Short-Term Load Forecasting of Natural Gas with Deep Neural Network Regression

Deep neural networks are proposed for short-term natural gas load forecasting. Deep learning has proven to be a powerful tool for many classification problems seeing significant use in machine learning fields such as image recognition and speech processing. We provide an overview of natural gas forecasting. Next, the deep learning method, contrastive divergence is explained. We compare our proposed deep neural network method to a linear regression model and a traditional artificial neural network on 62 operating areas, each of which has at least 10 years of data. The proposed deep network outperforms traditional artificial neural networks by 9.83% weighted mean absolute percent error (WMAPE)

Opportunistic Collaborative Beamforming with One-Bit Feedback

An energy-efficient opportunistic collaborative beamformer with one-bit feedback is proposed for ad hoc sensor networks over Rayleigh fading channels. In contrast to conventional collaborative beamforming schemes in which each source node uses channel state information to correct its local carrier offset and channel phase, the proposed beamforming scheme opportunistically selects a subset of source nodes whose received signals combine in a quasi-coherent manner at the intended receiver. No local phase-precompensation is performed by the nodes in the opportunistic collaborative beamformer. As a result, each node requires only one-bit of feedback from the destination in order to determine if it should or shouldn't participate in the collaborative beamformer. Theoretical analysis shows that the received signal power obtained with the proposed beamforming scheme scales linearly with the number of available source nodes. Since the the optimal node selection rule requires an exhaustive search over all possible subsets of source nodes, two low-complexity selection algorithms are developed. Simulation results confirm the effectiveness of opportunistic collaborative beamforming with the low-complexity selection algorithms.Comment: Proceedings of the Ninth IEEE Workshop on Signal Processing Advances in Wireless Communications, Recife, Brazil, July 6-9, 200

Diabetes in California: Findings From the 2001 California Health Interview Survey

Examines the prevalence of diabetes in California, with particular attention paid to disparities between different population groups. Includes access to medical care, diabetes care and management, and identifying at-risk populations

12-Month Continuous Eligibility in Medicaid: Impact on Service Utilization

Summarizes findings on how allowing Medicaid enrollees to remain enrolled without reapplying for twelve months affected the number of Medi-Cal-enrolled children's emergency room visits and physician visits compared with those with discontinuous coverage

Number of Uninsured Jumped to More Than Eight Million from 2007 to 2009

Updates 2007 California Health Interview Survey data with estimates for 2009 population growth and changes in insurance status among the non-elderly. Examines trends by source of coverage and explores contributing factors

SOYBEAN TRADER: A MICROCOMPUTER SIMULATION OF INTERNATIONAL AGRICULTURAL TRADE

Soybean Trader is a microcomputer simulation of international grain trading. The program uses the format of a graphics-oriented game to teach basic economic principles and to stimulate interest in agricultural trade. Profits from trading serve as a score, and competition is encouraged by ranking top scores in Trader's Hall of Fame. Results of tests with adult and youth audiences indicated that the program is an interesting and effective teaching tool.International Relations/Trade,

California Adolescents Increasingly Inactive

Explores the health benefits of regular exercise; the extent to which adolescents in California are getting adequate levels of physical activity; and factors that affect high rates of inactivity. Provides policy recommendations

Low-Income Adolescents Face More Barriers to Healthy Weight

Examines the causes behind the higher prevalence of obesity among low-income adolescents, including unhealthy food environments, few opportunities for physical activity, and irregular family meals. Makes policy recommendations to address such disparities

Health Coverage Expansion in California: What Can Consumers Afford to Spend?

Analyzes Californians' current spending on insurance premiums and out-of-pocket expenditures to assess whether proposals to make obtaining health insurance mandatory include sufficient measures to make it affordable for low- and middle-income families