bluuebunny/crossref_metadata_2025_split huggingface dataset:
“5G+TSN+DT” Solutions for Digital Factory Key Issues of Networking, Precision, Automation and Digitalization
Authors: Wang Han , Li Shaobin 
Published: February 2022

Abstract
With advanced technologies of the Internet of Things (IoT) and Artificial Intelligence (AI) developing, key issues and challenges of networking, precision, automation and digitalization are arising for digital factory (DF) top designing and establishing. Advanced technologies of 5G, Time Sensitive Network (TSN) and Digital Twin (DT) provide new solutions for DT planning and operating. This study explores “5G+TSN +DT” practical solutions for DF designing and building, especially in the aspects of networking, precision, automation and digitalization, which is of great significance to understand the opportunities and challenges of DF industry development.
Intelligent Software Service Configuration Technology Based on Association Mining
Authors: Wang Fei , Zhao Zhengjian , Wang Zhichao , Ma Minchao , Lu Junjie 
Published: February 2022

Abstract
Association relationship and types between software service configuration parameters determine that the configuration items must meet the corresponding rules and constraints in parameter value and setting order. However, the distribution of software services and the architecture based on the loose coupling of heterogeneous components make the association of configuration parameters more concealed. The correlation and constraints of configuration parameters are crucial to ensure system configuration. When deploying, migrating, and updating systems, violating constraints will lead to configuration errors, resulting in system failures. To minimize the loss caused by configuration errors, association rules between configuration items can be mined to avoid potential incorrect settings. This paper proposes an intelligent software service configuration technology based on association mining by analyzing configuration items. The sample data of the configuration file is extracted from the open source code base, and the configuration file is parsed to obtain the configuration item name and value. Then mine the association rule of each configuration item pair based on the configuration item name, value, and type. According to the mined configuration constraints, configuration item error detection, cascade update and value recommendation are performed. Finally, the proposed method is tested and evaluated on six typical open source software, and the experimental results prove the accuracy and effectiveness of the method in this paper.
Target Detection of Marine Ships Based on a Cascade RCNN
Authors: Wu Lei , Chen Shicai , Liang Chengcheng 
Published: February 2022

Abstract
Faster RCNN is a classic algorithm with high accuracy and a wide range of applications in the field of target detection, and Cascade RCNN is improved based on Faster RCNN. The article applies the Cascade RCNN method to the detection of marine ship targets. It improves the traditional Faster RCNN algorithm and extracts areas that may contain pedestrians through RPN. In this paper, a multi-layer cascade detector is used to distinguish and classify the target area, and an algorithm is designed to detect and verify the data set. In the end, it is concluded that the Cascade RCNN algorithm performs better than the traditional algorithm.
The Optimization of Multi-classifier Ensemble Method Based on Dynamic Weighted Voting
Authors: Yang Ping , Fang Jian , Xu Junting , Jin Guanghao , Song Qingzeng 
Published: February 2022

Abstract
Generally, on the same data set, different deep learning classification models will achieve different performances. The existing weighted voting method can combine the results of models, which can improve the performance of classification. On the other side, its classification accuracy is affected by the accuracy of all models. In this paper, we proposed a dynamic weighted voting method. Our method dynamically selects models on different data sets, and integrates them according to their weights, thereby improving the classification accuracy. We evaluated the methods on three data sets of CIFAR10, CIFAR100 and Existing, which increased the accuracy about 0.65%, 0.91%, and 0.78% respectively compared with the existing weighted voting method.
Development of End Beam Obstacle Avoidance Program based on ABB Automatic Painting Programming
Authors: Li Jingyu , Shao Wangsheng , Li Xiaochuang , Sun Yuhang 
Published: February 2022

Abstract
In order to improve the company’s production efficiency, in response to the call of the country to accelerate the industrial automation, the company’s developers have independently developed a painting line parametric automatic programming system based on ABB robot using C++ language, the automatic spraying of the main beams of the crane is realized. The automatic programming system can only spray the main beam of the end beam without end. The end beams obstacle avoidance program is optimized based on the automatic programming system, which aims to control the robot to avoid the end beam of the main beam, so that the system can spray the main beam of the crane with the end beam normally.
The Risk Analysis Model Design of the Emergency-Food Supply under Blizzard Conditions
Authors: Liu Yan , Dong Xinpeng 
Published: February 2022

Abstract
This work aims to improve the risk analysis system of the preparation and the transportation of emergency food and to improve the safety, efficiency, and speed of the emergency-food supply in China. We combined the fuzzy analysis and the convolutional neural network to identify the main risk factors of the emergency-food supply. The identification of the risk factors by the fuzzy analysis improved the food-safety risk analysis system. On the other hand, the use of the convolutional neural network to determine the early-warning threshold and to optimize the transportation plan of emergency food effectively improved the safety, efficiency, and speed of the emergency-food supply.
Convolution Neural Network for Renal Function Assessment Based on Glomerular Filtration Rate
Authors: Wu Congzhong , Wang Lulu , Yang Zhen , Wang Jing , Han Li , Li Fei 
Published: February 2022

Absract
✓Objective: To develop a Convolution Neural Network (CNN) and discuss its performance in the estimation of Glomerular Fifiltration Rate (GFR) for patients with chronic kidney disease (CKD). Methods: A total of 112 patients with chronic kidney disease were enrolled in this study. The GFR is measured by 99mTc-DTPA renal dynamic and used as standard GFR after normalization by body surface area imaging. We established a CNN model and verified the performance of the model by comparing the GFR predicted by the model with the standard GFR. It turned out that the CNN could better evaluate the GFR of patients which is superior to the CG formula, MDRD formula, CKD-EPI formula and GRNN model. Conclusions: The CNN significantly evaluated GFR for patients with CKD, and it showed better performance than traditional methods and GRNN model and closer to the results of 99mTc-DTPA. The experimental results demonstrated that CNN could be used to estimate GFR.
Design of Intelligent Drip Infusion Control System Based on Huawei Internet of Things Platform
Authors: Hu Yingkun , Chen Guangfeng , Lan Maokun , Zhou Jingfeng 
Published: February 2022

Abstract
In order to solve the problems of heavy labor burden, cumbersome work, patients can not get comfortable care and low medical efficiency, an intelligent drip infusion control system based on Huawei Internet of things platform is designed. The system first describes the system implementation technical principle, hardware design idea, Huawei cloud platform upper management application solution idea, using NB-IoT to communicate with Huawei cloud platform, Huawei cloud server design, web back-end, web front-end and mobile app design process. The test results show that the system has the functions of web page and mobile app remote centralized monitoring, remote speed regulation and remote run out alarm, which reduces the burden of nurses, reduces the contact time between nurses and patients, and improves the medical efficiency.
Driving Capability, a Unified Driver Model for ADAS
Authors: Sun Bohua , Zhai Yang , Li Yaxin , Deng Weiwen , Zhao Shuai 
Published: February 2022

Abstract
To allocate driving privilege in a reasonable way in shared control for intelligent vehicle, the study on driving capability, the unified driver model for ADAS in the longitudinal and lateral scenarios was proposed, which can improve the safety and comfort for intelligent vehicles as well. Driving capability is defined and analyzed and car-following stimulate in longitudinal scenario and moving double lane change stimulate in lateral scenario were designed. Data collection was conducted in Driver-In-the-Loop Intelligent Simulation Platform (DILISP). Driving capability identification model was established basing on Hammerstein process and Principal Component Analysis (PCA) was used to decouple and reduce the dimension for the key parameters in Hammerstein identification model. The classification is done basing on the particle clustering algorithm and the evaluation equation for driving capability was calculated by Multiple Linear Regression (MLR). Results show that the proposed evaluation method for driving capability in the longitudinal and lateral scenarios can achieve accurate and reliable evaluation results.
Research on Fast Pre-Processing Method of Tunnel Point Cloud Data in Complex Environment
Authors: Zhu Ming , Leng Biao , Xiao Chunhong , Hou Gaopeng , Yao Xiangchen , Li Kai 
Published: February 2022

AbstractIn recent years, the application and research of three-dimensional laser scanning technology in tunnel engineering has continuously emerged, while the shortcomings still exists. This paper conducts research on quick preprocessing method of tunnel point cloud data based on three-dimensional laser scanning. For streamlining the tunnel point cloud model data, comparison analysis discusses are applied to both the downsampling algorithm and the point cloud denoising method respectively. Simulation experiments are introduced to compare the effects of different downsampling algorithms applied to the tunnel point cloud model, analyze the sampling efficiency and performance of each algorithm. Combining with statistical denoising and radius denoising algorithms, a distance denoising based on an iterative filtering model method is proposed. The result shows that this method is suitable for the tunnel point cloud model during the construction period with complex environment, and can effectively eliminate most of the point cloud noise.
Research on Heating and Temperature Control System with Solid Electric Heat Storage Based on Improved Smith Predictive Control
Authors: Liu Chunlei , Wang Yi , Zhang Mengru , Wu Wenjie , Cai Yang , Zhang Zhihong 
Published: February 2022

Abstract
In view of the hysteretic nature of the heating and temperature control system with solid electric heat storage, this paper intends to control the related equipment by improved Smith predictive control method relying on the solid energy storage heating demonstration project of a university. This control method adds an additional regulator to the Smith predictive control method; in this manner, it can appropriately reduce the sensitivity of model accuracy, enhance the adaptability and effectively overcome the influence of delay on system stability, thus creating better robustness. The experimental results indicated that the temperature control accuracy could reach ±1°C.
Study on the Influence of Residual Deformation in Old Subsidence Area on the Safety of New Buildings
Authors: Sun Shiguo , Jia Xinxin , Wei Shuaiying , Xiao Jian 
Published: February 2022

Abstract
The new buildings on the surface of the old subsidence area and the ecological restoration and treatment of the subsidence area are the hot and difficult problems behind the mining of many mining areas. Taking the subsidence area of Laohutai Mine as an engineering example, this paper uses the finite element numerical simulation software to systematically simulate and analyze the stress and deformation of the buildings to be built, raft foundation and foundation soil in different deformation areas. It reveals the deformation and movement law of the building structure at the geometric center area, the maximum negative curvature at the inner edge, the maximum positive curvature at the outer edge and the inflection point of the intersection of positive and negative curvature. The middle zone has the greatest influence on the vertical deformation of the building structure, and the inflection point of the positive and negative curvature has the greatest influence on the inclined deformation of the building structure. The stability of the foundation at four different working conditions is evaluated. Accordingly, it is proposed that reasonable design should be carried out for different regions in architectural design to ensure the safe use of architectural structures.
Study on Temperature Control and Crack Prevention Scheme for Lining Concrete Construction of Spillway Tunnel in Summer
Authors: Ma Shouxun , Hu Shuhong , Wei Baolong , Zhang Lei , Xin Jianda , Sun Changmao , Zheng Lei 
Published: February 2022

Abstract
In view of the characteristics of high strength and thin thickness of spillway tunnel lining concrete, the temperature field and stress field of spillway tunnel lining concrete during summer construction are simulated by using large-scale finite element software SAPTIS, and the risk assessment of lining concrete surface flow maintenance time and internal water passage time on its own cracking during summer construction is analyzed. For a project, the simulation calculation is carried out, and the results show that under the given working conditions, compared with non-flow curing, the surface point stress of surface flow curing for 28 d decreases by 1.34 MPa, and the minimum crack safety factor increases by 0.79 ; the internal middle point stress decreases by 0.75 MPa, and the safety factor increases by 0.31. The cooling time of internal water in lining concrete is longer than the time when the maximum temperature of concrete occurs, which cannot effectively reduce the maximum temperature of internal temperature, but it can reduce the internal tensile stress to a small extent and improve the safety factor. The research results have guiding value for thermal control and crack prevention of lining concrete.
Analysis on Energy Saving Transformation of Central Heating System in Existing Buildings
Authors: Sun Yony , Zhang Hongxi , Xu Huixuan , Liu Yang 
Published: February 2022

Abstract
By comparing the indexes before and after the energy-saving transformation, the heating system in the northern cold region after the transformation of the existing pipe network is studied. Taking a renovation project in severe cold area as an example, the energy-saving renovation of heating system is analyzed. Through data collation and comparison, after the renovation, all energy-saving indexes of heating pipe network meet the requirements of heat users, and good results are achieved. After the renovation, the water consumption and electricity consumption in heating season are saved by 24% and 21%, and the cost of heating system is saved by 335,100 yuan compared with that before the renovation. After the transformation, the user satisfaction is increased by 59%, and the energy-saving effect is remarkable.
Numerical Simulation Study of Anti-Large Deformation Bolt Structure
Authors: Wang Rongrong , Zha WenHua 
Published: February 2022

Abstract
In order to study the mechanics of the anti-deformation hemp anchor rod, and numerical simulation was carried out with ANSYS finitengen software, the mechanics characteristics of a single spiral anchor and a hemp anchor rod under different spiral rings were compared and analyzed. The results show that for a single screw anchor, the number of spiral turns has a greater effect on the stretch elongation rate of the anchor test piece, and the more spiral turns, the greater the elongation when the anchor is destroyed, and the structural deformation of the anchor rod force is greater, which is the main reason for the increase of the elongation with the increase of the number of spiral rings. The hemp anchor is affected by the number and spacing of spiral rings, and does not produce yield stage and destruction stage when stretching, which indicates that the hemp anchor has better ability to resist shearing and deformation. In engineering applications, the ability of hemp anchor rod to resist large deformation of surrounding rock can be effectively improved, the effect of roadway support can be ensured, and the research results provide theoretical basis for the application and parameter design of hemp anchor.
Study on Rock Cutting Mechanism and Efficient Shield Tunneling Control in Mixed-Ground with Different Strengths
Authors: Shi Hongbing , Huang Xing , Liu Bin , Luan Shuai , Li Linfeng , Liu Shaoran , Lu Xingli 
Published: February 2022

Abstract
Mixed ground condition exerts very significant influences on the rock fragmentation mechanism, rock cutting efficiency, and operational parameters selection of the shield boring machine. In order to reveal the rock cutting mechanism when the shield tunnel boring machine advances through the mixed grounds in Line 13 of the Shenzhen Metro Tunnels, according to several linear cutting tests were conducted using a constant cross-section disc-cutter and five rock types with different strengths. The change of disc-cutter cutting force and rock boreability index were analyzed, and some suggestions were proposed to fulfill the safe and efficient tunneling of the shield machine in mixed ground conditions. The results of this study can offer useful suggestions for the operation parameter selection of the shield tunnel boring machine tunneling through the mixed ground in the Shenzhen Metro Line 13 and similar projects.
Vibration Mitigation of Tunnel Structures via a Novel Passive Tuned Mass Damper
Authors: Cheng Z P , Qiao X L , Cheng Z B 
Published: February 2022

AbstractIn this work, a novel passive tuned mass damper is introduced to mitigate the harmful vibrations in tunnel structures under moving trains/vehicles. First, a mechanism with inertial amplification effect is introduced. The transfer function of an SDOF system with the proposed inertial amplification system (SDOF-IAM) is presented. The adjustability of the proposed IAM is discussed. Second, replacing the SDOF by using the SDOF-IAM system, a novel passive tuned mass damper is proposed. Superior to the traditional TMD, the geometrical parameters of the present IAM-TMD can be changed to adjust to the vibration mitigation property of the TMD. A parametric study is also conducted to evaluate the influences of the geometrical parameters on the critical parameters of the TMD (the anti-resonant frequency, the effective mass parameter, and so on). Superior to the TMD, the vibration mitigation effect of the IAM-TMD can be adjusted effectively, which can be used to suppress vibrations of tunnel structures under moving trains.
The Feasibility Study of Quantitative Flaw Detection of Grouted Sleeve Connection by Ultrasonics
Authors: Zhang Lu , Fang Zhenmin , Li Hongyu , Zhao Yunliang , Jiang Zishi 
Published: February 2022

Abstract
Grouted sleeve connection has been widely used to connect rebars in prefabricated concrete (PC) structures. Due to the complexities of materials and internal configurations, the flaws or defects are inevitable, which may cause the negative impact on the mechanical properties of reinforcement sleeve connection, ultimately leading to the hidden risk in the PC structures. It is challenging to explore a reliable and efficient flaw detection method for the grouting sleeve. In this paper, an active grout defects detection approach for grouted sleeve connectors using UT wave measurement is proposed, where piezoelectric-lead-zirconate-titanate (PZT) transducer are mounted on surface of the sleeve as transmitter and receivers; and experimental study is carried out to validate the feasibility of the proposed method. In order to investigate the effect of grout defects on UT wave measurement, five grouted sleeve specimens with different degrees of the artificial grout defects are designed and analysis on the PZT transducer was used for measurement. By comparing the PZT transducers measurement of different specimens with different grout defects under an identical impulse excitation signal, the grout defect is detected. Experimental results indicate grout defect leads to decrease in PZT transducers measurement UT energy, the relationship between the UT energy ratio and the internal grouting flaws is established: the UT energy decreases with the increment of flaw size. Therefore, the UT method provides a feasible option to evaluate the internal flaws of grouted sleeve connection.
Research on Anti-Noise Ability of Offshore Platform Health Monitoring System Based on Strain Mode Structural Damage Identification
Authors: Ye Hailin , Liu Lu , Qi Wenhao 
Published: February 2022

Abstract
Strain modal structural damage identification is widely used in offshore platform health monitoring. However, due to the limitation of structural testing technology, the complex marine environment around the offshore platform structure is superimposed, such as wind, wave, tidal current and other dynamic environments. In the actual test, many factors interfere with modal identification and damage detection, which brings a certain amount of errors to the identification of modal parameters of offshore platform structure, Thus, the accuracy of loss identification of offshore platform structure is affected. In this paper, the health monitoring system of offshore platform based on strain mode structural damage identification is studied by analyzing the damage identification effect of strain mode structure under different degrees of environmental noise superimposed by single member damage and multi member damage. The research results show that strain mode damage identification can not only accurately locate members, which has better anti-noise ability, but the anti-noise ability under multi member loss is also lower than that under single damage condition. For single member damage, it has better damage identification effect within 10% noise level, and for multi member damage, it just has better damage identification effect within 8% noise level. The research results of this paper find out the base number of damage identification ability of jacket platform structure based on modal parameters, which is a great significance for using strain modal damage identification method in offshore platform structure health monitoring.
Nonlinear Stress Analysis of Key Joints of Steel Truss Bridge
Authors: Liu Zhenlei , Sun Hao 
Published: February 2022

Abstract
Steel truss bridges are widely used in bridge engineering for the advantages of good ability of spanning capacity, construction and light self-weight. Main trusses are the main stressed component of steel truss bridge. And the main truss are made of truss members connected by integral joints. So, the safety of integral joints are very important for normal operation of steel truss bridge. The superstructure of the continuous steel truss bridge with double decks was selected as the engineering example. The software, MIDAS/CIVIL is used to establish the full finite element model of the continuous steel truss bridge. Based on the results of the full bridge model, the 3D finite element model integral joint considering material nonlinearity was established by software Abaqus. The stress distribution of the integral joint under the unfavorable external force were analyzed and compared. The results showed that the most parts of the integral joint are in elastic stage, and the stress distribution is inhomogeneous. The stresses of integral joint are greater than that of truss members. Except for individual stress concentration areas, the stresses in the center area of the integral joint are greater than the stress at the edge. All in all, the safety of integral joints for the engineering example can be guaranteed.