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<?xml version="1.0" encoding="utf-8" standalone="yes" ?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
<channel>
<title>CRUISE</title>
<link>https://kaiqinchi.github.io/</link>
<atom:link href="https://kaiqinchi.github.io/index.xml" rel="self" type="application/rss+xml" />
<description>CRUISE</description>
<generator>Source Themes Academic (https://sourcethemes.com/academic/)</generator><language>en-us</language><lastBuildDate>Sun, 20 Sep 2020 15:43:16 +1100</lastBuildDate>
<image>
<url>https://kaiqinchi.github.io/images/icon_hua992cb10085e06a51eab2da50465a284_10796_512x512_fill_lanczos_center_2.png</url>
<title>CRUISE</title>
<link>https://kaiqinchi.github.io/</link>
</image>
<item>
<title>Behaviour Analytics of Indoor Occupants</title>
<link>https://kaiqinchi.github.io/project/behaviour_analytics_of_indoor_occupants/</link>
<pubDate>Sun, 20 Sep 2020 15:43:16 +1100</pubDate>
<guid>https://kaiqinchi.github.io/project/behaviour_analytics_of_indoor_occupants/</guid>
<description><p>This project will deploy machine learning to human behaviour and building operational data obtained through Activity Based Working (ABW), aimed at providing insights towards optimising and personalising ABW. The outcome is a cloud-based integrated platform, with tailored ABW apps, for capturing and analysing occupancy behaviour and building performance data.</p>
<p>A rich model of workers’ movements, online activities, and social groupings will be learned from synthesising fine-grained ABW behaviours and space utilisation patterns. The web dashboard will be used by Arup to approach their work holistically, making decisions based on a clear view of the total outcomes for their clients and stakeholders, including value for money. It allows Arup to close the design feedback loop, through a deeper understanding of the impact of the engineered parameters of modern offices on ABW and building operations, enhancing the precision with which Arup prescribe solutions on multiple client contexts.</p>
</description>
</item>
<item>
<title>Swarming: Micro-flight Data Capture and Analysis</title>
<link>https://kaiqinchi.github.io/project/swarming_micro-flight_data_capture/</link>
<pubDate>Sun, 20 Sep 2020 15:43:16 +1100</pubDate>
<guid>https://kaiqinchi.github.io/project/swarming_micro-flight_data_capture/</guid>
<description><p>In response to the urgent need for more site specific and vertical environmental information to inform the design of sustainable urban design, this project investigates the use of Micro Air Vehicles (drones) equipped with diverse lightweight sensing equipment to gather site specific environmental sensor data.</p>
<p>This multidisciplinary team of researchers from RMIT, with Aurecon, one of the world’s leading engineering, design, planning, project management and consulting company and Australian unmanned aerial vehicle specialist UAV-Australia, are proposing to research, for the first time the usage of emerging micro flight technology to gather and analyse large volume of heterogeneous sensor data, over extended time periods and locations, with the aim to inform urban design and planning, and integrate them for urban design and urban computing applications.</p>
<p>-Australian Research Council (ARC) Linkage project (2016-2019)</p>
</description>
</item>
<item>
<title>Time-series Forecasting and Segmentation</title>
<link>https://kaiqinchi.github.io/project/time-series_forecasting_and_segmentation/</link>
<pubDate>Sun, 20 Sep 2020 15:43:16 +1100</pubDate>
<guid>https://kaiqinchi.github.io/project/time-series_forecasting_and_segmentation/</guid>
<description><p>Today, we are faced with the increasing growth of ubiquitous sensors in various fields, generating an enormous amount of time-series. This growing number of sensor-based time-series applications require new approaches in data mining, knowledge discovery, and ubiquitous computing.</p>
<p>We proposed a general framework for multivariate time series forecasting, called evolutionary model construction (EMC), to jointly select the informative channels of the factors, to extract the valuable features from the selected channels applied to the optimal-configured model, and to improve prediction accuracy[5,6].</p>
<p>When dealing with high-dimensional time-series from mobile, wearable, and Internet of Things streamed from the field, the data is often noisy and unlabelled. We perform unsupervised and self-supervised multivariate time-series pre-processing approaches such as segmentation and change point detection problems to extract the most homogeneous segments in the absence of ground truth labels.</p>
<p>To solve multidimensional time-series segmentation, we have proposed an unsupervised approach, IGTS (Information Gain-based Temporal Segmentation)[1,2], a technique to find the transition times in human activities and daily routines[3], from heterogeneous sensor data.
Further, ESPRESSO [4] (Entropy and ShaPe awaRe time-series SegmentatiOn), a general multivariate segmentation method, is proposed as an improvement to IGTS, specifically to cover a broader range of inputs by combining statistical (entropy) and shape-based features of time-series.</p>
<p>[1] Sadri, A., Ren, Y. and Salim, F.D., 2017. Information gain-based metric for recognizing transitions in human activities. Pervasive and Mobile Computing, 38, pp.92-109.</p>
<p>[2] Zameni, M., Sadri, A., Ghafoori, Z., Moshtaghi, M., Salim, F.D., Leckie, C. and Ramamohanarao, K., 2020. Unsupervised online change point detection in high-dimensional time series. Knowledge and Information Systems, 62(2), pp.719-750.</p>
<p>[3] Sadri, A., Salim, F.D., Ren, Y., Shao, W., Krumm, J.C. and Mascolo, C., 2018. What will you do for the rest of the day? an approach to continuous trajectory prediction. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2(4), pp.1-26.</p>
<p>[4] Deldari, S., Smith, D.V., Sadri, A. and Salim, F., 2020. ESPRESSO: Entropy and ShaPe awaRe timE-Series SegmentatiOn for processing heterogeneous sensor data. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4(3), pp.1-24. <a href="https://dl.acm.org/doi/abs/10.1145/3411832">https://dl.acm.org/doi/abs/10.1145/3411832</a></p>
<p>[5] Song, H., Qin, A.K. and Salim, F.D., 2018, July. Evolutionary multi-objective ensemble learning for multivariate electricity consumption prediction. In 2018 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.</p>
<p>[6] Song, H., Qin, A.K. and Salim, F.D., 2020. Evolutionary model construction for electricity consumption prediction. Neural Computing and Applications, 32(16), pp.12155-12172.</p>
</description>
</item>
<item>
<title>Multi-resolution Situation Recognition for Urban-Aware Smart Assistant</title>
<link>https://kaiqinchi.github.io/project/multi-resolution_situation_recognition/</link>
<pubDate>Wed, 15 Jan 2020 15:43:16 +1100</pubDate>
<guid>https://kaiqinchi.github.io/project/multi-resolution_situation_recognition/</guid>
<description><p>This research aims to develop a framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, social group, and urban level, and at multiple locations and time scales. This should provide users with timely notifications and recommendations to resume their activities and routines. The expected benefits will be far-ranging and adaptable to many domains, from personal smart assistants to trip planning and emergency services. - ARC Discovery Project DP190101485</p>
</description>
</item>
<item>
<title>Deep Learning for Situation Awareness in Airport Operations</title>
<link>https://kaiqinchi.github.io/project/deep_learning_for-situation-awareness/</link>
<pubDate>Wed, 15 Jan 2020 15:42:51 +1100</pubDate>
<guid>https://kaiqinchi.github.io/project/deep_learning_for-situation-awareness/</guid>
<description><p>This project that is funded by Northrop Grumman Corporation investigates the patterns of ground vehicles and aircraft trajectories, combining the analysis of their spatial movement behaviours and contextual information. We utilise state-of-the-art artificial intelligence and big data analytics techniques to clean, preprocess, and analyse sizeable on-ground aircraft GPS data. We also establish a context-aware system to predict the delay time of each aircraft by developing a novel Airport Traffic Complexity (ATC) model.</p>
<p>The outcome leads to multiple economic and security benefits for airline passengers, air traffic controllers, and airport managers. Our work provides a situational awareness map to the airport traffic controller, which reveals the potential factors that affect the traffic flow at the airport, as well as points out the hot spots and anomalous cases. Additionally, our proposed solution could inform airport managers and traffic controllers regarding the estimated delay time of flights on the tarmac at the specific airport.</p>
</description>
</item>
<item>
<title>Microsoft RMIT Cortana Intelligence Institute</title>
<link>https://kaiqinchi.github.io/project/microsoft_rmit_cortana_intelligence_institute/</link>
<pubDate>Wed, 15 Jan 2020 15:42:51 +1100</pubDate>
<guid>https://kaiqinchi.github.io/project/microsoft_rmit_cortana_intelligence_institute/</guid>
<description><p>Cortana Intelligence Institute is a co-funded initiative between Microsoft Research, Cortana Research and RMIT University, which will drive the next-generation of capabilities for Microsoft’s digital assistant, Cortana.</p>
<p>The Institute focused on researching work-related tasks, an area that will help make Cortana a more proactive and context-aware digital assistant that truly amplifies human capabilities. Using sensors in mobile phones, the team built a complex multidimensional data set, which will be used to model and predict a person’s work-related tasks. This includes the physical activity and location of a user, their online and app behaviour, and their interactions with their social groups or peers. Microsoft’s researchers collaborated with RMIT team members on the development of algorithms that use the novel dataset to improve Cortana.</p>
<p>This research project contributes to a greater understanding of the contextual factors that may characterize, or even influence, the tasks being performed by professionals and non-professionals. We take rich contextual factors derived from spatial, temporal, and online activities to better understand participants’ task habits. We use repeated patterns of tasks as cues in characterizing implicit task habits. We examine task batching behaviours and predict the tasks participants are about to undertake.</p>
<p>You can see more relevant information from this link: <a href="https://www.microsoft.com/en-us/research/blog/new-institute-explores-future-cortana/">https://www.microsoft.com/en-us/research/blog/new-institute-explores-future-cortana/</a>.</p>
</description>
</item>
<item>
<title>Monington Peninsula Smart Parking and Amenities for High Demand Areas</title>
<link>https://kaiqinchi.github.io/project/monington_peninsula_smart_parking/</link>
<pubDate>Wed, 15 Jan 2020 15:42:51 +1100</pubDate>
<guid>https://kaiqinchi.github.io/project/monington_peninsula_smart_parking/</guid>
<description><p>The Mornington Peninsula Shire (MPS) will develop a Smart Technology project to address growing demand on parking and amenity facilities in towns particularly with high tourist
attraction. There is an increasing pressure to understand the volume of pedestrians, public transport users, and road users (in particular, private vehicle drivers) throughout the major townships in MPS and meet the increasing demand.</p>
<p>The ability to model future scenarios will provide a basis to plan infrastructure, provide better routing recommendations, and to assist the planning of events throughout the Shire. Latest smart technology has been sourced along with high-level expertise to develop the necessary systems to gather and translate data into productive outcomes to provide better services to the community and tourists.</p>
<p>The targeted parking and amenities in the high demand towns have varying operations that need specific sensor types to provide the required data. Consequently, the sensors will
require the development and implementation of a tailored system to gather the data and provide information for the community, visitors, Council service teams and planners.</p>
</description>
</item>
<item>
<title>User Context and Community Modelling using Proximity Signals and Cyber, Physical, Social Behaviours</title>
<link>https://kaiqinchi.github.io/project/context_community_modelling/</link>
<pubDate>Wed, 15 Jan 2020 15:42:51 +1100</pubDate>
<guid>https://kaiqinchi.github.io/project/context_community_modelling/</guid>
<description><p>The modeling of social and mobility networks continues to gain importance in a variety of fields ranging from epidemiology social group and community detection [1, 2], to user movement and behavior understanding [3, 4, 5].</p>
<p>In the Simultaneous Extraction of Context and Community (SECC) model that is proposed by Nguyen et al. [1, 2], each context is represented as a multinomial distribution, which indicates the participating level of the users to such context. To detect communities, it then computes the clusters of multinomial distribution to discover proximity contexts and users.</p>
<p>In our project, in collaboration with Scentre Group (Westfield malls), we analysed visitor behaviour in shopping malls, with joint learning of semantic behaviours from cyber, physical, and social behaviours [4,5], for contextual recommendations with tripartite graph models [6].</p>
<p>[1] Nguyen, T., Nguyen, V., Salim, F. D., &amp; Phung, D. (2016, March). SECC: Simultaneous extraction of context and community from pervasive signals. In 2016 IEEE International Conference on Pervasive Computing and Communications (PerCom) (pp. 1-9). IEEE.</p>
<p>[2] Nguyen, T., Nguyen, V., Salim, F. D., Le, D. V., &amp; Phung, D. (2017). A Simultaneous Extraction of Context and Community from pervasive signals using nested Dirichlet process. Pervasive and Mobile Computing, 38, 396-417.</p>
<p>[3] Ren, Y., Tomko, M., Salim, F. D., Chan, J., &amp; Sanderson, M. (2018). Understanding the predictability of user demographics from cyber-physical-social behaviours in indoor retail spaces. EPJ Data Science, 7, 1-21.</p>
<p>[4] Manpreet Kaur, Flora D. Salim, Yongli Ren, Jeffrey Chan, Martin Tomko, and Mark Sanderson. 2020. Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors. ACM Trans. Sen. Netw. 16, 3, Article 28 (August 2020), 25 pages. DOI:https://doi.org/10.1145/3393692</p>
<p>[5] Manpreet Kaur, Flora D. Salim, Yongli Ren, Jeffrey Chan, Martin Tomko, and Mark Sanderson. 2018. Shopping intent recognition and location prediction from cyber-physical activities via wi-fi logs. In Proceedings of the 5th Conference on Systems for Built Environments (BuildSys &lsquo;18). Association for Computing Machinery, New York, NY, USA, 130–139. DOI:https://doi.org/10.1145/3276774.3276786</p>
<p>[6] Y. Ren, M. Tomko, F. D. Salim, J. Chan, C. L. A. Clarke and M. Sanderson, &ldquo;A Location-Query-Browse Graph for Contextual Recommendation,&rdquo; in IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 2, pp. 204-218, 1 Feb. 2018, doi: 10.1109/TKDE.2017.2766059.
<a href="https://ieeexplore.ieee.org/document/8081816">https://ieeexplore.ieee.org/document/8081816</a></p>
</description>
</item>
<item>
<title>An Ambient-Physical System to Infer Concentration in Open-plan Workplace</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalscorrabs-2005-13535/</link>
<pubDate>Wed, 01 Jan 2020 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalscorrabs-2005-13535/</guid>
<description></description>
</item>
<item>
<title>Deep Learning Assisted Memetic Algorithm for Shortest Route Problems</title>
<link>https://kaiqinchi.github.io/publication/dblp-conficc-s-turky-r-0-sbs-20/</link>
<pubDate>Wed, 01 Jan 2020 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-conficc-s-turky-r-0-sbs-20/</guid>
<description></description>
</item>
<item>
<title>DroTrack: High-speed Drone-based Object Tracking Under Uncertainty</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalscorrabs-2005-00828/</link>
<pubDate>Wed, 01 Jan 2020 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalscorrabs-2005-00828/</guid>
<description></description>
</item>
<item>
<title>Evolutionary model construction for electricity consumption prediction</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalsnca-song-qs-20/</link>
<pubDate>Wed, 01 Jan 2020 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalsnca-song-qs-20/</guid>
<description></description>
</item>
<item>
<title>Exploring the Impact of COVID-19 Lockdown on Social Roles and Emotions while Working from Home</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalscorrabs-2007-12353/</link>
<pubDate>Wed, 01 Jan 2020 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalscorrabs-2007-12353/</guid>
<description></description>
</item>
<item>
<title>FADACS: A Few-shot Adversarial Domain Adaptation Architecture for Context-Aware Parking Availability Sensing</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalscorrabs-2007-08551/</link>
<pubDate>Wed, 01 Jan 2020 00:00:00 +1100</pubDate>
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<title>Federated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence</title>
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<title>G-CREWE: Graph CompREssion With Embedding for Network Alignment</title>
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<item>
<title>grid2vec: Learning Efficient Visual Representations via Flexible Grid-Graphs</title>
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<item>
<title>Incorporating LSTM Auto-Encoders in Optimizations to Solve Parking Officer Patrolling Problem</title>
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<item>
<title>Intelligent Task Recognition: Towards Enabling Productivity Assistance in Daily Life</title>
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<item>
<title>Multi-officer Routing for Patrolling High Risk Areas Jointly Learned from Check-ins, Crime and Incident Response Data</title>
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<item>
<title>n-Gage: Predicting in-class Emotional, Behavioural and Cognitive Engagement in the Wild</title>
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<item>
<title>Realtime Predictive Patrolling and Routing with Mobility and Emergency Calls Data</title>
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<item>
<title>Relation Embedding for Personalised POI Recommendation</title>
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<item>
<title>Relation Embedding for Personalised Translation-Based POI Recommendation</title>
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<title>Seating preference analysis for hybrid workplaces</title>
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<item>
<title>SmartMeeting: An Novel Mobile Voice Meeting Minutes Generation and Analysis System</title>
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<title>Solving multiple travelling officers problem with population-based optimization algorithms</title>
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<item>
<title>Transfer Learning for Thermal Comfort Prediction in Multiple Cities</title>
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<item>
<title>Unsupervised online change point detection in high-dimensional time series</title>
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<item>
<title>Approximating Optimisation Solutions for Travelling Officer Problem with Customised Deep Learning Network</title>
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<item>
<title>COLTRANE: ConvolutiOnaL TRAjectory NEtwork for Deep Map Inference</title>
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<item>
<title>COLTRANE: ConvolutiOnaL TRAjectory NEtwork for Deep Map Inference</title>
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<item>
<title>Crime Rate Prediction with Region Risk and Movement Patterns</title>
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<item>
<title>Efficient trip scheduling algorithms for groups</title>
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<item>
<title>Flight Delay Prediction using Airport Situational Awareness Map</title>
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<item>
<title>Flight Delay Prediction using Airport Situational Awareness Map</title>
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</item>
<item>
<title>Improving Experience Sampling with Multi-view User-driven Annotation Prediction</title>
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<item>
<title>Learning About Work Tasks to Inform Intelligent Assistant Design</title>
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<item>
<title>OccuSpace: Towards a Robust Occupancy Prediction System for Activity Based Workplace</title>
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<item>
<title>OnlineAirTrajClus: An Online Aircraft Trajectory Clustering for Tarmac Situation Awareness</title>
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<item>
<title>Predicting Personality Traits From Physical Activity Intensity</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalscomputer-gao-ss-19/</link>
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<item>
<title>Predicting Personality Traits from Physical Activity Intensity</title>
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<item>
<title>QDaS: Quality driven data summarisation for effective storage management in Internet of Things</title>
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<item>
<title>Using Big Spatial Data for Planning User Mobility</title>
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<item>
<title>A Location-Query-Browse Graph for Contextual Recommendation</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalstkde-ren-tsccs-18/</link>
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<item>
<title>A Scalable Room Occupancy Prediction with Transferable Time Series Decomposition of CO(_mbox2) Sensor Data</title>
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<item>
<title>Algorithmic Governance in Smart Cities: The Conundrum and the Potential of Pervasive Computing Solutions</title>
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<item>
<title>BLEDoorGuard: A Device-Free Person Identification Framework Using Bluetooth Signals for Door Access</title>
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<item>
<title>CoAcT: A Framework for Context-Aware Trip Planning Using Active Transport</title>
<link>https://kaiqinchi.github.io/publication/dblp-confpercom-rahaman-hs-18/</link>
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<item>
<title>Crime event prediction with dynamic features</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalsepjds-rumi-ds-18/</link>
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<item>
<title>Crowd-enabled Processing of Trustworthy, Privacy-Enhanced and Personalised Location Based Services with Quality Guarantee</title>
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<item>
<title>Data-driven occupant modeling strategies and digital tools enabled by IEA EBC annex 79: poster abstract</title>
<link>https://kaiqinchi.github.io/publication/dblp-confsensys-kjaergaard-dcsya-18/</link>
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<item>
<title>Evolutionary Multi-objective Ensemble Learning for Multivariate Electricity Consumption Prediction</title>
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<item>
<title>Identifying In-App User Actions from Mobile Web Logs</title>
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<item>
<title>Inferring Transportation Mode and Human Activity from Mobile Sensing in Daily Life</title>
<link>https://kaiqinchi.github.io/publication/dblp-confmobiquitous-liono-aqs-18/</link>
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<item>
<title>Mining User Behavioral Rules from Smartphone Data Through Association Analysis</title>
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<item>
<title>Mining User Behavioral Rules from Smartphone Data through Association Analysis</title>
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<item>
<title>Parking Availability Prediction with Long Short Term Memory Model</title>
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<item>
<title>Predicting Citywide Passenger Demand via Reinforcement Learning from Spatio-Temporal Dynamics</title>
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<item>
<title>ProMETheus: An Intelligent Mobile Voice Meeting Minutes System</title>
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<item>
<title>RUP: Large Room Utilisation Prediction with carbon dioxide sensor</title>
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<item>
<title>Shopping intent recognition and location prediction from cyber-physical activities via wi-fi logs</title>
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<item>
<title>Theft prediction with individual risk factor of visitors</title>
<link>https://kaiqinchi.github.io/publication/dblp-confgis-rumi-ds-18/</link>
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<item>
<title>Traveling Officer Problem: Managing Car Parking Violations Efficiently Using Sensor Data</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalsiotj-shao-sgdc-18/</link>
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<item>
<title>Understanding the predictability of user demographics from cyber-physical-social behaviours in indoor retail spaces</title>
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<item>
<title>Wait Time Prediction for Airport Taxis Using Weighted Nearest Neighbor Regression</title>
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<item>
<title>What Will You Do for the Rest of the Day?: An Approach to Continuous Trajectory Prediction</title>
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<item>
<title>A Simultaneous Extraction of Context and Community from pervasive signals using nested Dirichlet process</title>
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<item>
<title>Analyzing Web behavior in indoor retail spaces</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalsjasis-ren-tsos-17/</link>
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<item>
<title>Automated density-based clustering of spatial urban data for interactive data exploration</title>
<link>https://kaiqinchi.github.io/publication/dblp-confinfocom-rosalina-ss-17/</link>
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<item>
<title>CAPRA: A contour-based accessible path routing algorithm</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalsisci-rahaman-mhs-17/</link>
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<item>
<title>CD-HOC: Indoor Human Occupancy Counting using Carbon Dioxide Sensor Data</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalscorr-ang-sh-17/</link>
<pubDate>Sun, 01 Jan 2017 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalscorr-ang-sh-17/</guid>
<description></description>
</item>
<item>
<title>D-Log: A WiFi Log-based differential scheme for enhanced indoor localization with single RSSI source and infrequent sampling rate</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalspercom-ren-stbcqs-17/</link>
<pubDate>Sun, 01 Jan 2017 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalspercom-ren-stbcqs-17/</guid>
<description></description>
</item>
<item>
<title>DA-HOC: semi-supervised domain adaptation for room occupancy prediction using CO(_mbox2) sensor data</title>
<link>https://kaiqinchi.github.io/publication/dblp-confsensys-ang-sh-17/</link>
<pubDate>Sun, 01 Jan 2017 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confsensys-ang-sh-17/</guid>
<description></description>
</item>
<item>
<title>Full trajectory prediction: what will you do the rest of the day?</title>
<link>https://kaiqinchi.github.io/publication/dblp-confhuc-sadri-sr-17/</link>
<pubDate>Sun, 01 Jan 2017 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confhuc-sadri-sr-17/</guid>
<description></description>
</item>
<item>
<title>Information gain-based metric for recognizing transitions in human activities</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalspercom-sadri-rs-17/</link>
<pubDate>Sun, 01 Jan 2017 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalspercom-sadri-rs-17/</guid>
<description></description>
</item>
<item>
<title>Multi-resolution Selective Ensemble Extreme Learning Machine for Electricity Consumption Prediction</title>
<link>https://kaiqinchi.github.io/publication/dblp-conficonip-song-qs-17/</link>
<pubDate>Sun, 01 Jan 2017 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-conficonip-song-qs-17/</guid>
<description></description>
</item>
<item>
<title>Predicting Imbalanced Taxi and Passenger Queue Contexts in Airport</title>
<link>https://kaiqinchi.github.io/publication/dblp-confpacis-rahaman-hs-17/</link>
<pubDate>Sun, 01 Jan 2017 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confpacis-rahaman-hs-17/</guid>
<description></description>
</item>
<item>
<title>Predicting the city foot traffic with pedestrian sensor data</title>
<link>https://kaiqinchi.github.io/publication/dblp-confmobiquitous-wang-lms-17/</link>
<pubDate>Sun, 01 Jan 2017 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confmobiquitous-wang-lms-17/</guid>
<description></description>
</item>
<item>
<title>Queue Context Prediction Using Taxi Driver Knowledge</title>
<link>https://kaiqinchi.github.io/publication/dblp-confkcap-rahaman-hs-17/</link>
<pubDate>Sun, 01 Jan 2017 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confkcap-rahaman-hs-17/</guid>
<description></description>
</item>
<item>
<title>SD-HOC: Seasonal Decomposition Algorithm for Mining Lagged Time Series</title>
<link>https://kaiqinchi.github.io/publication/dblp-confausdm-ang-sh-17/</link>
<pubDate>Sun, 01 Jan 2017 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confausdm-ang-sh-17/</guid>
<description></description>
</item>
<item>
<title>Shrink: Distance preserving graph compression</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalsis-sadri-srzcs-17/</link>
<pubDate>Sun, 01 Jan 2017 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalsis-sadri-srzcs-17/</guid>
<description></description>
</item>
<item>
<title>Who Opened the Room? Device-Free Person Identification Using Bluetooth Signals in Door Access</title>
<link>https://kaiqinchi.github.io/publication/dblp-confithings-shao-sny-17/</link>
<pubDate>Sun, 01 Jan 2017 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confithings-shao-sny-17/</guid>
<description></description>
</item>
<item>
<title>AutoJammin': Designing Progression in Traffic and Music</title>
<link>https://kaiqinchi.github.io/publication/dblp-confautomotive-ui-krome-lsgs-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confautomotive-ui-krome-lsgs-16/</guid>
<description></description>
</item>
<item>
<title>Clustering Big Spatiotemporal-Interval Data</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalstbd-shao-ssb-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalstbd-shao-ssb-16/</guid>
<description></description>
</item>
<item>
<title>CoSDEO 2016: Contact-free ambient sensing - Welcome and committees: Welcome message from the CoSDEO 2016 workshop co-chairs</title>
<link>https://kaiqinchi.github.io/publication/dblp-confpercom-salim-sx-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confpercom-salim-sx-16/</guid>
<description></description>
</item>
<item>
<title>Efficient meta-heuristics for the Multi-Objective Time-Dependent Orienteering Problem</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalseor-mei-sl-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalseor-mei-sl-16/</guid>
<description></description>
</item>
<item>
<title>Human occupancy recognition with multivariate ambient sensors</title>
<link>https://kaiqinchi.github.io/publication/dblp-confpercom-ang-sh-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confpercom-ang-sh-16/</guid>
<description></description>
</item>
<item>
<title>Measuring passers-by engagement with AmPost: a printed interactive audio poster</title>
<link>https://kaiqinchi.github.io/publication/dblp-confozchi-liono-vks-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confozchi-liono-vks-16/</guid>
<description></description>
</item>
<item>
<title>Multivariate electricity consumption prediction with Extreme Learning Machine</title>
<link>https://kaiqinchi.github.io/publication/dblp-confijcnn-song-qs-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confijcnn-song-qs-16/</guid>
<description></description>
</item>
<item>
<title>Optimal time window for temporal segmentation of sensor streams in multi-activity recognition</title>
<link>https://kaiqinchi.github.io/publication/dblp-confmobiquitous-liono-qs-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confmobiquitous-liono-qs-16/</guid>
<description></description>
</item>
<item>
<title>SECC: Simultaneous extraction of context and community from pervasive signals</title>
<link>https://kaiqinchi.github.io/publication/dblp-confpercom-nguyen-nsp-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confpercom-nguyen-nsp-16/</guid>
<description></description>
</item>
<item>
<title>Smart cities: Intelligent environments and dumb people? Panel summary</title>
<link>https://kaiqinchi.github.io/publication/dblp-confpercom-zambonelli-mkls-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confpercom-zambonelli-mkls-16/</guid>
<description></description>
</item>
<item>
<title>Topical Event Detection on Twitter</title>
<link>https://kaiqinchi.github.io/publication/dblp-confadc-cui-zzs-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confadc-cui-zzs-16/</guid>
<description></description>
</item>
<item>
<title>Urban HCI: (Re)adapting the City Together</title>
<link>https://kaiqinchi.github.io/publication/dblp-confac-mdis-mascio-cas-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confac-mdis-mascio-cas-16/</guid>
<description></description>
</item>
<item>
<title>UTE: A Ubiquitous Data Exploration Platform for Mobile Sensing Experiments</title>
<link>https://kaiqinchi.github.io/publication/dblp-confmdm-liono-njs-16/</link>
<pubDate>Fri, 01 Jan 2016 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confmdm-liono-njs-16/</guid>
<description></description>
</item>
<item>
<title>An Energy-Efficient Inter-organizational Wireless Sensor Data Collection Framework</title>
<link>https://kaiqinchi.github.io/publication/dblp-conficws-chang-ldssll-15/</link>
<pubDate>Thu, 01 Jan 2015 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-conficws-chang-ldssll-15/</guid>
<description></description>
</item>
<item>
<title>Analyzing Web Behavior in Indoor Retail Spaces</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalscorr-ren-tsos-15/</link>
<pubDate>Thu, 01 Jan 2015 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalscorr-ren-tsos-15/</guid>
<description></description>
</item>
<item>
<title>Heuristic evolution with Genetic Programming for Traveling Thief Problem</title>
<link>https://kaiqinchi.github.io/publication/dblp-confcec-mei-lsy-15/</link>
<pubDate>Thu, 01 Jan 2015 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confcec-mei-lsy-15/</guid>
<description></description>
</item>
<item>
<title>Mobile Computing, Applications, and Services - 7th International Conference, MobiCASE 2015, Berlin, Germany, November 12-13, 2015, Revised Selected Papers</title>
<link>https://kaiqinchi.github.io/publication/dblp-confmobicase-2015/</link>
<pubDate>Thu, 01 Jan 2015 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confmobicase-2015/</guid>
<description></description>
</item>
<item>
<title>Urban computing in the wild: A survey on large scale participation and citizen engagement with ubiquitous computing, cyber physical systems, and Internet of Things</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalsijmms-salim-h-15/</link>
<pubDate>Thu, 01 Jan 2015 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalsijmms-salim-h-15/</guid>
<description></description>
</item>
<item>
<title>Visualization Oriented Spatiotemporal Urban Data Management and Retrieval</title>
<link>https://kaiqinchi.github.io/publication/dblp-confcikm-liono-ss-15/</link>
<pubDate>Thu, 01 Jan 2015 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confcikm-liono-ss-15/</guid>
<description></description>
</item>
<item>
<title>Day type classification using cell tower connectivity data from smartphones</title>
<link>https://kaiqinchi.github.io/publication/dblp-confmum-sadri-s-14/</link>
<pubDate>Wed, 01 Jan 2014 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confmum-sadri-s-14/</guid>
<description></description>
</item>
<item>
<title>Design and evaluation of smart wearable undergarment for monitoring physiological extremes in firefighting</title>
<link>https://kaiqinchi.github.io/publication/dblp-confiswc-salim-bphf-14/</link>
<pubDate>Wed, 01 Jan 2014 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confiswc-salim-bphf-14/</guid>
<description></description>
</item>
<item>
<title>EnviS Tag, Scan, View: A Location-Based App for Visualizing Spatio-temporal Data from Sensor Cloud</title>
<link>https://kaiqinchi.github.io/publication/dblp-confmdm-salim-ppsws-14/</link>
<pubDate>Wed, 01 Jan 2014 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confmdm-salim-ppsws-14/</guid>
<description></description>
</item>
<item>
<title>Genetic Programming for Channel Selection from Multi-stream Sensor Data with Application on Learning Risky Driving Behaviours</title>
<link>https://kaiqinchi.github.io/publication/dblp-confseal-dau-sxsc-14/</link>
<pubDate>Wed, 01 Jan 2014 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confseal-dau-sxsc-14/</guid>
<description></description>
</item>
<item>
<title>Navigating multiple augmented reality overlays through occlusion-based triggers</title>
<link>https://kaiqinchi.github.io/publication/dblp-confmum-thakar-sg-14/</link>
<pubDate>Wed, 01 Jan 2014 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confmum-thakar-sg-14/</guid>
<description></description>
</item>
<item>
<title>Phone based fall detection by genetic programming</title>
<link>https://kaiqinchi.github.io/publication/dblp-confmum-dau-sshh-14/</link>
<pubDate>Wed, 01 Jan 2014 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confmum-dau-sshh-14/</guid>
<description></description>
</item>
<item>
<title>VDIM: vector-based diffusion and interpolation matrix for computing region-based crowdsourced ratings: towards safe route selection for human navigation</title>
<link>https://kaiqinchi.github.io/publication/dblp-confmum-elsmore-ssh-14/</link>
<pubDate>Wed, 01 Jan 2014 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confmum-elsmore-ssh-14/</guid>
<description></description>
</item>
<item>
<title>Visualization of wireless sensor networks using ZigBee's Received Signal Strength Indicator (RSSI) for indoor localization and tracking</title>
<link>https://kaiqinchi.github.io/publication/dblp-confpercom-salim-wsppsw-14/</link>
<pubDate>Wed, 01 Jan 2014 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confpercom-salim-wsppsw-14/</guid>
<description></description>
</item>
<item>
<title>emoTicSpace: when the built environments get emotional..</title>
<link>https://kaiqinchi.github.io/publication/dblp-confhuc-salim-k-13/</link>
<pubDate>Tue, 01 Jan 2013 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confhuc-salim-k-13/</guid>
<description></description>
</item>
<item>
<title>Learning Risky Driver Behaviours from Multi-Channel Data Streams Using Genetic Programming</title>
<link>https://kaiqinchi.github.io/publication/dblp-confausai-xie-ssbsb-13/</link>
<pubDate>Tue, 01 Jan 2013 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confausai-xie-ssbsb-13/</guid>
<description></description>
</item>
<item>
<title>Lumina: a soft kinetic material for morphing architectural skins and organic user interfaces</title>
<link>https://kaiqinchi.github.io/publication/dblp-confhuc-khoo-s-13/</link>
<pubDate>Tue, 01 Jan 2013 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confhuc-khoo-s-13/</guid>
<description></description>
</item>
<item>
<title>Form fostering: A novel design approach for interacting with parametric models in the embodied virtuality</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalsitcon-salim-mb-11/</link>
<pubDate>Sat, 01 Jan 2011 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalsitcon-salim-mb-11/</guid>
<description></description>
</item>
<item>
<title>Transafe: a crowdsourced mobile platform for crime and safety perception management</title>
<link>https://kaiqinchi.github.io/publication/dblp-confistas-hamilton-scc-11/</link>
<pubDate>Sat, 01 Jan 2011 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confistas-hamilton-scc-11/</guid>
<description></description>
</item>
<item>
<title>Transafe: a crowdsourced mobile platform for crime and safety perception management</title>
<link>https://kaiqinchi.github.io/publication/dblp-journalssigcas-hamilton-scc-11/</link>
<pubDate>Sat, 01 Jan 2011 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-journalssigcas-hamilton-scc-11/</guid>
<description></description>
</item>
<item>
<title>Software Openness: Evaluating Parameters of Parametric Modeling Tools to Support Creativity and Multidisciplinary Design Integration</title>
<link>https://kaiqinchi.github.io/publication/dblp-conficcsa-salim-b-10/</link>
<pubDate>Fri, 01 Jan 2010 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-conficcsa-salim-b-10/</guid>
<description></description>
</item>
<item>
<title>Towards Adaptive Mobile Mashups: Opportunities for Designing Effective Persuasive Technology on the Road</title>
<link>https://kaiqinchi.github.io/publication/dblp-confaina-salim-10/</link>
<pubDate>Fri, 01 Jan 2010 00:00:00 +1100</pubDate>
<guid>https://kaiqinchi.github.io/publication/dblp-confaina-salim-10/</guid>
<description></description>
</item>
<item>
<title>Road Intersections as Pervasive Computing Environments: Towards a Multiagent Real-Time Collision Warning System</title>
<link>https://kaiqinchi.github.io/publication/dblp-confpercom-salim-cil-08/</link>
<pubDate>Tue, 01 Jan 2008 00:00:00 +1100</pubDate>