ORCID Profile
0000-0003-2698-3319
Current Organisation
Zhejiang University of Technology
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Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2020
Publisher: Hindawi Limited
Date: 2013
DOI: 10.1155/2013/947808
Abstract: Cyber-Physical Systems (CPS) that collect, exchange, manage information, and coordinate actions are an integral part of the Smart Grid. In addition, Quality of Service (QoS) provisioning in CPS, especially in the wireless sensor/actuator networks, plays an essential role in Smart Grid applications. IEEE 802.15.4, which is one of the most widely used communication protocols in this area, still needs to be improved to meet multiple QoS requirements. This is because IEEE 802.15.4 slotted Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) employs static parameter configuration without supporting differentiated services and network self-adaptivity. To address this issue, this paper proposes a priority-based Service Differentiated and Adaptive CSMA/CA (SDA-CSMA/CA) algorithm to provide differentiated QoS for various Smart Grid applications as well as dynamically initialize backoff exponent according to traffic conditions. Simulation results demonstrate that the proposed SDA-CSMA/CA scheme significantly outperforms the IEEE 802.15.4 slotted CSMA/CA in terms of effective data rate, packet loss rate, and average delay.
Publisher: Springer Science and Business Media LLC
Date: 02-2011
Publisher: Springer New York
Date: 19-11-2010
Publisher: Public Library of Science (PLoS)
Date: 05-02-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2018
Publisher: IEEE
Date: 12-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: Springer Science and Business Media LLC
Date: 28-05-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2020
Publisher: Elsevier BV
Date: 02-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Publisher: Elsevier BV
Date: 02-2020
DOI: 10.1016/J.SCHRES.2019.10.026
Abstract: Voice-hearing experiences can be distressing and impairing, and existing psychological treatments show modest effectiveness. Ecological momentary assessment and intervention (EMA/I) are two promising approaches which may be used as digital tools to support and enhance existing psychological therapies. The aim of this study was to investigate the potential clinical utility of smartphone-based EMA/I in a blended, coping focused therapy for voice-hearing experiences. This pilot RCT focused on feasibility, acceptability and preliminary estimations of efficacy. Thirty-four participants with persisting and distressing voices were randomised to receive the four-session intervention along-side treatment-as-usual (TAU) or TAU-only. Findings supported the feasibility and acceptability of the approach, with good engagement and satisfaction rates, and clinical outcomes showed the intervention holds promise for improving coping, overall severity of voices and to some degree their negative impact. This is the first examination of the use of EMA/I in a blended therapy for psychotic experiences, with findings suggesting these technologies show promise as clinical tools.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2019
Publisher: Elsevier BV
Date: 2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2018
Publisher: Association for Computing Machinery (ACM)
Date: 30-05-2020
DOI: 10.1145/3385530
Abstract: This article elaborates how to identify and evaluate causal factors to improve scientific impact. Currently, analyzing scientific impact can be beneficial to various academic activities including funding application, mentor recommendation, discovering potential cooperators, and the like. It is universally acknowledged that high-impact scholars often have more opportunities to receive awards as an encouragement for their hard work. Therefore, scholars spend great efforts in making scientific achievements and improving scientific impact during their academic life. However, what are the determinate factors that control scholars’ academic success? The answer to this question can help scholars conduct their research more efficiently. Under this consideration, our article presents and analyzes the causal factors that are crucial for scholars’ academic success. We first propose five major factors including article-centered factors, author-centered factors, venue-centered factors, institution-centered factors, and temporal factors. Then, we apply recent advanced machine learning algorithms and jackknife method to assess the importance of each causal factor. Our empirical results show that author-centered and article-centered factors have the highest relevancy to scholars’ future success in the computer science area. Additionally, we discover an interesting phenomenon that the h -index of scholars within the same institution or university are actually very close to each other.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2019
Publisher: IEEE
Date: 07-2010
Publisher: Springer Science and Business Media LLC
Date: 17-06-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2016
DOI: 10.1109/MCC.2016.82
Publisher: Public Library of Science (PLoS)
Date: 29-03-2018
Publisher: Springer Science and Business Media LLC
Date: 04-05-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Springer Science and Business Media LLC
Date: 15-12-2018
Publisher: IEEE
Date: 05-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2018
Publisher: Association for Computing Machinery (ACM)
Date: 24-02-2023
DOI: 10.1145/3564594
Abstract: Predicting traffic accidents can help traffic management departments respond to sudden traffic situations promptly, improve drivers’ vigilance, and reduce losses caused by traffic accidents. However, the causality of traffic accidents is complex and difficult to analyze. Most existing traffic accident prediction methods do not consider the dynamic spatio-temporal correlation of traffic data, which leads to unsatisfactory prediction accuracy. To address this issue, we propose a multi-task learning framework (TAP) based on the Spatio-temporal Variational Graph Auto-Encoders (ST-VGAE) for traffic accident profiling. We firstly capture the dynamic spatio-temporal correlation of traffic conditions through a spatio-temporal graph convolutional encoder and embed it as a low-latitude vector. Then, we use a multi-task learning scheme to combine external factors to generate the traffic accident profiling. Furthermore, we propose a traffic accident profiling application framework based on edge computing. This method increases the speed of calculation by offloading the calculation of traffic accident profiling to edge nodes. Finally, the experimental results on real datasets demonstrate that TAP outperforms other state-of-the-art baselines.
Publisher: MDPI AG
Date: 25-06-2017
DOI: 10.3390/INFO8030073
Publisher: Springer Science and Business Media LLC
Date: 19-04-2017
Publisher: Springer Science and Business Media LLC
Date: 10-12-2014
Publisher: Springer Science and Business Media LLC
Date: 20-10-2013
Publisher: Springer Science and Business Media LLC
Date: 27-06-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Publisher: Elsevier BV
Date: 11-2019
Publisher: Springer International Publishing
Date: 2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2020
Publisher: Elsevier BV
Date: 11-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: Oxford University Press (OUP)
Date: 13-03-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: Elsevier BV
Date: 07-2014
Publisher: Springer Science and Business Media LLC
Date: 07-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2019
Publisher: National Library of Serbia
Date: 2016
Publisher: Elsevier BV
Date: 04-2019
Publisher: IEEE
Date: 08-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2013
Publisher: SAGE Publications
Date: 08-2015
DOI: 10.1155/2015/671012
Abstract: Socially aware networking (SAN) provides a new paradigm for intermittently connected networks which exploits social properties of mobile users to guide the design of protocols. In SAN, data forwarding performance will be degraded dramatically due to the existence of users' selfish behaviors. To address the selfishness problem, barter-based incentive scheme is a fair approach in which two encounter nodes exchange the same amount of data with one another. However, it is a challenging issue for nodes to decide when two nodes contact and how many messages they will exchange for their next contacts. We consider this problem as a resource allocation problem and propose a community-based Barter incentive scheme for SAN paradigm (Com-BIS). In this method, network nodes are grouped into communities and they allocate their forwarding services for different communities optimally using 0-1 knapsack algorithm. The simulation results show that Com-BIS stimulates selfish nodes to cooperate in data delivery for other nodes effectively which improves the forwarding performance considerably.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Springer Science and Business Media LLC
Date: 10-08-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Publisher: Springer Science and Business Media LLC
Date: 10-12-2018
No related grants have been discovered for Xiangjie Kong.