Power to the people: local governments go green
Abstract Local governments could become important vehicles for green power by acting as community aggregators and offering consumers the opportunity to express local preferences for cleaner power sources through the purchase of renewable energy.
The role of public policy in emerging green power markets: an analysis of marketer preferences
Green power marketing has been heralded by some as a means to create a private market for renewable energy that is driven by customer demand for green products. This article challenges the premise -- sometimes proffered in debates over green markets -- that profitable, sizable, credible markets for green products will evolve naturally without supportive public policies. Relying primarily on surveys and interviews of US green power marketers, the article examines the role of specific regulatory and legislative policies in 'enabling' the green market, and searches for those policies that are believed by marketers to be the most conducive or detrimental to the expansion of the green market. We find that marketers: (1) believe that profitable green power markets will only develop if a solid foundation of supportive policies exists; (2) believe that establishing overall price competition and encouraging customer switching are the top priorities; (3) are somewhat leery of government-sponsored or mandated public information programs; and (4) oppose three specific renewable energy policies that are frequently advocated by renewable energy enthusiasts, but that may have negative impacts on the green marketers' profitability. The stated preferences of green marketers shed light on ways to foster renewables by means of the green market. Because the interests of marketers do not coincide perfectly with those of society, however, this study also recognizes other normative perspectives and highlights policy tensions at the heart of current debates related to green markets. By examining these conflicts, we identify three key policy questions that should direct future research: To what extent should price competition and customer switching be encouraged at the expense of cost shifting? What requirements should be imposed to ensure credibility in green products and marketing? How should the green power market and broader renewable energy policies interact?
Automatic classification of TV news articles based on telop character recognition
The purpose of this study is to develop a multimedia database system for TV news video data. TV news video data consist of speech, characters and images. In this study, telop characters are recognized and given to the news articles as indices for classification. At first, telop frames which include telop characters are detected and then the telop characters are extracted and recognized. Through morphological analysis of the recognized telop characters, keywords are extracted which consist of more than two characters. Their keywords are used as indices to classify the TV news articles. We carried out experiments for 30 days of NHK 5 minutes news and obtained 95.4% telop character extraction rate, 81.4% character recognition rate and 83.8% article classification rate. We improved the article classification rate by 43.4% through character recognition improvement from 44.1% to 81.4%.