144,285 research outputs found
Urbanization, Inequality, and Poverty in the People’s Republic of China
Relying on the present literature, official statistics, and household survey data in the People’s Republic of China, this paper summarizes research findings on the relationship between urbanization, urban–rural inequality, and poverty, and provides further empirical evidence on the role of urbanization and government policies in urban poverty. Several conclusions can be drawn from. First, urbanization has a significant effect on reducing both poverty of rural residents and poverty of migrating peasants, and, consequently, has a positive effect on narrowing the rural–urban income or consumption gap. Urban labor markets play an important role in this effect. Second, urbanization is positively correlated with urban poverty. This can be explained by the competition between migrating peasants and urban workers in the labor market, and the failure of the government’s anti-poverty policies in urban areas. Third, the existence of an informal sector has a negative effect on the poverty of urban citizens. Being employed by the informal sector significantly increases the probability of falling into poverty for urban citizens. Fourth, the minimum wage has a positive effect on reducing urban poverty, while the effect of other policies, such as Di Bao and the minimum living standard, is limited
Community Structure Detection in Complex Networks with Partial Background Information
Constrained clustering has been well-studied in the unsupervised learning
society. However, how to encode constraints into community structure detection,
within complex networks, remains a challenging problem. In this paper, we
propose a semi-supervised learning framework for community structure detection.
This framework implicitly encodes the must-link and cannot-link constraints by
modifying the adjacency matrix of network, which can also be regarded as
de-noising the consensus matrix of community structures. Our proposed method
gives consideration to both the topology and the functions (background
information) of complex network, which enhances the interpretability of the
results. The comparisons performed on both the synthetic benchmarks and the
real-world networks show that the proposed framework can significantly improve
the community detection performance with few constraints, which makes it an
attractive methodology in the analysis of complex networks
Secrecy Wireless Information and Power Transfer in OFDMA Systems
In this paper, we consider simultaneous wireless information and power
transfer (SWIPT) in orthogonal frequency division multiple access (OFDMA)
systems with the coexistence of information receivers (IRs) and energy
receivers (ERs). The IRs are served with best-effort secrecy data and the ERs
harvest energy with minimum required harvested power. To enhance physical-layer
security and yet satisfy energy harvesting requirements, we introduce a new
frequency-domain artificial noise based approach. We study the optimal resource
allocation for the weighted sum secrecy rate maximization via transmit power
and subcarrier allocation. The considered problem is non-convex, while we
propose an efficient algorithm for solving it based on Lagrange duality method.
Simulation results illustrate the effectiveness of the proposed algorithm as
compared against other heuristic schemes.Comment: To appear in Globecom 201
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