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  • 1.
    Eriksson, Per Erik
    et al.
    Dalarna University, School of Humanities and Media Studies, Moving Image Production.
    Swenberg, Thorbjörn
    Dalarna University, School of Humanities and Media Studies, Moving Image Production.
    Zhao, Xiaoyun
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Eriksson, Yvonne
    Mälardalens Högskola / IPR.
    How gaze time on screen impacts the efficacy of visual instructions2018In: Heliyon, ISSN 2405-8440, Vol. 4, no 6, article id e00660Article in journal (Refereed)
    Abstract [en]

    This article explores whether GTS (gaze time on screen) can be useful as an engagement measure in the screen mediated learning context. Research that exemplifies ways of measuring engagement in the on-line education context usually does not address engagement metrics and engagement evaluation methods that are unique to the diverse contemporary instructional media landscape. Nevertheless, unambiguous construct definitions of engagement and standardized engagement evaluation methods are needed to leverage instructional media's efficacy. By analyzing the results from a mixed methods eye-tracking study of fifty-seven participants evaluating their visual and assembly performance levels in relation to three visual, procedural instructions that are versions of the same procedural instruction, we found that the mean GTS-values in each group were rather similar. However, the original GTS-values outputted from the ET-computer were not entirely correct and needed to be manually checked and cross validated. Thus, GTS appears not to be a reliable, universally applicable automatic engagement measure in screen-based instructional efforts. Still, we could establish that the overall performance of learners was somewhat negatively impacted by lower than mean GTS-scores, when checking the performance levels of the entire group (N = 57). When checking the stimuli groups individually (N = 17, 20, 20), the structural diagram group's assembly time durations were positively influenced by higher than mean GTS-scores.

  • 2. Wei, Yixuan
    et al.
    Zhang, Xingxing
    Dalarna University, School of Technology and Business Studies, Energy Technology.
    Shi, Yong
    Xia, Liang
    Pan, Song
    Wu, Jinshun
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Zhao, Xiaoyun
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    A review of data-driven approaches for prediction and classification of building energy consumption2018In: Renewable & sustainable energy reviews, ISSN 1364-0321, E-ISSN 1879-0690, Vol. 82, no 1, p. 1027-1047Article in journal (Refereed)
    Abstract [en]

    A recent surge of interest in building energy consumption has generated a tremendous amount of energy data, which boosts the data-driven algorithms for broad application throughout the building industry. This article reviews the prevailing data-driven approaches used in building energy analysis under different archetypes and granularities, including those methods for prediction (artificial neural networks, support vector machines, statistical regression, decision tree and genetic algorithm) and those methods for classification (K-mean clustering, self-organizing map and hierarchy clustering). The review results demonstrate that the data-driven approaches have well addressed a large variety of building energy related applications, such as load forecasting and prediction, energy pattern profiling, regional energy-consumption mapping, benchmarking for building stocks, global retrofit strategies and guideline making etc. Significantly, this review refines a few key tasks for modification of the data-driven approaches in the context of application to building energy analysis. The conclusions drawn in this review could facilitate future micro-scale changes of energy use for a particular building through the appropriate retrofit and the inclusion of renewable energy technologies. It also paves an avenue to explore potential in macro-scale energy-reduction with consideration of customer demands. All these will be useful to establish a better long-term strategy for urban sustainability.

  • 3.
    Zhao, Xiaoyun
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Government vs Market in Sustainable Residential Development?: Microdata analysis of car travel, CO2 emission and residence location2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Increasing car usage and travel demands between residential locations and destinations in order to fulfill the various needs of residents is a primary cause of CO2 emissions. To win the battle against climate change, a better understanding of the question relating to which urban residential form may most effectively mitigate the CO2 emissions is the key pathway.

    This dissertation is concerned with the above problem and it mainly considers three objectives in providing insights on answering the question. The first objective is to comprehensively and microscopically understand intra-urban car travel behavior. The second objective is to estimate the induced CO2 emissions from daily intra-urban car travel and to ex-ante evaluate residential plans. The third objective is to assess whether the governmental sustainable residential development objective is aligned with the objectives of the estate market actors. To explore the research questions related to the objectives, a microdata analysis process (data collection, data assessment and transformation, data storage, data analysis and decision-making) is applied and is found essential in gaining access to key variables in exploring the answer of a preferable urban form. The dissertation offers many new solutions to various technical aspects through a microdata analysis process.

    The primary contribution of this dissertation is that it outlines an operational model that comprehensively integrates the investors’ investment strategy, the residents’ choice behavior, and the governmental sustainability objective in the interest of making an ex-ante assessment of residential plans. This ex-ante assessment provides decision-support in sustainable residential development at foremost local level.

    The first finding from the implementation of the model on the case study is that the market actors’ objectives are, in general, aligned with the government’s sustainable residential development objective. The second finding indicates that re-shaping the urban form into a compact city is preferable in mitigating CO2 emissions, in spite of the fact that the case city is of a polycentric urban form. These findings provide support for those advocating the compact city as the ideal for sustainable residential development, and also provide foresight on settling the answer to the preferred re-shaping of urban forms in climate change.

  • 4.
    Zhao, Xiaoyun
    Dalarna University, School of Technology and Business Studies, Statistics.
    On processing GPS tracking data of car-movements in Borlänge, Sweden2014Report (Other academic)
    Abstract [en]

    The advancement of GPS technology enables GPS devices not only to be used as orientation and navigation tools, but also to track travelled routes. GPS tracking data provides essential information for a broad range of urban planning applications such as transportation routing and planning, traffic management and environmental control. This paper describes on processing the data that was collected by tracking the cars of 316 volunteers over a seven-week period. The detailed information is extracted. The processed data is further connected to the underlying road network by means of maps. Geographical maps are applied to check how the car-movements match the road network. The maps capture the complexity of the car-movements in the urban area. The results show that 90% of the trips on the plane match the road network within a tolerance.

  • 5.
    Zhao, Xiaoyun
    Dalarna University, School of Technology and Business Studies, Statistics.
    On processing GPS tracking data of spatiotemporal car movements: a case study2015Report (Other academic)
    Abstract [en]

    The advancement of GPS technology has made it possible to use GPS devices as orientation and navigation tools, but also as tools to track spatiotemporal information. GPS tracking data can be broadly applied in location-based services, such as spatial distribution of the economy, transportation routing and planning, traffic management and environmental control. Therefore, knowledge of how to process the data from a standard GPS device is crucial for further use. Previous studies have considered various issues of the data processing at the time. This paper, however, aims to outline a general procedure for processing GPS tracking data. The procedure is illustrated step-by-step by the processing of real-world GPS data of car movements in Borlänge in the centre of Sweden.

  • 6.
    Zhao, Xiaoyun
    Dalarna University, School of Technology and Business Studies, Statistics.
    On processing GPS tracking data of spatio-temporal car movements: a case study2015In: Journal of Location Based Services, ISSN 1748-9725, Vol. 9, no 4, p. 235-253Article in journal (Refereed)
    Abstract [en]

    The advancement of GPS technology has made it possible to use GPS devices as orientation and navigation tools, but also as tools to track spatio-temporal information. GPS tracking data can be broadly applied in location-based services, such as spatial distribution of the economy, transportation routing and planning, traffic management and environmental control. Therefore, knowledge of how to process the data from a standard GPS device is crucial for further use. Previous studies have considered various issues of the data processing at the time. This paper, however, aims to outline a general procedure for processing GPS tracking data. The procedure is illustrated step by step by the processing of real-world GPS data of car movements in Borlänge in the centre of Sweden. 

  • 7.
    Zhao, Xiaoyun
    Dalarna University, School of Technology and Business Studies, Statistics.
    Road network and GPS tracking with data processing and quality assessment2015Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application.

    This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost.

    The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.

  • 8.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Dan, Zhiguang
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography.
    Network density and the p-median solution2013Report (Other academic)
    Abstract [en]

    The p-medianmodel is commonly used to find optimal locations of facilities for geographically distributed demands. So far, there are few studies that have considered the importance of the road network in the model. However, Han, Håkansson, and Rebreyend (2013) examined the solutions of the p-median model with densities of the road network varying from 500 to 70,000 nodes. They found as the density went beyond some 10,000 nodes, solutions have no further improvements but gradually worsen. The aim of this study is to check their findings by using an alternative heuristic being vertex substitution, as a complement to their using simulated annealing. We reject the findings in Han et al (2013). The solutions do not further improve as the nodes exceed 10,000, but neither do the solutions deteriorate.

  • 9.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    An evaluation of the reliability of GPS-based transportation data2017In: Proceedings of IAC in Vienna 2017, 2017, p. 323-334, article id IAC201711035Conference paper (Refereed)
    Abstract [en]

    GPS-based data are becoming a cornerstone for real-time transportation applications. Tracking data of vehicles from GPS receivers are however susceptible to measurement errors. The assessment of the reliability of data from GPS receiver is a neglected issue, especially in a real road network setting and in the phase after data transfer but before information identification. An evaluation method is outlined and carried out by conducting a randomized experiment. We assess the reliability of GPS-based transportation data on geographical position, speed, and elevation from three varied receivers GlobalSat BT-338X, Magellan SporTrak Pro and smart phone for three transportation modes: bicycle, car, and bus. The positional error ranging from 0158 meters, and 74% to 100% with an error within 5 meters depending on the transportation mode and route, there is also a non-negligible risk for aberrant positioning. Speed is slightly underestimated or overestimated with errors around 5km/h except for SporTrak Pro which had an error of -10 km/h. Elevation measurements are unreliable with errors bigger than 100 meters.

  • 10.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    An Evaluation of the Reliability of GPS-Based Transportation Data2014Report (Other academic)
    Abstract [en]

    GPS-based data are becoming a cornerstone for real-time transportation applications. Tracking data of vehicles from GPS receivers are however susceptible to measurement errors. The assessment of the reliability of data from GPS receiver is a neglected issue, especially in a real road network setting and in the phase after data transfer but before information identification. An evaluation method is outlined and carried out by conducting a randomized experiment. We assess the reliability of GPS-based transportation data on geographical position, speed, and elevation from three varied receivers GlobalSat BT-338X, Magellan SporTrak Pro and smart phone for three transportation modes: bicycle, car, and bus. The positional error ranging from 0158 meters, and 74% to 100% with an error within 5 meters depending on the transportation mode and route, there is also a non-negligible risk for aberrant positioning. Speed is slightly underestimated or overestimated with errors around 5km/h except for SporTrak Pro which had an error

  • 11.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    On assessing governmental sustainable residential planning and its alignment with residents’ and estate investors’ objectives2017Report (Other academic)
    Abstract [en]

    There are three key actors in forming the sustainable spatial distribution of residency in an area, (local) government, the estate investor and the resident, each with its own objective. Most urban planning studies have mainly focused on the ex-post evaluation of residential development by considering the objective of each actor separately. This paper outlines a conceptual model where the three key actors and their unique objectives are integrated with the aim of providing an ex-ante evaluation of residential development for government to make policies operational on a micro level. The methodology is implemented on a Swedish city, where sustainable residential development is in high need due to the influx of immigrants. The case study demonstrates that the model can integrate the macro and micro actors well. The model can provide noteworthy insights for the government on where the objectives of sustainability, livability and profit can be met. A sensitivity check of the parameter settings shows that the implementation of the model is robust for replication in other cities.

  • 12.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography.
    Reliability of GPS based traffic data: an experimental evaluation2014Report (Other academic)
    Abstract [en]

    GPS tracking of mobile objects provides spatial and temporal data for a broad range of applications including traffic management and control, transportation routing and planning. Previous transport research has focused on GPS tracking data as an appealing alternative to travel diaries. Moreover, the GPS based data are gradually becoming a cornerstone for real-time traffic management. Tracking data of vehicles from GPS devices are however susceptible to measurement errors – a neglected issue in transport research. By conducting a randomized experiment, we assess the reliability of GPS based traffic data on geographical position, velocity, and altitude for three types of vehicles; bike, car, and bus. We find the geographical positioning reliable, but with an error greater than postulated by the manufacturer and a non-negligible risk for aberrant positioning. Velocity is slightly underestimated, whereas altitude measurements are unreliable.

  • 13.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography. Dalarna University, School of Technology and Business Studies, Information Systems.
    Residential planning, driver mobility and CO2 emission2016Report (Other academic)
    Abstract [en]

    In a city there are hotspots that attract the citizens and most of the transportation in the city arises when citizens move between their residence and the hotspots. However, the evaluation between energy-efficient mobility and urban residential planning has been found to be rather weak. In this paper, we propose an ex-ante evaluation method to quantify the impacts in terms of CO2 emissions induced by intra-urban car mobility due to different residential plans implemented at various urban areas. The method is illustrated by a Swedish midsize city which is presently preoccupied with urban planning of new residential areas in response to substantial population growth due to immigration. On average, the CO2 emissions increase from the continued urban core area (CUCA) to the suburban polycentric area (SPA) to the edge urbanization area (EUA), EUA is almost 3 times more than CUCA. The average travel distances also increase in the same sequence, the overall increase is more than 4 times. Apartment buildings could be more effective in meeting residential needs and mitigating CO2 emissions than dispersed single-family houses.

  • 14.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Residential planning, driver mobility and CO2 emission: a microscopic look at Borlänge in Sweden2017In: European Planning Studies, ISSN 0965-4313, E-ISSN 1469-5944, Vol. 25, no 9, p. 1597-1614Article in journal (Refereed)
    Abstract [en]

    In a city there are hotspots that attract citizens, and most of the transportation arises when citizens move between their residence and primary destinations (i.e. hotspots). However, an ex ante evaluation of energy-efficient mobility and urban residential planning has seldom been conducted. Therefore, this paper proposes an ex ante evaluation method to quantify the impacts, in terms of CO2 emissions induced by intra-urban car mobility, of residential plans for various urban areas. The method is illustrated in a case study of a Swedish midsize city, which is presently preoccupied with urban planning of new residential areas in response to substantial population growth due to immigration. In general, CO2 emissions increase from the continued urban core area (CUCA), to the sub-polycentric area (SPA), to the edge urbanization area (EUA), where CO2 emission of EUA is twice that of the CUCA. The average travel distances also increase in the same pattern, though the relative increase is more than four times. Apartment buildings could be more effective in meeting residential needs and mitigating CO2 emissions than dispersed single-family houses. 

  • 15.
    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. 

  • 16.
    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.

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