Global ETD Search

1	Fart Kamrat Berg Bring, Josefine January 2016 (has links) Rörelse och den sociala samvaron ligger i fokus i förskolans pedagogik och byggnaden är utformad för att understödja det med hjälp av dess form, öppenhet, och flexibilitet. Möjligheten att ändra salarnas storlek gör rummen mer användbara utifrån olika behov som uppstår i undervisningen och leken. Den nedsänkta huskroppen formar en kuperad och varierad omkringliggande miljö som uppmuntrar barnen till spring och lek. Den invändiga öppna planlösningen och alla gemensamma utrymmen skapar möjlighet till många möten mellan alla barnen och skapar en gemenskap. / Movement and social interaction are the main focus of this preschools philosophy, and the building is designed to support that with the help of its shape, transparency, and flexibility. The ability to change the size of the rooms makes the areas more useful based on different needs that arise in the education and the children’s play. The underground part of the building forms a hilly and varied surrounding environment that encourages kids to run and play. The interior open floor plan and all common areas create the opportunity for many meetings between all the children and it creates a community. Förskolan Fart Kamrat Solna EQ Rörelse Architecture Arkitektur
2	Deinterleaving pulse trains with DBSCAN and FART Mahmod, Shad January 2019 (has links) Studying radar pulses and looking for certain patterns is critical in order to assess the threat level of the environment around an antenna. In order to study the electromagnetic pulses emitted from a certain radar, one must first register and identify these pulses. Usually there are several active transmitters in anenvironment and an antenna will register pulses from various sources. In order to study the different pulse trains, the registered pulses first have to be sorted sothat all pulses that are transmitted from one source are grouped together. This project aims to solve this problem, using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and compare the results with those obtained by Fuzzy Adaptive Resonance Theory (FART). We aim to further dig into these methods and map out how factors such as feature selection and training time affects the results. A solution based on the DBSCAN method is proposed which allows online clustering of new points introduced to the system. The methods are implemented and tested on simulated data. The data consists of pulse trains from simulated transmitters with unique behaviors. The deployed methods are then tested varying the parameters of the models as well as the number of pulse trains they are asked to deinterleave. The results when applying the models are then evaluated using the adjusted Rand index (ARI). The results indicate that in most cases using all possible data (in this case the angle of arrival, radio frequency, pulse width and amplitudes of the pulses) generate the best results. Rescaling the data further improves the result and tuning the parameters shows that the models work well when increasing the number of emitters. The results also indicate that the DBSCAN method can be used to get accurate estimates of the number of emitters transmitting. The online DBSCAN generates a higher ARI than FART on the simulated data set but has a higher worst case computational cost. DBSCAN FART Fuzzy Adaptive Resonance Theory Radar Clustering Deinterleaving Machine Learning Other Computer and Information Science Annan data- och informationsvetenskap
3	Med för hög musikvolym hör du inte farten / With too high musicvolume you will not hear the speed Hjertstedt, Mikael January 2013 (has links) Att tidsperceptionen är påverkbar har tidigare påvisats. Studien syftar till att undersöka huruvida tidsperceptionen påverkar fartperceptionen, med hypotesen att när interna taktgivaren går snabbare uppfattas farten som lägre. 28 försöksdeltagare fick under fyra betingelser (Lugn, Stressig, Egen musik och Tyst) utföra tids- och fartestimationer under bilfärd. Inga signifikanta resultat påvisades ifråga om vare sig tidsperceptionen eller dess inverkan på fartperceptionen. Däremot skilde sig prospektiv estimation av medelfart åt beroende på betingelsen. Tyst betingelse befrämjade mer korrekt fartestimation, stressig musik och egen musik gjorde estimationen mindre korrekt. Likt tidigare forskning var det fråga om ”response expansion” avseende upplevelsen av deceleration medan fartupplevelsen var relativt linjär i fråga om konstant fart och acceleration. Då inga signifikanta skillnader i tidsperception uppnåddes kan dess inverkan på fartperceptionen ej förkastas. Studien bör replikeras med en annan på förhand testad stressor. / Time perception has been shown to be influenceable. This study aims to investigate whether time perception affects speed perception, with the hypothesis that when the internal pacemaker have a faster pace, speed are perceived as lower. 28 participants performed time and speed estimations while they were passengers in a car. These were made under four conditions (Calm, Stressful, Own music, Quiet). No significant results were found in terms of whether time perception or its impact on speed perception. However the prospective estimation of speed differed depending on condition. Quiet condition promoted more accurate speed estimation, stressful music, and own music made the estimation less accurate. Similar to previous research, there was an effect of "response expansion" for the experience of deceleration while speed experience was relatively linear in terms of constant speed and acceleration. Since no differences in time perception was achieved, their impact on speed perception can not be rejected. The study should be replicated with another pre-tested stressor. speed velocity time temporal music tempo tempi arousal perception psychophysics speedperception timeperception traffic transport safety trafficsafety road driving drivinglicense drivingeducation car vehicle fart hastighet tid musik tempo arousal perception psykofysik fartperception tidsperception trafik transport trafiksäkerhet körkortsutbildning körkort bil fordon väg trafikplanering vägbeläggning
4	Analysis of Accuracy for Engine and Gearbox Sensors Dogantimur, Erkan, Johnsson, Daniel January 2019 (has links) This thesis provides a standardized method to measure accuracy for engine and gearbox sensors. Accuracy is defined by ISO 5725, which states that trueness and precision need to be known to provide a metric for accuracy. However, obtaining and processing the data required for this is not straight forward. In this thesis, a method is presented that consists of two main parts: data acquisition and data analysis. The data acquisition part shows how to connect all of the equipment used and how to sample and store all the raw data from the sensors. The data analysis part shows how to process that raw data into statistical data, such as trueness, repeatability and reproducibility for the sensors. Once repeatability and reproducibility are known, the total precision can be determined. Accuracy can then be obtained by using information from trueness and precision. Besides, this thesis shows that measurement error can be separated into error caused by the sensors and error caused by the measurand. This is useful information, because it can be used to assess which type of error is the greatest, whether or not it can be compensated for, and if it is economically viable to compensate for such error. The results are then shown, where it is possible to gain information about the sensors’ performance from various graphs. Between Hall and inductive sensors, there were no superior winner, since they both have their strengths and weaknesses. The thesis ends by making recommendations on how to compensate for some of the errors, and how to improve upon the method to make it more automatic in the future. statistical analysis engine gearbox sensor sensors rotation rotational speed differential pressure performance characteristics trueness precision accuracy Hall inductive induction gauge pressure reference hysteresis bias noise linearity non-linearity DEWESoft DAQ wheel tooth teeth absolute rotary encoder matlab XOR Gray binary LabView sampling measurement measuring statistisk analys motor växellåda sensor sensorer rotation rotationell hastighet fart differentiell tryck prestanda karaktäristik trueness precision accuracy noggrannhet onoggrannhet Hall induktiv induktion tryckskillnad referens hysteres bias avstånd brus linjäritet linearitet olinear olinjär olinearitet olinjäritet DEWESoft DAQ sampling mätning hjul tand tänder absolut rotationsgivare givare matlab XOR Gray binär LabView Elektroteknik och elektronik
5	Dynamic Speed Adaptation for Curves using Machine Learning / Dynamisk hastighetsanpassning för kurvor med maskininlärning Narmack, Kirilll January 2018 (has links) The vehicles of tomorrow will be more sophisticated, intelligent and safe than the vehicles of today. The future is leaning towards fully autonomous vehicles. This degree project provides a data driven solution for a speed adaptation system that can be used to compute a vehicle speed for curves, suitable for the underlying driving style of the driver, road properties and weather conditions. A speed adaptation system for curves aims to compute a vehicle speed suitable for curves that can be used in Advanced Driver Assistance Systems (ADAS) or in Autonomous Driving (AD) applications. This degree project was carried out at Volvo Car Corporation. Literature in the field of speed adaptation systems and factors affecting the vehicle speed in curves was reviewed. Naturalistic driving data was both collected by driving and extracted from Volvo's data base and further processed. A novel speed adaptation system for curves was invented, implemented and evaluated. This speed adaptation system is able to compute a vehicle speed suitable for the underlying driving style of the driver, road properties and weather conditions. Two different artificial neural networks and two mathematical models were used to compute the desired vehicle speed in curves. These methods were compared and evaluated. / Morgondagens fordon kommer att vara mer sofistikerade, intelligenta och säkra än dagens fordon. Framtiden lutar mot fullständigt autonoma fordon. Detta examensarbete tillhandahåller en datadriven lösning för ett hastighetsanpassningssystem som kan beräkna ett fordons hastighet i kurvor som är lämpligt för förarens körstil, vägens egenskaper och rådande väder. Ett hastighetsanpassningssystem för kurvor har som mål att beräkna en fordonshastighet för kurvor som kan användas i Advanced Driver Assistance Systems (ADAS) eller Autonomous Driving (AD) applikationer. Detta examensarbete utfördes på Volvo Car Corporation. Litteratur kring hastighetsanpassningssystem samt faktorer som påverkar ett fordons hastighet i kurvor studerades. Naturalistisk bilkörningsdata samlades genom att köra bil samt extraherades från Volvos databas och bearbetades. Ett nytt hastighetsanpassningssystem uppfanns, implementerades samt utvärderades. Hastighetsanpassningssystemet visade sig vara kapabelt till att beräkna en lämplig fordonshastighet för förarens körstil under rådande väderförhållanden och vägens egenskaper. Två olika artificiella neuronnätverk samt två matematiska modeller användes för att beräkna fordonets hastighet. Dessa metoder jämfördes och utvärderades. Machine Learning Artificial Intelligence MachineLearning Machine-Learning AI ML MLP Neural Networks Multilayer-Perceptron RFB RBF-Network Vehicle Automation AutonomousVehicles Autonomous SelfDriving Self-Driving Self Driving Curve Speed Adaptation Adaption CSA ACC Adaptive Cruise Control Driving Style Driver Behavior Behaviour Sample Samples Distance Derivative Speed Velocity Curvature Road Inclination Lane Width Type Acceleration Longitudinal Lateral Data Training Test Validation Results Discussion Sustainability Ethics Ethical Sustainable Future Today Tomorrow Yesterday Robot Robotics System Systems Class Classes Bin Bins Tree One A Dynamic Using Time Delay Volvo Car Cars Corporation Zenuity School Computer Science Master Degree Project Thesis Paper Object GPS Map Length Research Advanced Машинное Обучение Искусственный Интеллект AI ML MLP RBF Автомобиль Машына Сеть Робот Водитель Заворот Дорога Сам Сама Едет Ехать Учить Учит Учится Автоматизация Адаптация Результат Один Одна Одно Вчера Сегодня Завтра Дерево Карта ГПС Информатика Компьютер Наука Научная Работа Школа Вольво Завод Транспорт Maskininlärning Artificiell Intelligens Inlärning Maskin AI ML MLP RBF Neural Neurala Nätverk Artificiella Automation Själv Självkörande Körande Bil Fordon Robot Robotik Körstil Stil Beteende Adaption Kurva Lutning Väg CSA ACC Farthållare Hastighet Fart Hållare Inclination Körfält Fält Spår Bredd Typ Acceleration Longitudinell Lateral Data Traingin Test Validation Resultat Diskussion Längd Hållbarhet Etik Etiskt Framtid Dåtid Idag Imorgon System Class Klass Classer Klasser Träd En Ett Fler Flera Dynamisk Använda Tid Fördröjning Tids Volvo Car Corporation Object Zenuity Skola Dator Vetenskap Forkning Avancerad Projekt Exjobb Examensarbete Betyg GPS Karta Computer Sciences Datavetenskap (datalogi)

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