BIB(Bag In Box)是近20年从欧洲开始发展的一种全新的包装概念,并由此诞生了一个全新的包装行业。随着BIB包装应用的延伸,已经从最初的果汁浓缩液的无菌包装领域发展到了涵盖各种液态食品和饮品的包装领域,并已在欧美被广泛应用在红酒...BIB(Bag In Box)是近20年从欧洲开始发展的一种全新的包装概念,并由此诞生了一个全新的包装行业。随着BIB包装应用的延伸,已经从最初的果汁浓缩液的无菌包装领域发展到了涵盖各种液态食品和饮品的包装领域,并已在欧美被广泛应用在红酒包装上。文中将从概念、材料、环保和成本等多角度介绍BIB红酒包装,并与传统的瓶装进行对比,全面地勾勒出BIB创意的优势和其创意产业的发展前景。展开更多
Outlier detection techniques play a vital role in exploring unusual data of extreme events that have a critical effect considerably in the modeling and forecasting of functional data. The functional methods have an ef...Outlier detection techniques play a vital role in exploring unusual data of extreme events that have a critical effect considerably in the modeling and forecasting of functional data. The functional methods have an effective way of identifying outliers graphically, which might not be visible through the original data plot in classical analysis. This study’s main objective is to detect the extreme rainfall events using functional outliers detection methods depending on the depth and density functions. In order to identify the unusual events of rainfall variation over long time intervals, this work conducts based on the average monthly rainfall of the Taiz region from 1998 to 2019. Data were extracted from the Tropical Rainfall Measuring Mission and the analysis has been processed by R software. The approaches applied in this study involve rainbow plots, functional highest density region box-plot as well as functional bag-plot. According to the current results, the functional density box-plot method has proven effective in detecting outlier compared to the functional depth bag-plot method. In conclusion, the results of the current study showed that the rainfall over the Taiz region during the last two decades was influenced by the extreme events of years 1999, 2004, 2005, and 2009.展开更多
文摘BIB(Bag In Box)是近20年从欧洲开始发展的一种全新的包装概念,并由此诞生了一个全新的包装行业。随着BIB包装应用的延伸,已经从最初的果汁浓缩液的无菌包装领域发展到了涵盖各种液态食品和饮品的包装领域,并已在欧美被广泛应用在红酒包装上。文中将从概念、材料、环保和成本等多角度介绍BIB红酒包装,并与传统的瓶装进行对比,全面地勾勒出BIB创意的优势和其创意产业的发展前景。
文摘Outlier detection techniques play a vital role in exploring unusual data of extreme events that have a critical effect considerably in the modeling and forecasting of functional data. The functional methods have an effective way of identifying outliers graphically, which might not be visible through the original data plot in classical analysis. This study’s main objective is to detect the extreme rainfall events using functional outliers detection methods depending on the depth and density functions. In order to identify the unusual events of rainfall variation over long time intervals, this work conducts based on the average monthly rainfall of the Taiz region from 1998 to 2019. Data were extracted from the Tropical Rainfall Measuring Mission and the analysis has been processed by R software. The approaches applied in this study involve rainbow plots, functional highest density region box-plot as well as functional bag-plot. According to the current results, the functional density box-plot method has proven effective in detecting outlier compared to the functional depth bag-plot method. In conclusion, the results of the current study showed that the rainfall over the Taiz region during the last two decades was influenced by the extreme events of years 1999, 2004, 2005, and 2009.
