Permutations Containing Many Patterns

It is shown that the maximum number of patterns that can occur in a permutation of length $n$ is asymptotically $2^n$. This significantly improves a previous result of Coleman

Prospects for detecting the Rossiter-McLaughlin effect of Earth-like planets: the test case of TRAPPIST-1b and c

The Rossiter-McLaughlin effect is the principal method of determining the sky-projected spin--orbit angle ($\beta$) of transiting planets. Taking the example of the recently discovered TRAPPIST-1 system, we explore how ultracool dwarfs facilitate the measurement of the spin--orbit angle for Earth-sized planets by creating an effect that can be an order of magnitude more ample than the Doppler reflex motion caused by the planet if the star is undergoing rapid rotation. In TRAPPIST-1's case we expect the semi-amplitudes of the Rossiter-McLaughlin effect to be $40-50$ m/s for the known transiting planets. Accounting for stellar jitter expected for ultracool dwarfs, instrumental noise, and assuming radial velocity precisions both demonstrated and anticipated for upcoming near-infrared spectrographs, we quantify the observational effort required to measure the planets' masses and spin--orbit angles. We conclude that if the planetary system is well-aligned then $\beta$ can be measured to a precision of $\lesssim 10^{\circ}$ if the spectrograph is stable at the level of 2 m/s. We also investigate the measure of $\Delta \beta$, the mutual inclination, when multiple transiting planets are present in the system. Lastly, we note that the rapid rotation rate of many late M-dwarfs will amplify the Rossiter-McLaughlin signal to the point where variations in the chromatic Rossiter-McLaughlin effect from atmospheric absorbers should be detectable.Comment: 11 pages, 4 figures. Accepted to MNRAS. Comments welcom

A unified model of the electrical power network

Traditionally, the different infrastructure layers, technologies and management activities associated with the design, control and protection operation of the Electrical Power Systems have been supported by numerous independent models of the real world network. As a result of increasing competition in this sector, however, the integration of technologies in the network and the coordination of complex management processes have become of vital importance for all electrical power companies. The aim of the research outlined in this paper is to develop a single network model which will unify the generation, transmission and distribution infrastructure layers and the various alternative implementation technologies. This 'unified model' approach can support ,for example, network fault, reliability and performance analysis. This paper introduces the basic network structures, describes an object-oriented modelling approach and outlines possible applications of the unified model

Update of an early warning fault detection method using artificial intelligence techniques

This presentation describes a research investigation to access the feasibility of using an Artificial Intelligence (AI) method to predict and detect faults at an early stage in power systems. An AI based detector has been developed to monitor and predict faults at an early stage on particular sections of power systems. The detector for this early warning fault detection device only requires external measurements taken from the input and output nodes of the power system. The AI detection system is capable of rapidly predicting a malfunction within the system. Artificial Neural Networks (ANNs) are being used as the core of the fault detector. In an earlier paper [11], a computer simulated medium length transmission line has been tested by the detector and the results clearly demonstrate the capability of the detector. Today’s presentation considers a case study illustrating the suitability of this AI Technique when applied to a distribution transformer. Furthermore, an evolutionary optimisation strategy to train ANNs is also briefly discussed in this presentation, together with a ‘crystal ball’ view of future developments in the operation and monitoring of transmission systems in the next millennium

Power system fault prediction using artificial neural networks

The medium term goal of the research reported in this paper was the development of a major in-house suite of strategic computer aided network simulation and decision support tools to improve the management of power systems. This paper describes a preliminary research investigation to access the feasibility of using an Artificial Intelligence (AI) method to predict and detect faults at an early stage in power systems. To achieve this goal, an AI based detector has been developed to monitor and predict faults at an early stage on particular sections of power systems. The detector only requires external measurements taken from the input and output nodes of the power system. The AI detection system is capable of rapidly predicting a malfunction within the system . Simulation will normally take place using equivalent circuit representation. Artificial Neural Networks (ANNs) are used to construct a hierarchical feed-forward structure which is the most important component in the fault detector. Simulation of a transmission line (2-port circuit ) has already been carried out and preliminary results using this system are promising. This approach provided satisfactory results with accuracy of 95% or higher

Early warning fault detection using artificial intelligent methods

This paper describes a research investigation to access the feasibility of using an Artificial Intelligence (AI) method to predict and detect faults at an early stage in power systems. An AI based detector has been developed to monitor and predict faults at an early stage on particular sections of power systems. The detector for this early warning fault detection device only requires external measurements taken from the input and output nodes of the power system. The AI detection system is capable of rapidly predicting a malfunction within the system. Artificial Neural Networks (ANNs) are being used as the core of the fault detector. A simulated medium length transmission line has been tested by the detector and the results demonstrate the capability of the detector. Furthermore, comments on an evolutionary technique as the optimisation strategy for ANNs are included in this paper

"The War for the Fare": How Driver Compensation Affects Bus System Performance

Two systems of bus driver compensation exist in Santiago, Chile. Most drivers are paid per passenger transported, while a second system compensates other drivers with a fixed wage. Compared with fixed-wage drivers, per-passenger drivers have incentives to engage in "La Guerra por el Boleto" ("The War for the Fare"), in which drivers change their driving patterns to compete for passengers. This paper takes advantage of a natural experiment provided by the coexistence of these two compensation schemes on similar routes in the same city. Using data on intervals between bus arrivals, we find that the fixed-wage contract leads to more bunching of buses, and hence longer average passenger wait times. The per-passenger drivers are assisted by a group of independent information intermediaries called "sapos" who earn their living by standing at bus stops, recording arrival times, and selling the information to subsequent drivers who drive past. We find that a typical bus passenger in Santiago waits roughly 10% longer for a bus on a fixed-wage route relative to an incentive-contract route. However, the incentives also lead drivers to drive noticeably more aggressively, causing approximately 67% more accidents per kilometer driven. Our results have implications for the design of incentives in public transportation systems.

Nematic Order by Disorder in Spin-2 BECs

The effect of quantum and thermal fluctuations on the phase diagram of spin-2 BECs is examined. They are found to play an important role in the nematic part of the phase diagram, where a mean-field treatment of two-body interactions is unable to lift the accidental degeneracy between nematic states. Quantum and thermal fluctuations resolve this degeneracy, selecting the uniaxial nematic state, for scattering lengths $a_4>a_2$, and the square biaxial nematic state for $a_4<a_2$. Paradoxically, the fluctuation induced order is stronger at higher temperatures, for a range of temperatures below $T_c$. For the experimentally relevant cases of spin-2 $^{87}$Rb and $^{23}$Na, we argue that such fluctuations could successfully compete against other effects like the quadratic Zeeman field, and stabilize the uniaxial phase for experimentally realistic conditions. A continuous transition of the Ising type from uniaxial to square biaxial order is predicted on raising the magnetic field. These systems present a promising experimental opportunity to realize the `order by disorder' phenomenon.Comment: 5 pages, 4 figures; 1 reference and 1 minor correctio

Texas Business Review, January 1976

The Business Situation in Texas; The Last Hundred Years; The Next Hundred Years; Electric Funds Transference: Development and Prospects; Texas Construction: Four Decades of ChangeBureau of Business Researc