Entropy production in a photovoltaic cell

We evaluate entropy production in a photovoltaic cell that is modeled by four electronic levels resonantly coupled to thermally populated field modes at different temperatures. We use a formalism recently proposed, the so-called multiple parallel worlds, to consistently address the nonlinearity of entropy in terms of density matrix. Our result shows that entropy production is the difference between two flows: a semiclassical flow that linearly depends on occupational probabilities, and another flow that depends nonlinearly on quantum coherence and has no semiclassical analog. We show that entropy production in the cells depends on environmentally induced decoherence time and energy detuning. We characterize regimes where reversal flow of information takes place from a cold to hot bath. Interestingly, we identify a lower bound on entropy production, which sets limitations on the statistics of dissipated heat in the cells.Comment: 7 pages, 2 figure

Sutte Indicator: an approach to predict the direction of stock market movements

The purpose of this research is to apply technical analysis of Sutte Indicator in stock trading which will assist in the investment decision making process i.e. buying or selling shares. This research takes data of "A" on the Indonesia Stock Exchange(IDX or BEI) 29 November 2006 until 20 September 2016 period. To see the performance of Sutte Indicator, other technical analysis are used as a comparison, Simple Moving Average (SMA) and Moving Average Convergence/Divergence (MACD). To see a comparison of the level of reliability prediction, the stock data were compared using the mean absolute deviation (MAD), mean of square error (MSE), and mean absolute percentage error (MAPE). The result of this research is that Sutte Indicator can be used as a reference in predicting stock movements, and if it is compared to other indicator methods (SMA and MACD) via MAD, MSE, and MAPE, the Sutte Indicator has a better level of reliability

The teaching of Relational On-Line Analytical Processing (ROLAP) in Advanced Database courses.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. © 2012 Higher Education AcademyDatabases are taught as a core subject at undergraduate and postgraduate levels in computer science degrees. The subject is often divided into conceptual database design and database technologies including physical database design. One of the problems with teaching the topic of ROLAP and Data Warehousing is the difficulty of providing practical exposure to the students. The approach taken in this work is intended to help students apply their knowledge learnt throughout the subject and gain some practical understanding leading to its application and implementation which furthermore provides the basis for analysis and evaluation at the level of critical analysis that would be expected on an advanced level course and at the highest level of learning taxonomies. In our work we have reverse engineered a large Oracle sample dataset and adapted it for use in the teaching of ROLAP. We have also produced our own smaller sample dataset for simplification and understanding of complex queries involving Slicing, Dicing , Pivoting, Rollup and Cube operations. In our examples ROLAP operations and their alternative SQL approaches are performed to provide multi-dimensional results