The Mechanics of supply-demand adjusters for midwestern milk markets /

Cover title.

The demand for light duty trucks: the Wharton EFA Motor Vehicle Demand Model (Mark II). Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

Motor vehicle demand models: assessment of the state of the art and directions for future research. Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

Revisions to the Wharton EFA Automobile Demand Model (Mark I). Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

Minerals in the U.S. economy : ten-year supply-demand profiles for mineral and fuel commodities (1966-1975) /

Mode of access: Internet.

Agricultural supply & demand estimates.

"Approved by the World Food and Agricultural Outlook and Situation Board."

Update #3 : Crestwood public water supply groundwater modeling -- bedrock well installation /

"September 11, 2009"

Graduates of higher education in the food and agricultural sciences : an analysis of supply/demand relationships /

Issued July 1980.

Fuel cells, hydrogen and energy supply in Australia

Australia is unique in terms of its geography, population distribution, and energy sources. It has an abundance of fossil fuel in the form of coal, natural gas, coal seam methane (CSM), oil, and a variety renewable energy sources that are under development. Unfortunately, most of the natural gas is located so far away from the main centres of population that it is more economic to ship the energy as LNG to neighboring countries. Electricity generation is the largest consumer of energy in Australia and accounts for around 50% of greenhouse gas emissions as 84% of electricity is produced from coal. Unless these emissions are curbed, there is a risk of increasing temperatures throughout the country and associated climatic instability. To address this, research is underway to develop coal gasification and processes for the capture and sequestration Of CO2. Alternative transport fuels such as biodiesel are being introduced to help reduce emissions from vehicles. The future role of hydrogen is being addressed in a national study commissioned this year by the federal government. Work at the University of Queensland is also addressing full-cycle analysis of hydrogen production, transport, storage, and utilization for both stationary and transport applications. There is a modest but growing amount of university research in fuel cells in Australia, and an increasing interest from industry. Ceramic Fuel Cells Ltd. (CFCL) has a leading position in planar solid oxide fuel cells (SOFCs) technology, which is being developed for a variety of applications, and next year Perth in Western Australia is hosting a trial of buses powered by proton-exchange fuel cells. (C) 2004 Elsevier B.V. All rights reserved.

Improved Annual Average Daily Traffic (AADT) estimation for local roads using parcel-level travel demand modeling

Annual Average Daily Traffic (AADT) is a critical input to many transportation analyses. By definition, AADT is the average 24-hour volume at a highway location over a full year. Traditionally, AADT is estimated using a mix of permanent and temporary traffic counts. Because field collection of traffic counts is expensive, it is usually done for only the major roads, thus leaving most of the local roads without any AADT information. However, AADTs are needed for local roads for many applications. For example, AADTs are used by state Departments of Transportation (DOTs) to calculate the crash rates of all local roads in order to identify the top five percent of hazardous locations for annual reporting to the U.S. DOT. ^ This dissertation develops a new method for estimating AADTs for local roads using travel demand modeling. A major component of the new method involves a parcel-level trip generation model that estimates the trips generated by each parcel. The model uses the tax parcel data together with the trip generation rates and equations provided by the ITE Trip Generation Report. The generated trips are then distributed to existing traffic count sites using a parcel-level trip distribution gravity model. The all-or-nothing assignment method is then used to assign the trips onto the roadway network to estimate the final AADTs. The entire process was implemented in the Cube demand modeling system with extensive spatial data processing using ArcGIS. ^ To evaluate the performance of the new method, data from several study areas in Broward County in Florida were used. The estimated AADTs were compared with those from two existing methods using actual traffic counts as the ground truths. The results show that the new method performs better than both existing methods. One limitation with the new method is that it relies on Cube which limits the number of zones to 32,000. Accordingly, a study area exceeding this limit must be partitioned into smaller areas. Because AADT estimates for roads near the boundary areas were found to be less accurate, further research could examine the best way to partition a study area to minimize the impact.^

A Look Back To Look Forward: New Patterns In The Supply/Demand Equation In The Lodging Industry

In his dialogue entitled - A Look Back to Look Forward: New Patterns In The Supply/Demand Equation In The Lodging Industry - by Albert J. Gomes, Senior Principal, Pannell Kerr Forster, Washington, D.C. What the author intends for you to know is the following: “Factors which influence the lodging industry in the United States are changing that industry as far as where hotels are being located, what clientele is being served, and what services are being provided at different facilities. The author charts these changes and makes predictions for the future.” Gomes initially alludes to the evolution of transportation – the human, animal, mechanical progression - and how those changes, in the last 100 years or so, have had a significant impact on the hotel industry. “A look back to look forward treats the past as prologue. American hoteliers are in for some startling changes in their business,” Gomes says. “The man who said that the three most important determinants for the success of a hotel were “location, location, location” did a lot of good only in the short run.” Gomes wants to make you aware of the existence of what he calls, “locational obsolescence.” “Locational obsolescence is a fact of life, and at least in the United States bears a direct correlation to evolutionary changes in transportation technology,” he says. “…the primary business of the hospitality industry is to serve travelers or people who are being transported,” Gomes expands the point. Tied to the transportation element, the author also points out an interesting distinction between hotels and motels. In addressing, “…what clientele is being served, and what services are being provided at different facilities,” Gomes suggests that the transportation factor influences these constituents as well. Also coupled with this discussion are oil prices and shifts in transportation habits, with reference to airline travel being an ever increasing method of travel; capturing much of the inter-city travel market. Gomes refers to airline deregulation as an impetus. The point being, it’s a fluid market rather than a static one, and [successful] hospitality properties need to be cognizant of market dynamics and be able to adjust to the variables in their marketplace. Gomes provides many facts and figures to bolster his assertions. Interestingly and perceptively, at the time of this writing, Gomes alludes to America’s deteriorating road and bridge network. As of right now, in 2009, this is a major issue. Gomes rounds out this study by comparing European hospitality trends to those in the U.S.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

New Developments in Tourism and Hotel Demand Modeling and Forecasting

Abstract Purpose The purpose of the study is to review recent studies published from 2007-2015 on tourism and hotel demand modeling and forecasting with a view to identifying the emerging topics and methods studied and to pointing future research directions in the field. Design/Methodology/approach Articles on tourism and hotel demand modeling and forecasting published in both science citation index (SCI) and social science citation index (SSCI) journals were identified and analyzed. Findings This review found that the studies focused on hotel demand are relatively less than those on tourism demand. It is also observed that more and more studies have moved away from the aggregate tourism demand analysis, while disaggregate markets and niche products have attracted increasing attention. Some studies have gone beyond neoclassical economic theory to seek additional explanations of the dynamics of tourism and hotel demand, such as environmental factors, tourist online behavior and consumer confidence indicators, among others. More sophisticated techniques such as nonlinear smooth transition regression, mixed-frequency modeling technique and nonparametric singular spectrum analysis have also been introduced to this research area. Research limitations/implications The main limitation of this review is that the articles included in this study only cover the English literature. Future review of this kind should also include articles published in other languages. The review provides a useful guide for researchers who are interested in future research on tourism and hotel demand modeling and forecasting. Practical implications This review provides important suggestions and recommendations for improving the efficiency of tourism and hospitality management practices. Originality/value The value of this review is that it identifies the current trends in tourism and hotel demand modeling and forecasting research and points out future research directions.