Renmin University of China

About: Renmin University of China is a education organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: China & Population. The organization has 11325 authors who have published 15498 publications receiving 238419 citations. The organization is also known as: Renmin University & People's University of China.

Social Exchange Implications of Own and CoWorkers' Experiences of Supervisory Abuse

Abstract: This study examines how the quality of individuals’ social exchange relationships with their leaders and separately, their work unit peers, mediate the interactive effects of abusive supervision directed toward themselves (own abusive supervision) and toward their work unit peers (peer abusive supervision) on individual task performance and helping behavior directed toward coworkers. Testing the model using a sample of 358 workers from 25 organizations, we found support for our hypotheses that leader– member exchange (LMX) and affect-based trust in peers each partially mediated the interactive effects of own and peer abusive supervision. Workers that exhibited high levels of task performance and engaged in more helping behaviors tended to have both low own abusive supervision and low peer abusive supervision. Own abusive supervision was unrelated to the behavioral outcomes among workers whose peers were victims of supervisory abuse. We discuss the implications of relational dynamics with peers and the immediate supervisor for understanding the scope of the impact of abusive supervision on follower outcomes.

Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement, and Retrieval

Abstract: Where previous reviews on content-based image retrieval emphasize what can be seen in an image to bridge the semantic gap, this survey considers what people tag about an image A comprehensive treatise of three closely linked problems (ie, image tag assignment, refinement, and tag-based image retrieval) is presented While existing works vary in terms of their targeted tasks and methodology, they rely on the key functionality of tag relevance, that is, estimating the relevance of a specific tag with respect to the visual content of a given image and its social context By analyzing what information a specific method exploits to construct its tag relevance function and how such information is exploited, this article introduces a two-dimensional taxonomy to structure the growing literature, understand the ingredients of the main works, clarify their connections and difference, and recognize their merits and limitations For a head-to-head comparison with the state of the art, a new experimental protocol is presented, with training sets containing 10,000, 100,000, and 1 million images, and an evaluation on three test sets, contributed by various research groups Eleven representative works are implemented and evaluated Putting all this together, the survey aims to provide an overview of the past and foster progress for the near future

Interface Coupling in Twisted Multilayer Graphene by Resonant Raman Spectroscopy of Layer Breathing Modes.

Abstract: Raman spectroscopy is the prime nondestructive characterization tool for graphene and related layered materials. The shear (C) and layer breathing modes (LBMs) are due to relative motions of the planes, either perpendicular or parallel to their normal. This allows one to directly probe the interlayer interactions in multilayer samples. Graphene and other two-dimensional (2d) crystals can be combined to form various hybrids and heterostructures, creating materials on demand with properties determined by the interlayer interaction. This is the case even for a single material, where multilayer stacks with different relative orientations have different optical and electronic properties. In twisted multilayer graphene there is a significant enhancement of the C modes due to resonance with new optically allowed electronic transitions, determined by the relative orientation of the layers. Here we show that this applies also to the LBMs, which can be now directly measured at room temperature. We find that twistin...

DADA: a data cube for dominant relationship analysis

Abstract: The concept of dominance has recently attracted much interest in the context of skyline computation. Given an N-dimensional data set S, a point p is said to dominate q if p is better than q in at least one dimension and equal to or better than it in the remaining dimensions. In this paper, we propose extending the concept of dominance for business analysis from a microeconomic perspective. More specifically, we propose a new form of analysis, called Dominant Relationship Analysis (DRA), which aims to provide insight into the dominant relationships between products and potential buyers. By analyzing such relationships, companies can position their products more effectively while remaining profitable.To support DRA, we propose a novel data cube called DADA (Data Cube for Dominant Relationship Analysis), which captures the dominant relationships between products and customers. Three types of queries called Dominant Relationship Queries (DRQs) are consequently proposed for analysis purposes: 1)Linear Optimization Queries (LOQ), 2)Subspace Analysis Queries (SAQ), and 3)Comparative Dominant Queries (CDQ). Algorithms are designed for efficient computation of DADA and answering the DRQs using DADA. Results of our comprehensive experiments show the effectiveness and efficiency of DADA and its associated query processing strategies.