Simeng Liu

Australian National University

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Kun Tracy Wang

Australian National University

Laxmikant V. Kalé

University of Illinois Urbana-Champaign

Zane Fink

University of Illinois Urbana-Champaign

Weili Shao

Zhongyuan University of Technology

Matthias Diener

University of Illinois Urbana-Champaign

Fan Liu

State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation

Jianxin He

Zhongyuan University of Technology

Yongli Hu

Beijing University of Technology

Yanfeng Sun

Qingdao University of Science and Technology

Jaemin Choi

University of Illinois Urbana-Champaign

Cooperative Institutions

Zhongyuan University of Technology

University of Illinois Urbana-Champaign

Chinese Academy of Sciences

Huazhong University of Science and Technology

Jiangsu Normal University

Google (United States)

Beijing Normal University

Zhejiang University

National Center for Supercomputing Applications

Beijing University of Technology

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Fabrication of fully degradable branched poly (lactic acid) nanofiber membranes for high‐efficiency filter paper materials

Journal of Applied Polymer Science (2022)

Ning Sun Weili Shao Jin Zheng Yuting Zhang Junli Li

Abstract Air pollution caused by particulate matter (PM) poses an imminent threat to the global environment and public health. However, balancing the removal efficiency and pressure drop of most filter materials is difficult. Moreover, filter materials are non‐degradable and non‐recyclable, causing serious harm to the environment. Herein, a strategy to create fully degradable branched poly (lactic acid) (PLA) nanofibers based on electrospinning by adjusting the spinning solution properties was reported and branched PLA nanofibers were applied as nanofiber filter paper for air filtration materials. When the PLA and tetrabutylammonium chloride concentrations were 8 and 5 wt%, respectively, PLA nanofibers with branched structures were obtained. The obtained nanofibers possessed a small pore size (0.70 μm), high porosity (92.3%), appropriate mechanical properties, resulting in high PM 0.3 removal efficiency (99.95%), low air resistance (79.67 Pa), and promising long‐term PM 2.5 purification. Notably, branched T‐PLA‐5 nanofibers exhibited excellent filtration performance when applied to cellulose wood pulp paper. The filtration efficiency of the nanofiber filter paper remained stable above 85% for PM 0.3 (32 L min −1 ) after 5000 backflushings. Thus, the preparation of such nanomaterials may provide new insights into the design and development of high‐performance degradable filtration materials for various applications.

Electrospinning

Filtration (mathematics)

Air filter

Nanomaterials

10.1002/app.53186

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Citations (7)

A Study on the Effects of Human Capital of Chinese High Tech Companies on Innovation Performance - Focused on the Mediating Effects of Absorptive Capacity -

Journal of China Area Studies (2021)

Simeng Liu Tae Won Kang Tae-Uk Ahn

Absorptive Capacity

High tech

10.34243/jcas.8.4.241

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A Study on the Impact of Digital Empowerment, Value Co-Creation and Hotel Service Innovation Capability

Advances in computer science research (2024)

Simeng Liu Rujie Zhu Hong Yu Lu

Co-Creation

Service Innovation

Value (mathematics)

10.2991/978-94-6463-562-1_27

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Citations (1)

LinguaLinked: A Distributed Large Language Model Inference System for Mobile Devices

arXiv (Cornell University) (2023)

Junchen Zhao Yurun Song Simeng Liu Ian G. Harris Sangeetha Abdu Jyothi

Deploying Large Language Models (LLMs) locally on mobile devices presents a significant challenge due to their extensive memory requirements. In this paper, we introduce LinguaLinked, a system for decentralized, distributed LLM inference on mobile devices. LinguaLinked enables collaborative execution of the inference task across multiple trusted devices. LinguaLinked ensures data privacy by processing information locally. LinguaLinked uses three key strategies. First, an optimized model assignment technique segments LLMs and uses linear optimization to align segments with each device's capabilities. Second, an optimized data transmission mechanism ensures efficient and structured data flow between model segments while also maintaining the integrity of the original model structure. Finally, LinguaLinked incorporates a runtime load balancer that actively monitors and redistributes tasks among mobile devices to prevent bottlenecks, enhancing the system's overall efficiency and responsiveness. We demonstrate that LinguaLinked facilitates efficient LLM inference while maintaining consistent throughput and minimal latency through extensive testing across various mobile devices, from high-end to low-end Android devices. In our evaluations, compared to the baseline, LinguaLinked achieves an inference performance acceleration of $1.11\times$ to $1.61\times$ in single-threaded settings, $1.73\times$ to $2.65\times$ with multi-threading. Additionally, runtime load balancing yields an overall inference acceleration of $1.29\times$ to $1.32\times$.

10.48550/arxiv.2312.00388

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Citations (2)

Mixture of Bilateral-Projection Two-dimensional Probabilistic Principal Component Analysis

arXiv (Cornell University) (2016)

Fujiao Ju Yanfeng Sun Junbin Gao Simeng Liu Yongli Hu

The probabilistic principal component analysis (PPCA) is built upon a global linear mapping, with which it is insufficient to model complex data variation. This paper proposes a mixture of bilateral-projection probabilistic principal component analysis model (mixB2DPPCA) on 2D data. With multi-components in the mixture, this model can be seen as a soft cluster algorithm and has capability of modeling data with complex structures. A Bayesian inference scheme has been proposed based on the variational EM (Expectation-Maximization) approach for learning model parameters. Experiments on some publicly available databases show that the performance of mixB2DPPCA has been largely improved, resulting in more accurate reconstruction errors and recognition rates than the existing PCA-based algorithms.

Component (thermodynamics)

Sparse PCA

10.48550/arxiv.1601.01431

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Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

Zenodo (CERN European Organization for Nuclear Research) (2021)

Zane Fink Simeng Liu Jaemin Choi Matthias Diener Laxmikant V. Kalé

All data relevant for the paper "Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py". To use with the analysis scripts, clone the github repository https://github.com/UIUC-PPL/charm4py-mpi4py-compare, and check out the "espm2_2021" branch. Unzip this file into the cloned repository, the analysis scripts will access it from there.

Python

10.5281/zenodo.5629345

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Knowledge Discovery of the Orientation of University Graduates in Beijing Area Based on Decision Tree

DEStech Transactions on Computer Science and Engineering (2019)

Simeng Liu

With the expansion of undergraduate enrolment in universities in Beijing, the pressure on the graduates is increasing. It is particularly important to study the orientation of graduates. In this paper, through questionnaire method to collect information about undergraduates in Beijing, according to the characteristics of undergraduates from the data collected, we built a decision tree model with C5.0 algorithm and pruned. The rules of classification are used to display the mining results intuitively. Then, we analyzed and verified the model to provide theoretical support for the undergraduates' choice of direction.

Tree (set theory)

10.12783/dtcse/msota2018/27556

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Citations (0)

tensorflow-tracing: A Performance Tuning Framework for Production

Sayed Hadi Hashemi Paul Rausch Benjamin Rabe Kuan-Yen Chou Simeng Liu

Tracing

Source

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Citations (2)

Discovery of novel chalcone-dithiocarbamates as ROS-mediated apoptosis inducers by inhibiting catalase

Bioorganic Chemistry (2019)

Dong‐Jun Fu Jiahuan Li Jiajia Yang Ping Li Yan‐Bing Zhang

Chalcone

MMP2

10.1016/j.bioorg.2019.01.023

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Citations (30)

Integrating Corporate Social Responsibility Criteria into Executive Compensation and Firm Innovation: International Evidence

SSRN Electronic Journal (2021)

Albert Tsang Kun Tracy Wang Simeng Liu Li Yu

Using a large sample of firms from 30 countries, we find that the integration of corporate social responsibility (CSR) criteria into executive compensation is associated with greater innovation output in countries around the world. We also find that this positive association is stronger in countries with weak stakeholder orientation, countries with weak legal environments, and countries without mandatory CSR reporting requirements. These findings suggest that CSR contracting can compensate for institutional voids and high stakeholder demand for CSR, and thereby foster firm innovation. The results of the channel analyses suggest that a greater level of employee innovation productivity, enhanced managerial risk-taking, and greater responsiveness of firms' R&D investment to their investment opportunities play a significant role in the association between CSR contracting and innovation. Overall, our study demonstrates in a global context the importance of linking executive compensation to nonfinancial criteria in addition to financial criteria, and it documents the heterogeneity in the effect of CSR contracting on firm innovation in different countries. doi link: https://doi.org/10.1016/j.jcorpfin.2021.102070 Free share link (before October 12 2021) provided by Elsevier: https://authors.elsevier.com/a/1ddKR3JGUMs5N9

Executive compensation

Investment

Sample (material)

Source

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