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31st Annual ACM Symposium on Applied Computing, SAC 2016

作者： Long, Zhenyue Zhang, Yu State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China Laboratory of Symbol Computation and Knowledge Zhuhai College Jilin University China Information Center Guangdong Power Grid Co. Ltd. China

ISBN: (纸本)9781450337397

Linearizability is an important correctness criterion for concurrent objects and automatic checking of linearizability often involves searching a sequential witness in an exponentially growing space of traces. We present two acceleration techniques for checking linearizability based on fine-grained traces: one is based on speculation of linearization points, and the other is to separate read-only methods from the enumeration of serial witnesses. We have applied them to checking linearizability of eight different algorithms and the experiment shows that both can offer significant speed-up, allowing us to explore further on error analysis of concurrent objects based on fine-grained traces. © 2016 ACM.

关键词： fine-grained trace automatic verification linearizability

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A model for representing topological relations between regions with holes

A model for representing topological relations between regio...

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1st International Conference on Information Science and engineering, ICISE2009

作者： Huo, Linlin Ouyang, Jihong Liu, Dayou College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

ISBN: (纸本)9780769538877

This paper proposes a unified model - D9-intersection model to represent topological relations between regions with holes. D9-intersection model can describe simple regional relations as accurately as 9-intersection model. When holes are allowed, D9-intersection model can distinguish relations that 9 - intersection could not and then be more expressive than 9-intersection model. In addition, we present the reasoning method based on D9-intersection model restricting to regions with at most one hole. ©2009 IEEE.

关键词： Topology

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Algorithmic challenges in structure-based drug design and NMR structural biology

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Frontiers of Electrical and Electronic engineering in China 2012年第1期7卷 69-84页

作者： Lincong WANG Shuxue ZOU Yao WANG College of Computer Science and Technology The Joint Center for Systems Biology of Jilin University and the University of Georgia Jilin University Changchun 130012 China Key Laboratory of Symbol Computation and Knowledge Engineer-ing of Ministry of Education Jilin University Changchun 130012China

The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly by two techniques： X-ray crystallog- raphy and nuclear magnetic resonance （NMR） spec- troscopy. Because neither X-ray crystallography nor NMR spectroscopy could directly measure the positions of atoms in a biomolecule, algorithms must be designed to compute atom coordinates from the data. One salient feature of most NMR structure computation algorithms is their reliance on stochastic search to find the lowest energy conformations that satisfy the experimentally- derived geometric restraints. However, neither the cor- rectness of the stochastic search has been established nor the errors in the output structures could be quantified. Though there exist exact algorithms to compute struc- tures from angular restraints, similar algorithms that use distance restraints remain to be developed. An important application of structures is rational drug design where protein-ligand docking plays a crit- ical role. In fact, various docking programs that place a compound into the binding site of a target protein have been used routinely by medicinal chemists for both lead identification and optimization. Unfortunately, de- spite ongoing methodological advances and some success stories, the performance of current docking algorithms is still data-dependent. These algorithms formulate the docking problem as a match of two sets of feature points. Both the selection of feature points and the search for the best poses with the minimum scores are accomplished through some stochastic search methods. Both the un- certainty in the scoring function and the limited sam- pling space attained by the stochastic search contribute to their failures. Recently, we have developed two novel docking algorithms： a data-driven docking algorithm and a general docking algorithm that does not re

关键词： structure-based drug design （SBDD） vir- tual screening （VC） protein-ligand docking scoring function molecular dynamics （MD） Monte Carlo （MC） simulated annealing （SA） Markov chain Monte Carlo （MCMC） nuclear magnetic resonance （NMR） nuclear Overhauser effect （NOE） residual dipolar couplings （RDCs） chemical shift （CS） inference structure deter- mination （ISD） Bayesian Gibbs sampling probabil- ity distribution functions （PDFs） degrees of freedom （DOF） van der Waals （VDW） root mean square devi- ation （RMSD） manifold Poisson-Boltzmann equation （PBE）

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Hybrid Parameter Update: Alleviating Imbalance Impacts for Distributed Deep Learning 24

Hybrid Parameter Update: Alleviating Imbalance Impacts for D...

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24th IEEE International Conference on High Performance Computing and Communications, 8th IEEE International Conference on Data Science and Systems, 20th IEEE International Conference on Smart City and 8th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Li, Hongliang Xu, Dong Xu, Zhewen Li, Xiang College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Changchun China

ISBN: (纸本)9798350319934

Nowadays, data parallelism has been widely applied to train large datasets on distributed deep learning clusters, but it has suffered from costly global parameter updates at batch barriers. Performance imbalance among worker instances, introduced by uneven workload partitioning or biased resource allocation, can cause straggly workers, which can lead to severe impacts on both training speed and result accuracy. This paper studies the issue focusing on the tradeoff between training speed and result accuracy. We propose Cooperate Grouping Parallel (CGP), a hybrid parameter update solution that allows the flexibility of both synchronous and asynchronous update schemes. We introduce a novel Cooperate Worker Grouping Problem (CWGP) that seeks a task grouping configuration that leads to maximum model accuracy and holds customized training speed guarantees. We propose an evolution-based Pareto local searching algorithm to compute efficient worker grouping configurations. Comprehensive evaluation results are presented to demonstrate the effectiveness of CGP under both persistent and fluctuant imbalances. The proposed method alleviates the imbalance impacts without introducing extra adjustment over-heads. © 2022 IEEE.

关键词： Large dataset

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An unmanned aerial vehicle pose estimation system guided by desired shot 2

An unmanned aerial vehicle pose estimation system guided by ...

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2nd IEEE International Conference on Automation, Electronics and Electrical engineering, AUTEEE 2019

作者： Dou, Xinglei Ding, Qijian Du, Qiao Yang, Min Huo, Yuzhou Wang, Xin College of Software Engineering Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineer Ministry of Education Jilin University Changchun China

ISBN: (纸本)9781728150291

Unmanned aerial vehicles (UAVs) are widely used in aerial photography nowadays for their strong maneuverability, good image quality and high cost performance, while they have limited battery capacity and difficulty in operation. It is difficult to reach the ideal pose and get the desired shot by manual manipulation in a short time. To solve these problems, an UAV pose estimation system guided by desired shot is constructed. Either a sequence of images or a video is taken as input. The user interacts with the system to express the desired shot. The 3D-reconstruction is done by Structure from Motion (SfM). Then the Perspective-n-Point (PnP) problem is solved to estimate the ideal pose of the UAV. The experimental results proves that the system is effective and valid. © 2019 IEEE.

关键词： Aerial photography

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A FAST AND SCALABLE SUPERVISED TOPIC MODEL USING STOCHASTIC VARIATIONAL INFERENCE AND MAPREDUCE 5

A FAST AND SCALABLE SUPERVISED TOPIC MODEL USING STOCHASTIC ...

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2016 5th IEEE International Conference on Network Infrastructure and Digital Content(IC-NIDC 2016)

作者： Wenzhuo Song Bo Yang Xuehua Zhao Fei Li Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University School of Digital Media Shenzhen Institute of Information Technology George Mason University

ISBN: (纸本)9781509012473

An important and widespread topic in cloud computing is text *** often use topic model which is a popular and effective technology to deal with related *** all the topic models,sLDA is acknowledged as a popular supervised topic model,which adds a response variable or category label with each document,so that the model can uncover the latent structure of a text dataset as well as retains the predictive power for supervised ***,sLDA needs to process all the documents at each iteration in the training *** the size of dataset increases to the volume that one node cannot deal with,sLDA will no longer be *** this paper we propose a novel model named *** which extends sLDA with stochastic variational inference(SVI) and *** can reduce the computational burden of sLDA and MapReduce extends the algorithm with *** makes the training become more efficient and the training method can be easily implemented in a large computer cluster or cloud *** results show that our approach has an efficient training process,and similar accuracy with sLDA.

关键词： Text classification MapReduce Variational inference Topic modeling

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Superpixels Based Interactive Image Segmentation Algorithm

Superpixels Based Interactive Image Segmentation Algorithm

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2013 International Conference on Information,Business and Education Technology(ICIBET 2013)

作者： LONG Jian-wu SHEN Xuan-jing ZANG Hui CHEN Hai-peng College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University

ISBN: (纸本)9781629932101

A superpixels based interactive image segmentation algorithm is proposed in this paper. Firstly the initial segmentation is obtained by MeanShift algorithm, and then a graph is built using pre-segmented regions as nodes, finally min-cut/maxflow algorithm is implemented for global solution. In this process, each region is represented by a color histogram and Bhattacharyya coefficient is chosen to calculate the similarity between any two regions. Extensive experiments are performed and the results show that the presented algorithm obtains much more satisfactory segmentation results with less user interaction and less comsuming time than MSRM algorithm.

关键词： interactive image segmentation graph cut mean shift

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Recognizing event in short text based on decision tree

Recognizing event in short text based on decision tree

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作者： Lu, Jing Ya Zuo, Wan Li Zhu, Liang College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education of China China

ISBN: (纸本)9783038351399

Mining newsworthy events from a large number of microblogging information is not only the primary problem that several big microblogging websites need to solve, but also a new research field in micro-information age. For now, a lot of study about even recognizing has been made at home and abroad, but relatively rarely contrapose short text(microblogging message). The paper considers newsworthy event recognizing in short text as classification problem, utilizes the decision tree classification algorithm in data mining, sufficiently mines features of event in short text, and then recognizes the newsworthy event in microblogging. In the last, we verify the effect of the model. © (2014) Trans Tech Publications, Switzerland.

关键词： Data mining

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Adaptive Image Thresholding by Background Subtraction

Adaptive Image Thresholding by Background Subtraction

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2013 International Conference on Information,Business and Education Technology(ICIBET 2013)

ISBN: (纸本)9781629932101

In this paper, an adaptive image thresholding algorithm is proposed for thresholding images with uneven illumination. Firstly, a Gaussian scale space, which is produced from the convolution of a two-dimensional Gaussian function with an input image, is used to estimate the background image. Followed by background subtraction, the objective image can be easily obtained to eliminate interference of uneven illumination. Thirdly, to highlight those darker objects, gamma correction is employed to enhance the objective image. Finally, the thresholding result is extracted easily using the global valley-emphasis Otsu method. The experimental results show that the introduced method yields satisfactory visual quality.

关键词： thresholding background estimation background subtraction

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SMRI: A New Method for siRNA Design for COVID-19 Therapy

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Journal of Computer Science & Technology 2022年第4期37卷 991-1002页

作者： Meng-Xin Chen Xiao-Dong Zhu Hao Zhang Zhen Liu Yuan-Ning Liu College of Software Jilin UniversityChangchun 130012China Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Jilin UniversityChangchun 130012China College of Computer Science and Technology Jilin UniversityChangchun 130012China Graduate School of Engineering Nagasaki Institute of Applied ScienceNagasaki 851-0193Japan

First discovered in Wuhan, China, SARS-CoV-2 is a highly pathogenic novel coronavirus, which rapidly spreads globally and becomes a pandemic with no vaccine and limited distinctive clinical drugs available till March 13th, 2020. Ribonucleic Acid interference (RNAi) technology, a gene-silencing technology that targets mRNA, can cause damage to RNA viruses effectively. Here, we report a new efficient small interfering RNA (siRNA) design method named Simple Multiple Rules Intelligent Method (SMRI) to propose a new solution of the treatment of COVID-19. To be specific, this study proposes a new model named Base Preference and Thermodynamic Characteristic model (BPTC model) indicating the siRNA silencing efficiency and a new index named siRNA Extended Rules index (SER index) based on the BPTC model to screen high-efficiency siRNAs and filter out the siRNAs that are difficult to take effect or synthesize as a part of the SMRI method, which is more robust and efficient than the traditional statistical indicators under the same circumstances. Besides, to silence the spike protein of SARS-CoV-2 to invade cells, this study further puts forward the SMRI method to search candidate high-efficiency siRNAs on SARS-CoV-2's S gene. This study is one of the early studies applying RNAi therapy to the COVID-19 treatment. According to the analysis, the average value of predicted interference efficiency of the candidate siRNAs designed by the SMRI method is comparable to that of the mainstream siRNA design algorithms. Moreover, the SMRI method ensures that the designed siRNAs have more than three base mismatches with human genes, thus avoiding silencing normal human genes. This is not considered by other mainstream methods, thereby the five candidate high-efficiency siRNAs which are easy to take effect or synthesize and much safer for human body are obtained by our SMRI method, which provide a new safer, small dosage and long efficacy solution for the treatment of COVID-19.

关键词： COVID-19 SARS-CoV-2 RibonucleicAcid interference

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