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学者姓名：刘博
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Abstract ：
针对服务计算、物联网、云计算、服务互联网、工业互联网、数字智慧服务等新兴产业对具有原始创新能力的软件设计人才需求，探讨如何围绕软件设计核心价值体系进行本科软件设计与体系结构课程内容建设及实践环节创新，提出以“知识型工程创新设计(KEID)”为核心价值的课程知识体系结构并介绍以开放式领域建模为基础的创新性实践环节设计。
Keyword ：
软件体系结构 软件体系结构 KIIC实践环节设计 KIIC实践环节设计 知识型工程创新设计(KEID) 知识型工程创新设计(KEID) 开放式领域建模 开放式领域建模
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| GB/T 7714 | 张建 , 刘博 , 朱青 et al. 软件设计与体系结构课程内容建设及创新探索 [J]. | 计算机教育 , 2022 , PageCount-页数: 5 (07) : 62-66 . |
| MLA | 张建 et al. "软件设计与体系结构课程内容建设及创新探索" . | 计算机教育 PageCount-页数: 5 . 07 (2022) : 62-66 . |
| APA | 张建 , 刘博 , 朱青 , 张丽 . 软件设计与体系结构课程内容建设及创新探索 . | 计算机教育 , 2022 , PageCount-页数: 5 (07) , 62-66 . |
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| GB/T 7714 | Liu, Bo , Ji, Xinchan , Li, Jinmeng et al. Integrative analysis identifies three molecular subsets in ovarian cancer [J]. | CLINICAL AND TRANSLATIONAL MEDICINE , 2022 , 12 (9) . |
| MLA | Liu, Bo et al. "Integrative analysis identifies three molecular subsets in ovarian cancer" . | CLINICAL AND TRANSLATIONAL MEDICINE 12 . 9 (2022) . |
| APA | Liu, Bo , Ji, Xinchan , Li, Jinmeng , Zhu, Nian , Long, Junqi , Zhuang, Xujie et al. Integrative analysis identifies three molecular subsets in ovarian cancer . | CLINICAL AND TRANSLATIONAL MEDICINE , 2022 , 12 (9) . |
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Abstract ：
Upper limb kinematic analysis that has been employed in the clinical assessment of motion functions or rehabilitation training is traditionally tested manually with a goniometer. Nowadays, it is a trend to deploy different technology and devices including low-cost but accurate RGB cameras in order to save manual efforts. Among these, a new method using deep learning-based cameras has been investigated to provide the same ease and accessibility as a manual handheld goniometer. The key to measuring upper limb Range of Motion (ROM) using a camera is to estimate upper limb joints accurately. Many existing joint estimation algorithms focus on improving the accuracy performance but put the efficiency concerns aside. It is still challenging to apply those algorithms to low-capacity and budget-friendly devices, which is highly demanding in clinical scenarios. We propose a lightweight and fast deep learning model to estimate human pose and then use predicted joints to measure the range of motion for upper limb joints. Unlike other human pose estimation methods that learn and predict all major joints of the human body, the proposed model only focuses on the upper limb, which improves the accuracy and reduces the overhead of prediction. To further reduce model size and latency, our model is based on a compact neural network architecture, and parameters in the network are quantized to 8-bit precision. As a result, our model runs 4.1 times faster and is 15.5 times smaller compared with a full sized state of the art human pose estimation model. The proposed method is further evaluated on different upper limb functional tasks. Results show that our new method achieves a satisfying accuracy in ROM measurement and a high degree of agreement with a goniometer. Compared with the goniometer to measure ROM, our presented method is easier to operate and can be performed remotely, while still retaining good accuracy.
Keyword ：
2D body estimate 2D body estimate low-capacity device low-capacity device range of motion range of motion quantized convolutional neural network quantized convolutional neural network deep learning deep learning
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| GB/T 7714 | Yan, Xuke , Zhang, Linxi , Liu, Bo et al. A Lightweight and Fast Approach for Upper Limb Range of Motion Assessment [J]. | 2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA , 2022 : 53-60 . |
| MLA | Yan, Xuke et al. "A Lightweight and Fast Approach for Upper Limb Range of Motion Assessment" . | 2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA (2022) : 53-60 . |
| APA | Yan, Xuke , Zhang, Linxi , Liu, Bo , Qu, Guangzhi . A Lightweight and Fast Approach for Upper Limb Range of Motion Assessment . | 2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA , 2022 , 53-60 . |
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Abstract ：
本发明公开了基于节点级嵌入特征三维关系重建的图数据相似度方法，属于深度学习领域，首先通过孪生图卷积层和相似节点交互模块生成节点级嵌入特征三维关系，然后将节点级嵌入特征三维关系经过三维卷积提取特征，将三维特征经过Flatten层展开为一维，获得最终节点级关系向量。这一关系向量输入到由全连接层构成的结果输出模块得到预测输出。这一预测输出与实际的标签值进行比较，通过损失函数和反向传播算法对整体模型参数进行更新以达到学习的目的。完成训练的DeepSIM‑3D模型能高效可靠地计算输入的两个图结构数据的相似度。
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| GB/T 7714 | 刘博 , 武嘉慧 , 王志晗 et al. 基于节点级嵌入特征三维关系重建的图数据相似度方法 : CN202210059012.6[P]. | 2022-01-18 . |
| MLA | 刘博 et al. "基于节点级嵌入特征三维关系重建的图数据相似度方法" : CN202210059012.6. | 2022-01-18 . |
| APA | 刘博 , 武嘉慧 , 王志晗 , 张冀东 . 基于节点级嵌入特征三维关系重建的图数据相似度方法 : CN202210059012.6. | 2022-01-18 . |
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Abstract ：
Background. Currently, predictive models were not developed based on the signaling pathway signatures of immune-related lncRNAs in breast cancer (BRCA) patients. Methods. We selected unsupervised hierarchical clustering algorithm to classify patients with BRCA based on the significant immune-derived lncRNAs from the TCGA dataset. And different methods including ESTIMATE, ImmuneCellAI, and CIBERSORT were performed to evaluate the immune infiltration of tumor microenvironment. Using Lasso regression algorithm, we filtered the significant signaling pathways enriched by GSEA, GSVA, or PPI analysis to develop a prognostic model. And a nomogram integrated with clinical factors and significant pathways was constructed to predict the precise probability of overall survival (OS) of BRCA patients in the TCGA dataset (n =1,098) and another two testing sets (n = 415). Results. BRCA patients were stratified into the PC (n = 571) and GC (n = 527) subgroup with significantly different prognosis with 550 immune-related lncRNAs in the TCGA dataset. Integrated analysis revealed different immune response, oncogenic signaling, and metabolic reprograming pathways between these two subgroups. And a 5-pathway signature could predict the prognosis of BRCA patients between these two subgroups independently in the TCGA dataset, which was confirmed in another two cohorts from the GEO dataset. In the TCGA dataset, 5-year OS rate was 78% (95% CI: 73-84) vs. 82% (95% CI: 77-87) for the PC and GC group (HR = 1.63 (95% CI: 1.17-2.28), p 0.004). The predictive power was similar in another two testing sets (HR > 1.20, p < 0.01). Finally, a nomogram is developed for clinical application, which integrated this signature and age to accurately predict the survival probability in BRCA patients. Conclusion. This 5-pathway signature correlated with immune derived lncRNAs was able to precisely predict the prognosis for patients with BRCA and provided a rich source characterizing immune-related lncRNAs and further informed strategies to target BRCA vulnerabilities.
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| GB/T 7714 | Liu, Bo , Zhu, Nian , Huo, Huixia et al. A 5-Pathway Signature Predicts Prognosis Based on Immune-Derived lncRNAs in Patients with Breast Cancer [J]. | JOURNAL OF ONCOLOGY , 2022 , 2022 . |
| MLA | Liu, Bo et al. "A 5-Pathway Signature Predicts Prognosis Based on Immune-Derived lncRNAs in Patients with Breast Cancer" . | JOURNAL OF ONCOLOGY 2022 (2022) . |
| APA | Liu, Bo , Zhu, Nian , Huo, Huixia , Long, Junqi , Ji, Xinchan , Li, Jinmeng et al. A 5-Pathway Signature Predicts Prognosis Based on Immune-Derived lncRNAs in Patients with Breast Cancer . | JOURNAL OF ONCOLOGY , 2022 , 2022 . |
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Abstract ：
With the continuous development of bioinformatics, traditionally biological sequence analysis methods are insufficient to deal with the increasingly complex and huge biological data. In the face of this situation, deep learning has been gradually applied in biological analysis and made a series of progresses, which has become a hot research topic in biological data analysis with its advantages in processing high-dimensional data. The current research status was reviewed to better understand the new development of deep learning in the field of bioinformatics data analysis. First, the importance of applying deep learning were introduced. Second, representative deep learning models in the current application fields was described. Then, the application research status of deep learning in this field was analyzed. Finally, current limitations of deep learning in the bioinformatics field and the factors that should be considered in future development were illustrated in this paper. © 2022, Editorial Department of Journal of Beijing University of Technology. All right reserved.
Keyword ：
Bioinformatics; Biological sequences analysis; Deep learning; Gene; Nucleic acid; Protein Bioinformatics; Biological sequences analysis; Deep learning; Gene; Nucleic acid; Protein
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| GB/T 7714 | Zhang, J. , Wang, Z. , Liu, B. . Progress in the Applications of Deep Learning in Biological Sequences Analysis [深度学习在生物序列分析领域的应用进展] [J]. | Journal of Beijing University of Technology , 2022 , 48 (8) : 878-887 . |
| MLA | Zhang, J. et al. "Progress in the Applications of Deep Learning in Biological Sequences Analysis [深度学习在生物序列分析领域的应用进展]" . | Journal of Beijing University of Technology 48 . 8 (2022) : 878-887 . |
| APA | Zhang, J. , Wang, Z. , Liu, B. . Progress in the Applications of Deep Learning in Biological Sequences Analysis [深度学习在生物序列分析领域的应用进展] . | Journal of Beijing University of Technology , 2022 , 48 (8) , 878-887 . |
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Abstract ：
The implementation of two-dimensional materials into memristor architectures has recently been a new research focus by taking advantage of their atomic thickness, unique lattice, and physical and electronic properties. Among the van der Waals family, Bi2O2Se is an emerging ternary two-dimensional layered material with ambient stability, suitable band structure, and high conductivity that exhibits high potential for use in electronic applications. In this work, we propose and experimentally demonstrate a Bi2O2Se-based memristor-aided logic. By carefully tuning the electric field polarity of Bi2O2Se through a Pd contact, a reconfigurable NAND gate with zero static power consumption is realized. To provide more knowledge on NAND operation, a kinetic Monte Carlo simulation is carried out. Because the NAND gate is a universal logic gate, cascading additional NAND gates can exhibit versatile logic functions. Therefore, the proposed Bi2O2Se-based MAGIC can be a promising building block for developing next-generation in-memory logic computers with multiple functions.
Keyword ：
RRAM RRAM CAFM CAFM MAGIC MAGIC Bi2O2Se Bi2O2Se kinetic Monte Carlo kinetic Monte Carlo
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| GB/T 7714 | Liu Bo , Zhao Yudi , Verma Dharmendra et al. Bi2O2Se-Based Memristor-Aided Logic. [J]. | ACS applied materials & interfaces , 2021 , 13 (13) : 15391-15398 . |
| MLA | Liu Bo et al. "Bi2O2Se-Based Memristor-Aided Logic." . | ACS applied materials & interfaces 13 . 13 (2021) : 15391-15398 . |
| APA | Liu Bo , Zhao Yudi , Verma Dharmendra , Wang Le An , Liang Hanyuan , Zhu Hui et al. Bi2O2Se-Based Memristor-Aided Logic. . | ACS applied materials & interfaces , 2021 , 13 (13) , 15391-15398 . |
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Abstract ：
In this paper, we studied infrared (IR) maritime salient object detection based on convolutional neural networks (CNNs). There are mainly two contributions. Firstly, we constructed a large extended IR ship image dataset (ExtIRShip) for salient maritime target detection, including 9,123 labelled IR images. Secondly, we proposed a global guided lightweight non-local depth feature (DG-Light-NLDF) model. We introduced Dilated Linear Bottleneck (DLB) to replace the standard convolution and adding a simplified global module to provide the location information of the potential salient object, the proposed method can significantly improve the efficiency of Light-NLDF. Experimental results demonstrate that the proposed DG-Light-NLDF model could detect IR maritime salient objects more accurately with less parameters. In addition, comparison experiments between two datasets validated that the larger dataset is also much more beneficial in improving saliency detection performance. © 2021 Elsevier B.V.
Keyword ：
Large dataset Large dataset Object recognition Object recognition Ships Ships Convolution Convolution Neural networks Neural networks Object detection Object detection Infrared imaging Infrared imaging Feature extraction Feature extraction
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| GB/T 7714 | Liu, Zhaoying , Zhang, Xuesi , Jiang, Tianpeng et al. Infrared salient object detection based on global guided lightweight non-local deep features [J]. | Infrared Physics and Technology , 2021 , 115 . |
| MLA | Liu, Zhaoying et al. "Infrared salient object detection based on global guided lightweight non-local deep features" . | Infrared Physics and Technology 115 (2021) . |
| APA | Liu, Zhaoying , Zhang, Xuesi , Jiang, Tianpeng , Zhang, Ting , Liu, Bo , Waqas, Muhammad et al. Infrared salient object detection based on global guided lightweight non-local deep features . | Infrared Physics and Technology , 2021 , 115 . |
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Abstract ：
The realization of stable partial nitrification and advanced nitrogen removal are not acquired effectively in conventional pre-denitrification biological nitrogen removal processes treating domestic sewage. Herein, a novel anaerobic/aerobic/anoxic/aerobic (AOAO) continuous plug-flow reactor, characterized with double sludge reflux and a bypass of anaerobic mixed liquor conveyed to anoxic zone, was first constructed to realize stable partial nitrification in treating domestic sewage. The alternating anoxic/aerobic conditions and longer anoxic sludge retention time might be responsible for the partial nitrification. Nitrite accumulation ratio reached 89.3 +/- 3.3% with the maximum activity ratio of AOB to NOB increasing from 0.72 to 8.17. A content total inorganic nitrogen (TIN) removal efficiency (93.7 +/- 2.2%) and effluent TIN concentration (2.9 +/- 0.9 mg N/L) were obtained after 238 days' operation. Specifically, nitrogen balance of the typical cycle showed that about 30.1% of TIN was removed through simultaneous partial nitrification and denitrification (SND) in aerobic zone and 48.2% by endogenous denitrification in anoxic zone. The AOAO process is an economic treatment for domestic sewage with aerobic hydraulic retention time (HRT) of 4 h. (C) 2021 Elsevier B.V. All rights reserved.
Keyword ：
Advanced nitrogen removal Advanced nitrogen removal Low COD/TIN sewage Low COD/TIN sewage Endogenous denitrification Endogenous denitrification Partial nitrification Partial nitrification
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| GB/T 7714 | Feng, Yan , Peng, Yongzhen , Wang, Bo et al. A continuous plug-flow anaerobic/aerobic/anoxic/aerobic (AOAO) process treating low COD/TIN domestic sewage: Realization of partial nitrification and extremely advanced nitrogen removal [J]. | SCIENCE OF THE TOTAL ENVIRONMENT , 2021 , 771 . |
| MLA | Feng, Yan et al. "A continuous plug-flow anaerobic/aerobic/anoxic/aerobic (AOAO) process treating low COD/TIN domestic sewage: Realization of partial nitrification and extremely advanced nitrogen removal" . | SCIENCE OF THE TOTAL ENVIRONMENT 771 (2021) . |
| APA | Feng, Yan , Peng, Yongzhen , Wang, Bo , Liu, Bo , Li, Xiyao . A continuous plug-flow anaerobic/aerobic/anoxic/aerobic (AOAO) process treating low COD/TIN domestic sewage: Realization of partial nitrification and extremely advanced nitrogen removal . | SCIENCE OF THE TOTAL ENVIRONMENT , 2021 , 771 . |
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Abstract ：
In this paper, it is proved that for one-hidden-layer ReLU networks all differentiable local minima are global inside each differentiable region. Necessary and sufficient conditions for the existences of differentiable local minima, saddle points and non-differentiable local minima are given, as well as their locations if they do exist. Building upon the theory, a linear programming based algorithm is designed to judge the existence of differentiable local minima, and is used to predict whether spurious local minima exist for the MNIST and CIFAR-10 datasets. Experimental results show that there are no spurious local minima for most typical weight vectors. These theoretical predictions are verified by demonstrating the consistency between them and the results of gradient descent search. ? 2021 Elsevier B.V. All rights reserved. Superscript/Subscript Available</comment
Keyword ：
ReLU networks ReLU networks Deep learning theory Deep learning theory Saddle points Saddle points Local minima Local minima Loss landscape Loss landscape
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| GB/T 7714 | Liu, Bo . Understanding the loss landscape of one-hidden-layer ReLU networks [J]. | KNOWLEDGE-BASED SYSTEMS , 2021 , 220 . |
| MLA | Liu, Bo . "Understanding the loss landscape of one-hidden-layer ReLU networks" . | KNOWLEDGE-BASED SYSTEMS 220 (2021) . |
| APA | Liu, Bo . Understanding the loss landscape of one-hidden-layer ReLU networks . | KNOWLEDGE-BASED SYSTEMS , 2021 , 220 . |
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