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| 3. |
- Aarno, Daniel, 1979-
(författare)
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Intention recognition in human machine collaborative systems
- 2007
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Robotsystem har använts flitigt under de senaste årtiondena för att skapa automationslösningar i ett flertal områden. De flesta nuvarande automationslösningarna är begränsade av att uppgifterna de kan lösa måste vara repetitiva och förutsägbara. En av anledningarna till detta är att dagens robotsystem saknar förmåga att förstå och resonera om omvärlden. På grund av detta har forskare inom robotik och artificiell intelligens försökt att skapa intelligentare maskiner. Trots att stora framsteg har gjorts då det gäller att skapa robotar som kan fungera och interagera i en mänsklig miljö så finns det för nuvarande inget system som kommer i närheten av den mänskliga förmågan att resonera om omvärlden. För att förenkla problemet har vissa forskare föreslagit en alternativ lösning till helt självständiga robotar som verkar i mänskliga miljöer. Alternativet är att kombinera människors och maskiners förmågor. Exempelvis så kan en person verka på en avlägsen plats, som kanske inte är tillgänglig för personen i fråga på grund av olika orsaker, genom att använda fjärrstyrning. Vid fjärrstyrning skickar operatören kommandon till en robot som verkar som en förlängning av operatörens egen kropp. Segmentering och identifiering av rörelser skapade av en operatör kan användas för att tillhandahålla korrekt assistans vid fjärrstyrning eller samarbete mellan människa och maskin. Assistansen sker ofta inom ramen för virtuella fixturer där eftergivenheten hos fixturen kan justeras under exekveringen för att tillhandahålla ökad prestanda i form av ökad precision och minskad tid för att utföra uppgiften. Den här avhandlingen fokuserar på två aspekter av samarbete mellan människa och maskin. Klassificering av en operatörs rörelser till ett på förhand specificerat tillstånd under en manipuleringsuppgift och assistans under manipuleringsuppgiften baserat på virtuella fixturer. Den specifika tillämpningen som behandlas är manipuleringsuppgifter där en mänsklig operatör styr en robotmanipulator i ett fjärrstyrt eller samarbetande system. En metod för att följa förloppet av en uppgift medan den utförs genom att använda virtuella fixturer presenteras. Istället för att följa en på förhand specificerad plan så har operatören möjlighet att undvika oväntade hinder och avvika från modellen. För att möjliggöra detta estimeras kontinuerligt sannolikheten att operatören följer en viss trajektorie (deluppgift). Estimatet används sedan för att justera eftergivenheten hos den virtuella fixturen så att ett beslut om hur rörelsen ska fixeras kan tas medan uppgiften utförs. En flerlagers dold Markovmodell (eng. layered hidden Markov model) används för att modellera mänskliga färdigheter. En gestemklassificerare som klassificerar en operatörs rörelser till olika grundläggande handlingsprimitiver, eller gestemer, evalueras. Gestemklassificerarna används sedan i en flerlagers dold Markovmodell för att modellera en simulerad fjärrstyrd manipuleringsuppgift. Klassificeringsprestandan utvärderas med avseende på brus, antalet gestemer, typen på den dolda Markovmodellen och antalet tillgängliga träningssekvenser. Den flerlagers dolda Markovmodellen tillämpas sedan på data från en trajektorieföljningsuppgift i 2D och 3D med en robotmanipulator för att ge både kvalitativa och kvantitativa resultat. Resultaten tyder på att den flerlagers dolda Markovmodellen är väl lämpad för att modellera trajektorieföljningsuppgifter och att den flerlagers dolda Markovmodellen är robust med avseende på felklassificeringar i de underliggande gestemklassificerarna.
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- Abas, Riad Abdul
(författare)
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Property measurements towards understanding process phenomena
- 2005
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The main objective of this industrially important work was to gain an increasing understanding of the properties of materials such as CMSX-4 nickel base super alloy, mould powder used in continuous casting of steel and coke used in blast furnace, with special reference to the thermal diffusivities. The measurements were carried out in a wide temperature range, solid, liquid, glassy and crystalline states. For CMSX-4 alloy, the thermal conductivities were calculated from the experimental thermal diffusivities. Both the diffusivities and conductivities were found to increase with increasing temperature. Microscopic analysis showed the presence of intermetallic phases such as NiTi and NiTi2 below 1253 K. In this region, the mean free path of the phonons is likely to be limited by scattering against lattice defects. Between 1253 K and solidus temperature, these phases dissolved in the alloy adding to the impurities in the matrix, which, in turn, caused a decrease in the thermal diffusivity. This effect was confirmed by annealing the samples at 1573 K. The thermal diffusivities of the annealed samples measured at 1277, 1403 and 1531 K were found to be lower than the thermal diffusivities of non-annealed samples and the values did not show any noticeable change with time. It could be related to the attainment of equilibrium with the completion of the dissolution of γ and γ´ phases during the annealing process. Liquid CMSX-4 does not show any change of thermal diffusivity with temperature. It may be attributed to the decreasing the mean free path being shorter than characteristic distance between two neighbouring atoms. On the other hand thermal diffusivities of mould powder having glassy and crystalline states decrease with increasing temperature at lower temperature and are constant at higher temperature except for one glassy sample. Analogously, the thermal diffusivity measurements of mould powder did not show any significant change with temperature in liquid state. It is likely to be due to the silicate network being largely broken down. The thermal diffusivity is increased with increasing crystallisation degree of mould powder, which is expected from theoretical considerations. The coke sample, taken from deeper level of the blast furnace, is found to have larger thermal diffusivity. This could be correlated to the average crystallite size along the structural c-axis, Lc, which is indicative of the higher degree of graphitisation. This was also confirmed by XRD measurements of the different coke samples. The degree of graphitisation was found to increase with increasing temperature. Further, XRD measurements of coke samples taken from different levels in the shaft of the blast furnace show that the graphitisation of coke was instantaneous between room temperature and 1473 K.
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- Abbasi, Saeed
(författare)
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Characterisation of airborne particles from rail traffic
- 2011
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Since the investigation of wear particles in rail transport started in late-1910s, the high mass concentration of these particles has raised worries among researchers concerned with air quality. However, effective action has yet to be taken because of lack of relevant knowledge. This thesis provides applicable information for the airborne wear particles in rail transport. Some aspects of their characteristics such as diameter size, mass concentration, number concentration, and morphology of particles were investigated in field tests and laboratory tests.The effects on particle characterisations from different operational conditions in the field tests, and applying different braking materials, conducting tests in different applied loads or sliding velocities in the laboratory tests were studied. The main advantage of conducting laboratory tests was to focus on studying particles from one source. The possibility of repetition, using high sensitive instruments and conducting tests at low costs are the other advantages of laboratory studies. Paper A describes how a pin-on-disc machine was used to reproduce similar real operational conditions during mechanical braking in a train. The results were validated by comparing the field tests results with the laboratory studies. The particles morphology and size distribution were also studied.Paper B presents a summary of field tests results. The effects of curve negotiating and applying braking in different real conditions were investigated with an on-board measurement.The element composition of the particles and their potential sources were also investigated outside of the particles morphologies.Paper C presents comprehensive results from laboratory studies on airborne particles from different braking materials. The differences in the particle characteristics in similar test conditions were attributable to different material compositions and dominant wear mechanisms. A new index was introduced in this paper and is suggested to be used as a qualitative factor with regard to the airborne wear particle emission rate.Paper D is a review of the recent studies of exhaust emission and non-exhaust emission from rail vehicles. A summary of results, measurements, adverse health effects, and proposed or applied solutions are reviewed in this paper.
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- Abbasiverki, Roghayeh
(författare)
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Analysis of underground concrete pipelines subjected to seismic high-frequency loads
- 2016
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Buried pipelines are tubular structures that are used for transportation of important liquid materials and gas in order to provide safety for human life. During an earthquake, imposed loads from soil deformations on concrete pipelines may cause severe damages, possibly causing disturbance in vital systems, such as cooling of nuclear power facilities. The high level of safety has caused a demand for reliable seismic analyses, also for structures built in the regions that have not traditionally been considered as highly seismically active. The focus in this study is on areas with seismic and geological conditions corresponding to those in Sweden and Northern Europe. Earthquakes in Sweden for regions with hard rock dominated by high-frequency ground vibrations, Propagation of such high-frequency waves through the rock mass and soil medium affect underground structures such as pipelines.The aim of this project is investigating parameters that affect response of buried pipelines due to high-frequency seismic excitations. The main focus of the study is on reinforced concrete pipelines. Steel pipelines are also studied for comparison purposes. The effects of water mass, burial depth, soil layer thickness and non-uniform ground thickness caused by inclined bedrock are studied. The results are compared to those obtained for low-frequency earthquakes and the relationship between strong ground motion parameters and pipelines response is investigated. It is shown that, especially for high frequency earthquake excitations, non-uniform ground thickness due to inclined bedrock significantly increase stresses in the pipelines. For the conditions studied, it is clear that high-frequency seismic excitation is less likely to cause damage to buried concrete pipelines. However, the main conclusion is that seismic analysis is motivated also for pipelines in high-frequency earthquake areas since local variation in the ground conditions can have a significant effect on the safety.
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| 7. |
- Abbes, Yacine
(författare)
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Educational studies in heat and power technology : how students learn with multimedia tools and problem-based learning
- 2005
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Higher education is undergoing continuous changes and new learning tools and methods are implemented. Researchers in education do not always agree upon the effectiveness of some of the methods introduced into engineering education. The present thesis consists of two case studies on educational methods introduced at the Department of Energy Technology, at Royal Institute of Technology (KTH), Sweden. The qualitative research methodology has been used in case one and a combination of qualitative and quantitative methodology has been used in the second case. The sources of evidences consisted of: unstructured interviews, analysis of video recording, questionnaires, and analysis of a variety of documents. In the first case, an educational program in heat and power technology was analysed. The second case consists in an in-depth study of group dynamics in a Problem –Based Learning course. These studies showed that the learning approach adopted by students depends strongly on the way they view the particular learning tool or method. The first case study revealed the existence of two types of learners. Surfacelearners follow the structure suggested by the designers of the multimedia program. This category of learners focuses only on the material available in the program. Deep-learners go beyond the information and the structure suggested in the program and combine different learning tools in their learning. These students do not follow the structure of the tutorials’ of the multimedia program. This study showed that students who had a strong view how to learn with a multimedia program or a learning method benefited less from the learning tools available. Students with weak views on how to learn from educational program or leaning tool benefit less from the presentation and engage in more surface learning. Self-motivated learners use the multimedia presentation in novel ways and crosscheck the information given with other material. The second study showed that students have unclear and weak views on how to learn with student-directed Problem- Based Learning model. Four types of learners were identified in Problem-Based Learning project: Leaders, Key Actors, Common Students and Social Loafers. Leaders and Key Actors are self-motivated individuals and participate most in the projects. Students who viewed themselves or were viewed as leaders were held responsible to take most of the decisions and students expected them to work more than the average student. Students who viewed themselves as common team members expected a lower workload than leaders’. Key Actors are self-motivated students who do not view themselves as separate from other group members but who participate more than others. Leaders learned more group and social processes, that they did not fully take part in, while common students learned more from the project management aspects that they did not take part in. The study also found that Problem-Based Learning groups can become very cohesive, and can develop distorted views on how to learn with Problem-Based Learning, and un-common group dynamics phenomena such as groupthink can occur in Problem-Based Learning setting.
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- Abburu, Sai Kausik
(författare)
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Vehicle Conceptualisation, Compactness, and Subsystem Interaction : A network approach to design and analyse the complex interdependencies in vehicles
- 2023
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The conventional approach to vehicle design is restrictive, limited, andbiased. This often leads to sub-optimal utilisation of vehicle capabilities and allocated resources and ultimately entails the repercussions of designing andlater on an using an inefficient vehicle. To overcome these limitations, it is important to gain a deeper understanding of the interaction effects at component,subsystem, and system level. In this thesis, the research is focused on identifying appropriate methods and developing robust models to facilitate the interaction analysis.To scrutinise and identify appropriate methods, criteria were developed.Initially, the Design Structure Matrix (DSM) and its variations were examined.While DSM proved to be fundamental for capturing interaction effects,it lacked the ability to answer questions about the structure and behaviour ofinteractions and to predict unintended effects. Therefore, network theory wasexplored as a complementary method to DSM which was capable of providing insights into interaction structures and identifying influential variables.Subsequently, two criteria were established to identify subsystems significant to interaction analysis: high connectivity to other subsystems and multidisciplinary composition. The traction motor was observed to satisfyboth criteria as it had higher connectivity with other subsystems and was composed of multiple disciplines. Therefore, a detailed model of an induction motor was developed to enable the interaction analysis.The induction motor model was integrated into a cross-scalar design tool.The tool employed a two-step process: translating operational parametersto motor inputs using Newtonian equations and deriving physical attributes,performance characteristics, and performance attributes of the motor. Comparing the obtained performance characteristics curve against existing studiesvalidated the model’s reliability and capabilities. The design tool demonstrated adaptability to different drive cycles and the ability to modify motor performance without affecting operational parameters. Thus validating the capability of the design tool to capture cross-scalar and intra-subsystem interaction effects. To examine inter-subsystem interaction, a thermal model of an inverter was developed, capturing temperature variations in the power electronics based on motor inputs. The design tool successfully captured interaction effects between motor and inverter designs, highlighting the interplay with operational parameters.Thus, this thesis identifies methods for interaction analysis and develops robust subsystem models. The integrated design tool effectively captures intra-subsystem, inter-subsystem, and cross-scalar interaction effects. The research presented contributes to the overarching project goal of developing methods and models that capture interaction effects and in turn serve as a guiding tool for designers to understand the consequences of their design choices.
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- Abdalmoaty, Mohamed, 1986-
(författare)
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Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors
- 2017
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. Albeit asymptotically optimal, these methods come with several computational challenges and fundamental limitations.The contributions of this thesis can be divided into two main parts. In the first part, approximate solutions to the maximum likelihood problem are explored. Both analytical and numerical approaches, based on the expectation-maximization algorithm and the quasi-Newton algorithm, are considered. While analytic approximations are difficult to analyze, asymptotic guarantees can be established for methods based on Monte Carlo approximations. Yet, Monte Carlo methods come with their own computational difficulties; sampling in high-dimensional spaces requires an efficient proposal distribution to reduce the number of required samples to a reasonable value.In the second part, relatively simple prediction error method estimators are proposed. They are based on non-stationary one-step ahead predictors which are linear in the observed outputs, but are nonlinear in the (assumed known) input. These predictors rely only on the first two moments of the model and the computation of the likelihood function is not required. Consequently, the resulting estimators are defined via analytically tractable objective functions in several relevant cases. It is shown that, under mild assumptions, the estimators are consistent and asymptotically normal. In cases where the first two moments are analytically intractable due to the complexity of the model, it is possible to resort to vanilla Monte Carlo approximations. Several numerical examples demonstrate a good performance of the suggested estimators in several cases that are usually considered challenging.
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