Ultra Wideband (UWB) technology is promising for wireless personal area network (WPAN) applications due to its high data rate, low power requirement and short-range characteristics. Instead of exploring new unused fre...Ultra Wideband (UWB) technology is promising for wireless personal area network (WPAN) applications due to its high data rate, low power requirement and short-range characteristics. Instead of exploring new unused frequency band, the UWB communication follows the overlay principle, i.e., sharing the spectrum with existing systems and devices. This novel radio technology has been recently approved by the regulatory authorities in the United States and Canada, and is being considered for approval in Europe and Asia. In this paper, an overview of the UWB radio technology from the technical, economical, and regulatory perspectives is provided. Firstly, the definition of UWB by the Federal Communications Commission (FCC) is introduced, followed by a brief introduction to the history. The current status of the standardization process resulting from the FCC’s recent decision to permit unlicensed operation in the [3.1 - 10.6] GHz band is discussed. Then, the reasons of considering UWB as a future solution for WLAN/WPAN applications are studied. In particular, the unique properties of UWB and its difference from other wireless technology alternatives are studied. Then, the benefits and challenges related to the commercial deployment of UWB for future applications are discussed. Finally, the research problems and challenges posed by the UWB technology are focused.展开更多
Freshwater biodiversity and ecosystem integrity are under threat from biological invasions. The ＂killer shrimp＂ Dikerogammarus villosus is a highly predatory amphipod that has spread readily across Central Europe an...Freshwater biodiversity and ecosystem integrity are under threat from biological invasions. The ＂killer shrimp＂ Dikerogammarus villosus is a highly predatory amphipod that has spread readily across Central Europe and recently the UK and its arrival has been associated with the significant loss of resident species. Despite this, studies of its behavioral ecology are sparse, even though its be- havior may contribute to its invasion success. For the first time, we investigated antipredator ＂fleeing＂ behavior in D. villosus and how this changed with water temperature. Three key patterns emerged from our analysis. First, within a particular temperature condition there are moderate but consistent among-individual differences in behavior. These are driven by a combination of mean level among-individual differences and within-individual relative consistency in behavior, and pro- vide the key marker for animal personalities. Second, the fleeing responses were not influenced by temperature and third, regardless of temperature, all individuals appeared to habituate to a repeated nondangerous stimulus, indicating a capacity for individual learning. We suggest that the antipreda- tor behavior of D. villosus contributes to its rapid spread and that consistent among-individual differ- ences in behavior may promote biological invasions across heterogeneous conditions. Robustness to changing water temperatures may also be potentially advantageous, particularly in an era of glo- bal climate change, where average temperatures could be elevated and less predictable.展开更多
Trading rules performing well on a given data set seldom lead to promising out-of-sample results, a problem which is a consequence of the in-sample data snooping bias. Efforts to justify the selection of trading rules...Trading rules performing well on a given data set seldom lead to promising out-of-sample results, a problem which is a consequence of the in-sample data snooping bias. Efforts to justify the selection of trading rules by assessing the out-of-sample performance will not really remedy this predica- ment either, because they are prone to be trapped in what is known as the out-of-sample data-snooping bias. Our approach to curb the data-snooping bias consists of constructing a framework for trading rule selection using a-priori robustness strategies, where robustness is gauged on the basis of time- series bootstrap and multi-objective criteria. This approach focuses thus on building robustness into the process of trading rule selection at an early stage, rather than on an ex-post assessment of trading rule fitness. Intra-day FX market data constitute the empirical basis of the proposed investigations. Trading rules are selected from a wide universe created by evolutionary computation tools. The authors show evidence of the benefit of this approach in terms of indirect forecasting accuracy when investing in FX markets.展开更多
文摘Ultra Wideband (UWB) technology is promising for wireless personal area network (WPAN) applications due to its high data rate, low power requirement and short-range characteristics. Instead of exploring new unused frequency band, the UWB communication follows the overlay principle, i.e., sharing the spectrum with existing systems and devices. This novel radio technology has been recently approved by the regulatory authorities in the United States and Canada, and is being considered for approval in Europe and Asia. In this paper, an overview of the UWB radio technology from the technical, economical, and regulatory perspectives is provided. Firstly, the definition of UWB by the Federal Communications Commission (FCC) is introduced, followed by a brief introduction to the history. The current status of the standardization process resulting from the FCC’s recent decision to permit unlicensed operation in the [3.1 - 10.6] GHz band is discussed. Then, the reasons of considering UWB as a future solution for WLAN/WPAN applications are studied. In particular, the unique properties of UWB and its difference from other wireless technology alternatives are studied. Then, the benefits and challenges related to the commercial deployment of UWB for future applications are discussed. Finally, the research problems and challenges posed by the UWB technology are focused.
文摘Freshwater biodiversity and ecosystem integrity are under threat from biological invasions. The ＂killer shrimp＂ Dikerogammarus villosus is a highly predatory amphipod that has spread readily across Central Europe and recently the UK and its arrival has been associated with the significant loss of resident species. Despite this, studies of its behavioral ecology are sparse, even though its be- havior may contribute to its invasion success. For the first time, we investigated antipredator ＂fleeing＂ behavior in D. villosus and how this changed with water temperature. Three key patterns emerged from our analysis. First, within a particular temperature condition there are moderate but consistent among-individual differences in behavior. These are driven by a combination of mean level among-individual differences and within-individual relative consistency in behavior, and pro- vide the key marker for animal personalities. Second, the fleeing responses were not influenced by temperature and third, regardless of temperature, all individuals appeared to habituate to a repeated nondangerous stimulus, indicating a capacity for individual learning. We suggest that the antipreda- tor behavior of D. villosus contributes to its rapid spread and that consistent among-individual differ- ences in behavior may promote biological invasions across heterogeneous conditions. Robustness to changing water temperatures may also be potentially advantageous, particularly in an era of glo- bal climate change, where average temperatures could be elevated and less predictable.
文摘Trading rules performing well on a given data set seldom lead to promising out-of-sample results, a problem which is a consequence of the in-sample data snooping bias. Efforts to justify the selection of trading rules by assessing the out-of-sample performance will not really remedy this predica- ment either, because they are prone to be trapped in what is known as the out-of-sample data-snooping bias. Our approach to curb the data-snooping bias consists of constructing a framework for trading rule selection using a-priori robustness strategies, where robustness is gauged on the basis of time- series bootstrap and multi-objective criteria. This approach focuses thus on building robustness into the process of trading rule selection at an early stage, rather than on an ex-post assessment of trading rule fitness. Intra-day FX market data constitute the empirical basis of the proposed investigations. Trading rules are selected from a wide universe created by evolutionary computation tools. The authors show evidence of the benefit of this approach in terms of indirect forecasting accuracy when investing in FX markets.
