21,143 research outputs found
Multi-view shaker detection: Insights from a noise-immune influence analysis Perspective
Entities whose changes will significantly affect others in a networked system
are called shakers. In recent years, some models have been proposed to detect
such shaker from evolving entities. However, limited work has focused on shaker
detection in very short term, which has many real-world applications. For
example, in financial market, it can enable both investors and governors to
quickly respond to rapid changes. Under the short-term setting, conventional
methods may suffer from limited data sample problems and are sensitive to
cynical manipulations, leading to unreliable results. Fortunately, there are
multi-attribute evolution records available, which can provide compatible and
complementary information. In this paper, we investigate how to learn reliable
influence results from the short-term multi-attribute evolution records. We
call entities with consistent influence among different views in short term as
multi-view shakers and study the new problem of multi-view shaker detection. We
identify the challenges as follows: (1) how to jointly detect short-term
shakers and model conflicting influence results among different views? (2) how
to filter spurious influence relation in each individual view for robust
influence inference? In response, a novel solution, called Robust Influence
Network from a noise-immune influence analysis perspective is proposed, where
the possible outliers are well modelled jointly with multi-view shaker
detection task. More specifically, we learn the influence relation from each
view and transform influence relation from different views into an intermediate
representation. In the meantime, we uncover both the inconsistent and spurious
outliers.Comment: 14 pages, 4 figure
Prospecting Community Development Strength based on Economic Graph: From Categorization to Scoring
Recent years have witnessed a growing number of researches on community
characterization. In contrast to the large body of researches on the
categorical measures (rise or decline) for evaluating the community
development, we propose to estimate the community development strength (to
which degree the rise or decline is). More specifically, given already known
categorical information of community development, we are attempting to quantify
the community development strength, which is of great interest. Motivated by
the increasing availability of large-scale data on the network between entities
among communities, we investigate how to score the the community's development
strength. We formally define our task as prospecting community development
strength from categorization based on multi-relational network information and
identify two challenges as follows: (1) limited guidance for integrating entity
multi-relational network in quantifying the community development strength; (2)
the existence of selection effect that the community development strength has
on network formation. Aiming at these challenges, we start by a hybrid of
discriminative and generative approaches on multi-relational network-based
community development strength quantification. Then a network generation
process is exploited to debias the selection process. In the end, we
empirically evaluate the proposed model by applying it to quantify enterprise
business development strength. Experimental results demonstrate the
effectiveness of the proposed method.Comment: 12 pages, 3 figure
Flux enhancements in cross-flow microfiltration
Two-phase flow microfiltration successfully reduced the fouling problem for several microfiltration processes. Two-phase flow, created by introducing air into the fluid, increased the permeate flux 120%, 45%, and 40% for three different fermented biomass solutions at one hour operating time. For cheese whey microfiltration, the two-phase flow method successfully improved the permeate flux approximately 50% with only 5% air. Without the two-phase flow method, the permeate flux increased 20% when the liquid flow rate was doubled. Intermittent use of air was less effective than continual addition. Operating parameters of two-phase flow microfiltration, such as liquid flow rate and air percentage, were optimized based on permeate flux and energy requirements. The two-phase flow technique saved more energy and processing time than simply increasing the liquid flow rate. An economic analysis was performed to estimate the annual costs for scale-up of a cheese whey microfiltration process
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