Highlights of the CHA Survey on the Status of Women, 1989

In the spring of 1989, a survey was conducted of individuals and departments of history (in universities primarily) in order to update information from a previous survey and to examine both the actual career paths of women and men in the profession and their attitudes toward the status of women. One hundred and twenty-three me

Consumers and Sustainability at Walmart: A Student\u27s Perspective

To further encourage students to analyze initial goals in comparison with outcomes over time, we have developed a consumer-oriented case—“Consumers and Sustainability at Walmart: A Student’s Perspective”—that moves beyond the perspective of internal Walmart participants to explores issues of sustainability from the point of view of a typical Walmart shopper. In this case, we examine the experience of a fictional student shopper who goes to Walmart and wants to buy sustainable products, which helps raise questions for students about what Walmart’s actions mean to them as consumers, citizens as well as business professionals. The case also asks students to evaluate the progress that Walmart has made in its stores over the course of its sustainability journey, particularly in comparison to its initial aspirations and goa

Introduction for the Special Issue on Beyond the Hypes of Geospatial Big Data: Theories, Methods, Analytics, and Applications

We live in the era of ‘Big Data’. In particular, Geospatial data, whether captured through remote sensors (e.g., satellite imagery) or generated from large-scale simulations (e.g., climate change models) have always been significantly large in size. Over the last decade however, advances in instrumentation and computation has seen the volume, variety, velocity, and veracity of this data increase exponentially. Of the 2.5 quintillion (1018) bytes of data that are generated on a daily basis across the globe, a large portion (arguably as much as 80%) is found to be geo-referenced. Therefore, this special issue is dedicated to the innovative theories, methods, analytics, and applications of geospatial big data

The capacity of non-identical adaptive group testing

We consider the group testing problem, in the case where the items are defective independently but with non-constant probability. We introduce and analyse an algorithm to solve this problem by grouping items together appropriately. We give conditions under which the algorithm performs essentially optimally in the sense of information-theoretic capacity. We use concentration of measure results to bound the probability that this algorithm requires many more tests than the expected number. This has applications to the allocation of spectrum to cognitive radios, in the case where a database gives prior information that a particular band will be occupied.Comment: To be presented at Allerton 201

RECREATIONAL SWIMMING BENEFITS OF NEW HAMPSHIRE LAKE WATER QUALITY POLICIES: AN APPLICATION OF A REPEATED DISCRETE CHOICE MODEL

Water pollution control policies generally direct sources (i.e., industry, agriculture) to reduce loadings of certain pollutants. Thus, evaluating the relative net recreation benefits of policies to improve water quality requires establishing a linkage between the sources, the resultant water quality degradation at the affected water bodies, and, ultimately, the effect on recreation behavior. This linkage is rarely present in the empirical literature which is, thus, deficient for water pollution control policy assessment purposes. In this paper, we estimate the relative recreational swimming benefits that may result from controlling point and nonpoint sources of pollution, respectively, in New Hampshire's lakes. We use a repeated discrete choice framework to model swimming behavior as a function of each lake's level of eutrophication, bacteria, and oil and grease. For each pollutant, at each affected lake, we identify which source is responsible for the pollution, and we conduct scenarios controlling each pollution source independently, and then, taken together. Seasonal benefit estimates are presented for each scenario. Coupled with information on the most cost effective means of generating the scenarios, these estimates provide a useful starting point for a quantitative assessment of the net recreation benefits of policies to improve the quality of New Hampshire lakes.Environmental Economics and Policy,

The Missing Parameter in Renewable Energy Power Quality Analysis, i.e. The Coefficient of Variation: Case study of a 3-MW on-site wind turbine project in Ireland

Businesses are employing distributed generation techniques, such as wind turbines, to decarbonise their electrical energy supply by reducing their dependence on fossil-fuel-generated energy. This study investigates the effectiveness of a company making a €3,500,000 investment in a 3-MW on-site wind turbine to supply some or all of their factory electrical loads. The results should benefit the investing company and other potential investors by evaluating the economic, environmental, and social outcomes of the investment. A case study methodology was used. The study found that the payback period was six and a half years, and the turbine installation benefited the environment by offsetting 3,195 tonnes of CO2 per annum. As part of the power-quality analysis of the wind-turbine output, the short-term variability of the power output signal was calculated as the coefficient of variation values. The study found that the most stable power output is achieved when the turbine is generating at full output power (i.e., 3-MW). In addition to the existing range of traditional power quality parameters, the coefficient of variation parameter was found to be an essential aspect of electrical power quality and should be included in future practice

Identification and PID Control of Time-delayed Processes

This research was conducted primarily to investigate a selection of known methods for the identification of a mathematical model for processes with an inherent time delay, and subsequently, use the parameters of the identified model to regulate the processes via the PI/PID control strategy. The research examines the level of difficulty in performing or sanctioning different system identification methods in order to re-tune the controller. The process model identification methods are carried out on both simulated and real processes in the first part of the research. The selected parametric identification methods are chosen because they encompass open- and closed- loop techniques, first –order-plus-dead-time and second-order-plus-dead-time process models and both frequency- and time-domain identification methods. The second part of the research considers the PI/PID control strategy to regulate the processes identified using the aforementioned process model identification methods. The link between the identification and control sections in this thesis is the tuning rule. Even though the PID control loop is the most common industrial controller, poor tuning has contributed to the control loop not working as well as it should. The thesis considers the level of expertise required and the complexity of implementing eleven representative tuning rules using different PID controller structure

Small-Scale Wind Turbines: an Appraisal

This research seeks to evaluate the economic benefits to be gained by installing a small-scale wind turbine for a customer with a three-phase electrical supply requirement. The evidence for the claims made in this paper is obtained by using actual data obtained from the installed equipment over a three year period. The objective is to accurately appraise the financial investment using real data. There appears to be limited studies conducted into this type of research, possibly because the renewable energy sector is in the infancy stage in the host country, Ireland. There are some wind energy installations with financial appraisal techniques based on modeled data, which may, or may not, be accurate. The study concludes by claiming that the financial benefits of the wind energy turbine installation had disappointing results when compared to predicted benefits based on modeled data