Control design for interconnected power systems with OLTCs via robust decentralized control

This paper addresses the problem of designing a decentralized control of interconnected power systems, with OLTC and SVCs, under large changes in real and reactive loads that cause large structural changes in the system model. In addition to this, small changes in load are regulated by small disturbance controllers whose gains are adjusted for variations in power system model due to large changes in loads. The only feedback needed by subsystem controllers is the state of the subsystem itself. The design is carried out within a large-scale Markov jump parameter systems framework. In this paper, unlike other control schemes, OLTC transformers are used to damp power-angle oscillations. Simulation results are presented to demonstrate the performance of the designed controller. © 2006 IEEE

Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation

Image-to-image translation has been made much progress with embracing Generative Adversarial Networks (GANs). However, it's still very challenging for translation tasks that require high quality, especially at high-resolution and photorealism. In this paper, we present Discriminative Region Proposal Adversarial Networks (DRPAN) for high-quality image-to-image translation. We decompose the procedure of image-to-image translation task into three iterated steps, first is to generate an image with global structure but some local artifacts (via GAN), second is using our DRPnet to propose the most fake region from the generated image, and third is to implement "image inpainting" on the most fake region for more realistic result through a reviser, so that the system (DRPAN) can be gradually optimized to synthesize images with more attention on the most artifact local part. Experiments on a variety of image-to-image translation tasks and datasets validate that our method outperforms state-of-the-arts for producing high-quality translation results in terms of both human perceptual studies and automatic quantitative measures.Comment: ECCV 201

Design of switching damping controllers for power systems based on a Markov jump parameter system approach

The application of a new technique, based on the theory of Markov Jump Parameter Systems (MJPS), to the problem of designing controllers to damp power system oscillations is presented in this paper. This problem is very difficult to address, mainly because these controllers are required to have an output feedback decentralized structure. The technique relies on the statistical knowledge about the system operating conditions to provide less conservative controllers than other modern robust control approaches. The influence of the system interconnections over its modes of oscillation is reduced by means of a proper control design formulation involving Integral Quadratic Constraints. The discrete nature of some typical events in power systems (such as line tripping or load switching) is adequately modeled by the MJPS approach, therefore allowing the controller to withstand such abrupt changes in the operating conditions of the system, as shown in the results. © 2006 IEEE

A reduced-reference perceptual image and video quality metric based on edge preservation

In image and video compression and transmission, it is important to rely on an objective image/video quality metric which accurately represents the subjective quality of processed images and video sequences. In some scenarios, it is also important to evaluate the quality of the received video sequence with minimal reference to the transmitted one. For instance, for quality improvement of video transmission through closed-loop optimisation, the video quality measure can be evaluated at the receiver and provided as feedback information to the system controller. The original image/video sequence-prior to compression and transmission-is not usually available at the receiver side, and it is important to rely at the receiver side on an objective video quality metric that does not need reference or needs minimal reference to the original video sequence. The observation that the human eye is very sensitive to edge and contour information of an image underpins the proposal of our reduced reference (RR) quality metric, which compares edge information between the distorted and the original image. Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art RR metric. © 2012 Martini et al

Satellite estimates of wide-range suspended sediment concentrations in Changjiang (Yangtze) estuary using MERIS data

The Changjiang (Yangtze) estuarine and coastal waters are characterized by suspended sediments over a wide range of concentrations from 20 to 2,500 mg l-1. Suspended sediment plays important roles in the estuarine and coastal system and environment. Previous algorithms for satellite estimates of suspended sediment concentration (SSC) showed a great limitation in that only low to moderate concentrations (up to 50 mg l-1) could be reliably estimated. In this study, we developed a semi-empirical radiative transfer (SERT) model with physically based empirical coefficients to estimate SSC from MERIS data over turbid waters with a much wider range of SSC. The model was based on the Kubelka–Munk two-stream approximation of radiative transfer theory and calibrated using datasets from in situ measurements and outdoor controlled tank experiments. The results show that the sensitivity and saturation level of remote-sensing reflectance to SSC are dependent on wavelengths and SSC levels. Therefore, the SERT model, coupled with a multi-conditional algorithm scheme adapted to satellite retrieval of wide-range SSC, was proposed. Results suggest that this method is more effective and accurate in the estimation of SSC over turbid water

Decentralized Estimation over Orthogonal Multiple-access Fading Channels in Wireless Sensor Networks - Optimal and Suboptimal Estimators

Optimal and suboptimal decentralized estimators in wireless sensor networks (WSNs) over orthogonal multiple-access fading channels are studied in this paper. Considering multiple-bit quantization before digital transmission, we develop maximum likelihood estimators (MLEs) with both known and unknown channel state information (CSI). When training symbols are available, we derive a MLE that is a special case of the MLE with unknown CSI. It implicitly uses the training symbols to estimate the channel coefficients and exploits the estimated CSI in an optimal way. To reduce the computational complexity, we propose suboptimal estimators. These estimators exploit both signal and data level redundant information to improve the estimation performance. The proposed MLEs reduce to traditional fusion based or diversity based estimators when communications or observations are perfect. By introducing a general message function, the proposed estimators can be applied when various analog or digital transmission schemes are used. The simulations show that the estimators using digital communications with multiple-bit quantization outperform the estimator using analog-and-forwarding transmission in fading channels. When considering the total bandwidth and energy constraints, the MLE using multiple-bit quantization is superior to that using binary quantization at medium and high observation signal-to-noise ratio levels

A survey on health-promoting lifestyle among community-dwelling older people with hypertension in Macau

2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Possible mechanisms of host resistance to Haemonchus contortus infection in sheep breeds native to the Canary Islands

Haemonchus contortus appears to be the most economically important helminth parasite for small ruminant production in many regions of the world. The two sheep breeds native to the Canary Islands display distinctly different resistant phenotypes under both natural and experimental infections. Canaria Hair Breed (CHB) tends to have significantly lower worm burden and delayed and reduced egg production than the susceptible Canaria Sheep (CS). To understand molecular mechanisms underlying host resistance, we compared the abomasal mucosal transcriptome of the two breeds in response to Haemonchus infection using RNAseq technology. The transcript abundance of 711 and 50 genes were significantly impacted by infection in CHB and CS, respectively (false discovery rate <0.05) while 27 of these genes were significantly affected in both breeds. Likewise, 477 and 16 Gene Ontology (GO) terms were significantly enriched in CHB and CS, respectively (P < 1.0 × 10(−4)). A broad range of mechanisms have evolved in resistant CHB to provide protection against the parasite. Our findings suggest that readily inducible acute inflammatory responses, complement activation, accelerated cell proliferation and subsequent tissue repair, and immunity directed against parasite fecundity all contributed to the development of host resistance to parasitic infection in the resistant breed