45,868 research outputs found
Expert system training and control based on the fuzzy relation matrix
Fuzzy knowledge, that for which the terms of reference are not crisp but overlapped, seems to characterize human expertise. This can be shown from the fact that an experienced human operator can control some complex plants better than a computer can. Proposed here is fuzzy theory to build a fuzzy expert relation matrix (FERM) from given rules or/and examples, either in linguistic terms or in numerical values to mimic human processes of perception and decision making. The knowledge base is codified in terms of many implicit fuzzy rules. Fuzzy knowledge thus codified may also be compared with explicit rules specified by a human expert. It can also provide a basis for modeling the human operator and allow comparison of what a human operator says to what he does in practice. Two experiments were performed. In the first, control of liquid in a tank, demonstrates how the FERM knowledge base is elicited and trained. The other shows how to use a FERM, build up from linguistic rules, and to control an inverted pendulum without a dynamic model
Cascaded Scene Flow Prediction using Semantic Segmentation
Given two consecutive frames from a pair of stereo cameras, 3D scene flow
methods simultaneously estimate the 3D geometry and motion of the observed
scene. Many existing approaches use superpixels for regularization, but may
predict inconsistent shapes and motions inside rigidly moving objects. We
instead assume that scenes consist of foreground objects rigidly moving in
front of a static background, and use semantic cues to produce pixel-accurate
scene flow estimates. Our cascaded classification framework accurately models
3D scenes by iteratively refining semantic segmentation masks, stereo
correspondences, 3D rigid motion estimates, and optical flow fields. We
evaluate our method on the challenging KITTI autonomous driving benchmark, and
show that accounting for the motion of segmented vehicles leads to
state-of-the-art performance.Comment: International Conference on 3D Vision (3DV), 2017 (oral presentation
Static, massive fields and vacuum polarization potential in Rindler space
In Rindler space, we determine in terms of special functions the expression
of the static, massive scalar or vector field generated by a point source. We
find also an explicit integral expression of the induced electrostatic
potential resulting from the vacuum polarization due to an electric charge at
rest in the Rindler coordinates. For a weak acceleration, we give then an
approximate expression in the Fermi coordinates associated with the uniformly
accelerated observer.Comment: 11 pages, latex, no figure
Whatever It Takes: How and When Supervisor Bottom-Line Mentality Motivates Employee Contributions in the Workplace
Given that many organizations are competitive and finance centered, organizational leaders may lead with a primary focus on bottom-line attainment, such that they are perceived by their subordinates as having a bottom-line mentality (BLM) that entails pursuing bottom-line outcomes above all else. Yet, the field is limited in understanding why such a leadership approach affects employees’ positive and negative contributions in the workplace. Drawing on social exchange theory, we theorize that supervisors high in BLM can influence employees’ felt obligation toward the bottom line, which in turn can influence employees’ task performance and unethical pro-organizational behavior (UPB). We also examine employee ambition as a moderator of this process. Using three-wave, multisource data collected from the financial services industry, our results revealed that high-BLM supervisors elevate employee task performance as well as UPB by motivating employees’ felt obligation toward the bottom line. Furthermore, we found that employee ambition served as a first-stage moderator, such that the mediated relationships were stronger when employee ambition was high as opposed to low. Our findings break away from the dominant dysfunctional view of BLM and provide a more balanced view of this mentality
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