Delay-rate tradeoff for ergodic interference alignment in the Gaussian case

In interference alignment, users sharing a wireless channel are each able to achieve data rates of up to half of the non-interfering channel capacity, no matter the number of users. In an ergodic setting, this is achieved by pairing complementary channel realizations in order to amplify signals and cancel interference. However, this scheme has the possibility for large delays in decoding message symbols. We show that delay can be mitigated by using outputs from potentially more than two channel realizations, although data rate may be reduced. We further demonstrate the tradeoff between rate and delay via a time-sharing strategy. Our analysis considers Gaussian channels; an extension to finite field channels is also possible.Comment: 7 pages, 2 figures, presented at 48th Allerton Conference on Communication Control and Computing, 2010. Includes appendix detailing Markov chain analysi

Structural Analysis and Control of a Model of Two-site Electricity and Heat Supply

This paper introduces a control problem of regulation of energy flows in a two-site electricity and heat supply system, where two Combined Heat and Power (CHP) plants are interconnected via electricity and heat flows. The control problem is motivated by recent development of fast operation of CHP plants to provide ancillary services of power system on the order of tens of seconds to minutes. Due to the physical constraint that the responses of the heat subsystem are not necessary as fast as those of the electric subsystem, the target controlled state is not represented by any isolated equilibrium point, implying that stability of the system is lost in the long-term sense on the order of hours. In this paper, we first prove in the context of nonlinear control theory that the state-space model of the two-site system is non-minimum phase due to nonexistence of isolated equilibrium points of the associated zero dynamics.Instead, we locate a one-dimensional invariant manifold that represents the target controlled flows completely. Then, by utilizing a virtual output under which the state-space model becomes minimum phase, we synthesize a controller that achieves not only the regulation of energy flows in the short-term regime but also stabilization of an equilibrium point in the long-term regime. Effectiveness of the synthesized controller is established with numerical simulations with a practical set of model parameters

A REEXAMINATION OF FRACTIONAL INTEGRATING DYNAMICS IN FOREIGN CURRENCY MARKETS

This paper reexamines foreign currency markets for evidence of fractional integration, and extends the extant literature in several important dimensions. First, we utilize a new semiparametric wavelet-based estimator, which is far superior to the more prevalent GPH estimator on the basis of mean squared error. Second, we utilize a broader and longer sample, which better facilitates the detection of long memory dynamics. Our analysis yields interesting empirical results that contrast with other recent studies. In particular, we find new evidence that a large proportion (fourteen out of nineteen) of exchange rate series display evidence of long memory, with little variation over alternative sample periods.Financial Economics,

Etanercept in the treatment of plaque psoriasis

Etanercept is approved for the treatment of moderate to severe plaque psoriasis at a dose of 50 mg twice weekly for 3 months followed by a maintenance dosage of 50 mg weekly thereafter. Clinical studies have shown excellent efficacy, favorable benefit to side-effects ratio, and safe long-term usage. Extensive information on safety is available as etanercept has been used for many years for other indications such as rheumatoid arthritis and psoriatic arthritis and is the first of the tumor necrosis factor antagonists to gain approval in psoriasis

Towards Sustainable Water Supply: Schematic Development of Big Data Collection Using Internet of Things (IoT)

Water supply systems in the United States connect raw water sources to hundreds of millions of water consumers through humongous infrastructure that include approximately one million miles of buried water mains and service connections and thousands of treatment facilities and appurtenances. This enormous set-up is currently operated by more than 170,000 public water systems. Sustainability of the water supply system faces several imminent challenges such as: 1) increasing water main breaks, 2) decreasing fresh water resources, 3) untraceable non-revenue water use, and 4) increasing water demands. However, current water supply management practices are not capable of providing fundamental solutions to the issues identified above. Big Data is a new technical concept to collect massive amounts of relevant data from sensors installed to monitor structural condition, usage, and system performance. This Big Data concept can be realized by deploying Internet of Things (IoT) technology throughout the water supply infrastructure and consumers’ usage. This paper presents a schematic development of IoT application for Big Data collection through a myriad of water clients. The scheme consists of downstream and upstream data collection using Wireless Sensor Network (WSN) technologies connecting to IoT. Downstream data shall provide water usage and performance data to clients and upstream data is similar to traditional SCADA and Automated Meter Reading (AMR) systems. Ultimately, all data will be converged to build a Big Data collection system where data mining identifies 1) local and system performances including pressure and flow, 2) non-revenue and illegitimate water consumption, and 3) locations and quantity of water breaks and water losses. The goal of this development is to enable both utilities and consumers to proactively manage their water usage and achieve higher levels of sustainability in water supply