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Zhang, F., Fleyeh, H., Wang, X. & Lu, M. (2019). Construction site accident analysis using text mining and natural language processing techniques. Automation in Construction, 99, 238-248
Open this publication in new window or tab >>Construction site accident analysis using text mining and natural language processing techniques
2019 (English)In: Automation in Construction, ISSN 0926-5805, E-ISSN 1872-7891, Vol. 99, p. 238-248Article in journal (Refereed) Published
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.

Keywords
Construction site accident analysis, Machine learning, Natural language processing, Optimization, Sequential quadratic programming, Text mining
National Category
Computer and Information Sciences
Research subject
Energy, Forests and Built Environments
Identifiers
urn:nbn:se:du-29254 (URN)10.1016/j.autcon.2018.12.016 (DOI)2-s2.0-85058940383 (Scopus ID)
Available from: 2019-01-07 Created: 2019-01-07 Last updated: 2019-01-07Bibliographically approved
Aghanavesi, S., Fleyeh, H., Memedi, M. & Dougherty, M. (2019). Feasibility of using smartphones for quantification of Parkinson’s disease motor states during hand rotation tests. In: : . Paper presented at 41st International Engineering in Medicine and Biology Conference, Berlin, Germany, July 23–27, 2019.
Open this publication in new window or tab >>Feasibility of using smartphones for quantification of Parkinson’s disease motor states during hand rotation tests
2019 (English)Conference paper, Published paper (Refereed)
National Category
Medical Engineering
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-29543 (URN)
Conference
41st International Engineering in Medicine and Biology Conference, Berlin, Germany, July 23–27, 2019
Available from: 2019-02-21 Created: 2019-02-21 Last updated: 2019-02-27Bibliographically approved
Zhang, F. & Fleyeh, H. (2018). A review on electricity price forecasting using neural network based models.
Open this publication in new window or tab >>A review on electricity price forecasting using neural network based models
2018 (English)Report (Other (popular science, discussion, etc.))
Publisher
p. 100
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-28694 (URN)
Available from: 2018-10-12 Created: 2018-10-12 Last updated: 2018-12-17Bibliographically approved
Zhang, F. & Fleyeh, H. (2018). Short term electricity price forecasting using CatBoost and bidirectional long short term memory neural network.
Open this publication in new window or tab >>Short term electricity price forecasting using CatBoost and bidirectional long short term memory neural network
2018 (English)Report (Other (popular science, discussion, etc.))
Publisher
p. 37
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-28693 (URN)
Available from: 2018-10-12 Created: 2018-10-12 Last updated: 2018-12-17Bibliographically approved
Paidi, V., Fleyeh, H., Håkansson, J. & Nyberg, R. G. (2018). Smart parking sensors, technologies and applications for open parking lots: a review. IET Intelligent Transport Systems, 12(8), 735-741
Open this publication in new window or tab >>Smart parking sensors, technologies and applications for open parking lots: a review
2018 (English)In: IET Intelligent Transport Systems, ISSN 1751-956X, E-ISSN 1751-9578, Vol. 12, no 8, p. 735-741Article in journal (Refereed) Published
Abstract [en]

Parking a vehicle in traffic dense environments often leads to excess time of driving in search for free space which leads to congestions and environmental pollution. Lack of guidance information to vacant parking spaces is one reason for inefficient parking behaviour. Smart parking sensors and technologies facilitate guidance of drivers to free parking spaces thereby improving parking efficiency. Currently, no such sensors or technologies is in use for open parking lot. This paper reviews the literature on the usage of smart parking sensors, technologies, applications and evaluate their applicability to open parking lots. Magnetometers, ultrasonic sensors and machine vision were few of the widely used sensors and technologies on closed parking lots. However, this paper suggests a combination of machine vision, convolutional neural network or multi-agent systems suitable for open parking lots due to less expenditure and resistance to varied environmental conditions. Few smart parking applications show drivers the location of common open parking lots. No application provided real time parking occupancy information, which is a necessity to guide them along the shortest route to free space. To develop smart parking applications for open parking lots, further research is needed in the fields of deep learning and multi-agent systems.

Place, publisher, year, edition, pages
Institution of Engineering and Technology, 2018
National Category
Computer Systems
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-27619 (URN)10.1049/iet-its.2017.0406 (DOI)000444389300001 ()2-s2.0-85053198237 (Scopus ID)
Available from: 2018-05-04 Created: 2018-05-04 Last updated: 2018-12-17Bibliographically approved
Paidi, V., Fleyeh, H., Håkansson, J. & Nyberg, R. G. (2018). Smart Parking Tools Suitability for Open Parking Lots: A Review. In: Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems: . Paper presented at 4th International Conference on Vehicle Technology and Intelligent Transport Systems, March 16-18 2018, Funchal, Madeira (pp. 600-609). Madeira
Open this publication in new window or tab >>Smart Parking Tools Suitability for Open Parking Lots: A Review
2018 (English)In: Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems, Madeira, 2018, p. 600-609Conference paper, Published paper (Refereed)
Abstract [en]

Parking a vehicle in traffic dense environments is a common issue in many parts of the world which oftenleads to congestion and environmental pollution. Lack of guidance information to vacant parking spaces isone of the reasons for inefficient parking behaviour. Smart parking sensors and technologies facilitateguidance of drivers to free parking spaces thereby improving parking efficiency. Currently, no such sensorsor technologies are in use for the common open parking lot. This paper reviews the literature on the usage ofsmart parking sensors, technologies, applications and evaluate their suitability to open parking lots. Suitabilitywas made in terms of expenditure and reliability. Magnetometers, ultrasonic sensors and machine vision werefew of the widely used sensors and technologies used in closed parking lots. However, this paper suggests acombination of machine vision, fuzzy logic or multi-agent systems suitable for open parking lots due to lessexpenditure and resistance to varied environmental conditions. No application provided real time parkingoccupancy information of open parking lots, which is a necessity to guide them along the shortest route tofree space. To develop smart parking applications for open parking lots, further research is needed in the fieldsof deep learning.

Place, publisher, year, edition, pages
Madeira: , 2018
Keywords
Decision support system, sensors, technologies, applications
National Category
Computer Systems
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-27616 (URN)10.5220/0006812006000609 (DOI)2-s2.0-85051933085 (Scopus ID)978-989-758-293-6 (ISBN)
Conference
4th International Conference on Vehicle Technology and Intelligent Transport Systems, March 16-18 2018, Funchal, Madeira
Available from: 2018-05-04 Created: 2018-05-04 Last updated: 2018-12-17Bibliographically approved
Li, Y. & Fleyeh, H. (2018). Twitter Sentiment Analysis of New IKEA Stores Using Machine Learning. In: 2018 International Conference on Computer and Applications, ICCA 2018: . Paper presented at International Conference on Computer and Applications, July 25th-26th, 2018, Beirut, Lebanon (pp. 4-11). , Article ID 8460277.
Open this publication in new window or tab >>Twitter Sentiment Analysis of New IKEA Stores Using Machine Learning
2018 (English)In: 2018 International Conference on Computer and Applications, ICCA 2018, 2018, p. 4-11, article id 8460277Conference paper, Published paper (Refereed)
Abstract [en]

This paper studied public emotion and opinion concerning the opening of new IKEA stores, specifically, how much attention are attracted, how much positive and negative emotion are aroused, what IKEA-related topics are talked due to this event. Emotion is difficult to measure in retail due to data availability and limited quantitative tools. Twitter texts, written by the public to express their opinion concerning this event, are used as a suitable data source to implement sentiment analysis. Around IKEA opening days, local people post IKEA related tweets to express their emotion and opinions on that. Such “IKEA” contained tweets are collected for opinion mining in this work. To compute sentiment polarity of tweets, lexiconbased approach is used for English tweets, and machine learning methods for Swedish tweets. The conclusion is new IKEA store are paid much attention indicated by significant increasing tweets frequency, most of them are positive emotions, and four studied cities have different topics and interests related IKEA. This paper extends knowledge of consumption emotion studies of prepurchase, provide empirical analysis of IKEA entry effect on emotion. Moreover, it develops a Swedish sentiment prediction model, elastic net method, to compute Swedish tweets’ sentiment polarity which has been rarely conducted.  

Keywords
big-box effect, opinion analysis, customer emotion, elastic net model, text mining, natural language processing
National Category
Computer Sciences
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-27646 (URN)10.1109/COMAPP.2018.8460277 (DOI)000450258100002 ()2-s2.0-85054497923 (Scopus ID)9781538643716 (ISBN)
Conference
International Conference on Computer and Applications, July 25th-26th, 2018, Beirut, Lebanon
Available from: 2018-05-08 Created: 2018-05-08 Last updated: 2018-11-29Bibliographically approved
Jayaram, M. & Fleyeh, H. (2018). Whither Edge Computing? – A Futuristic Review. International Journal of Applied Research on Information Technology and Computing, 9(2), 180-188
Open this publication in new window or tab >>Whither Edge Computing? – A Futuristic Review
2018 (English)In: International Journal of Applied Research on Information Technology and Computing, ISSN 0975-8070, Vol. 9, no 2, p. 180-188Article in journal (Refereed) Published
Abstract [en]

It is a well-known fact that the current day Internet is increasingly becoming laden with content that is bandwidth demanding due to ever-increasing number of things getting attached on a day-in and day-out basis. Hand-in-hand, mobile networks and data networks are converging into cloud computing bandwagon. Edge computing as a promising feature has already made inroads to face future requirements and to address exponential demands from cloud. This feature is all about inserting computing power and storage in the vicinity of the network edge. It is asserted that this scheme of operation brings down the data transport time, quick response times and increased availability. Edge computing brings bandwidthintensive content and latency-sensitive applications closer to the user or data source. In this paper, we explain the drivers of edge computing and have delved on various types of edge computing currently available and going to throng in near future. This paper is intended to draw a comprehensive picture of what is happening in edge currently and what would happen in the near foreseeable future.

Place, publisher, year, edition, pages
India: , 2018
Keywords
Edge computing, Edge analytics, Cloud, Fog, Mobile edge, IoT, Smart city
National Category
Computer Systems
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-28821 (URN)10.5958/0975-8089.2018.00019.2 (DOI)
Available from: 2018-10-23 Created: 2018-10-23 Last updated: 2018-10-24Bibliographically approved
Fleyeh, H. (2017). Traffic Sign detection and recognition (1ed.). In: Computer Vision and Imaging in Intelligent Transportation Systems: (pp. 343-374). John Wiley & Sons
Open this publication in new window or tab >>Traffic Sign detection and recognition
2017 (English)In: Computer Vision and Imaging in Intelligent Transportation Systems, John Wiley & Sons, 2017, 1, p. 343-374Chapter in book (Refereed)
Abstract [en]

This chapter presents an overview of traffic sign detection and recognition. It describes the characteristics of traffic signs and the requirements and difficulties when dealing with traffic sign detection and recognition in outdoor images. The chapter also covers the different techniques invoked to segment traffic signs from the different traffic scenes and the techniques employed for the recognition and classification of traffic signs. It points many problems regarding the stability of the received colour information, variations of these colours with respect to the daylight conditions, and absence of a colour model that can led to a good solution. It also proposes an adaptive colour segmentation model based on Neural Networks. The chapter demonstrates the way to classify segmented traffic signs by employing one of widely used classifiers, AdaBoost , based on a set of features, in this case HOG descriptors, which was developed for pedestrian recognition but found the way for many applications in different fields. The chapter ends by showing examples where traffic sign recognition is applicable in vehicle industry

Place, publisher, year, edition, pages
John Wiley & Sons, 2017 Edition: 1
Keywords
Traffic sign, recognition, classification, color segmentation, SOM, HOG
National Category
Computer Systems
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-25069 (URN)9781118971604 (ISBN)
Available from: 2017-05-30 Created: 2017-05-30 Last updated: 2017-05-30Bibliographically approved
Jayaram, M. & Fleyeh, H. (2016). Convex Hulls in Image Processing: A Scoping Review. American Journal of Intelligent Systems, 6(2), 48-58
Open this publication in new window or tab >>Convex Hulls in Image Processing: A Scoping Review
2016 (English)In: American Journal of Intelligent Systems, ISSN 2165-8978, E-ISSN 2165-8994, Vol. 6, no 2, p. 48-58Article in journal (Refereed) Published
Abstract [en]

The demands of image processing related systems are robustness, high recognition rates, capability to handle incomplete digital information, and magnanimous flexibility in capturing shape of an object in an image. It is exactly here that, the role of convex hulls comes to play. The objective of this paper is twofold. First, we summarize the state of the art in computational convex hull development for researchers interested in using convex hull image processing to build their intuition, or generate nontrivial models. Secondly, we present several applications involving convex hulls in image processing related tasks. By this, we have striven to show researchers the rich and varied set of applications they can contribute to. This paper also makes a humble effort to enthuse prospective researchers in this area. We hope that the resulting awareness will result in new advances for specific image recognition applications.

Keywords
Convex hull, Image processing, Image Classification, Image retrieval, Shape detection
National Category
Computer Systems
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-21491 (URN)
Available from: 2016-05-26 Created: 2016-05-26 Last updated: 2017-11-30Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-1429-2345

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