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  • 351.
    Yella, Siril
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyberg, Roger G.
    Dalarna University, School of Technology and Business Studies, Information Systems.
    Assessing the quality and reliability of visual estimates in determining plant cover on railway embankments2016In: Web Information Systems Engineering – WISE 2016: 17th International Conference, Shanghai, China, November 8-10, 2016, Proceedings, Part II / [ed] Wojciech Cellary, Mohamed F. Mokbel, Jianmin Wang, Hua Wang, Rui Zhou, Yanchun Zhang, 2016, Vol. 10042, p. 404-410Conference paper (Refereed)
    Abstract [en]

    This study has investigated the quality and reliability of manual assessments on railway embankments within the domain of railway maintenance. Manually inspecting vegetation on railway embankments is slow and time consuming. Maintenance personnel also require extensive knowledge of the plant species, ecology and bio-diversity to be able to recommend appropriate maintenance action. The overall objective of the study is to investigate the reliable nature of manual inspection routines in favour an automatic approach. Visual estimates of plant cover reported by domain experts’ have been studied on two separate railway sections in Sweden. The first study investigated visual estimates using aerial foliar cover (AFC) and sub-plot frequency (SF) methods to assess the plant cover on a railway section in Oxberg, Alvdalsbanan, Sweden. The second study investigated visual estimates using aerial canopy cover method on a railway section outside Vetlanda, Sweden. Visual estimates of the domain experts were recorded and analysis-of-variance (ANOVA) tests on the mean estimates were investigated to see whether if there were disagreements between the raters’. ICC(2, 1) was used to study the differences between the estimates. Results achieved in this work indicate statistically significant differences in the mean estimates of cover (p < 0.05) reported by the domain experts on both the occasions.

  • 352.
    Yella, Siril
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyberg, Roger G
    Dalarna University, School of Technology and Business Studies, Information Systems.
    Gupta, Narendra K.
    Edinburgh Napier University.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Reliability of manual assessments in determining the types of vegetation on railway tracks2015In: Web Information Systems Engineering – WISE 2015: 16th International Conference, Miami, FL, USA, November 1-3, 2015, Proceedings, Part II / [ed] Wang, J., Cellary, W., Wang, D., Wang, H., Chen, S.-C., Li, T., Zhang, Y., Springer, 2015, Vol. 9149, p. 391-399Conference paper (Refereed)
    Abstract [en]

    Current day vegetation assessments within railway maintenance are (to a large extent) carried out manually. This study has investigated the reliability of such manual assessments by taking three non-domain experts into account. Thirty-five track images under different conditions were acquired for the purpose. For each image, the raters’ were asked to estimate the cover of woody plants, herbs and grass separately (in %) using methods such as aerial canopy cover, aerial foliar cover and sub-plot frequency. Visual estimates of raters’ were recorded and analysis-of-variance tests on the mean cover estimates were investigated to see whether if there were disagreements between the raters’.  In tra-correl ation coefficient was used to study the differences between the estimates. Results achieved in this work revealed that seven out of the nine analysis-of-variance tests conducted in this study have demonstrated significant difference in the mean estimates of cover (p < 0.05).

  • 353.
    Yella, Siril
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyberg, Roger G.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Payvar, Barsam
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Gupta, Narendra
    Edinburgh Napier University.
    Machine vision approach for automating vegetation detection on railway tracks2013In: Journal of Intelligent Systems, ISSN 2191-026X, Vol. 22, no 2, p. 179-196Article in journal (Refereed)
    Abstract [en]

    The presence of vegetation on railway tracks (amongst other issues) threatens track safety and longevity. However, vegetation inspections in Sweden (and elsewhere in the world) are currently being carried out manually. Manually inspecting vegetation is very slow and time consuming. Maintaining an even quality standard is also very difficult. A machine vision-based approach is therefore proposed to emulate the visual abilities of the human inspector. Work aimed at detecting vegetation on railway tracks has been split into two main phases. The first phase is aimed at detecting vegetation on the tracks using appropriate image analysis techniques. The second phase is aimed at detecting the rails in the image to determine the cover of vegetation that is present between the rails as opposed to vegetation present outside the rails. Results achieved in the current work indicate that the machine vision approach has performed reasonably well in detecting the presence/absence of vegetation on railway tracks when compared with a human operator.

  • 354.
    Yella, Siril
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Pasha, Sajjad M.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Gupta, Narendra K.
    Classifier fusion for condition monitoring of wooden railway sleepers2008In: Engineer IT, ISSN 1991-5047, p. 31-35Article in journal (Other academic)
  • 355.
    Yella, Siril
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Shaik, Asif ur Rahman
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Pattern recognition for classifying the condition of wooden railway sleepers2010In: Multimedia Computing and Information Technology (MCIT), 2010 International Conference on Multimedia Computing and Information Technology, Sharjah, 2010, p. 61-64Conference paper (Refereed)
    Abstract [en]

    This paper summarises the results of using a pattern recognition approach for classifying the condition of wooden railway sleepers. Railway sleeper inspections are currently done manually; visual inspection being the most common approach, with some deeper examination using an axe to judge the condition. Digital images of the sleepers were acquired to compensate for the human visual capabilities. Appropriate image analysis techniques were applied to further process the images and necessary features such as number of cracks, crack length etc have been extracted. Finally a pattern recognition and classification approach has been adopted to further classify the condition of the sleeper into classes (good or bad). A Support Vector Machine (SVM) using a Gaussian kernel has achieved good classification rate (86%) in the current case.

  • 356.
    Zakrisson, Emma
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    En granskning av personuppgifters flöde genom Falu kommuns gymnasiala Vuxenutbildning i enlighet med General Data Protection Regulation, GDPR2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    On May 25, 2018, the EU's new data protection regulation will come into force throughout the EU. The English name of this regulation is the Data Protection Regulation which is shortened GDPR. The purpose of the new data protection regulation is to ensure people's right to protection of their personal data, which will strengthen personal integrity in an increasingly digitized world. This will be done by establishing rules for the free flow of personal data within the EU. The Data Protection Regulation will place high demands on organizations that have to undergo major change efforts to comply with the regulatory requirements.

    One of the aims of this study has been to investigate whether the operation of the adult education within the municipality of Falun is sustainable in view of the requirements of the new data protection regulation. With this as a starting point, a review of the handling of personal data has been identified. One of the study's issues has been to identify critical points in the adult education activities where personal data incidents could occur. In the study, mixed techniques have been used to gather the necessary information in relation to the questions. Literature studies have been conducted in the field of data protection regulation and information security in general. In addition, gathering of empirical data has been done through oral and written interviews with selected key persons in the organization. Based on this information, a mapping and analysis has been made, which has resulted in an evaluation of the organizations processes in which personal data are handled. With that as a starting point, the questions have been as critical points have been identified and recommended working methods have been presented.

    The study's results show that the municipality of Falun has begun adaptation work to meet the requirements of the new data protection regulation. However, the work has started so late that you still have a lot of work left to implement in the organization. The Data Protection Regulation was adopted on April 27, 2016, which means that in practice they have had at least two years to prepare. For Falun municipality to meet the new requirements of the Data Protection Regulation, key factors are the management's commitment and understanding, as well as the implementation of custom education for all staff in the organization. The study also shows that the adaptation to the new data protection regulation is a continuous work, which should be achieved systematically over time.

    In the environmental surveillance of other municipalities, many have begun their work with an adaptation to the new data protection regulation. These are, like the municipality of Falun, far from fully prepared for the data protection regulation to enter into force on May 25, 2018.

  • 357.
    Zhang, Fan
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Fleyeh, Hasan
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    A review on electricity price forecasting using neural network based models2018Report (Other (popular science, discussion, etc.))
  • 358.
    Zhang, Fan
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Fleyeh, Hasan
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Short term electricity price forecasting using CatBoost and bidirectional long short term memory neural network2018Report (Other (popular science, discussion, etc.))
  • 359.
    Zhang, Fan
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Fleyeh, Hasan
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Wang, X.
    Lu, M.
    Construction site accident analysis using text mining and natural language processing techniques2019In: Automation in Construction, ISSN 0926-5805, E-ISSN 1872-7891, Vol. 99, p. 238-248Article in journal (Refereed)
    Abstract [en]

    Workplace safety is a major concern in many countries. Among various industries, construction sector is identified as the most hazardous work place. Construction accidents not only cause human sufferings but also result in huge financial loss. To prevent reoccurrence of similar accidents in the future and make scientific risk control plans, analysis of accidents is essential. In construction industry, fatality and catastrophe investigation summary reports are available for the past accidents. In this study, text mining and natural language process (NLP) techniques are applied to analyze the construction accident reports. To be more specific, five baseline models, support vector machine (SVM), linear regression (LR), K-nearest neighbor (KNN), decision tree (DT), Naive Bayes (NB) and an ensemble model are proposed to classify the causes of the accidents. Besides, Sequential Quadratic Programming (SQP) algorithm is utilized to optimize weight of each classifier involved in the ensemble model. Experiment results show that the optimized ensemble model outperforms rest models considered in this study in terms of average weighted F1 score. The result also shows that the proposed approach is more robust to cases of low support. Moreover, an unsupervised chunking approach is proposed to extract common objects which cause the accidents based on grammar rules identified in the reports. As harmful objects are one of the major factors leading to construction accidents, identifying such objects is extremely helpful to mitigate potential risks. Certain limitations of the proposed methods are discussed and suggestions and future improvements are provided.

  • 360.
    Zhao, Ping
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    A Contour-based Separation of Vertically Attached Traffic Signs2007Independent thesis Advanced level (degree of Master (Two Years))Student thesis
    Abstract [en]

    This report presents an algorithm for locating the cut points for and separating vertically attached traffic signs in Sweden. This algorithm provides several advanced digital image processing features: binary image which represents visual object and its complex rectangle background with number one and zero respectively, improved cross correlation which shows the similarity of 2D objects and filters traffic sign candidates, simplified shape decomposition which smoothes contour of visual object iteratively in order to reduce white noises, flipping point detection which locates black noises candidates, chasm filling algorithm which eliminates black noises, determines the final cut points and separates originally attached traffic signs into individual ones. At each step, the mediate results as well as the efficiency in practice would be presented to show the advantages and disadvantages of the developed algorithm. This report concentrates on contour-based recognition of Swedish traffic signs. The general shapes cover upward triangle, downward triangle, circle, rectangle and octagon. At last, a demonstration program would be presented to show how the algorithm works in real-time environment.

  • 361.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography.
    Does road network density matter in optimally locating facilities?2015Report (Other (popular science, discussion, etc.))
    Abstract [en]

    Optimal location on the transport infrastructure is the preferable requirement for many decision making processes. Most studies have focused on evaluating performances of optimally locate p facilities by minimizing their distances to a geographically distributed demand (n) when p and n vary. The optimal locations are also sensitive to geographical context such as road network, especially when they are asymmetrically distributed in the plane. The influence of alternating road network density is however not a very well-studied problem especially when it is applied in a real world context. This paper aims to investigate how the density level of the road network affects finding optimal location by solving the specific case of p-median location problem. A denser network is found needed when a higher number of facilities are to locate. The best solution will not always be obtained in the most detailed network but in a middle density level. The solutions do not further improve or improve insignificantly as the density exceeds 12,000 nodes, some solutions even deteriorate. The hierarchy of the different densities of network can be used according to location and transportation purposes and increase the efficiency of heuristic methods. The method in this study can be applied to other location-allocation problem in transportation analysis where the road network density can be differentiated. 

  • 362.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography.
    How does the complexity of a road network affect optimal facility locations?2015Report (Other academic)
    Abstract [en]

    The road network is a necessary component in transportation. It facilitiesspatial movements of people and goods, and it also influences the optimal locations of facilities that usually serve as destinations of the movements. To fulfill the transportation needs and to adapt to the facility development, the road network is often organized hierarchically and asymmetrically with various road levels and spatial structures. The complexity of the road network increases along with the increase of road levels and spatial structures. However, location models locate facilities on a given road network, usually the most complex one, and the influence from the complexity of road network in finding optimal locations is not well-studied. This paper aims to investigate how the complexity of a road network affects the optimal facility locations by applying the widely-applied p-median model. The main result indicates that an increase in road network complexity, up to a certain level, can obviously improve the solution, and the complexity beyond that level does not always lead to better solutions. Furthermore, the result is not sensitive to the choice of algorithms. In a specific case study, a detailed sensitivity analysis of algorithm and facility number further provides insight into computation complexity and location problems from intra-urban to inter-urban.

  • 363.
    Zhong, Shengtong
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    The remote control of mobile robot on the Internet2007Independent thesis Advanced level (degree of Master (Two Years))Student thesis
    Abstract [en]

    During last decades, the Internet teleobotics has been growing at an enormous rate due to the rapid improvement of Internet technology. This paper presents the internet-based remote control of mobile robot. To face unpredictable Internet delays and possible connection rupture, a direct continuous control based teleoperation architecture with “Speed Limit Module” (SLM) and “Delay Approximator” (DA) is proposed. This direct continuous control architecture guarantees the path error of the robot motion is restricted within the path error tolerance of the application. Experiment results show the feasibility and effectiveness of this direct Internet control architecture in the real Internet environment.

5678 351 - 363 of 363
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