88 research outputs found
Driving the Use of Enterprise Social Media at Work: A Framework for Employeesâ Adoption
More and more organizations are using enterprise social media (ESM) to improve the efficiency of communication and collaboration. Although many studies have tried to investigate employeesâ adoption of this technology, most only provide limited insights and fail to capture the differences between ESM and other information systems used in organizations. In this article, we introduce a framework for enterprise social media adoption at the individual level. Our framework is based on the unified theory of acceptance and use of technology (UTAUT) and enterprise social media affordances. It is necessary to divide employeesâ usage behavior into three types: not use, contribute, and lurk. We propose that the affordances initiate new types of factors that drive the three types of employeesâ usage behavior differently
Learning Rich Features for Gait Recognition by Integrating Skeletons and Silhouettes
Gait recognition captures gait patterns from the walking sequence of an
individual for identification. Most existing gait recognition methods learn
features from silhouettes or skeletons for the robustness to clothing,
carrying, and other exterior factors. The combination of the two data
modalities, however, is not fully exploited. Previous multimodal gait
recognition methods mainly employ the skeleton to assist the local feature
extraction where the intrinsic discrimination of the skeleton data is ignored.
This paper proposes a simple yet effective Bimodal Fusion (BiFusion) network
which mines discriminative gait patterns in skeletons and integrates with
silhouette representations to learn rich features for identification.
Particularly, the inherent hierarchical semantics of body joints in a skeleton
is leveraged to design a novel Multi-Scale Gait Graph (MSGG) network for the
feature extraction of skeletons. Extensive experiments on CASIA-B and OUMVLP
demonstrate both the superiority of the proposed MSGG network in modeling
skeletons and the effectiveness of the bimodal fusion for gait recognition.
Under the most challenging condition of walking in different clothes on
CASIA-B, our method achieves the rank-1 accuracy of 92.1%.Comment: The paper is under consideration at Multimedia Tools and Application
Inherent SM Voltage Balance for Multilevel Circulant Modulation in Modular Multilevel DC--DC Converters
The modularity of a modular multilevel dc converter (MMDC) makes it attractive for medium-voltage distribution systems. Inherent balance of submodule (SM) capacitor voltages is considered as an ideal property, which avoids a complex sorting process based on many measurements thereby reducing costs and enhancing reliability. This article extends the inherent balance concept previously shown for square-wave modulation to a multilevel version for MMDCs. A switching duty matrix dU is introduced: it is a circulant matrix of preset multilevel switching patterns with multiple stages and multiple durations. Inherent voltage balance is ensured with a full-rank dU . Circulant matrix theory shows that this is equivalent to a simplified common factor criterion. A nonfull rank dU causes clusters of SM voltage rather than a single common value, with the clusters indicated by the kernel of the matrix. A generalized coprime criterion is developed into several deductions that serve as practical guidance for design of multilevel circulant modulation. The theoretical development is verified through full-scale simulations and downscaled experiments. The effectiveness of the proposed circulant modulation in achieving SM voltage balance in an MMDC is demonstrated
A seismic prediction method of reservoir brittleness based on mineral composition and pore structure
The Lucaogou Formation, a typical fine-grained mixed formation in the Jimusaer Sag of the Junggar Basin, exhibits considerable potential for hydrocarbon exploration. Accurate brittle prediction is a crucial factor in determining hydraulic fracturing effectiveness. However, the area features complex lithological characteristics, including carbonate rocks, clastic rocks, volcanic rocks, and gypsum interbeds, along with thin layering and sporadic sweet spots. Traditional prediction methods offer limited resolution and there is an urgent need for a seismic brittle prediction method tailored to this complex geological environment. This paper presents a multi-mineral composition equivalent model for complex lithologies that enables the accurate calculation of Vp and Vs These ratios serve as the foundation for pre-stack elastic parameter predictions, which include Poissonâs ratio and Youngâs modulus. By comparing the predicted parameters with well-logging measurements, the prediction accuracy is improved to 82%, with particularly high conformity in intervals characterized by high organic matter and clay content. Additionally, a three-dimensional brittle modeling approach reveals that the brittleness of the reservoir exceeds that of the surrounding rock, showing a gradual improvement in brittleness with increasing burial depth from southeast to northwest. The central area exhibits relatively good brittleness, with a stable, blocky distribution pattern
The oyster genome reveals stress adaptation and complexity of shell formation
The Pacific oyster Crassostrea gigas belongs to one of the most species-rich but genomically poorly explored phyla, the Mollusca. Here we report the sequencing and assembly of the oyster genome using short reads and a fosmid-pooling strategy, along with transcriptomes of development and stress response and the proteome of the shell. The oyster genome is highly polymorphic and rich in repetitive sequences, with some transposable elements still actively shaping variation. Transcriptome studies reveal an extensive set of genes responding to environmental stress. The expansion of genes coding for heat shock protein 70 and inhibitors of apoptosis is probably central to the oyster's adaptation to sessile life in the highly stressful intertidal zone. Our analyses also show that shell formation in molluscs is more complex than currently understood and involves extensive participation of cells and their exosomes. The oyster genome sequence fills a void in our understanding of the Lophotrochozoa. © 2012 Macmillan Publishers Limited. All rights reserved
Polymorphisms of HIF1A gene are associated with prognosis of early stage non-small-cell lung cancer patients after surgery
Inherent SM Voltage Balance for Multilevel Circulant Modulation in Modular Multilevel DC--DC Converters
The modularity of a modular multilevel dc converter (MMDC) makes it attractive for medium-voltage distribution systems. Inherent balance of submodule (SM) capacitor voltages is considered as an ideal property, which avoids a complex sorting process based on many measurements thereby reducing costs and enhancing reliability. This article extends the inherent balance concept previously shown for square-wave modulation to a multilevel version for MMDCs. A switching duty matrix dU is introduced: it is a circulant matrix of preset multilevel switching patterns with multiple stages and multiple durations. Inherent voltage balance is ensured with a full-rank dU. Circulant matrix theory shows that this is equivalent to a simplified common factor criterion. A nonfull rank dU causes clusters of SM voltage rather than a single common value, with the clusters indicated by the kernel of the matrix. A generalized coprime criterion is developed into several deductions that serve as practical guidance for design of multilevel circulant modulation. The theoretical development is verified through full-scale simulations and downscaled experiments. The effectiveness of the proposed circulant modulation in achieving SM voltage balance in an MMDC is demonstrated.</p
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