Markov Models of Policy Support for Technology Transitions

2019 ◽  
Author(s):  
Max Brozynski ◽  
Benjamin D. Leibowicz
Keyword(s):  
Markov Models ◽  
Policy Support ◽  
Technology Transitions

Markov models of policy support for technology transitions

2020 ◽  
Vol 286 (3) ◽  
pp. 1052-1069 ◽  
Author(s):  
Max T. Brozynski ◽  
Benjamin D. Leibowicz
Keyword(s):  
Markov Models ◽  
Policy Support ◽  
Technology Transitions

Transition (markov) models for the analysis of survival times in clinical research

1999 ◽  
Vol 28 (1) ◽  
pp. 165-176
Author(s):  
Sati Mazumdar ◽  
Kenneth Liu ◽  
Sang Ahnn ◽  
Patricia R. Houck ◽  
Charles F. Reynolds
Keyword(s):  
Clinical Research ◽  
Markov Models ◽  
Survival Times

Markov models—Markov chains

2019 ◽  
Vol 16 (8) ◽  
pp. 663-664 ◽  
Author(s):  
Jasleen K. Grewal ◽  
Martin Krzywinski ◽  
Naomi Altman
Keyword(s):  
Markov Chains ◽  
Markov Models

Use of soil and climate data to assess the risk of agricultural drought for policy support in Europe

Agronomie ◽  
2001 ◽  
Vol 21 (1) ◽  
pp. 45-56 ◽  
Author(s):  
Pandi Zdruli ◽  
Robert J.A. Jones ◽  
Luca Montanarella
Keyword(s):  
Policy Support ◽  
Agricultural Drought ◽  
Climate Data

Renewable Energy on Tribal Lands: A Feasibility Study for a Biomass-to-Energy Plant on the Cocopah Reservation in Arizona

2019 ◽  
Vol 3 (1) ◽  
pp. 1-12
Author(s):  
Lauren K. D’Souza ◽  
William L. Ascher ◽  
Tanja Srebotnjak
Keyword(s):  
Renewable Energy ◽  
Alternative Energy ◽  
Renewable Energy Sources ◽  
The United States ◽  
Biomass Energy ◽  
Policy Support ◽  
Small Scale ◽  
Energy Plant ◽  
Energy Projects ◽  
Alternative Investment

Native American reservations are among the most economically disadvantaged regions in the United States; lacking access to economic and educational opportunities that are exacerbated by “energy insecurity” due to insufficient connectivity to the electric grid and power outages. Local renewable energy sources such as wind, solar, and biomass offer energy alternatives but their implementation encounters barriers such as lack of financing, infrastructure, and expertise, as well as divergent attitudes among tribal leaders. Biomass, in particular, could be a source of stable base-load power that is abundant and scalable in many rural communities. This case study examines the feasibility of a biomass energy plant on the Cocopah reservation in southwestern Arizona. It considers feedstock availability, cost and energy content, technology options, nameplate capacity, discount and interest rates, construction, operation and maintenance (O&M) costs, and alternative investment options. This study finds that at current electricity prices and based on typical costs for fuel, O&M over 30 years, none of the tested scenarios is presently cost-effective on a net present value (NPV) basis when compared with an alternative investment yielding annual returns of 3% or higher. The technology most likely to be economically viable and suitable for remote, rural contexts—a combustion stoker—resulted in a levelized costs of energy (LCOE) ranging from US$0.056 to 0.147/kWh. The most favorable scenario is a combustion stoker with an estimated NPV of US$4,791,243. The NPV of the corresponding alternative investment is US$7,123,380. However, if the tribes were able to secure a zero-interest loan to finance the plant’s installation cost, the project would be on par with the alternative investment. Even if this were the case, the scenario still relies on some of the most optimistic assumptions for the biomass-to-power plant and excludes abatement costs for air emissions. The study thus concludes that at present small-scale, biomass-to-energy projects require a mix of favorable market and local conditions as well as appropriate policy support to make biomass energy projects a cost-competitive source of stable, alternative energy for remote rural tribal communities that can provide greater tribal sovereignty and economic opportunities.

Estimating Personality Impression from Speech Record Using Hidden Markov Models

2015 ◽  
Vol 135 (12) ◽  
pp. 1517-1523 ◽  
Author(s):  
Yicheng Jin ◽  
Takuto Sakuma ◽  
Shohei Kato ◽  
Tsutomu Kunitachi
Keyword(s):  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov

Hidden Markov Processes

2014 ◽  
Author(s):  
M. Vidyasagar
Keyword(s):  
Hidden Markov Models ◽  
Markov Processes ◽  
Viterbi Algorithm ◽  
Markov Models ◽  
Hidden Markov ◽  
Local Alignment ◽  
Biological Applications ◽  
Standard Material ◽  
Hidden Markov Processes ◽  
Genomics And Proteomics

This book explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems in computational biology. It starts from first principles, so that no previous knowledge of probability is necessary. However, the work is rigorous and mathematical, making it useful to engineers and mathematicians, even those not interested in biological applications. A range of exercises is provided, including drills to familiarize the reader with concepts and more advanced problems that require deep thinking about the theory. Biological applications are taken from post-genomic biology, especially genomics and proteomics. The topics examined include standard material such as the Perron–Frobenius theorem, transient and recurrent states, hitting probabilities and hitting times, maximum likelihood estimation, the Viterbi algorithm, and the Baum–Welch algorithm. The book contains discussions of extremely useful topics not usually seen at the basic level, such as ergodicity of Markov processes, Markov Chain Monte Carlo (MCMC), information theory, and large deviation theory for both i.i.d and Markov processes. It also presents state-of-the-art realization theory for hidden Markov models. Among biological applications, it offers an in-depth look at the BLAST (Basic Local Alignment Search Technique) algorithm, including a comprehensive explanation of the underlying theory. Other applications such as profile hidden Markov models are also explored.

Why do the national financial and monetary policies not boost the economy?

2020 ◽  
Vol 26 (7) ◽  
pp. 1496-1521
Author(s):  
N.I. Kulikov ◽  
M.A. Kulikova ◽  
A.A.S.R. Mobio
Keyword(s):  
Central Bank ◽  
Policy Support ◽  
Gdp Growth ◽  
Government Contracts ◽  
Monetary Policies ◽  
The Past ◽  
Russian Economy ◽  
Yearly Average ◽  
Analysis And Synthesis ◽  
The Government

Subject. This article assesses the reasons why the economic policy of the Government and Central Bank of Russia does not cause the economic advance. The article tries to find out why the two strategic programmes adopted over the past ten years have not been implemented in most indicators. Objectives. The article aims to analyze the results of financial and monetary policies in Russia over the past ten years, and establish why the Russian economy has been growing within one percent yearly average all these years, and its share in the world economy has not grown, but got reduced even. Methods. For the study, we used the methods of analysis and synthesis. Results. The article proposes certain measures and activities to move to soft financial and monetary policies of the State and corresponding changes in the structure of the Russian economy. This will help ensure six to seven percent GDP growth annually. Conclusions. High loan rates have become the main obstacle to GDP growth in Russia. It is necessary to accept concrete actions and decisions concerning the Bank of Russia key rate, expansion of the functions of the Central Bank of the Russian Federation, industrial policy, support of consumer demand, long-term government contracts for the real sector enterprises, etc.

APPLICATION OF MULTI-STATE SEMI-MARKOV MODELS ON HIV/AIDS DISEASE PROGRESSION

2018 ◽  
Vol 7 (3) ◽  
pp. 30
Author(s):  
KALAYU MENGESHA SOLOMON ◽  
ALEMU GEBREMEDHN GEBREGEWERGIS ◽  
FEREDE TILAHUN ◽  
ATSMEGIORGIS CHERU ◽  
◽  
...  
Keyword(s):  
Disease Progression ◽  
Markov Models ◽  
Hiv Aids
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