Solution Exemplars and Sales Performance of Crowdsourcing Solvers: the Moderating Role of Reputation and Competence

An increasing number of signals are using to entice solvers to make online purchases by seekers in the competitive online markets today. However, how solution exemplars are in terms of their reputation or competence to improve sales performance has not yet been investigated. Extending signal theory to the online service marketplaces, we analyses the effect of solution exemplars’ structural characteristics on seekers’ sales performance such as quantity, diversity and popularity, exploring the moderating impact of seeker’s reputation and competence. We test the model using data from ZBJ.com, a popular crowdsourcing contest platform in China. Our analysis conducts a series of interesting findings, the impact of exemplar quantity and popularity on sales performance is positively significant, contrary to solution exemplar diversity. Regarding the moderation effects, reputation is proved to be negative, which is opposite to competence. We also elaborate on the theoretical contribution and practical significance

Application of DMSP/OLS nighttime light images : a meta-analysis and a systematic literature review

© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 6 (2014): 6844-6866, doi:10.3390/rs6086844.Since the release of the digital archives of Defense Meteorological Satellite Program Operational Line Scanner (DMSP/OLS) nighttime light data in 1992, a variety of datasets based on this database have been produced and applied to monitor and analyze human activities and natural phenomena. However, differences among these datasets and how they have been applied may potentially confuse researchers working with these data. In this paper, we review the ways in which data from DMSP/OLS nighttime light images have been applied over the past two decades, focusing on differences in data processing, research trends, and the methods used among the different application areas. Five main datasets extracted from this database have led to many studies in various research areas over the last 20 years, and each dataset has its own strengths and limitations. The number of publications based on this database and the diversity of authors and institutions involved have shown promising growth. In addition, researchers have accumulated vast experience retrieving data on the spatial and temporal dynamics of settlement, demographics, and socioeconomic parameters, which are “hotspot” applications in this field. Researchers continue to develop novel ways to extract more information from the DMSP/OLS database and apply the data to interdisciplinary research topics. We believe that DMSP/OLS nighttime light data will play an important role in monitoring and analyzing human activities and natural phenomena from space in the future, particularly over the long term. A transparent platform that encourages data sharing, communication, and discussion of extraction methods and synthesis activities will benefit researchers as well as public and political stakeholders.This work is supported by the 111 project “Hazard and Risk Science Base at Beijing Normal University” under Grant B08008 (Ministry of Education and State Administration of Foreign Experts Affairs, PRC), the State Key Laboratory of Earth Surface Processes and Resource Ecology of Beijing Normal University (No. 2013-RC-03), and the Fundamental Research Funds for the Central Universities (Grant No. 201413037)

Research on Face Recognition Based on Embedded System

Because a number of image feature data to store, complex calculation to execute during the face recognition, therefore the face recognition process was realized only by PCs with high performance. In this paper, the OpenCV facial Haar-like features were used to identify face region; the Principal Component Analysis (PCA) was employed in quick extraction of face features and the Euclidean Distance was also adopted in face recognition; as thus, data amount and computational complexity would be reduced effectively in face recognition, and the face recognition could be carried out on embedded platform. Finally, based on Tiny6410 embedded platform, a set of embedded face recognition systems was constructed. The test results showed that the system has stable operation and high recognition rate can be used in portable and mobile identification and authentication

Linearized Tensor Renormalization Group Algorithm for Thermodynamics of Quantum Lattice Models

A linearized tensor renormalization group (LTRG) algorithm is proposed to calculate the thermodynamic properties of one-dimensional quantum lattice models, that is incorporated with the infinite time-evolving block decimation technique, and allows for treating directly the two-dimensional transfer-matrix tensor network. To illustrate its feasibility, the thermodynamic quantities of the quantum XY spin chain are calculated accurately by the LTRG, and the precision is shown to be comparable with (even better than) the transfer matrix renormalization group (TMRG) method. Unlike the TMRG scheme that can only deal with the infinite chains, the present LTRG algorithm could treat both finite and infinite systems, and may be readily extended to boson and fermion quantum lattice models.Comment: published versio

Kosterlitz-Thouless phase transition and reentrance in an anisotropic 3-state Potts model on the generalized Kagome lattice

The unusual reentrant phenomenon is observed in the anisotropic 3-state Potts model on a gen- eralized Kagome lattice. By employing the linearized tensor renormalization group method, we find that the reentrance can appear in the region not only under a partial ordered phase as commonly known but also a phase without a local order parameter, which is uncovered to fall into the uni- versality of the Kosterlitz-Thouless (KT) type. The region of the reentrance depends strongly on the ratios of the next nearest couplings {\alpha} = J2 /|J1 | and {\beta} = J3 /|J1 |. The phase diagrams in the plane of temperature versus {\beta} for different {\alpha} are obtained. Through massive calculations, it is also revealed that the quasi-entanglement entropy can be used to accurately detect the KT transition temperature