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Optimal CNN-based semantic segmentation model of cutting slope images

Mansheng LIN; Shuai TENG; Gongfa CHEN; Jianbing LV; Zhongyu HAO

《结构与土木工程前沿（英文）》 2022年 第16卷 第4期   页码 414-433 doi: 10.1007/s11709-021-0797-6

摘要： This paper utilizes three popular semantic segmentation networks, specifically DeepLab v3+, fully convolutional network (FCN), and U-Net to qualitively analyze and identify the key components of cutting slope images in complex scenes and achieve rapid image-based slope detection. The elements of cutting slope images are divided into 7 categories. In order to determine the best algorithm for pixel level classification of cutting slope images, the networks are compared from three aspects: a) different neural networks, b) different feature extractors, and c) 2 different optimization algorithms. It is found that DeepLab v3+ with Resnet18 and Sgdm performs best, FCN 32s with Sgdm takes the second, and U-Net with Adam ranks third. This paper also analyzes the segmentation strategies of the three networks in terms of feature map visualization. Results show that the contour generated by DeepLab v3+ (combined with Resnet18 and Sgdm) is closest to the ground truth, while the resulting contour of U-Net (combined with Adam) is closest to the input images.

关键词： slope damage     image recognition     semantic segmentation     feature map     visualizations    

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A hybrid Wavelet-CNN-LSTM deep learning model for short-term urban water demand forecasting

《环境科学与工程前沿（英文）》 2023年 第17卷 第2期 doi: 10.1007/s11783-023-1622-3

摘要：

● A novel deep learning framework for short-term water demand forecasting.

关键词： Short-term water demand forecasting     Long-short term memory neural network     Convolutional Neural Network     Wavelet multi-resolution analysis     Data-driven models    

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Additive manufacturing: technology, applications and research needs

Nannan GUO, Ming C. LEU

《机械工程前沿（英文）》 2013年 第8卷 第3期   页码 215-243 doi: 10.1007/s11465-013-0248-8

摘要：

Additive manufacturing (AM) technology has been researched and developed for more than 20 years. Rather than removing materials, AM processes make three-dimensional parts directly from CAD models by adding materials layer by layer, offering the beneficial ability to build parts with geometric and material complexities that could not be produced by subtractive manufacturing processes. Through intensive research over the past two decades, significant progress has been made in the development and commercialization of new and innovative AM processes, as well as numerous practical applications in aerospace, automotive, biomedical, energy and other fields. This paper reviews the main processes, materials and applications of the current AM technology and presents future research needs for this technology.

关键词： additive manufacturing (AM)     AM processes     AM materials     AM applications    

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一种基于高斯过程与粒子群算法的CNN超参数自动搜索混合模型优化算法 Research Article

闫涵,仲崇权,吴玉虎,张立勇,卢伟

《信息与电子工程前沿（英文）》 2023年 第24卷 第11期   页码 1557-1573 doi: 10.1631/FITEE.2200515

摘要： 卷积神经网络（CNN）在许多实际应用领域中有着快速发展。然而，CNN性能很大程度上取决于其超参数，而为CNN配置合适的超参数通常面临着以下3个挑战：（1）不同类型CNN超参数的混合变量编码问题；（2）评估候选模型的昂贵计算成本问题；（3）确保搜索过程中收敛速率和模型性能问题针对上述问题，提出一种基于高斯过程（GP）和粒子群优化算法（PSO）的混合模型优化算法（GPPSO），用于自动搜索最优的CNN超参数配置。首先，设计一种新的编码方法高效编码CNN中不同类型的超参数。

关键词： 卷积神经网络；高斯过程；混合模型；超参数优化；混合变量；粒子群优化    

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基于图像的深度学习降雨强度估计方法 Article

尹航, 郑飞飞, 段焕丰, Dragan Savic, Zoran Kapelan

《工程（英文）》 2023年 第21卷 第2期   页码 162-174 doi: 10.1016/j.eng.2021.11.021

摘要：

城市洪水是世界性的重大问题，造成巨大的经济损失，严重威胁公共安全。减轻其影响的一种有希望的方法是开发实时洪水风险管理系统；然而，由于缺乏高时空降雨数据，构建这样一个系统通常具有挑战性。虽然一些方法（即地面降雨站或雷达和卫星技术）可用于测量和（或）预测降雨强度，但使用这些方法很难获得具有理想时空分辨率的准确降雨数据。本文提出了一种基于图像的深度学习模型来估计具有高时空分辨率的城市降雨强度。进一步来说，一种称为基于图像的降雨卷积神经网络（image-based rainfall convolutional neural network, irCNN）模型是使用从现有密集传感器（即智能手机或交通摄像头）收集的降雨图像及其相应的测量降雨强度值开发的。随后使用经过训练的irCNN 模型根据传感器的降雨图像有效地估计降雨强度。分别利用合成降雨数据和真实降雨图像来探索irCNN 在理论和实际模拟降雨强度方面的准确性。结果表明，irCNN 模型提供的降雨量估计值的平均绝对百分比误差在13.5%~21.9%之间，超过了文献中其他最先进的建模技术的性能。更重要的是，所提出的irCNN 的主要特点是它在有效获取高时空城市降雨数据方面成本较低。irCNN 模型为估算城市降雨强度提供了一种有前景的替代方案，可以极大地促进城市实时洪水风险管理的发展。

关键词： 城市洪水     降雨图像     深度学习模型     卷积神经网络（CNN）     降雨强度    

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typical dissolved black carbons and their influence on the formation of disinfection by-products in chlor(am

《环境科学与工程前沿（英文）》 2022年 第16卷 第12期 doi: 10.1007/s11783-022-1585-9

摘要：

● The physicochemical and structural properties of DBC were characterized.

关键词： Dissolved black carbon (DBC)     Chlorine     Chloramine     Disinfection by-products (DBPs)     Disinfection by-products formation potential (DBPFP)    

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Solution properties and self-association of multi-blocks like copolymer P(AM/AA) prepared by template

ZHANG Yuxi, WU Feipeng, LI Miaozhen, WANG Erjian

《化学科学与工程前沿（英文）》 2007年 第1卷 第1期   页码 68-71 doi: 10.1007/s11705-007-0014-8

摘要： The association and properties of multi-block like copolymers (TP) of acrylamide (AM) and acrylic acid (AA) prepared by template copolymerization in aqueous solution were studied. The results showed that the copolymers of this type exhibited a significant structure effect compared with that of similar random copolymers (CP) obtained by copolymerization in the absence of template. Decreasing the value of pH or adding Ca ion to the copolymer solution will make phase separation occur. The TEM images demonstrated that the phase separation caused by Ca ion was due to the formation of extensively intermolecular cross-linking. With the increase of the pH value of copolymer solution, the changes of the solution viscosity was similar with that of homopolyacrylic acid, which originally increased and then decreased. But the increase range of template copolymer was higher than that of homopolyacrylic acid. TEM images indicated that at the maximal viscosity the copolymer obtained in the presence of template formed coiled aggregates.

关键词： aqueous solution     homopolyacrylic     copolymer solution     significant structure     presence    

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基于海面更快区域卷积神经网络的导航雷达平面位置指示器图像海面目标检测方法 Research Article

陈小龙,牟效乾,关键,刘宁波,周伟

《信息与电子工程前沿（英文）》 2022年 第23卷 第4期   页码 630-643 doi: 10.1631/FITEE.2000611

摘要： 更快的区域卷积神经网络（Faster R-CNN）作为一种经典深度学习目标检测算法，已广泛应用于高分辨率合成孔径雷达和逆合成孔径雷达的图像检测。本文以导航雷达PPI图像为例，针对复杂背景（如海杂波）和目标特性情况，提出一种基于海面的更快的区域卷积神经网络（Marine-Faster R-CNN）算法的海面目标检测方法。该方法利用卷积神经网络（CNN）对雷达回波生成的PPI图像进行特征提取和目标识别。，并基于此建立Marine-Faster R-CNN海面目标检测模型。最后，与经典Faster R-CNN方法和恒虚警率算法对比，证明所提方法准确率更高，稳健性更佳，泛化能力更强，可应用于导航雷达海面目标检测。

关键词： 海面目标检测；导航雷达；平面位置指示器（PPI）图像；卷积神经网络；更快的区域卷积神经网络    

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什么才是做出最佳基础设施投资的依据？经济因素？恢复力？或二者皆是？

David Singleton AM

《工程（英文）》 2018年 第4卷 第2期   页码 180-181 doi: 10.1016/j.eng.2018.04.001

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Arbuscular mycorrhizal associations and the major regulators

Li XUE, Ertao WANG

《农业科学与工程前沿（英文）》 2020年 第7卷 第3期   页码 296-306 doi: 10.15302/J-FASE-2020347

摘要：

Plants growing in natural soils encounter diverse biotic and abiotic stresses and have adapted with sophisticated strategies to deal with complex environments such as changing root system structure, evoking biochemical responses and recruiting microbial partners. Under selection pressure, plants and their associated microorganisms assemble into a functional entity known as a holobiont. The commonest cooperative interaction is between plant roots and arbuscular mycorrhizal (AM) fungi. About 80% of terrestrial plants can form AM symbiosis with the ancient phylum Glomeromycota. A very large network of extraradical and intraradical mycelium of AM fungi connects the underground biota and the nearby carbon and nutrient fluxes. Here, we discuss recent progress on the regulators of AM associations with plants, AM fungi and their surrounding environments, and explore further mechanistic insights.

关键词： AM symbiosis     signal     regulators     nutrients     phosphate     microbiota    

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一种基于特征模板和CNN-BiLSTM-CRF的网络安全实体识别方法 Research Papers

Ya QIN, Guo-wei SHEN, Wen-bo ZHAO, Yan-ping CHEN, Miao YU, Xin JIN

《信息与电子工程前沿（英文）》 2019年 第20卷 第6期   页码 872-884 doi: 10.1631/FITEE.1800520

摘要： 本文在神经网络模型基础上，提出基于特征模板的CNN-BiLSTM-CRF网络安全实体识别算法。首先构建人工特征模板，提取局部上下文特征。再利用CNN提取字符特征，与局部上下文特征结合，传入BiLSTM模型提取语义特征。最后利用CRF对安全实体进行标注。结果表明，在大规模网络安全数据集上，该方法优于其它算法，F值达到86%。

关键词： 网络安全知识图谱；网络安全实体；特征模板；实体识别；神经网络    

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Surface accuracy optimization of mechanical parts with multiple circular holes for additive manufacturing based on triangular fuzzy number

Jinghua XU, Hongsheng SHENG, Shuyou ZHANG, Jianrong TAN, Jinlian DENG

《机械工程前沿（英文）》 2021年 第16卷 第1期   页码 133-150 doi: 10.1007/s11465-020-0610-6

摘要： Surface accuracy directly affects the surface quality and performance of mechanical parts. Circular hole, especially spatial non-planar hole set is the typical feature and working surface of mechanical parts. Compared with traditional machining methods, additive manufacturing (AM) technology can decrease the surface accuracy errors of circular holes during fabrication. However, an accuracy error may still exist on the surface of circular holes fabricated by AM due to the influence of staircase effect. This study proposes a surface accuracy optimization approach for mechanical parts with multiple circular holes for AM based on triangular fuzzy number (TFN). First, the feature lines on the manifold mesh are extracted using the dihedral angle method and normal tensor voting to detect the circular holes. Second, the optimal AM part build orientation is determined using the genetic algorithm to optimize the surface accuracy of the circular holes by minimizing the weighted volumetric error of the part. Third, the corresponding weights of the circular holes are calculated with the TFN analytic hierarchy process in accordance with the surface accuracy requirements. Lastly, an improved adaptive slicing algorithm is utilized to reduce the entire build time while maintaining the forming surface accuracy of the circular holes using digital twins via virtual printing. The effectiveness of the proposed approach is experimentally validated using two mechanical models.

关键词： surface accuracy optimization     multiple circular holes     additive manufacturing (AM)     part build orientation     triangular fuzzy number (TFN)     digital twins    

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Degradation of polyacrylamide (PAM) and methane production by mesophilic and thermophilic anaerobic digestion: Effect of temperature and concentration

Mona Akbar, Muhammad Farooq Saleem Khan, Ling Qian, Hui Wang

《环境科学与工程前沿（英文）》 2020年 第14卷 第6期 doi: 10.1007/s11783-020-1277-2

摘要： Abstract • PAM degradation in thermophilic AD in comparison with mesophilic AD. • PAM degradation and its impact on thermophilic and mesophilic AD. • Enhanced methane yield in presence of PAM during thermophilic and mesophilic AD. • PAM degradation and microbial community analysis in thermophilic and mesophilic AD. Polyacrylamide (PAM) is generally employed in wastewater treatment processes such as sludge dewatering and therefore exists in the sludge. Furthermore, it degrades slowly and can deteriorate methane yield during anaerobic digestion (AD). The impact or fate of PAM in AD under thermophilic conditions is still unclear. This study mainly focuses on PAM degradation and enhanced methane production from PAM-added sludge during 15 days of thermophilic (55°C) AD compared to mesophilic (35°C) AD. Sludge and PAM dose from 10 to 50 g/kg TSS were used. The results showed that PAM degraded by 76% to 78% with acrylamide (AM) content of 0.2 to 3.3 mg/L in thermophilic AD. However, it degraded only 27% to 30% with AM content of 0.5 to 7.2 mg/L in mesophilic AD. The methane yield was almost 230 to 238.4 mL/g VSS on the 8th day in thermophilic AD but was 115.2 to 128.6 mL/g VSS in mesophilic AD. Mechanism investigation revealed that thermophilic AD with continuous stirring not only enhanced PAM degradation but also boosted the organics release from the sludge with added PAM and gave higher methane yield than mesophilic AD.

关键词： Polyacrylamide (PAM) degradation     Acrylamide (AM)     Mesophilic anaerobic digestion     Thermophilic anaerobic digestion     Methane production    

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Standard model of knowledge representation

Wensheng YIN

《机械工程前沿（英文）》 2016年 第11卷 第3期   页码 275-288 doi: 10.1007/s11465-016-0372-3

摘要：

Knowledge representation is the core of artificial intelligence research. Knowledge representation methods include predicate logic, semantic network, computer programming language, database, mathematical model, graphics language, natural language, etc. To establish the intrinsic link between various knowledge representation methods, a unified knowledge representation model is necessary. According to ontology, system theory, and control theory, a standard model of knowledge representation that reflects the change of the objective world is proposed. The model is composed of input, processing, and output. This knowledge representation method is not a contradiction to the traditional knowledge representation method. It can express knowledge in terms of multivariate and multidimensional. It can also express process knowledge, and at the same time, it has a strong ability to solve problems. In addition, the standard model of knowledge representation provides a way to solve problems of non-precision and inconsistent knowledge.

关键词： knowledge representation     standard model     ontology     system theory     control theory     multidimensional representation    

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受限空间火灾模型研究进展

郑昕,袁宏永

《中国工程科学》 2004年 第6卷 第3期   页码 68-74

摘要：

火灾模型是从工程科学的角度出发，分析研究火灾的发生、发展，烟气蔓延以及火灾对周围环境诸如建筑设备、森林植被及大气环境等影响的数学模型。介绍了广泛应用于建筑物内部受限空间的场、区域、网模型以及经验模型的理论思想与数学方程，分析了4种模型在相应环境下应用的合理性，并对火灾模型的发展做出了展望。

关键词： 受限空间     场模型     区域模型     网模型     场区网模型     经验模型    

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标题 作者 时间 类型 操作

Optimal CNN-based semantic segmentation model of cutting slope images

Mansheng LIN; Shuai TENG; Gongfa CHEN; Jianbing LV; Zhongyu HAO

期刊论文

A hybrid Wavelet-CNN-LSTM deep learning model for short-term urban water demand forecasting

期刊论文

Additive manufacturing: technology, applications and research needs

Nannan GUO, Ming C. LEU

期刊论文

一种基于高斯过程与粒子群算法的CNN超参数自动搜索混合模型优化算法

闫涵,仲崇权,吴玉虎,张立勇,卢伟

期刊论文

基于图像的深度学习降雨强度估计方法

尹航, 郑飞飞, 段焕丰, Dragan Savic, Zoran Kapelan

期刊论文

typical dissolved black carbons and their influence on the formation of disinfection by-products in chlor(am

期刊论文

Solution properties and self-association of multi-blocks like copolymer P(AM/AA) prepared by template

ZHANG Yuxi, WU Feipeng, LI Miaozhen, WANG Erjian

期刊论文

基于海面更快区域卷积神经网络的导航雷达平面位置指示器图像海面目标检测方法

陈小龙,牟效乾,关键,刘宁波,周伟

期刊论文

什么才是做出最佳基础设施投资的依据？经济因素？恢复力？或二者皆是？

David Singleton AM

期刊论文

Arbuscular mycorrhizal associations and the major regulators

Li XUE, Ertao WANG

期刊论文

一种基于特征模板和CNN-BiLSTM-CRF的网络安全实体识别方法

Ya QIN, Guo-wei SHEN, Wen-bo ZHAO, Yan-ping CHEN, Miao YU, Xin JIN

期刊论文

Surface accuracy optimization of mechanical parts with multiple circular holes for additive manufacturing based on triangular fuzzy number

Jinghua XU, Hongsheng SHENG, Shuyou ZHANG, Jianrong TAN, Jinlian DENG

期刊论文

Degradation of polyacrylamide (PAM) and methane production by mesophilic and thermophilic anaerobic digestion: Effect of temperature and concentration

Mona Akbar, Muhammad Farooq Saleem Khan, Ling Qian, Hui Wang

期刊论文

Standard model of knowledge representation

Wensheng YIN

期刊论文

受限空间火灾模型研究进展

郑昕,袁宏永

期刊论文