Real time video segmentation for recognising paint marks on bad wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are based on visual analysis. Machine vision based approach has been done to emulate the visual abilities of human operator to enable automation of the process. Through this process bad sleepers are identified, and a spot is marked on it with specific color (blue in the current case) on the rail so that the maintenance operators are able to identify the spot and replace the sleeper. The motive of this thesis is to help the operators to identify those sleepers which are marked by color (spots), using an “Intelligent Vehicle” which is capable of running on the track. Capturing video while running on the track and segmenting the object of interest (spot) through this vehicle; we can automate this work and minimize the human intuitions. The video acquisition process depends on camera position and source light to obtain fine brightness in acquisition, we have tested 4 different types of combinations (camera position and source light) here to record the video and test the validity of proposed method. A sequence of real time rail frames are extracted from these videos and further processing (depending upon the data acquisition process) is done to identify the spots. After identification of spot each frame is divided in to 9 regions to know the particular region where the spot lies to avoid overlapping with noise, and so on. The proposed method will generate the information regarding in which region the spot lies, based on nine regions in each frame. From the generated results we have made some classification regarding data collection techniques, efficiency, time and speed. In this report, extensive experiments using image sequences from particular camera are reported and the experiments were done using intelligent vehicle as well as test vehicle and the results shows that we have achieved 95% success in identifying the spots when we use video as it is, in other method were we can skip some frames in pre-processing to increase the speed of video but the segmentation results we reduced to 85% and the time was very less compared to previous one. This shows the validity of proposed method in identification of spots lying on wooden railway sleepers where we can compromise between time and efficiency to get the desired result.

Machine vision for the automatic classification of images acquired from Non-destructive tests

This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required.Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.

Gruvrätten vid Stora Kopparberget 1641-1682 : en undersökning över rannsakade brott och utdömda straff

The purpose of this essay is to examine and explain how the Swedish mining court of Stora Kopparberget (the Great Copper Mountain) implemented its judicial legislation between 1641-1682. Questions are asked about which counts of indictments the court tried, which sentences they handed out, in what quantities and how these results looks in comparison with other contemporary courts. The index cards of the court judicial protocols are the primary source of information. The methods are those of quantity- and comparative analysis.The results show that theft of copper ore was the most common crime ransacked by the court. Other common crimes were (in order): sin of omission, transgression of work directions, fights, slander and disdain, trade of stolen ore, failing appearance in court etc.Fines were by far the most common sentence followed by shorter imprisonments, gauntlets, loss of right to mine possession, twig beating, loss of work, penal servitude, banishment, “wooden horse riding” and finally military transcription. Even though previous re-search, in the field of Swedish specialized courts, is almost non existent evidence confirms great similarities between the Stora Kopparberget mining court and Sala mining court. This essay will, hopefully, enrich our knowledge of specialized courts, of 17th century mining industry and society and let us reach a broader understanding of the working conditions of the mountain.

Nonstationary feature extraction techniques for automatic classification of impact acoustic signals

Condition monitoring of wooden railway sleepers applications are generallycarried out by visual inspection and if necessary some impact acoustic examination iscarried out intuitively by skilled personnel. In this work, a pattern recognition solutionhas been proposed to automate the process for the achievement of robust results. Thestudy presents a comparison of several pattern recognition techniques together withvarious nonstationary feature extraction techniques for classification of impactacoustic emissions. Pattern classifiers such as multilayer perceptron, learning cectorquantization and gaussian mixture models, are combined with nonstationary featureextraction techniques such as Short Time Fourier Transform, Continuous WaveletTransform, Discrete Wavelet Transform and Wigner-Ville Distribution. Due to thepresence of several different feature extraction and classification technqies, datafusion has been investigated. Data fusion in the current case has mainly beeninvestigated on two levels, feature level and classifier level respectively. Fusion at thefeature level demonstrated best results with an overall accuracy of 82% whencompared to the human operator.

MACHINE VISION FOR AUTOMATICVISUAL INSPECTION OF WOODENRAILWAY SLEEPERS USING UNSUPERVISED NEURAL NETWORKS

The motivation for this thesis work is the need for improving reliability of equipment and quality of service to railway passengers as well as a requirement for cost-effective and efficient condition maintenance management for rail transportation. This thesis work develops a fusion of various machine vision analysis methods to achieve high performance in automation of wooden rail track inspection.The condition monitoring in rail transport is done manually by a human operator where people rely on inference systems and assumptions to develop conclusions. The use of conditional monitoring allows maintenance to be scheduled, or other actions to be taken to avoid the consequences of failure, before the failure occurs. Manual or automated condition monitoring of materials in fields of public transportation like railway, aerial navigation, traffic safety, etc, where safety is of prior importance needs non-destructive testing (NDT).In general, wooden railway sleeper inspection is done manually by a human operator, by moving along the rail sleeper and gathering information by visual and sound analysis for examining the presence of cracks. Human inspectors working on lines visually inspect wooden rails to judge the quality of rail sleeper. In this project work the machine vision system is developed based on the manual visual analysis system, which uses digital cameras and image processing software to perform similar manual inspections. As the manual inspection requires much effort and is expected to be error prone sometimes and also appears difficult to discriminate even for a human operator by the frequent changes in inspected material. The machine vision system developed classifies the condition of material by examining individual pixels of images, processing them and attempting to develop conclusions with the assistance of knowledge bases and features.A pattern recognition approach is developed based on the methodological knowledge from manual procedure. The pattern recognition approach for this thesis work was developed and achieved by a non destructive testing method to identify the flaws in manually done condition monitoring of sleepers.In this method, a test vehicle is designed to capture sleeper images similar to visual inspection by human operator and the raw data for pattern recognition approach is provided from the captured images of the wooden sleepers. The data from the NDT method were further processed and appropriate features were extracted.The collection of data by the NDT method is to achieve high accuracy in reliable classification results. A key idea is to use the non supervised classifier based on the features extracted from the method to discriminate the condition of wooden sleepers in to either good or bad. Self organising map is used as classifier for the wooden sleeper classification.In order to achieve greater integration, the data collected by the machine vision system was made to interface with one another by a strategy called fusion. Data fusion was looked in at two different levels namely sensor-level fusion, feature- level fusion. As the goal was to reduce the accuracy of the human error on the rail sleeper classification as good or bad the results obtained by the feature-level fusion compared to that of the results of actual classification were satisfactory.

DC Motor Speed Control via Fuzzy / Pole Placement / PI Controller

This report presents a new way of control engineering. Dc motor speed controlled by three controllers PID, pole placement and Fuzzy controller and discusses the advantages and disadvantages of each controller for different conditions under loaded and unloaded scenarios using software Matlab. The brushless series wound Dc motor is very popular in industrial application and control systems because of the high torque density, high efficiency and small size. First suitable equations are developed for DC motor. PID controller is developed and tuned in order to get faster step response. The simulation results of PID controller provide very good results and the controller is further tuned in order to decrease its overshoot error which is common in PID controllers. Further it is purposed that in industrial environment these controllers are better than others controllers as PID controllers are easy to tuned and cheap. Pole placement controller is the best example of control engineering. An addition of integrator reduced the noise disturbances in pole placement controller and this makes it a good choice for industrial applications. The fuzzy controller is introduce with a DC chopper to make the DC motor speed control smooth and almost no steady state error is observed. Another advantage is achieved in fuzzy controller that the simulations of three different controllers are compared and concluded from the results that Fuzzy controller outperforms to PID controller in terms of steady state error and smooth step response. While Pole placement controller have no comparison in terms of controls because designer can change the step response according to nature of control systems, so this controller provide wide range of control over a system. Poles location change the step response in a sense that if poles are near to origin then step response of motor is fast. Finally a GUI of these three controllers are developed which allow the user to select any controller and change its parameters according to the situation.

Talangfabriken : Om organisation av kunskap och kreativitet i skivindustrin

The purpose of this dissertation is to describe, explain and understand how record companies identify and develop new music and new talent. The analysis is carried out on three levels: individual, organizational and sector level. In a record company, this task formally goes to A&R (Artist and Repertoire). This dissertation takes its point of departure in how the capacity for discovering new talent can be understood in terms of knowledge, creativity and competence and how this capacity is affected in the meeting between the record company and the industry. The theoretical framework of the dissertation spans two sociological fields: the sociology of organizations and the sociology of knowledge. While it takes its organizational starting point in the Knowledge Company Approach, it employs a practice-based approach to discuss knowledge. I argue that within the Knowledge company approach there are two contrasting ways to understand knowledge; a distinction is made between knowledge- and creativity-intensive enterprises. The results show that the record industry’s polarized structure can be seen as a result of the Knowledge Company’s typical problems. The A&R’s work is described as including two phases, one intuitive and one analytical. The intuitive assessment is direct, unconscious and without reflection. This ability has been described as "intuition" and "gut feeling". The analytical phase adds analysis and reflection based on knowledge. The results from the interviews with A&R’s reveal the limit of formal and explicit knowledge not only in the choice of music but also in the marketing strategies. The overarching picture is one in which record companies move in a space characterized by tension between dichotomous forces – art and commercialism, creativity and knowledge, culture and economy, chaos and order, but where opposite poles are not mutually exclusive but complementary.

Health and quality of care from older peoples' and formal caregivers' perspective

Aim: The overall aim of this thesis was to gain a deeper understanding of older people's view of health and care while dependent on community care. Furthermore to describe and compare formal caregivers' perceptions of quality of care, working conditions, competence, general health, and factors associated with quality of care from the caregivers' perspective. Method: Qualitative interviews were conducted with 19 older people in community care who were asked to describe what health and ill health((I), good and bad care meant for them (II). Data were analyzed using content analysis (I) and a phenomenological analysis (II). The formal caregivers; 70 nursing assistants (NAs) 163 enrolled nurses (ENs) and 198 registered nurses (RNs), answered a questionnaire consisting of five instruments: quality of care from the patient's perspective modified to formal caregivers, creative climate questionnaire, stress of conscience, health index, sense of coherence and items on education and competence (III). Statistical analyses were performed containing descriptive statistics, and comparisons between the occupational groups were made using Kruskal-Wallis ANOVA, Mann-Whitney U-test and Pearson's Chi-square test (III). Pearson's  product moment correlation analysis and multiple regression analysis were performed studying the associations between organizational climate, stress of conscience, competence, general health and sense of coherence with quality of care (IV). Results: The older people's health and well-being were related to their own ability to adapt to and compensate for their disabilities and was described as negative and positive poles of autonomy vs. dependence, togetherness vs. being an onlooker, security vs. insecurity and tranquility vs. disturbance (I).  The meaning of good care (II) was that the formal caregivers respected the older people as unique individuals, having the opportunity to live their lives as usual and receiving a safe and secure care. Good care could be experienced when the formal caregivers had adequate knowledge and competence in caring for older people, adequate time and continuity in the care organization (II). Formal caregivers reported higher perceived quality of care in the dimensions medical-technical competence and physical-technical conditions than in identity-oriented approach and socio-cultural atmosphere (III). In the organizational climate three of the dimensions were close to the value of a creative climate and in seven near a stagnant climate. The formal caregivers reported low rate of stress of conscience. The RNs reported to a higher degree than the NAs/ENs a need to gain more knowledge, but the NAs and the ENs more often received training during working hours. The RNs reported lower emotional well-being than the NAs/ENs (III). The formal caregivers' occupation, organizational climate and stress of conscience were associated with perceived quality of care (IV). Implications: The formal caregivers should have an awareness of the importance of kindness and respect, supporting the older people to retain control over their lives. The nursing managers should employ highly competent and adequate numbers of skilled formal caregivers, organize formal caregivers having round the clock continuity. Improvements of organizational climate and stress of conscience are of importance for good quality of care.

Mellan etnologi och modern sociologi : K. Rob. V. Wikman som medlare i Finland och Sverige

Between ethnology and sociology: K. Rob. V. Wikman as a mediator in Finland and Sweden K. Rob. V. Wikman, professor in sociology at the Åbo Akademi University in Turku, Finland, played a central role both within Finnish and Swedish sociology in the 1940s and 1950s. He was a student of Westermarck and thus his own research represented an ethnosociological tradition, which at that time was challenged by modern, American-influenced sociological ideas. The aim of this article is to discuss the adaptation of “modern sociology” and the drawing of boundaries in Nordic sociology after the Second World War by focusing on Wikman’s work in Finnish as well as Swedish sociology, especially the assessor assignments he was given, and by giving emphasis to some of those that served as border poles or border markers in this process. The comparative starting point gives us reason to discuss some nationally characterized similarities and differences that can be observed in the establishment process of modern sociology in Finland and Sweden.

En böjd stavdesigns påverkan på stakfasens egenskaper

Syfte Studien syftar till att klarlägga hur stavisättningen och stakfasen påverkas vid användandet av en böjd jämfört med en rak stavdesign vid stakning i hög hastighet på rullskidor på rullband. Följande frågeställningar har undersökts:  Leder en böjd stavdesign till att stavisättningen sker längre fram?  Leder en böjd stavdesign till att stakfasens absoluta längd förändras?  Leder en böjd stavdesign till att stakfasens relativa längd förändras? Metod Tio manliga längdskidåkare (ålder 25,3 ± 5,1 år, kroppslängd 182,1 ± 8,6 cm, kroppsvikt 78 ± 6,5 kg) deltog i studien. Forskningspersonerna genomförde ett Vmax-protokoll stakning på rullskidor på rullband, med rak såväl som med böjd stavdesign. Rörelsedata samlades in och analyserades för att fastställa eventuella skillnader i stavisättning, stakfas, återförandefas och total cykeltid. Resultat En signifikant skillnad kan påvisas gällande stavisättning, där en böjd stavdesign leder till en stavisättning längre framför bindningen jämfört med en rak stavdesign. Ingen signifikant skillnad kan påvisas rörande stakfasen, återförandefasen eller total cykeltid. Slutsatser Studiens visar att stavspetsens rörelsebana flyttas vid nyttjande av en böjd stavdesign i riktning framåt. Dock påverkas inte stakfasen, återförandefasen eller total cykeltid, vilket innebär att stakfasens längd, i absoluta såväl som relativa termer, är densamma vid stakning med rak och böjd stavdesign.