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.

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.

Harold Pinter: A Night Out : A Study in the Political ConnotationsAnd the Abuse of Power

Harold Pinter’s A Night Out is a significant but rarely produced piece of drama. Therefore, there is very little criticism to support or contradict my argument. The reason why I chose to do my essay on this particular play is to open doors for academic research and to try and make it an equal to its sister plays. I will raise questions and topics to prove the play is worth the readers’ time and effort and that A Night Out is a sharp piece of political theatre. Although at first glance it is a simple enough story, a straightforward tale of the nasty consequences of motherly love when it is pushed to the limit, on deeper inspection, a more far reaching and complex analysis of the abuse of power can be observed. The play offers a variety of themes, including: interpersonal power struggles, failed attempts at communication, antagonistic relationships, the threat of impending or past violence, the struggle for survival or identity, domination and submission, politics, lies and verbal, physical, psychological and sexual abuse. The prevailing theme in the play is the abuse of power: powerful parties oppressing weaker ones, and the results of the oppressed party looking for a vent in someone even weaker than themselves.

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.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

Att hitta och utforska : Om Damien Echols autobiografi Life After Death

This paper investigates the autobiography of Damien Echols. The autobiographical subject, Echols, depicts his life as a marginalized youth during the nineteen seventies and nineteen eighties in Arkansas, USA. It also explores the years that Echols spent on Death Row after having been arrested along with two other youths for the murder of three eight-year-old boys; a crime all three of the accused denied having committed. In 2011, after eighteen years of incarceration, the three now grown up men were released from prison. The author of this paper discusses biography and especially autobiography as a genre and explores to what extent memories represent the actual life the autobiographical subject, Echols, has lived and if memories are or can be truthful. In order to find the underlying meanings of the autobiography, the author of this paper uses as a starting-point a psychoanalytic approach towards Echol’s text. Key terms that will undergo a more close inspection are horror, water and home. This paper concludes with the notion that autobiographical objective truth does not exist.

Module property verification : A method to plan and perform quality verifications in modular architectures

Modular product architectures have generated numerous benefits for companies in terms of cost, lead-time and quality. The defined interfaces and the module’s properties decrease the effort to develop new product variants, and provide an opportunity to perform parallel tasks in design, manufacturing and assembly. The background of this thesis is that companies perform verifications (tests, inspections and controls) of products late, when most of the parts have been assembled. This extends the lead-time to delivery and ruins benefits from a modular product architecture; specifically when the verifications are extensive and the frequency of detected defects is high. Due to the number of product variants obtained from the modular product architecture, verifications must handle a wide range of equipment, instructions and goal values to ensure that high quality products can be delivered. As a result, the total benefits from a modular product architecture are difficult to achieve. This thesis describes a method for planning and performing verifications within a modular product architecture. The method supports companies by utilizing the defined modules for verifications already at module level, so called MPV (Module Property Verification). With MPV, defects are detected at an earlier point, compared to verification of a complete product, and the number of verifications is decreased. The MPV method is built up of three phases. In Phase A, candidate modules are evaluated on the basis of costs and lead-time of the verifications and the repair of defects. An MPV-index is obtained which quantifies the module and indicates if the module should be verified at product level or by MPV. In Phase B, the interface interaction between the modules is evaluated, as well as the distribution of properties among the modules. The purpose is to evaluate the extent to which supplementary verifications at product level is needed. Phase C supports a selection of the final verification strategy. The cost and lead-time for the supplementary verifications are considered together with the results from Phase A and B. The MPV method is based on a set of qualitative and quantitative measures and tools which provide an overview and support the achievement of cost and time efficient company specific verifications. A practical application in industry shows how the MPV method can be used, and the subsequent benefits

Analysis of response to enteral infusion of levodopa in patients with Parkinson's disease

Objective: We present a new evaluation of levodopa plasma concentrations and clinical effects during duodenal infusion of a levodopa/carbidopa gel (Duodopa ) in 12 patients with advanced Parkinson s disease (PD), from a study reported previously (Nyholm et al, Clin Neuropharmacol 2003; 26(3): 156-163). One objective was to investigate in what state of PD we can see the greatest benefits with infusion compared with corresponding oral treatment (Sinemet CR). Another objective was to identify fluctuating response to levodopa and correlate to variables related to disease progression. Methods: We have computed mean absolute error (MAE) and mean squared error (MSE) for the clinical rating from -3 (severe parkinsonism) to +3 (severe dyskinesia) as measures of the clinical state over the treatment periods of the study. Standard deviation (SD) of the rating was used as a measure of response fluctuations. Linear regression and visual inspection of graphs were used to estimate relationships between these measures and variables related to disease progression such as years on levodopa (YLD) or unified PD rating scale part II (UPDRS II).Results: We found that MAE for infusion had a strong linear correlation to YLD (r2=0.80) while the corresponding relation for oral treatment looked more sigmoid, particularly for the more advanced patients (YLD>18).

Usability of government websites in Uganda

Government websites offer great benefits to citizens and governments. Such benefits, however,cannot be realized if websites are unusable. This study investigates usability of government websites in Uganda.Using the feature investigation method, the study evaluated four Ugandan government websites according tothree perspectives. Results show that websites are partially usable in the design layout and navigationperspectives but are rather weak in stating legal policies. Evaluation results provide the Ugandan governmentwith a clear picture of what needs to be improved according to international website design standards. Moreover,the parsimonious evaluation framework proposed in the research is useful for any country that wants to do aquick and easy evaluation of their government websites.

School leaders as agents of change : a case study on how two head teachers are trying to implement the learning study method in their school

This paper seeks to describe and discuss the impact of inspections of schools in Sweden. It outlines the political context, based on New Public Management (NPM) theory, according to what role the Schools Inspectorate is supposed to play in order to govern and control. Attention is also devoted, referring an on-going case study, to how inspections influence head teachers and their leadership in their everyday work.   Reports from the Schools inspectorate are public. This forces both politicians and head teachers to take measures. In this case, the head teachers perceived that the inspection reports confirmed what they already knew, but it also gave them an alibi and a tool to push their teachers to take part in everyday school development work. During the first year after the inspection the head teachers mainly strived to adjust formal deficiencies in local steering documents. However, some of the deviations reported from the Schools inspectorate are regarding pedagogical problems that are complicated and difficult to handle. As interventions in many cases will show up much later the results are, for example as increased goal fulfilment, in this case, still an open question. Nevertheless, it seems obvious that the Schools Inspectorate must be seen as a result of the governing philosophy that denotes New Public Management NPM).

Do inspections of schools influence head teachers’ leadership?

This paper seeks to describe and discuss the impact of inspections of schools in Sweden. It outlines the political context, based on New Public Management (NPM) theory, according to what role the Schools Inspectorate is supposed to play in order to govern and control. Attention is also devoted, referring an on-going case study, to how inspections influence head teachers and their leadership in their everyday work.   Reports from the Schools inspectorate are public. This forces both politicians and head teachers to take measures. In this case, the head teachers perceived that the inspection reports confirmed what they already knew, but it also gave them an alibi and a tool to push their teachers to take part in everyday school development work. During the first year after the inspection the head teachers mainly strived to adjust formal deficiencies in local steering documents. However, some of the deviations reported from the Schools inspectorate are regarding pedagogical problems that are complicated and difficult to handle. As interventions in many cases will show up much later the results are, for example as increased goal fulfilment, in this case, still an open question. Nevertheless, it seems obvious that the Schools Inspectorate must be seen as a result of the governing philosophy that denotes New Public Management NPM).

Automating condition monitoring of vegetation on railway trackbeds and embankments

Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.

Monitoring vegetation on railway embankments : supporting maintenance decisions

The national railway administrations in Scandinavia, Germany, and Austria mainly resort to manual inspections to control vegetation growth along railway embankments. Manually inspecting railways is slow and time consuming. A more worrying aspect concerns the fact that human observers are often unable to estimate the true cover of vegetation on railway embankments. Further human observers often tend to disagree with each other when more than one observer is engaged for inspection. Lack of proper techniques to identify the true cover of vegetation even result in the excess usage of herbicides; seriously harming the environment and threating the ecology. Hence work in this study has investigated aspects relevant to human variationand agreement to be able to report better inspection routines. This was studied by mainly carrying out two separate yet relevant investigations.First, thirteen observers were separately asked to estimate the vegetation cover in nine imagesacquired (in nadir view) over the railway tracks. All such estimates were compared relatively and an analysis of variance resulted in a significant difference on the observers’ cover estimates (p<0.05). Bearing in difference between the observers, a second follow-up field-study on the railway tracks was initiated and properly investigated. Two railway segments (strata) representingdifferent levels of vegetationwere carefully selected. Five sample plots (each covering an area of one-by-one meter) were randomizedfrom each stratumalong the rails from the aforementioned segments and ten images were acquired in nadir view. Further three observers (with knowledge in the railway maintenance domain) were separately asked to estimate the plant cover by visually examining theplots. Again an analysis of variance resulted in a significant difference on the observers’ cover estimates (p<0.05) confirming the result from the first investigation.The differences in observations are compared against a computer vision algorithm which detects the "true" cover of vegetation in a given image. The true cover is defined as the amount of greenish pixels in each image as detected by the computer vision algorithm. Results achieved through comparison strongly indicate that inconsistency is prevalent among the estimates reported by the observers. Hence, an automated approach reporting the use of computer vision is suggested, thus transferring the manual inspections into objective monitored inspections

Effects of computer reminders on complications of peripheral venous catheters and nurses' adherence to a guideline in paediatric care : a cluster randomised study

BACKGROUND: Reminder systems in electronic patient records (EPR) have proven to affect both health care professionals' behaviour and patient outcomes. The aim of this cluster randomised trial was to investigate the effects of implementing a clinical practice guideline (CPG) for peripheral venous catheters (PVCs) in paediatric care in the format of reminders integrated in the EPRs, on PVC-related complications, and on registered nurses' (RNs') self-reported adherence to the guideline. An additional aim was to study the relationship between contextual factors and the outcomes of the intervention. METHODS: The study involved 12 inpatient units at a paediatric university hospital. The reminders included choice of PVC, hygiene, maintenance, and daily inspection of PVC site. Primary outcome was documented signs and symptoms of PVC-related complications at removal, retrieved from the EPR. Secondary outcome was RNs' adherence to a PVC guideline, collected through a questionnaire that also included RNs' perceived work context, as measured by the Alberta Context Tool. Units were allocated into two strata, based on occurrence of PVCs. A blinded simple draw of lots from each stratum randomised six units to the control and intervention groups, respectively. Units were not blinded. The intervention group included 626 PVCs at baseline and 618 post-intervention and the control group 724 PVCs at baseline and 674 post-intervention. RNs included at baseline were 212 (65.4 %) and 208 (71.5 %) post-intervention. RESULTS: No significant effect was found for the computer reminders on PVC-related complications nor on RNs' adherence to the guideline recommendations. The complication rate at baseline and post-intervention was 40.6 % (95 % confidence interval (CI) 36.7-44.5) and 41.9 % (95 % CI 38.0-45.8), for the intervention group and 40.3 % (95 % CI 36.8-44.0) and 46.9 % (95 % CI 43.1-50.7) for the control. In general, RNs' self-rated work context varied from moderately low to moderately high, indicating that conditions for a successful implementation to occur were less optimal. CONCLUSIONS: The reminders might have benefitted from being accompanied by a tailored intervention that targeted specific barriers, such as the low frequency of recorded reasons for removal, the low adherence to daily inspection of PVC sites, and the lack of regular feedback to the RNs. TRIAL REGISTRATION: Current Controlled Trials ISRCTN44819426.