have been tentatively identified. The results are fully consistent with the currently accepted chromosomal homologies between D. repleta and D. melanogaster, and no evidence for reciprocal translocations or pericentric inversions has been found. The comparison of the gene map of D. repleta chromosome 2 with that of the homologous chromosome 3R of D. melanogaster shows an extensive reorganization via paracentric inversions and allows to estimate an evolution rate of ~1 inversion fixed per million years for this chromosome

A systematic mapping study of web services discovery mechanisms

Context: Web services have been gaining popularity due to the success of service oriented architecture and cloud computing. Web services offer tremendous opportunity for service developers to publish their services and applications over the boundaries of the organization or company. However, to fully exploit these opportunities it is necessary to find efficient discovery mechanism thus, Web services discovering mechanism has attracted a considerable attention in Semantic Web research, however, there have been no literature surveys that systematically map the present research result thus overall impact of these research efforts and level of maturity of their results are still unclear. This thesis aims at providing an overview of the current state of research into Web services discovering mechanism using systematic mapping. The work is based on the papers published 2004 to 2013, and attempts to elaborate various aspects of the analyzed literature including classifying them in terms of the architecture, frameworks and methods used for web services discovery mechanism. Objective: The objective if this work is to summarize the current knowledge that is available as regards to Web service discovery mechanisms as well as to systematically identify and analyze the current published research works in order to identify different approaches presented. Method: A systematic mapping study has been employed to assess the various Web Services discovery approaches presented in the literature. Systematic mapping studies are useful for categorizing and summarizing the level of maturity research area. Results: The result indicates that there are numerous approaches that are consistently being researched and published in this field. In terms of where these researches are published, conferences are major contributing publishing arena as 48% of the selected papers were conference published papers illustrating the level of maturity of the research topic. Additionally selected 52 papers are categorized into two broad segments namely functional and non-functional based approaches taking into consideration architectural aspects and information retrieval approaches, semantic matching, syntactic matching, behavior based matching as well as QOS and other constraints.

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.

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

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.

Functional mapping of the cardiorespiratory effects of dorsal and median raphe nuclei in the rat

The dorsal (DRN) and median (MRN) raphe nuclei are important sources of serotonergic innervation to the forebrain, projecting to sites involved in cardiovascular regulation. These nuclei have been mapped using electrical stimulation, which has the limitation of stimulating fibers of passage. The present study maps these areas with chemical stimulation, investigating their influence on cardiorespiratory parameters. Urethane-anesthetized (1.2 g/kg, iv) male Wistar rats (280-300 g) were instrumented for pulsatile and mean blood pressure (MBP), heart rate, renal nerve activity, and respiratory frequency recordings. Microinjections of L-glutamate (0.18 M, 50-100 nl with 1% Pontamine Sky Blue) were performed within the DRN or the MRN with glass micropipettes. At the end of the experiments the sites of microinjection were identified. The majority of sites within the MRN (86.1%) and DRN (85.4%) evoked pressor responses when stimulated (DRN: deltaMBP = +14.7 ± 1.2; MRN: deltaMBP = +13.6 ± 1.3 mmHg). The changes in renal nerve activity and respiratory rate caused by L-glutamate were +45 ± 11 and +42 ± 9% (DRN; P < 0.05%), +40 ± 10 and +29 ± 7% (MRN, P < 0.05), respectively. No significant changes were observed in saline-microinjected animals. This study shows that: a) the blood pressure increases previously observed by electrical stimulation within the raphe are due to activation of local neurons, b) this pressor effect is due to sympathoexcitation because the stimulation increased renal sympathetic activity but did not produce tachycardia, and c) the stimulation of cell bodies in these nuclei also increases the respiratory rate.

Control of Robot by Means of Human Thought

Brain computer interface (BCI) is a kind of human machine interface, which provides a new interaction method between human and computer or other equipment. The most significant characteristic of BCI system is that its control input is brain electrical activities acquired from the brain instead of traditional input such as hands or eyes. BCI technique has rapidly developed during last two decades and it has mainly worked as an auxiliary technique to help the disable people improve their life qualities. With the appearance of low cost novel electrical devices such as EMOTIV, BCI technique has been applied to the general public through many useful applications including video gaming, virtual reality and virtual keyboard. The purpose of this research is to be familiar with EMOTIV EPOC system and make use of it to build an EEG based BCI system for controlling an industrial manipulator by means of human thought. To build a BCI system, an acquisition program based on EMOTIV EPOC system is designed and a MFC based dialog that works as an operation panel is presented. Furthermore, the inverse kinematics of RV-3SB industrial robot was solved. In the last part of this research, the designed BCI system with human thought input is examined and the results indicate that the system is running smoothly and displays clearly the motion type and the incremental displacement of the motion.

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.

Mapping and signaling of neural pathways involved in the regulation of hydromineral homeostasis

Several forebrain and brainstem neurochemical circuitries interact with peripheral neural and humoral signals to collaboratively maintain both the volume and osmolality of extracellular fluids. Although much progress has been made over the past decades in the understanding of complex mechanisms underlying neuroendocrine control of hydromineral homeostasis, several issues still remain to be clarified. The use of techniques such as molecular biology, neuronal tracing, electrophysiology, immunohistochemistry, and microinfusions has significantly improved our ability to identify neuronal phenotypes and their signals, including those related to neuron-glia interactions. Accordingly, neurons have been shown to produce and release a large number of chemical mediators (neurotransmitters, neurohormones and neuromodulators) into the interstitial space, which include not only classic neurotransmitters, such as acetylcholine, amines (noradrenaline, serotonin) and amino acids (glutamate, GABA), but also gaseous (nitric oxide, carbon monoxide and hydrogen sulfide) and lipid-derived (endocannabinoids) mediators. This efferent response, initiated within the neuronal environment, recruits several peripheral effectors, such as hormones (glucocorticoids, angiotensin II, estrogen), which in turn modulate central nervous system responsiveness to systemic challenges. Therefore, in this review, we shall evaluate in an integrated manner the physiological control of body fluid homeostasis from the molecular aspects to the systemic and integrated responses.

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.

Development of a Control System for a Tele Operated Mobile Robot

Mobile robots are capable of performing spatial displacement motions in different environments. This motions can be calculated based on sensorial data (autonomous robot) or given by an operator (tele operated robot). This thesis is focused on the latter providing the control architecture which bridges the tele operator and the robot’s locomotion system and end effectors. Such a task might prove overwhelming in cases where the robot comprises a wide variety of sensors and actuators hence a relatively new option was selected: Robot Operating System (ROS). The control system of a new robot will be sketched and tested in a simulation model using ROS together with Gazebo in order to determine the viability of such a system. The simulated model will be based on the projected shape and main features of the real machine. A stability analysis will be performed first theoretically and afterwards using the developed model. This thesis concluded that both the physical properties and the control architecture are feasible and stable settling up the ground for further work with the same robot.