A methodology for sensor modeling and placement optimization to support temperature monitoring

This paper presents a modeling and optimization approach for sensor placement in a building zone that supports reliable environment monitoring. © 2012 ACM.

Uses and abuses of fractal methodology in ecology

Fractals have found widespread application in a range of scientific fields, including ecology. This rapid growth has produced substantial new insights, but has also spawned confusion and a host of methodological problems. In this paper, we review the value of fractal methods, in particular for applications to spatial ecology, and outline potential pitfalls. Methods for measuring fractals in nature and generating fractal patterns for use in modelling are surveyed. We stress the limitations and the strengths of fractal models. Strictly speaking, no ecological pattern can be truly fractal, but fractal methods may nonetheless provide the most efficient tool available for describing and predicting ecological patterns at multiple scales.

A methodology to analyse the impact of offshore wind forecasting error on electricity markets

Currently wind power is dominated by onshore wind farms in the British Isles, but both the United Kingdom and the Republic of Ireland have high renewable energy targets, expected to come mostly from wind power. However, as the demand for wind power grows to ensure security of energy supply, as a potentially cheaper alternative to fossil fuels and to meet greenhouse gas emissions reduction targets offshore wind power will grow rapidly as the availability of suitable onshore sites decrease. However, wind is variable and stochastic by nature and thus difficult to schedule. In order to plan for these uncertainties market operators use wind forecasting tools, reserve plant and ancillary service agreements. Onshore wind power forecasting techniques have improved dramatically and continue to advance, but offshore wind power forecasting is more difficult due to limited datasets and knowledge. So as the amount of offshore wind power increases in the British Isles robust forecasting and planning techniques are even more critical. This paper presents a methodology to investigate the impacts of better offshore wind forecasting on the operation and management of the single wholesale electricity market in the Republic of Ireland and Northern Ireland using PLEXOS for Power Systems. © 2013 IEEE.

Special condition wind power forecasting based on Gaussian process and similar historical data

Due to the variability of wind power, it is imperative to accurately and timely forecast the wind generation to enhance the flexibility and reliability of the operation and control of real-time power. Special events such as ramps, spikes are hard to predict with traditional methods using solely recently measured data. In this paper, a new Gaussian Process model with hybrid training data taken from both the local time and historic dataset is proposed and applied to make short-term predictions from 10 minutes to one hour ahead. A key idea is that the similar pattern data in history are properly selected and embedded in Gaussian Process model to make predictions. The results of the proposed algorithms are compared to those of standard Gaussian Process model and the persistence model. It is shown that the proposed method not only reduces magnitude error but also phase error.

The Historical Use of Amnesties, Immunities, and Sentence Reductions in Northern Ireland

While it is widely believed that the use of amnesties and similar measures would mark a new departure in NI and the UK, so that speculation about their introduction causes public controversy and threatens political instability, the report demonstrates that such measures have in fact been repeatedly used in a wide range of circumstances since the foundation of the NI state. The paper offers definitions of the key measures which have been employed, including amnesties, sentence reductions linked to peace building and use immunities. It explores their historical use and its consequences.

An alternative methodology in Schottky diode physics

The fabrication and electrical characterization of Schottky junction diodes have been extensively researched for three-quarters of a century since the original work of Schottky in 1938. This study breaks from the highly standardized regime of such research and provides an alternative methodology that prompts novel, more efficient applications of the adroit Schottky junction in areas such as chemical and thermal sensing. The core departure from standard Schottky diode configuration is that the metal electrode is of comparable or higher resistance than the underlying semiconductor. Further, complete electrical characterization is accomplished through recording four-probe resistance-temperature (R-D-T) characteristics of the device, where electrical sourcing and sensing is done only via the metal electrode and not directly through the semiconductor. Importantly, this results in probing a nominally unbiased junction while eliminating the need for an Ohmic contact to the semiconductor. The characteristic R-D-T plot shows two distinct regions of high (metal) and low (semiconductor) resistances at low and high temperatures, respectively, connected by a crossover region of width, DT, within which there is a large negative temperature coefficient of resistance. The R-D-T characteristic is highly sensitive to the Schottky barrier height; consequently, at a fixed temperature, R-D responds appreciably to small changes in barrier height such as that induced by absorption of a chemical species (e.g., H-2) at the interface. A theoretical model is developed to simulate the R-D-T data and applied to Pd/p-Si and Pt/p-Si Schottky diodes with a range of metal electrode resistance. The analysis gives near-perfect fits to the experimental R-D-T characteristics, yielding the junction properties as fit parameters. The modelling not only helps elucidate the underlying physics but also helps to comprehend the parameter space essential for the discussed applications. Although the primary regime of application is limited to a relatively narrow range (DT) for a given type of diode, the alternative methodology is of universal applicability to all metal-semiconductor combinations forming Schottky contacts. (C) 2015 AIP Publishing LLC.

Using film as a source

This book is a hands-on study skills guide that explores how film and moving image can be used as sources. It is aimed at those who want to use film and moving image as the basis for research and offers advice on research methods, theory and methodology, archival work and film-based analysis. It draws on the disciplines of film and history to offer advice for students and researchers in these fields.

The book includes sections on working with different kinds of moving images, how to explore visual sources, how to undertake film-related research and how to use film theory. In addition to providing detailed case studies, the guide also offers advice on research, writing and studying, creating a methodology, visiting archives, accessing material and exploring films from a historical perspective. The guide's focus is on good research practice, whether it be conducting an interview, visiting an archive, undertaking textual analysis or defining a research question.

Slow Release Drug Dissolution Profile Prediction in Pharmaceutical Manufacturing: a Multivariate and Machine Learning Approach

Slow release drugs must be manufactured to meet target specifications with respect to dissolution curve profiles. In this paper we consider the problem of identifying the drivers of dissolution curve variability of a drug from historical manufacturing data. Several data sources are considered: raw material parameters, coating data, loss on drying and pellet size statistics. The methodology employed is to develop predictive models using LASSO, a powerful machine learning algorithm for regression with high-dimensional datasets. LASSO provides sparse solutions facilitating the identification of the most important causes of variability in the drug fabrication process. The proposed methodology is illustrated using manufacturing data for a slow release drug.

A kinetic analysis methodology to elucidate the roles of metal, support and solvent for the hydrogenation of 4-phenyl-2-butanone over Pt/TiO2

The rate and, more importantly, selectivity (ketone vs aromatic ring) of the hydrogenation of 4-phenyl-2-butanone over a Pt/TiO2 catalyst have been shown to vary with solvent. In this study, a fundamental kinetic model for this multi-phase reaction has been developed incorporating statistical analysis methods to strengthen the foundations of mechanistically sound kinetic models. A 2-site model was determined to be most appropriate, describing aromatic hydrogenation (postulated to be over a platinum site) and ketone hydrogenation (postulated to be at the platinum–titania interface). Solvent choice has little impact on the ketone hydrogenation rate constant but strongly impacts aromatic hydrogenation due to solvent-catalyst interaction. Reaction selectivity is also correlated to a fitted product adsorption constant parameter. The kinetic analysis method shown has demonstrated the role of solvents in influencing reactant adsorption and reaction selectivity.