Recent Submissions

  • Proof-of-stake consensus mechanisms for future blockchain networks : fundamentals, applications and opportunities 

    Nguyen, Cong T.; Hoang, Dinh Thai; Nguyen, Diep N.; Niyato, Dusit; Nguyen, Huynh Tuong; Dutkiewicz, Eryk (2019)
    The rapid development of blockchain technology and their numerous emerging applications has received huge attention in recent years. The distributed consensus mechanism is the backbone of a blockchain network. It plays a ...
  • A power series approach for hybrid-duplex UAV communication systems under rician shadowed fading 

    Tan, Ernest Zheng Hui; Madhukumar, A. S.; Sirigina, Rajendra Prasad; Krishna, Anoop Kumar (2019)
    A hybrid-duplex (HBD) UAV communication system (UCS), i.e., HBD-UCS, to improve spectrum utilization is investigated in this work. By considering the combined effect of fading and shadowing, a comprehensive outage probability ...
  • One-step robust deep learning phase unwrapping 

    Wang, Kaiqiang; Li, Ying; Kemao, Qian; Di, Jianglei; Zhao, Jianlin (2019)
    Phase unwrapping is an important but challenging issue in phase measurement. Even with the research efforts of a few decades, unfortunately, the problem remains not well solved, especially when heavy noise and aliasing ...
  • Phase retrieval for high-speed 3D measurement using binary patterns with projector defocusing 

    Zheng, Dongliang; Kemao, Qian; Da, Feipeng; Seah, Hock Soon (2017)
    Recent digital technology allows binary patterns to be projected with a very high speed, which shows great potential for high-speed 3D measurement. However, how to retrieve an accurate phase with an even faster speed is ...
  • Towards personalized maps : mining user preferences from geo-textual data 

    Zhao, Kaiqi; Liu, Yiding; Yuan, Quan; Chen, Lisi; Chen, Zhida; Cong, Gao (2016)
    Rich geo-textual data is available online and the data keeps increasing at a high speed. We propose two user behavior models to learn several types of user preferences from geo-textual data, and a prototype system on top ...
  • Revisiting the stop-and-stare algorithms for influence maximization 

    Huang, Keke; Wang, Sibo; Bevilacqua, Glenn; Xiao, Xiaokui; Lakshmanan, Laks V. S. (2017)
    Influence maximization is a combinatorial optimization problem that finds important applications in viral marketing, feed recommendation, etc. Recent research has led to a number of scalable approximation algorithms for ...
  • Summarizing static and dynamic big graphs 

    Khan, Arijit; Bhowmick, Sourav Sara; Bonchi, Francesco (2017)
    Large-scale, highly-interconnected networks pervade our society and the natural world around us, including the World Wide Web, social networks, knowledge graphs, genome and scientific databases, medical and government ...
  • PICASSO : exploratory search of connected subgraph substructures in graph databases 

    Huang, Kai; Bhowmick, Sourav Sara; Zhou, Shuigeng; Choi, Byron (2017)
    Recently, exploratory search has received much attention in information retrieval and database fields. This search paradigm assists users who do not have a clear search intent and are unfamiliar with the underlying data ...
  • An experimental evaluation of point-of-interest recommendation in location-based social networks 

    Liu, Yiding; Pham, Tuan-Anh Nguyen; Cong, Gao; Yuan, Quan (2017)
    Point-of-interest (POI) recommendation is an important service to Location-Based Social Networks (LBSNs) that can benefit both users and businesses. In recent years, a number of POI recommender systems have been proposed, ...
  • A system for region search and exploration 

    Feng, Kaiyu; Zhao, Kaiqi; Liu, Yiding; Cong, Gao (2016)
    With the increasing popularity of mobile devices and location based services, massive amount of geo-textual data (e.g., geo-tagged tweets) is being generated everyday. Compared with traditional spatial data, the textual ...
  • Medusa : a parallel graph processing system on graphics processors 

    Zhong, Jianlong; He, Bingsheng (2014)
    Medusa is a parallel graph processing system on graphics processors (GPUs). The core design of Medusa is to enable developers to leverage the massive parallelism and other hardware features of GPUs by writing sequential ...
  • Wave forecasting using meta-cognitive interval type-2 fuzzy inference system 

    Anh, Nguyen; Prasad, Mukesh; Srikanth, Narasimalu; Sundaram, Suresh (2018)
    Renewable energy is fast becoming a mainstay in today’s energy scenario. One of the important sources of renewable energy is the wave energy, in addition to wind, solar, tidal, etc. Wave prediction/forecasting is consequently ...
  • A fast and self-adaptive on-line learning detection system 

    Prasad, Mukesh; Zheng, Ding-Rong; Mery, Domingo; Puthal, Deepak; Sundaram, Suresh; Lin, Chin-Teng (2018)
    This paper proposes a method to allow users to select target species for detection, generate an initial detection model by selecting a small piece of image sample and as the movie plays, continue training this detection ...
  • Online video streaming for human tracking based on weighted resampling particle filter 

    Prasad, Mukesh; Chang, Liang-Cheng; Gupta, Deepak; Pratama, Mahardhika; Sundaram, Suresh; Lin, Chin-Teng (2018)
    This paper proposes a weighted resampling method for particle filter which is applied for human tracking on active camera. The proposed system consists of three major parts which are human detection, human tracking, and ...
  • Wind speed intervals prediction using meta-cognitive approach 

    Anh, Nguyen; Prasad, Mukesh; Srikanth, Narasimalu; Sundaram, Suresh (2018)
    In this paper, an interval type-2 neural fuzzy inference system and its meta-cognitive learning algorithm for wind speed prediction is proposed. Interval type-2 neuro-fuzzy system is capable of handling uncertainty associated ...
  • Speed and energy optimized quasi-delay-insensitive block carry lookahead adder 

    Balasubramanian, Padmanabhan; Maskell, Douglas Leslie; Mastorakis, N. E. (2019)
    We present a new asynchronous quasi-delay-insensitive (QDI) block carry lookahead adder with redundant carry (BCLARC) realized using delay-insensitive dual-rail data encoding and 4-phase return-to-zero (RTZ) and 4-phase ...
  • Automated detection and localization of myocardial infarction with staked sparse autoencoder and TreeBagger 

    Zhang, Jieshuo; Lin, Feng; Xiong, Peng; Du, Haiman; Zhang, Hong; Liu, Ming; Hou, Zengguang; Liu, Xiuling (2019)
    Novel techniques in deep learning networks are proposed for the staked sparse autoencoder (SAE) and the bagged decision tree (TreeBagger), achieving significant improvement in detection and localization of myocardial ...
  • A revenue-maximizing bidding strategy for demand-side platforms 

    Wang, Tengyun; Yang, Haizhi; Yu, Han; Zhou, Wenjun; Liu, Yang; Song, Hengjie (2019)
    In real-time bidding (RTB) systems for display advertising, a demand-side platform (DSP) serves as an agent for advertisers and plays an important role in competing for online advertising spaces by placing proper bidding ...
  • Virtual storage-based DSM with error-driven prediction modulation for microgrids 

    Lee, Xuecong; Yan, Mengxuan; Xu, Fang Yuan; Wang, Yue; Fan, Yiliang; Lee, Zekai; Wen, Yonggang; Mohammad Shahidehpour; Lai, Loi Lei (2019)
    Microgrids consider adjustable loads in demand-side management (DSM), which respond to dynamic market prices. A reliable DSM strategy relies on load forecasting techniques in day-ahead (DA) scheduling. This paper applies ...
  • Evolutionary algorithms to optimize task scheduling problem for the IoT based bag-of-tasks application in cloud–fog computing environment 

    Nguyen, Binh Minh; Binh, Huynh Thi Thanh; Anh, Tran The; Son, Do Bao (2019)
    In recent years, constant developments in Internet of Things (IoT) generate large amounts of data, which put pressure on Cloud computing’s infrastructure. The proposed Fog computing architecture is considered the next ...

View more