List of Titles

Web-based collaborative document writing for emergency management

- Shatte, Adrian, Holdsworth, Jason, Lee, Ickjai

Authors: Shatte, Adrian , Holdsworth, Jason , Lee, Ickjai
Date: 2016
Type: Text , Conference proceedings
Relation: 49th Annual Hawaii International Conference on System Sciences HICSS 2016; 5-8 Jan. 2016; Koloa, HI, USA p. 217-226
Full Text: false
Reviewed:
Description: This paper describes the progress of our research into collaborative document writing for emergency management. Our focus is specifically on the use of web technologies to improve communication and shared knowledge in emergency situations. We present a prototype system built using Differential Synchronisation with flexible locking and user attribution features. Based on the past shortcomings of technologies and documents such as situation reports, we consider the potential benefits of a web-based system with flexible locking and user attribution for collaborative situation report writing.

Data-driven multi-resolution probabilistic energy and reserve bidding of wind power

- Hosseini, Seyyed, Toubeau, Jean-Francois, De Greve, Zacharie, Wang, Yi, Amjady, Nima, Vallee, Francois

Authors: Hosseini, Seyyed , Toubeau, Jean-Francois , De Greve, Zacharie , Wang, Yi , Amjady, Nima , Vallee, Francois
Date: 2023
Type: Text , Journal article
Relation: IEEE transactions on power systems Vol. 38, no. 1 (2023), p. 1-1
Full Text: false
Reviewed:
Description: The current wind farm control schemes qualify wind power producers (WPPs) to provide balancing services in complement to energy in modern electricity markets. In this context, WPPs are responsible for real-time deviations in both energy and reserve market floors, which are settled at different time scales. WPPs should adjust their output to cope with fast wind variations, which are critical in the balancing stage. In this paper, we devise a reliable high-temporal-resolution day-ahead bidding framework for WPPs considering the ultra-short-term wind stochasticity. To that end, the model for the bidding strategy is enriched with a probabilistic constraint controlling the confidence level on reserve bids to enhance the reliability of the offered capacity. Additionally, an original Auxiliary Classifier Wasserstein Generative Adversarial Network (ACWGAN) is proposed to generate high-temporal-resolution wind speed scenarios to be embedded into the bidding framework. The numerical results firstly confirm the superiority of the proposed ACWGAN over the other GAN-based alternatives. Then, the effectiveness of the proposed data-driven method over its single-resolution counterpart and other scenario representation methods is verified regarding the minimization of the negative impact of wind variability on WPPs' profit and reliability of offered reserve bids.

Background subtraction for real-time video analytics based on multi-hypothesis mixture-of-Gaussians

- Haque, Mahfuzul, Murshed, Manzur

Authors: Haque, Mahfuzul , Murshed, Manzur
Date: 2012
Type: Text , Conference proceedings
Relation: 2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance (AVSS), 18th-21st Sept, 2012. p1-6
Full Text: false
Reviewed:
Description: Robust background subtraction (BS) is essential for high quality foreground detection in most video analytics systems. Recent BS techniques achieve superior detection quality mostly by exploiting the complementary strengths of multiple background models or processing stages. Consequently, these techniques fail to meet the operational requirements of real-time video analytics due to high computational overhead where BS is just the primary processing task. In this paper, we propose a new BS technique, named multi-hypothesis mixture-of-Gaussians (MH-MOG), suitable for real-time video analytics. The essential idea is to maintain a single background model based on perception-aware mixture-of-Gaussians and then, generating multiple detection hypotheses with different processing bases. Finally, only during the detection stage, the complementary strengths of the hypotheses are exploited to achieve superior detection quality without significant computational overhead. Comprehensive experimental evaluation validates the efficacy of MH-MOG.

Tracking equilibrium point under real-time price-based residential demand response

- Ding, Tao, Qu, Ming, Amjady, Nima, Wang, Fengyu, Bo, Rui, Shahidehpour, Mohammad

Authors: Ding, Tao , Qu, Ming , Amjady, Nima , Wang, Fengyu , Bo, Rui , Shahidehpour, Mohammad
Date: 2021
Type: Text , Journal article
Relation: IEEE transactions on smart grid Vol. 12, no. 3 (2021), p. 2736-2740
Full Text: false
Reviewed:
Description: This letter proposes a model for tracking the equilibrium point of the real-time locational marginal price (LMP) based residential demand response program, where elastic demand is modeled as a monotonously decreasing linear function of the LMP. The resulting bi-level model contains both primary and dual variables, making it difficult to solve. Using duality, the dual model is formulated as a convex quadratic problem which is tractable to solve and find the global optimum. Furthermore, the condition for the existence of the equilibrium point is given. Numerical results on the IEEE 30-bus system verifies the effectiveness of the demand response model.

Error concealment for cloud-based and scalable video coding of hd videos

- Usman, Muhammad, He, Xiangjian, Lam, Kin-Man, Xu, Min, Bokhari, Syed, Chen, Jinjun, Jan, Mian

Authors: Usman, Muhammad , He, Xiangjian , Lam, Kin-Man , Xu, Min , Bokhari, Syed , Chen, Jinjun , Jan, Mian
Date: 2019
Type: Text , Journal article
Relation: IEEE transactions on cloud computing Vol. 7, no. 4 (2019), p. 975-987
Full Text: false
Reviewed:
Description: The encoding of HD videos faces two challenges: requirements for a strong processing power and a large storage space. One time-efficient solution addressing these challenges is to use a cloud platform and to use a scalable video coding technique to generate multiple video streams with varying bit-rates. Packet-loss is very common during the transmission of these video streams over the Internet and becomes another challenge. One solution to address this challenge is to retransmit lost video packets, but this will create end-to-end delay. Therefore, it would be good if the problem of packet-loss can be dealt with at the user's side. In this paper, we present a novel system that encodes and stores the videos using the Amazon cloud computing platform, and recover lost video frames on user side using a new Error Concealment (EC) technique. To efficiently utilize the computation power of a user's mobile device, the EC is performed based on a multiple-thread and parallel process. The simulation results clearly show that, on average, our proposed EC technique outperforms the traditional Block Matching Algorithm (BMA) and the Frame Copy (FC) techniques.

Showing items 1 - 5 of 5