bluuebunny/crossref_metadata_2025_split huggingface dataset:
The dose response of PTW microDiamond and microSilicon in transverse magnetic field under small field conditions
Authors: Blum Isabel , Tekin Tuba , Delfs Björn , Schönfeld Ann-Britt , Kapsch Ralf-Peter , Poppe Björn , Looe Hui Khee 
Published: June 2021

Abstract
The aim of the present work is to investigate the behavior of two diode-type detectors (PTW microDiamond 60019 and PTW microSilicon 60023) in transverse magnetic field under small field conditions. A formalism based on TRS 483 has been proposed serving as the framework for the application of these high-resolution detectors under these conditions. Measurements were performed at the National Metrology Institute of Germany (PTB, Braunschweig) using a research clinical linear accelerator facility. Quadratic fields corresponding to equivalent square field sizes S between 0.63 and 4.27 cm at the depth of measurement were used. The magnetic field strength was varied up to 1.4 T. Experimental results have been complemented with Monte Carlo simulations up to 1.5 T. Detailed simulations were performed to quantify the small field perturbation effects and the influence of detector components on the dose response. The does response of both detectors decreases by up to 10% at 1.5 T in the largest field size investigated. In S = 0.63 cm, this reduction at 1.5 T is only about half of that observed in field sizes S > 2 cm for both detectors. The results of the Monte Carlo simulations show agreement better than 1% for all investigated conditions. Due to normalization at the machine specific reference field, the resulting small field output correction factors for both detectors in magnetic field

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are smaller than those in the magnetic field-free case, where correction up to 6.2% at 1.5 T is required for the microSilicon in the smallest field size investigated. The volume-averaging effect of both detectors was shown to be nearly independent of the magnetic field. The influence of the enhanced-density components within the detectors has been identified as the major contributors to their behaviors in magnetic field. Nevertheless, the effect becomes weaker with decreasing field size that may be partially attributed to the deficiency of low energy secondary electrons originated from distant locations in small fields.
Application and Study of artificial neural network intelligent control
Authors: Zhao Jing , Zhang Bin 
Published: June 2021

Abstract
Artificial neural network is a computing system formed by several very simple parallel processing units connected with each other in a certain way. Its function depends on the structure of the network, the strength of connection and the processing mode of each unit. The system processes information by its state’s dynamic response to external input information. It is an important branch of intelligent control. By imitating human brain structure and some information processing mechanism, it can solve the nonlinear, uncertain and large lag system, and has a wide range of applications.
Performance Comparison of Multiple Containers Running Artificial Intelligence Applications
Authors: Sun Minghui , Guo Ying , Zhang hu , Cao Wentai , Yuan Meng 
Published: June 2021

Abstract
Due to the performance overhead of virtual machines, traditional virtualization solutions are generally not suitable for artificial intelligence applications. Container-based virtualization technology represented by Docker can provide a customized environment, good portability, good compatibility and low overhead. In this article, we give a performance comparison among Docker, Singularity, and Charliecloud containers. In particular, CPU and GPU are used in each container to run a real application of artificial intelligence for the performance comparison. Finally, the experimental results are given and discussed.
AGV path planning combining A* and ant colony algorithm
Authors: Zhou Le Jia , Cui Wei , Fu Hua Ye 
Published: June 2021

Abstract
Aiming at the problems of lack of pheromone, slow convergence, and falling into local optimum when the ant colony algorithm is applied to the AGV path planning of Xinjiang cotton factory, a fusion A* ant colony algorithm path planning is proposed. The algorithm first initializes the ant colony pheromone with the two-way search A* heuristic function to solve the problem of low ant colony efficiency in the early stage. Secondly, according to the different times of selection of different paths, different pheromone weights are set, and the pheromone reaches a certain level. The optimal solution converges. The experimental results show that the improved algorithm effectively solves the problems of slow convergence, long search paths and falling into local optima.
Multi-target tracking algorithm based on deep learning
Authors: Huo Wenxiao , Ou Jiayu , Li Tianping 
Published: June 2021

Abstract
With the continuous development of deep learning in multi-target tracking, the use of convolutional neural network for feature extraction has replaced the traditional feature extraction method, but the accuracy of target tracking needs to be improved. In order to further improve the accuracy of multi-target tracking, a new multi-target tracking algorithm based on RFB is proposed in this paper. The algorithm is mainly divided into three parts: multi-target detection, feature extraction and multi-target tracking. In the multi-target detection part, CenterNet was selected as the detection network to improve detection accuracy. In feature extraction part, RFBNET is combined with pedestrian re-recognition network to strengthen feature extraction capability. DeepSORT algorithm is used in multi - target tracking. Experimental results on MOT16 data set show that the proposed algorithm is more effective than other methods.
Research Towards Yolo-Series Algorithms: Comparison and Analysis of Object Detection Models for Real-Time UAV Applications
Authors: Wang Shuo 
Published: June 2021

Abstract
General Unmanned Aerial Vehicles (UAVs) are widely used through the computer vision functions of onboard cameras and embedded systems. However, due to the limited memory and computing power of embedded devices on the UAV platform, it is a very challenging issue to analyze the real-time scene through the object detection method. To deal with these challenges, this paper compares the performance of different Yolo series models on the Pascal VOC dataset, using mAP and FPS as evaluation metrics, and applies the training results to the XTDrone UAV Simulation Platform for testing. We evaluate YOLOv3, YOLOv3-tiny, YOLOv3-SPP3, YOLOv4, and YOLOv4-tiny on the Pascal VOC benchmark dataset; the mAP of YOLOv4 is 87.48%, which is 14.2% higher than that of YOLOv3. FPS reaches 72, and the test time on the test set is 103.86s; the shortest test time on the validation set is Yolov4-tiny, but the mAP only reaches 50.06%, which is not as good as Yolov3-tiny. This paper compares the performance of five models in the Pascal VOC Dataset and simulates them on the XTDrone platform, and finally concludes that Yolov3-Tiny can meet the requirements of real-time, lightweight, and high precision.
Design and implementation of strain testing system based on Qt
Authors: Guo Tai , Zhang SuoHuai , Jing XueDong , Wang XuFei 
Published: June 2021

Abstract
Strain testing system is an important research direction in the field of engineering testing, which is widely used in structural health monitoring, motion detection, civil engineering, and other fields. Aiming at the shortcomings of the traditional strain testing system, a strain testing system based on Qt is designed and developed independently, which can collect 8 channels of strain data at the same time and realize the interaction between software and hardware of the system. The system software is developed by Qt, integrated with signal filtering and spectrum analysis algorithms, and designed with a friendly graphical user interface, which is easy to operate. Through the test, the system can reliably measure the strain data and display the waveform of the signal in real-time. It has the advantages of high acquisition efficiency, stable running, good real-time performance and good scalability, which can provide a technical reference for the improvement of the strain test system.
SLAM closed-loop detection method of 2D laser fusion vision in a larger space
Authors: Tong Yong Cai , Cui Wei , Fu Hua Ye 
Published: June 2021

Abstract
In the process of implementing SLAM (Simultaneous-Localization-and-Mapping) for mobile robots, using a separate 2D lidar to build a map in a larger space will lead to inaccurate mapping and missed closed-loop detection. Therefore, an improved 2D laser fusion vision closed-loop detection algorithm is proposed. The algorithm first detects the loop through the visual information obtained by the camera, compares the similarity between the current frame and the key frame, and continuously selects a series of closed-loop frames to be selected near the current frame, and then filters the final closed-loop frame through geometric verification More matching points can be obtained through transformation matrix projection, and the matching points can optimize the transformation matrix. If the current frame and the closed-loop candidate frame get enough common-view space points, then the closed-loop detection is determined to be successful. Finally, the visual loop information is fed back to the laser, and the robot’s pose is adjusted to achieve global optimization. In the experimental environment, it is verified that the laser fusion vision effectively solves the problems such as the lack of robustness of the single laser closed loop detection.
A CycleGAN Adversarial Attack Method Based on Output Diversification Initialization
Authors: Liu Peiyuan , Sun Lei , Mao XiuQin , Dai Leyu , Guo Song , Yang Yu 
Published: June 2021

Abstract
The powerful image generation capabilities of generative adversarial networks (GAN) bring great threats to applications related to images. Style transfer networks realize the style transform between image domains through which we can easily modify images like portraits and calligraphy. To eliminate the negative impact caused by the forged images, there emerged technical methods to detect forged images, which might trigger remedial actions afterwards but cannot prevent maliciously tampered content from spreading over network media. Therefore, some scholars put forward the idea of protecting images from hostile generative networks with adversarial attack. However, the initial random noise of adversarial perturbation cannot be effectively mapped to the output space. In order to improve the visual effect of adversarial attacks, this paper proposes an adversarial attack algorithm based on output diversification initialization (ODI) for CycleGAN. We firstly utilize output diversification initialization to find an effective starting point for the adversarial attack, and then we use Project Gradient Descent (PGD) to iteratively attack the style transfer network by modifying the adversarial loss function. Experimental results demonstrate that the introduction of ODI can effectively enlarge the distance between the adversarial output and the original output. It achieves better results in identifying the forged images generated by the targeted model, and does not significantly increase the disturbance, which can guarantee the normal use of original images.
Crime prediction: pattern recognition and prediction of collusive bidding
Authors: Zhai Yiming , Cheng Junqing , Ding Ning , Fan Zhenyu , Lu Yang 
Published: June 2021

Abstract
Bidding is an effective means to promote fair competition in the market and optimize the allocation of social resources. However, with the increasing incidence of bid-rigging crimes, public resource regulatory agencies and public security agencies are facing new challenges. On the premise of fully studying the current trend of China’s domestic collusive bidding crimes, this paper summarized the abnormal characteristics of four categories of companies suspected of bid rigging, and selected seven representative subcategories of data based on actual conditions, and set thresholds for these data. Then machine learning methods were utilized to build a pre-warning model for collusion bidding. The results show that the use of machine learning methods to predict the bid collusion can achieve a maximum accuracy of 95%. The research can not only improve the early warning, monitoring, analysis and judgment capabilities of the economic crime investigation department, but ensure the benign operation of bidding, and protect the sustained and rapid development of the social economy.
Crime Prediction: An Empirical Study on the Impact of Housing Prices on the Regional Criminal Rate
Authors: Lu Yang , Ding Ning , Wang Yadi 
Published: June 2021

Abstract
The floating housing prices have been a topic that people have been eagerly paying attention to. The increase in housing prices may lead to the occurrence of group rents, triggering many social security and even criminal problems. This paper establishes a linear regression model and a random effect model, and uses China’s provincial panel data from 2000 to 2013. The results show that housing prices and per capita GDP are the more significant factors that explain the regional criminal crime rate. In the regression analysis of the sub-samples, it is found that the focus of the impact of housing prices and various control variables on criminal behavior is different. Regional economic development, population size, and employment conditions will all have a certain impact on criminal behavior. Therefore, studying the impact of housing prices on criminal behavior is conducive to maintaining regional security and stability. In the future, machine learning and other methods can be combined to construct crime monitoring and early warning methods, which can be applied to grassroots police work.
Research on robot target recognition based on deep learning
Authors: Sun Zhenyu , Guo Xiaoming , Zhang Xiaoyang , Han Jiangxue , Hou Jian 
Published: June 2021

Abstract
For the traditional machine vision recognition technology in the industrial field can not handle the problem of different classes of workpieces placed randomly and stacked on each other, this paper improves the SSD algorithm model based on the research of deep learning target detection algorithm. Firstly, a depth-separable convolutional structure is introduced to optimize the VGG backbone feature network. Then a multi-level feature fusion mechanism is introduced in the prediction part to increase the semantic information of features. Qualitative and quantitative experimental results show that the improved optimization method of the SSD model in this paper is validated well on the dataset, and the improved SSD model mAP value is increased by 4.3% compared with the original, and the detection speed is increased by nearly two times, thus proving the effectiveness of the improved method.
Research on Real-time Crawling and Marking Technology of Sensitive Access SQL Statements Based on Information Network Security Isolation Device
Authors: Wang Dong , Fan Huanyu , Li Guomin , Wang Xinnan , Yu Jia 
Published: June 2021

Abstract
Based on the information network security isolation device, this paper mainly analyzed the application status of dynamic desensitization technology in the data internal and external network penetration network. And on that basis, combining with the actual power system network, a real-time capture and marking technology of sensitive access SQL statements is proposed.
Research on Intelligent Question Answering System Based on College Enrollment
Authors: Song Bo , Li Xiao-Mei 
Published: June 2021

Abstract
Due to the increasing number of educated students and the continuous improvement of teaching level, China has formed the largest higher education system in the world, and the information about college enrollment has become the focus of the attention of Chinese students and parents. The intelligent question answering system for college enrollment can understand the user’s intention, provide students and parents with the enrollment information of the school more quickly and efficiently, make up for the shortcomings in the enrollment work, and greatly improve the efficiency of enrollment.
New Technology Integration in Environmental Corrosion Survey
Authors: Weng Yongji , Yan Maocheng 
Published: June 2021

Abstract
Environmental corrosion investigation is an important issue for all kinds of engineering material and construction. Based on the author’s 30 year experience in national soil websites, long-distance pipelines, oilfield areas, and marine atmosphere and other corrosion environment surveys, this article introduces the new technology integration of design arrangements, data collection, data analysis and comprehensive evaluation in environmental corrosion survey. It focuses on the design and arrangement of corrosion tests, detection technology, pattern recognition, fractal and other data processing and comprehensive evaluation methods of hazard matrix.
Real-time regulation of filling speed based on multiparameter synergistic coupling effect in fused deposition modeling
Authors: Chen Yulin , Chen Songmao , Lu Zhongchen , Mo Haijun , Xu Zhongyan 
Published: June 2021

Abstract
This paper aimed to perform a preliminary study on real-time regulation of filling speed by considering multiparameter synergistic coupling effect in fused deposition modeling. Bivariate experiments and sampling printing tests on designed samples, under different parameter combinations which are made up by filling speed, layer thickness, nozzle temperature and corner angle, were carried out to build and validate a real-time regulation model of filling speed by employing error analysis and multivariate nonlinear regression method. Results showed that the equivalent dimensional deviation values and area deviation values of Sample A, Sample B, Sample C by using real-time regulation algorithm of filling speed are lower than or close to the concentrated averages by using the optimal constant filling speed, with the maximum of 0.32 mm and 0.46 mm2. Actual and theoretical build time of Sample D at real-time regulated filling speed are less than those at 20 mm/s (“low speed”), and close to those at 45 mm/s (“medium speed”) or 70 mm/s (“high speed”), which indicates that the method of real-time dynamic adjusting filling speed can not only improve printing accuracy, but also give a full consideration to printing efficiency at the same time.
Research and design of jumping mechanism of jumping robot
Authors: Nan Qin , Lin Wang 
Published: June 2021

Abstract
Considering the research of mechanical knowledge and robotics, a robot with bouncing leg energy storage autonomous movement is designed to realize periodic jumping. The robot combines the spring energy storage process and the jump release process and uses the missing gear to achieve the ability of the jumping robot to complete a periodic stable jump. At the same time, it has long-term battery life, allowing it to overcome obstacles that are several times its own height.
Dielectric and Flash-over Characteristics of the ±1100kV Valve Side Converter Transformer Bushing with SF6 Gas Insulation
Authors: Shiling Zhang , Wei Song 
Published: June 2021

Abstract
The ±1100kV high voltage capacitor filled SF6 gas bushing is an important equipment to realize the electrical connection between the converter transformer and the valve tower. The paper mainly discusses the design of the external and internal insulation structure. The research content is divided into four parts, the actual operating environment and the characteristics of the voltage and current waveform of converter transformer bushing are discussed. The design and analysis of the hollow composite insulator, corona ring and tail end of the bushing have been done. The main insulation structure of bushing has been designed by the equal margin method, and simulation and analysis of the multi-physical field have been done. The three dimensional electric field simulation model has been set up to calculate and analyze the external insulation performance of the bushing. The results show that the main insulation of the bushing is fit to the capacitance structure, the maximum axial field strength of the bushing is 0.62kV·mm−1, and the end of the bushing should be equipped with apple type corona ring. The insulation distance of the hollow composite insulator is designed as 7490mm. The insulation distance of the bushing tail is designed as 3110mm. In the actual operating environment, the maximum field strength of the corona ring appears on the lower end surface, and the value is 2386V·mm−1. The results of the paper can provide the theoretical basis for the design of the external insulation of the converter transformer bushing used in the HVDC transmission project.
Application Analysis of Automated Production Technology Based on Industrial Robots
Authors: Pengcheng Luo 
Published: June 2021

Abstract
With the all-round development of China’s economy and society, the equipment manufacturing industry has shifted from Chinese manufacturing to creation in the past. The domestic production rate of many advanced manufacturing equipment is getting higher and higher, which has made a huge contribution to economic and social development. In recent years, with the rise of industrial robot technology, more and more industrial robots have replaced traditional manual operations, and they have created greater benefits for enterprises with their precision, speed, technology, and efficiency.
Discovering and Analyzing Internet of Things (IoT) Technologies and Applications for Aged Care
Authors: Mu Hongan , Zhang Fang , Xu Chaozhi , Ge Wei , Li Jihong , Yang Feng , Jiang Tao 
Published: June 2021

Abstract
With the increasing aging of the population, the use of the Internet of Things (IoT) is increasing. This research aimed to review the existing IoT literature in aged care. We analyzed IoT using reports for aged care from online stores, so as to discover IoT technologies and applications in aged care. Current research shows that IoT technologies can help elderly people improve their quality of life and they can reduce the pressure on the healthcare system and minimize its operating costs. While previous studies have summarized IoT/wearable applications for geriatric purposes, it is still necessary to review the aged care field. This paper analyzed the IoT/wearable technologies, including a collection of the typical types of devices used in geriatric healthcare. Technology acceptance model (TAM) and familiarity and trust model1 (FTM1) were further conducted on these using reports to value why IoT technologies and applications are accepted. We found IoT applications are ready used in aged care. IoT applications were significant positive advantages for aging population monitoring.
A Study on the Wireless Body Area Network MAC Protocol Using Dynamic Superframe for e-Health IoT
Authors: Su Haoru , Yuan Xiaoming , Tian Rui , Rong Li , Yan Hairong 
Published: June 2021

Abstract
One of the most remarkable applications of the Internet of Things is health monitoring. Wireless body area networks (WBANs) consist of several body sensors implanted in or place on a human body and a coordinator. One of the essential issues of WBANs is the design of Medium Access Control (MAC) protocol to improve system efficiency. In this paper, we modify the IEEE 802.15.4 standard MAC superframe structure and propose an energy-efficient MAC protocol for WBANs in the e-Health Internet of Things (IoT) systems. In this scheme, the time slots are divided into mini-slots. The lengths of the contention access period and the contention free period are both variable. By using this mechanism, the utility of time slots can be considerably increased.