The convergence of next-generation Networks and the emergence of new media systems have made media-rich digital libraries popular in application and research. The discovery of media content objects’ usage patterns, w...The convergence of next-generation Networks and the emergence of new media systems have made media-rich digital libraries popular in application and research. The discovery of media content objects’ usage patterns, where QPop Increment is the characteristic feature under study, is the basis of intelligent data migration scheduling, the very key issue for these systems to manage effectively the massive storage facilities in their backbones. In this paper, a clustering algorithm is established, on the basis of temporal segmentation of QPop Increment, so as to improve the mining performance. We employed the standard C-Means algorithm as the clustering kernel, and carried out the experimental mining process with segmented QPop Increases obtained in actual applications. The results indicated that the improved algorithm is more advantageous than the basic one in important indices such as the clustering cohesion. The experimental study in this paper is based on a Media Assets Library prototype developed for the use of the advertainment movie production project for Olympics 2008, under the support of both the Humanistic Olympics Study Center in Beijing, and China State Administration of Radio, Film and TV.展开更多
A structural model of cultivation theory is tested by using a national data set from 1957, before television became a dominant medium in the United States. Support is found for the basic tenet of cultivation theory, n...A structural model of cultivation theory is tested by using a national data set from 1957, before television became a dominant medium in the United States. Support is found for the basic tenet of cultivation theory, namely, that media use shapes people＇s perceptions and beliefs. Print media use predicts one＇s worldview, both of which predict attitudes toward science. By examining attitudes toward science before television became a dominant medium, this study extends the theory beyond the field＇s primary research focus on the relationship between television and violence.展开更多
Medialization has become like digitalization, rationalization, dynamization, globalization, pluralization, hybridization, and differentialization and is one of the buzzwords of modern Western industrialized societies,...Medialization has become like digitalization, rationalization, dynamization, globalization, pluralization, hybridization, and differentialization and is one of the buzzwords of modern Western industrialized societies, which are all together essentially responsible for structural change in communication. Medialization means the adaption of producers to media logics, media formats, and media routines ＆ workflows. There are consequently and logically influences because of the dynamic process of medialization to legal discourse and genres, law, media, and social power. It has to be discussed if the logics, data formats, and routines ＆ workflows of new media and information and communication technologies （ICTs） like social media are creating also a new generation of genres and novel form of legal discourses. Also, if social media will replace or complete old classic media （law of Riepl）, the question of the relevance of law concerning new ＆ social media has to be answered in close future. Lastly, if to the fore of social power, these new novel resources are actually framing for problem-based inquiries in law. There are big chances but also serious risks in cyberworld, their realities, and dangers. There actually exists an urgent call of action to theory building, development of methodologies, and empirical research.展开更多
In this paper, we review recent emerging theoretical and technological advances of artificial intelligence （AI） in the big data settings. We conclude that integrating data-driven machine learning with human knowled...In this paper, we review recent emerging theoretical and technological advances of artificial intelligence （AI） in the big data settings. We conclude that integrating data-driven machine learning with human knowledge （common priors or implicit intuitions） can effectively lead to explainable, robust, and general AI, as follows： from shallow computation to deep neural reasoning; from merely data-driven model to data-driven with structured logic rules models; from task-oriented （domain-specific） intelligence （adherence to explicit instructions） to artificial general intelligence in a general context （the capability to learn from experience）. Motivated by such endeavors, the next generation of AI, namely AI 2.0, is positioned to reinvent computing itself, to transform big data into structured knowledge, and to enable better decision-making for our society.展开更多
Dear Editor,In the＂big data era＂,the amount of digital information is growing explosively,therefore,a reliable data storage medium for large-scale digital archiving is urgently needed.However,the increase of existin...Dear Editor,In the＂big data era＂,the amount of digital information is growing explosively,therefore,a reliable data storage medium for large-scale digital archiving is urgently needed.However,the increase of existing storage capacity cannot keep up with the growth of digital information.Moreover,the durability of conventional storage teclanologles, sucn as magnetic and optical devices, is very limited. Since the first demonstration of using DNA to store messages in 1988, DNA has been considered as a promising data storage medium due to its high-density and long-term stability （half-life〉500years） （Allentoft et al., 2012）.展开更多
文摘The convergence of next-generation Networks and the emergence of new media systems have made media-rich digital libraries popular in application and research. The discovery of media content objects’ usage patterns, where QPop Increment is the characteristic feature under study, is the basis of intelligent data migration scheduling, the very key issue for these systems to manage effectively the massive storage facilities in their backbones. In this paper, a clustering algorithm is established, on the basis of temporal segmentation of QPop Increment, so as to improve the mining performance. We employed the standard C-Means algorithm as the clustering kernel, and carried out the experimental mining process with segmented QPop Increases obtained in actual applications. The results indicated that the improved algorithm is more advantageous than the basic one in important indices such as the clustering cohesion. The experimental study in this paper is based on a Media Assets Library prototype developed for the use of the advertainment movie production project for Olympics 2008, under the support of both the Humanistic Olympics Study Center in Beijing, and China State Administration of Radio, Film and TV.
文摘A structural model of cultivation theory is tested by using a national data set from 1957, before television became a dominant medium in the United States. Support is found for the basic tenet of cultivation theory, namely, that media use shapes people＇s perceptions and beliefs. Print media use predicts one＇s worldview, both of which predict attitudes toward science. By examining attitudes toward science before television became a dominant medium, this study extends the theory beyond the field＇s primary research focus on the relationship between television and violence.
文摘Medialization has become like digitalization, rationalization, dynamization, globalization, pluralization, hybridization, and differentialization and is one of the buzzwords of modern Western industrialized societies, which are all together essentially responsible for structural change in communication. Medialization means the adaption of producers to media logics, media formats, and media routines ＆ workflows. There are consequently and logically influences because of the dynamic process of medialization to legal discourse and genres, law, media, and social power. It has to be discussed if the logics, data formats, and routines ＆ workflows of new media and information and communication technologies （ICTs） like social media are creating also a new generation of genres and novel form of legal discourses. Also, if social media will replace or complete old classic media （law of Riepl）, the question of the relevance of law concerning new ＆ social media has to be answered in close future. Lastly, if to the fore of social power, these new novel resources are actually framing for problem-based inquiries in law. There are big chances but also serious risks in cyberworld, their realities, and dangers. There actually exists an urgent call of action to theory building, development of methodologies, and empirical research.
文摘In this paper, we review recent emerging theoretical and technological advances of artificial intelligence （AI） in the big data settings. We conclude that integrating data-driven machine learning with human knowledge （common priors or implicit intuitions） can effectively lead to explainable, robust, and general AI, as follows： from shallow computation to deep neural reasoning; from merely data-driven model to data-driven with structured logic rules models; from task-oriented （domain-specific） intelligence （adherence to explicit instructions） to artificial general intelligence in a general context （the capability to learn from experience）. Motivated by such endeavors, the next generation of AI, namely AI 2.0, is positioned to reinvent computing itself, to transform big data into structured knowledge, and to enable better decision-making for our society.
基金supported by the Suzhou Science and Technology Project and Fund for Young Scientists of Science and Technology Program of Jiangsu
文摘Dear Editor,In the＂big data era＂,the amount of digital information is growing explosively,therefore,a reliable data storage medium for large-scale digital archiving is urgently needed.However,the increase of existing storage capacity cannot keep up with the growth of digital information.Moreover,the durability of conventional storage teclanologles, sucn as magnetic and optical devices, is very limited. Since the first demonstration of using DNA to store messages in 1988, DNA has been considered as a promising data storage medium due to its high-density and long-term stability （half-life〉500years） （Allentoft et al., 2012）.
