The advancements of mobile devices, public networks and the Internet of creature huge amounts of complex data, both construct & unstructured are being captured in trust to allow organizations to produce better bus...The advancements of mobile devices, public networks and the Internet of creature huge amounts of complex data, both construct & unstructured are being captured in trust to allow organizations to produce better business decisions as data is now pivotal for an organizations success. These enormous amounts of data are referred to as Big Data, which enables a competitive advantage over rivals when processed and analyzed appropriately. However Big Data Analytics has a few concerns including Management of Data, Privacy & Security, getting optimal path for transport data, and Data Representation. However, the structure of network does not completely match transportation demand, i.e., there still exist a few bottlenecks in the network. This paper presents a new approach to get the optimal path of valuable data movement through a given network based on the knapsack problem. This paper will give value for each piece of data, it depends on the importance of this data (each piece of data defined by two arguments size and value), and the approach tries to find the optimal path from source to destination, a mathematical models are developed to adjust data flows between their shortest paths based on the 0 - 1 knapsack problem. We also take out computational experience using the commercial software Gurobi and a greedy algorithm (GA), respectively. The outcome indicates that the suggest models are active and workable. This paper introduced two different algorithms to study the shortest path problems: the first algorithm studies the shortest path problems when stochastic activates and activities does not depend on weights. The second algorithm studies the shortest path problems depends on weights.展开更多
Big data technology has become increasingly prevalent in facilitating the delivery of government services and public goods in China and beyond.This article seeks to examine how big data can be leveraged in poverty gov...Big data technology has become increasingly prevalent in facilitating the delivery of government services and public goods in China and beyond.This article seeks to examine how big data can be leveraged in poverty governance in rural China,and what the political implications are.This phenomenon of big data-driven welfare governance is particularly salient considering the broader context of governmental digital transformation,both within China and globally.This research sheds light on how big data usage functions in poverty alleviation,highlighting general motivations and developments in Chinese data-centric welfare governance.More importantly,this article introduces the novel concept of"digital cybernetic capacity"to examine public sector modernization as big data transforms the landscape of welfare delivery and governance.By delving into the intersection between technology and social welfare,we explicate how the use of big data in social welfare policies can go beyond merely improving information capacity to redefine state capacity.This article argues that such a new governance ecosystem,driven as it is by data technologies,not only provides insights about the transformative resilience of Chinese governance but also opens a new theoretical frontier for research into other countries.展开更多
文摘The advancements of mobile devices, public networks and the Internet of creature huge amounts of complex data, both construct & unstructured are being captured in trust to allow organizations to produce better business decisions as data is now pivotal for an organizations success. These enormous amounts of data are referred to as Big Data, which enables a competitive advantage over rivals when processed and analyzed appropriately. However Big Data Analytics has a few concerns including Management of Data, Privacy & Security, getting optimal path for transport data, and Data Representation. However, the structure of network does not completely match transportation demand, i.e., there still exist a few bottlenecks in the network. This paper presents a new approach to get the optimal path of valuable data movement through a given network based on the knapsack problem. This paper will give value for each piece of data, it depends on the importance of this data (each piece of data defined by two arguments size and value), and the approach tries to find the optimal path from source to destination, a mathematical models are developed to adjust data flows between their shortest paths based on the 0 - 1 knapsack problem. We also take out computational experience using the commercial software Gurobi and a greedy algorithm (GA), respectively. The outcome indicates that the suggest models are active and workable. This paper introduced two different algorithms to study the shortest path problems: the first algorithm studies the shortest path problems when stochastic activates and activities does not depend on weights. The second algorithm studies the shortest path problems depends on weights.
基金the youth project"Research on the Practical Challenges of Government Digital Transformation and Their Mitigation Mechanisms from the Perspective of Algorithmic Governance"supported by the National Social Science Fund of China(No.21CZZ039).
文摘Big data technology has become increasingly prevalent in facilitating the delivery of government services and public goods in China and beyond.This article seeks to examine how big data can be leveraged in poverty governance in rural China,and what the political implications are.This phenomenon of big data-driven welfare governance is particularly salient considering the broader context of governmental digital transformation,both within China and globally.This research sheds light on how big data usage functions in poverty alleviation,highlighting general motivations and developments in Chinese data-centric welfare governance.More importantly,this article introduces the novel concept of"digital cybernetic capacity"to examine public sector modernization as big data transforms the landscape of welfare delivery and governance.By delving into the intersection between technology and social welfare,we explicate how the use of big data in social welfare policies can go beyond merely improving information capacity to redefine state capacity.This article argues that such a new governance ecosystem,driven as it is by data technologies,not only provides insights about the transformative resilience of Chinese governance but also opens a new theoretical frontier for research into other countries.
