This page has only limited features, please log in for full access.
Junqing Tang. Assessment of Resilience in Complex Urban Systems. Encyclopedia of the UN Sustainable Development Goals 2021, 84 -93.
AMA StyleJunqing Tang. Assessment of Resilience in Complex Urban Systems. Encyclopedia of the UN Sustainable Development Goals. 2021; ():84-93.
Chicago/Turabian StyleJunqing Tang. 2021. "Assessment of Resilience in Complex Urban Systems." Encyclopedia of the UN Sustainable Development Goals , no. : 84-93.
This paper studies the resilient performance of urban rail transit systems by extending a linear programming optimization model, which can provide optimized commuter flows with contingency routing under multiple disruptions. The rail transit systems in Singapore and Chongqing (China) are selected as case studies, and the system resilience and the effectiveness of providing bus-bridging services are comparatively studied. Intuitively, failures of the interchange stations would inevitably lead to a significant loss of resilience due to deteriorated network connectivity. However, the Singapore case shows that attacking those interchange stations does not always result in an extensive resilience loss. Comparing with the Chongqing case, it is discernible that the position of interchange stations would affect the system resilience. The numerical simulations reveal that the positive effect of providing bus-bridging strategy, in terms of improving the system resilience, is heterogeneous in different systems, which varies from 14% to 30% on average. As demonstrated in the sensitivity on travel demands, this positive effect is robust, yet dynamic, indicating that there is no one-size-fits-all solution for designing transfer-based recovery strategies in disruption management of rail transit systems. The managerial implications for decision makers are also provided and discussed in terms of infrastructure planning.
Junqing Tang; Lei Xu; Chunling Luo; Tsan Sheng Adam Ng. Multi-disruption resilience assessment of rail transit systems with optimized commuter flows. Reliability Engineering & System Safety 2021, 214, 107715 .
AMA StyleJunqing Tang, Lei Xu, Chunling Luo, Tsan Sheng Adam Ng. Multi-disruption resilience assessment of rail transit systems with optimized commuter flows. Reliability Engineering & System Safety. 2021; 214 ():107715.
Chicago/Turabian StyleJunqing Tang; Lei Xu; Chunling Luo; Tsan Sheng Adam Ng. 2021. "Multi-disruption resilience assessment of rail transit systems with optimized commuter flows." Reliability Engineering & System Safety 214, no. : 107715.
The paper investigates the non-commuting travel demand of car commuters using Automatic Number Plate Recognition (ANPR) trip chain data in Cambridge, UK. A novel rule-based algorithm is developed for identifying commuting vehicles and the associated non-commuting trips. Identification results are validated with external data. Non-commuting travel demand is investigated in terms of trip probability, average trip frequency, duration and demand elasticity. The study finds that, first, non-commuting trips represent a significant source of travel demand for car commuters – car commuters who engage in non-commuting activities in their daily trip chains would on average spend approximately 2.7hr on those activities including travel time on a typical workday in Cambridge. Second, longer working hours are associated with a lower probability of engaging in non-commuting trips, implying a substitution effect within the daily travel time budget. Last, in terms of travel demand elasticity, non-commuting trips starting in the early morning (6–9am) are less elastic than those starting in the morning (9–12am) and during the lunch break (12-3pm). The varying demand elasticities are likely to be attributed to the different travel constraints associated with certain trip purposes. Implications for post-pandemic traffic demand and management are drawn.
Li Wan; Junqing Tang; Lihua Wang; Jennifer Schooling. Understanding non-commuting travel demand of car commuters – Insights from ANPR trip chain data in Cambridge. Transport Policy 2021, 106, 76 -87.
AMA StyleLi Wan, Junqing Tang, Lihua Wang, Jennifer Schooling. Understanding non-commuting travel demand of car commuters – Insights from ANPR trip chain data in Cambridge. Transport Policy. 2021; 106 ():76-87.
Chicago/Turabian StyleLi Wan; Junqing Tang; Lihua Wang; Jennifer Schooling. 2021. "Understanding non-commuting travel demand of car commuters – Insights from ANPR trip chain data in Cambridge." Transport Policy 106, no. : 76-87.
Regulations play an important role in assuring the quality of a building’s construction and minimizing its adverse environmental impacts. Engineers and the like need to retrieve regulatory information to ensure a building conforms to specified standards. Despite the availability of search engines and digital databases that can be used to store regulations, engineers, for example, are unable to retrieve information for domain-specific needs in a timely manner. As a consequence, users often have to deal with the burden of browsing and filtering information, which can be a time-consuming process. This research develops a robust end-to-end methodology to improve the efficiency and effectiveness of retrieving queries pertaining to building regulations. The developed methodology integrates information retrieval with a deep learning model of Natural Language Processing (NLP) to provide precise and rapid answers to user’s questions from a collection of building regulations. The methodology is evaluated and a prototype system to retrieve queries is developed. The paper’s contribution is therefore twofold as it develops a: (1) methodology that combines NLP and deep learning to be able to address queries raised about the building regulations; and (2) chatbot of question answering system, which we refer to as QAS4CQAR. Our proposed methodology has powerful feature representation and learning capability and therefore can potentially be adopted to building regulations in other jurisdictions.
Botao Zhong; Wanlei He; Ziwei Huang; Peter E.D. Love; Junqing Tang; Hanbin Luo. A building regulation question answering system: A deep learning methodology. Advanced Engineering Informatics 2020, 46, 101195 .
AMA StyleBotao Zhong, Wanlei He, Ziwei Huang, Peter E.D. Love, Junqing Tang, Hanbin Luo. A building regulation question answering system: A deep learning methodology. Advanced Engineering Informatics. 2020; 46 ():101195.
Chicago/Turabian StyleBotao Zhong; Wanlei He; Ziwei Huang; Peter E.D. Love; Junqing Tang; Hanbin Luo. 2020. "A building regulation question answering system: A deep learning methodology." Advanced Engineering Informatics 46, no. : 101195.
Xiaowei Li; Junqing Tang; Xiaojiao Hu; Wei Wang. Assessing intercity multimodal choice behavior in a Touristy City: A factor analysis. Journal of Transport Geography 2020, 86, 1 .
AMA StyleXiaowei Li, Junqing Tang, Xiaojiao Hu, Wei Wang. Assessing intercity multimodal choice behavior in a Touristy City: A factor analysis. Journal of Transport Geography. 2020; 86 ():1.
Chicago/Turabian StyleXiaowei Li; Junqing Tang; Xiaojiao Hu; Wei Wang. 2020. "Assessing intercity multimodal choice behavior in a Touristy City: A factor analysis." Journal of Transport Geography 86, no. : 1.
Sustainability and its component resilience have become an important issue that cannot be neglected in airspace planning and development. Resilience, as an emerging system concept, is critical to sustainability in many fields. With the rapidly growing demand in China’s air transportation sector, airspace congestion and flight delays have become a major issue in the fast development of this sector, and threatens the sustainability and resilience of air traffic control (ATC) systems such as waste of resources, air pollution, etc. Sectors, the basic units of an ATC system, play a significant role in ensuring the safe and smooth operations of day-to-day flights. In this paper, we apply the complex network theory to establish a model of China’s air sector network (CASN) and examine a series of characteristic parameters with an empirical analysis on its vulnerability and resilience. Through a simulation-based approach, the CASN’s resilience was quantitatively assessed with a resilience indicator (RI) in different scenarios to identify the optimal recovery strategy for building higher system resilience. The results show that the CASN has a lengthy average shortest path and a small clustering coefficient, which demonstrates a hybrid topological feature. We have also found that betweenness has the greatest impact on the resilience and has managerial implications to understand the relationship between vulnerability and resilience in CASN, so as to achieve the resilience and sustainability of CASN.
Xinglong Wang; Shangfei Miao; Junqing Tang. Vulnerability and Resilience Analysis of the Air Traffic Control Sector Network in China. Sustainability 2020, 12, 3749 .
AMA StyleXinglong Wang, Shangfei Miao, Junqing Tang. Vulnerability and Resilience Analysis of the Air Traffic Control Sector Network in China. Sustainability. 2020; 12 (9):3749.
Chicago/Turabian StyleXinglong Wang; Shangfei Miao; Junqing Tang. 2020. "Vulnerability and Resilience Analysis of the Air Traffic Control Sector Network in China." Sustainability 12, no. 9: 3749.
Vehicle mobility generates dynamic and complex patterns that are associated with our day-to-day activities in cities. To reveal the spatial–temporal complexity of such patterns, digital techniques, such as traffic-monitoring sensors, provide promising data-driven tools for city managers and urban planners. Although a large number of studies have been dedicated to investigating the sensing power of the traffic-monitoring sensors, there is still a lack of exploration of the resilient performance of sensor networks when multiple sensor failures occur. In this paper, we reveal the dynamic patterns of vehicle mobility in Cambridge, UK, and subsequently, explore the resilience of the sensor networks. The observability is adopted as the overall performance indicator to depict the maximum number of vehicles captured by the deployed sensors in the study area. By aggregating the sensor networks according to weekday and weekend and simulating random sensor failures with different recovery strategies, we found that (1) the day-to-day vehicle mobility pattern in this case study is highly dynamic and decomposed journey durations follow a power-law distribution on the tail section; (2) such temporal variation significantly affects the observability of the sensor network, causing its overall resilience to vary with different recovery strategies. The simulation results further suggest that a corresponding prioritization for recovering the sensors from massive failures is required, rather than a static sequence determined by the first-fail–first-repair principle. For stakeholders and decision-makers, this study provides insightful implications for understanding city-scale vehicle mobility and the resilience of traffic-monitoring sensor networks.
Junqing Tang; Li Wan; Timea Nochta; Jennifer Schooling; Tianren Yang. Exploring Resilient Observability in Traffic-Monitoring Sensor Networks: A Study of Spatial–Temporal Vehicle Patterns. ISPRS International Journal of Geo-Information 2020, 9, 247 .
AMA StyleJunqing Tang, Li Wan, Timea Nochta, Jennifer Schooling, Tianren Yang. Exploring Resilient Observability in Traffic-Monitoring Sensor Networks: A Study of Spatial–Temporal Vehicle Patterns. ISPRS International Journal of Geo-Information. 2020; 9 (4):247.
Chicago/Turabian StyleJunqing Tang; Li Wan; Timea Nochta; Jennifer Schooling; Tianren Yang. 2020. "Exploring Resilient Observability in Traffic-Monitoring Sensor Networks: A Study of Spatial–Temporal Vehicle Patterns." ISPRS International Journal of Geo-Information 9, no. 4: 247.
Recently, greater research attention has focused on the application of solar power generation technology in building construction to reduce building energy consumption and encourage increased sustainable development. An emerging solar power generation technology is in the use of Building-integrated Photovoltaics (BIPVs), where photovoltaic materials are used to replace conventional building materials. In order to map the development of BIPV technology over time and explore technology paths, this study retrieved a total of 4914 patents dated from 1972 to 2016 from the Derwent Innovations Index patent database. This study applies patent co-citation analysis to map the patent co-citation network in three periods based on Ucinet tool. Evolutional path and three key technology frontiers were identified using Social Network Analysis (SNA) and text clustering. The results of this study provide an informed reference for future researchers in understanding the historical development of BIPV, as an emerging and important solar power generation technology in the built environment. At the same time, big data of patents are analyzed using SNA and text clustering, which overcomes the limitation of previous methods of frontiers study that have depended on expert opinion or peer review.
Botao Zhong; Yongjian Hei; Li Jiao; Hanbin Luo; Junqing Tang. Technology Frontiers of Building-integrated Photovoltaics (BIPV): A Patent Co-citation Analysis. International Journal of Low-Carbon Technologies 2019, 15, 241 -252.
AMA StyleBotao Zhong, Yongjian Hei, Li Jiao, Hanbin Luo, Junqing Tang. Technology Frontiers of Building-integrated Photovoltaics (BIPV): A Patent Co-citation Analysis. International Journal of Low-Carbon Technologies. 2019; 15 (2):241-252.
Chicago/Turabian StyleBotao Zhong; Yongjian Hei; Li Jiao; Hanbin Luo; Junqing Tang. 2019. "Technology Frontiers of Building-integrated Photovoltaics (BIPV): A Patent Co-citation Analysis." International Journal of Low-Carbon Technologies 15, no. 2: 241-252.
This paper reports on the design of wildlife crossing structures (WCSs) along a new expressway in China, which exemplifies the country’s increasing efforts on wildlife protection in infrastructure projects. The line and belt transect method, the surface water survey, and the sign-tracking investigation were used to determine the target species in the study area and the quantity, candidate locations, size, and type of the WCSs. The intensity index and encounter rate showed that the ibex (Capra ibex), argali sheep (Ovis ammon), and goitered gazelle (Gazella subgutturosa) are the main ungulates in the study area. Among them, the goitered gazelle is the most widely distributed species. Underpass WCSs were proposed based on the expert knowledge and crossing hotspots estimated using survey results. The mean distance between estimated hotspots and their nearest proposed WCSs is around 341 m. In addition, those proposed WCSs have a width of no less than 12 m and height of no lower than 3.5 m, which is believed to be sufficient for ungulates in the area. Given the limited availability of high-resolution movement data and wildlife-vehicle collision data during the road’s early design stage, the approach demonstrated in this paper facilitates the practical spatial planning and provides insights into designing WCSs in a desert landscape.
Bin Zhang; Junqing Tang; Yi Wang; Hongfeng Zhang; Dong Wu; Gang Xu; Yu Lin; Xiaomin Wu. Designing wildlife crossing structures for ungulates in a desert landscape: A case study in China. Transportation Research Part D: Transport and Environment 2019, 77, 50 -62.
AMA StyleBin Zhang, Junqing Tang, Yi Wang, Hongfeng Zhang, Dong Wu, Gang Xu, Yu Lin, Xiaomin Wu. Designing wildlife crossing structures for ungulates in a desert landscape: A case study in China. Transportation Research Part D: Transport and Environment. 2019; 77 ():50-62.
Chicago/Turabian StyleBin Zhang; Junqing Tang; Yi Wang; Hongfeng Zhang; Dong Wu; Gang Xu; Yu Lin; Xiaomin Wu. 2019. "Designing wildlife crossing structures for ungulates in a desert landscape: A case study in China." Transportation Research Part D: Transport and Environment 77, no. : 50-62.
Junqing Tang; Hans R. Heinimann; Ke Han. A Bayesian Network Approach for Assessing the General Resilience of Road Transportation Systems: A Systems Perspective. CICTP 2019 2019, 1 .
AMA StyleJunqing Tang, Hans R. Heinimann, Ke Han. A Bayesian Network Approach for Assessing the General Resilience of Road Transportation Systems: A Systems Perspective. CICTP 2019. 2019; ():1.
Chicago/Turabian StyleJunqing Tang; Hans R. Heinimann; Ke Han. 2019. "A Bayesian Network Approach for Assessing the General Resilience of Road Transportation Systems: A Systems Perspective." CICTP 2019 , no. : 1.
Junqing Tang. Assessment of Resilience in Complex Urban Systems. Encyclopedia of the UN Sustainable Development Goals 2019, 1 -10.
AMA StyleJunqing Tang. Assessment of Resilience in Complex Urban Systems. Encyclopedia of the UN Sustainable Development Goals. 2019; ():1-10.
Chicago/Turabian StyleJunqing Tang. 2019. "Assessment of Resilience in Complex Urban Systems." Encyclopedia of the UN Sustainable Development Goals , no. : 1-10.
Financial markets can be seen as complex systems that are constantly evolving and sensitive to external disturbance, such as financial risks and economic instabilities. Analysis of resilient market performance, therefore, becomes useful for investors. From a systems perspective, this paper proposes a novel function-based resilience metric that considers the effect of two fault-tolerance thresholds: the Robustness Range (RR) and the Elasticity Threshold (ET). We examined the consecutive resilience cycles and their dynamics in the performance of three stock markets, NASDAQ, SSE, and NYSE. The proposed metric was also compared with three well-documented resilience models. The results showed that this new metric could satisfactorily quantify the time-varying resilience cycles in the multi-cycle volatile performance of stock markets while also being more feasible in comparative analysis. Furthermore, analysis of dynamics revealed that those consecutive resilience cycles in market performance were distributed non-linearly, following a power-law distribution in the upper tail. Finally, sensitivity tests demonstrated the large-value resilience cycles were relatively sensitive to changes in RR. In practice, RR could indicate investors’ psychological capability to withstand downturns. It supports the observation that perception on the market’s resilient responses may vary among investors. This study provides a new tool and valuable insights for researchers, practitioners, and investors when evaluating market performance.
Junqing Tang; Hans Heinimann; Layla Khoja. Quantitative evaluation of consecutive resilience cycles in stock market performance: A systems-oriented approach. Physica A: Statistical Mechanics and its Applications 2019, 532, 121794 .
AMA StyleJunqing Tang, Hans Heinimann, Layla Khoja. Quantitative evaluation of consecutive resilience cycles in stock market performance: A systems-oriented approach. Physica A: Statistical Mechanics and its Applications. 2019; 532 ():121794.
Chicago/Turabian StyleJunqing Tang; Hans Heinimann; Layla Khoja. 2019. "Quantitative evaluation of consecutive resilience cycles in stock market performance: A systems-oriented approach." Physica A: Statistical Mechanics and its Applications 532, no. : 121794.
This paper examines the dynamic evolutionary process in the London Stock Exchange and uses network statistical measures to model the resilience of stock. A large historical dataset of companies was collected over 40 years (1977-2017) and conceptualised into weighted, temporally evolving and signed networks using correlation-based interdependences. Our results revealed a “fission-fusion” market growth in network topologies, which indicated the dynamic and complex characteristics of its evolutionary process. In addition, our regression and modelling results offer insights for construction a “characterisation tool” which can be used to predict stocks that have delisted and continuing performance relatively well, but were less adequate for stocks with normal performance. Moreover, the analysis of deviance suggested that the survivability resilience could be described and approximated by degree-related centrality measures. This study introduces a novel alternative for looking at the bankruptcy in the stock market and is potentially helpful for shareholders, decision- and policy-makers.
Junqing Tang; Layla Khoja; Hans R. Heinimann. Characterisation of survivability resilience with dynamic stock interdependence in financial networks. Applied Network Science 2018, 3, 23 .
AMA StyleJunqing Tang, Layla Khoja, Hans R. Heinimann. Characterisation of survivability resilience with dynamic stock interdependence in financial networks. Applied Network Science. 2018; 3 (1):23.
Chicago/Turabian StyleJunqing Tang; Layla Khoja; Hans R. Heinimann. 2018. "Characterisation of survivability resilience with dynamic stock interdependence in financial networks." Applied Network Science 3, no. 1: 23.
Hehong Zhang; Yunde Xie; Gaoxi Xiao; Chao Zhai; Zhiqiang Long; Huangwei Kang; Junqing Tang. Tracking Differentiator via Time Criterion. 2018 Annual American Control Conference (ACC) 2018, 1 .
AMA StyleHehong Zhang, Yunde Xie, Gaoxi Xiao, Chao Zhai, Zhiqiang Long, Huangwei Kang, Junqing Tang. Tracking Differentiator via Time Criterion. 2018 Annual American Control Conference (ACC). 2018; ():1.
Chicago/Turabian StyleHehong Zhang; Yunde Xie; Gaoxi Xiao; Chao Zhai; Zhiqiang Long; Huangwei Kang; Junqing Tang. 2018. "Tracking Differentiator via Time Criterion." 2018 Annual American Control Conference (ACC) , no. : 1.
Traffic congestion brings not only delay and inconvenience, but other associated national concerns, such as greenhouse gases, air pollutants, road safety issues and risks. Identification, measurement, tracking, and control of urban recurrent congestion are vital for building a livable and smart community. A considerable amount of works has made contributions to tackle the problem. Several methods, such as time-based approaches and level of service, can be effective for characterizing congestion on urban streets. However, studies with systemic perspectives have been minor in congestion quantification. Resilience, on the other hand, is an emerging concept that focuses on comprehensive systemic performance and characterizes the ability of a system to cope with disturbance and to recover its functionality. In this paper, we symbolized recurrent congestion as internal disturbance and proposed a modified metric inspired by the well-applied “R4” resilience-triangle framework. We constructed the metric with generic dimensions from both resilience engineering and transport science to quantify recurrent congestion based on spatial-temporal traffic patterns and made the comparison with other two approaches in freeway and signal-controlled arterial cases. Results showed that the metric can effectively capture congestion patterns in the study area and provides a quantitative benchmark for comparison. Also, it suggested not only a good comparative performance in measuring strength of proposed metric, but also its capability of considering the discharging process in congestion. The sensitivity tests showed that proposed metric possesses robustness against parameter perturbation in Robustness Range (RR), but the number of identified congestion patterns can be influenced by the existence of ϵ. In addition, the Elasticity Threshold (ET) and the spatial dimension of cell-based platform differ the congestion results significantly on both the detected number and intensity. By tackling this conventional problem with emerging concept, our metric provides a systemic alternative approach and enriches the toolbox for congestion assessment. Future work will be conducted on a larger scale with multiplex scenarios in various traffic conditions.
Junqing Tang; Hans Rudolf Heinimann. A resilience-oriented approach for quantitatively assessing recurrent spatial-temporal congestion on urban roads. PLOS ONE 2018, 13, e0190616 -e0190616.
AMA StyleJunqing Tang, Hans Rudolf Heinimann. A resilience-oriented approach for quantitatively assessing recurrent spatial-temporal congestion on urban roads. PLOS ONE. 2018; 13 (1):e0190616-e0190616.
Chicago/Turabian StyleJunqing Tang; Hans Rudolf Heinimann. 2018. "A resilience-oriented approach for quantitatively assessing recurrent spatial-temporal congestion on urban roads." PLOS ONE 13, no. 1: e0190616-e0190616.
This paper examines the dynamic evolution process in London stock exchange and attempts to model stock survivability resilience in the financial networks. A big historical dataset of UK companies from London stock exchange for 40 years (1976–2016) was collected and conceptualized into weighted, temporally evolving and signed networks using correlation coefficients. Based on the legal definition of corporate failure, stocks were categorized into Continuing, Failed and Normal groups. Accordingly, we conducted analysis on (1) The long-term evolution process of the entire population with statistical inference and visualization. (2) Multivariate logistic modeling of survivability resilience using short-term network measures, degree ratio (\(r_{i}\)), node degree (\(k_{i}\)), and node strength (\(s_{i}\)). The results show an exponential market growth but with a “fission-fusion” behavior in network topologies, which indicates dynamic and complex characteristics of its expansion. On the other hand, regression and modeling outcomes show that the survivability resilience is correlated with \(k_{i}\) and \(s_{i}\). Moreover, the analysis of deviance suggests that the survivability resilience could be described, by and large, as a function of \(k_{i}\) since it contributes the most significant difference. The study provides a novel alternative to look at the bankruptcy in the stock market and is potentially helpful for shareholders, decision- and policy-makers.
Junqing Tang; Layla Khoja; Hans Rudolf Heinimann. Modeling Stock Survivability Resilience in Signed Temporal Networks: A Study from London Stock Exchange. Econometrics for Financial Applications 2017, 1041 -1052.
AMA StyleJunqing Tang, Layla Khoja, Hans Rudolf Heinimann. Modeling Stock Survivability Resilience in Signed Temporal Networks: A Study from London Stock Exchange. Econometrics for Financial Applications. 2017; ():1041-1052.
Chicago/Turabian StyleJunqing Tang; Layla Khoja; Hans Rudolf Heinimann. 2017. "Modeling Stock Survivability Resilience in Signed Temporal Networks: A Study from London Stock Exchange." Econometrics for Financial Applications , no. : 1041-1052.
Benedetto Piccoli; Ke Han; Terry L. Friesz; Tao Yao; Junqing Tang. Second-order models and traffic data from mobile sensors. Transportation Research Part C: Emerging Technologies 2015, 52, 32 -56.
AMA StyleBenedetto Piccoli, Ke Han, Terry L. Friesz, Tao Yao, Junqing Tang. Second-order models and traffic data from mobile sensors. Transportation Research Part C: Emerging Technologies. 2015; 52 ():32-56.
Chicago/Turabian StyleBenedetto Piccoli; Ke Han; Terry L. Friesz; Tao Yao; Junqing Tang. 2015. "Second-order models and traffic data from mobile sensors." Transportation Research Part C: Emerging Technologies 52, no. : 32-56.