Modeling and point cloud generation for street tree branchesZhang, Yongjun; Chen, Baisong; Qin, Xuzhou; Liu, Zhongwei
doi: 10.1117/12.3057073pmid: N/A
The modeling of street trees is of great significance to the research of highway landscape design. However, it is very difficult to accurately model a complete and realistic street tree. This paper simplifies the tree model by only retaining the main branches and imagining the branches as cones that bent along a 3D spline curve with gradually decreasing radius. Based on this simplification strategy, the tree branches are modeled by the main trunk and sub-branches, and finally, a spline curve skeleton and its 3D model are obtained. After that, the point cloud of tree branches can be obtained by simulating laser scanning to sample points on the 3D model. This method of obtaining 3D tree models, point clouds, and skeletons is flexible, efficient, and low-cost, which can efficiently generate a large amount of training data for further AI model trainings.
Design of a mobile fire alarm system capable of real-time alarmFeng, Wenhui; He, Qing; Wang, Tingli; Wang, Shixin
doi: 10.1117/12.3057491pmid: N/A
As the public pays more and more attention to fire, the importance of fire prevention is becoming increasingly prominent. This paper focuses on the realization of fire alarm software that can alarm in real time. Through in-depth research on sensor technology, cloud computing technology, mobile application development framework and real-time data processing algorithm, the accurate monitoring of smoke concentration and timely alarm function are realized. Through cloud server communication technology, the software can be stably connected with the supporting hardware equipment to complete the alarm notification in real time. At the same time, by continuously querying the server data at a frequency of once per second, it ensures that the alarm notification is issued to the user as soon as the server alarm data is updated. In addition, the software has a simple user interface, which is convenient for users to set up and view historical data, and fully considers the convenience of use. After rigorous testing, this software has excellent performance in accuracy, real-time and stability, providing a convenient and efficient solution for improving fire prevention capabilities, and has broad market prospects for its application in fire protection.
2D visualization of multiple groups of coronavirus gene sequencesZheng, Huaxian; Hou, Junlong; Zheng, Jeffrey
doi: 10.1117/12.3057280pmid: N/A
Study Finds Flu Virus Gene Sequences Differ in Each Outbreak. Viruses have been in a state of mutation during the evolutionary process, in which a certain segment of the sequence changes, but there is also a similar distribution of bases. Technological advances have allowed rapid access to coronavirus data, making it difficult to directly analyze large amounts of data. By visualizing the gene sequences into images and analyzing them with mature image processing techniques, we can effectively reveal the association between sequences and base distribution characteristics. In this paper, the visualization method for processing coronavirus gene data is based on the ideas of variational logic, bioinformatics and statistics, Firstly, the gene sequence was segmented, the base sequences were transformed accordingly and the number of bases in each segment was counted to calculate their corresponding probabilities; secondly, the probabilities were transformed using Polar Coordinate System, and then the Gramian matrix are used to map the polar coordinates into matrices, so that the one-dimensional sequences are processed into two-dimensional mapping, and the graphical results are analyzed at last. graphical results can be analyzed.
Design and application of multichannel focused ultrasound and electrical stimulation device for improving endometrial blood flowSun, Yixin
doi: 10.1117/12.3057377pmid: N/A
This paper reported a method of improving endometrium blood flow. Multi focused ultrasonic probe combined with vaginal cervix probe to stimulate the acupoint, pelvic muscle and cervix. The focused ultrasound module used the digital frequency generator technique and adaptive load technology to produce freguency (1MHz, 0.8MHz), and the electrical stimulation module used the programmable waveform constant current technology. This study used the device to produce focused ultrasound and electrical stimulation to treat the patient who got thin endometrium. The results show statistically significant difference in the level of VI, FI, VFI, PI, PS compared to prior treatment (P<0.05), and there was no statistically significant difference in the level of endometrium thickness, volume, shape and menstrual cycle (P>0.05). This project developed a new device for improving endometrial blood flow, which can effectively improve uterine blood circulation in infertile patients.
Experimental study on infrared detection and de-icing of icing cableShen, Jianhao; Li, Jingyu; Hu, TianKai; Li, Zhenmin; Li, Qingying
doi: 10.1117/12.3057448pmid: N/A
Ice accumulation on cables can severely compromise the stability and safety of power transmission, making efficient detection and de-icing of icing cable critically important. This study proposes a method for cable icing detection and de-icing based on infrared technology. By integrating infrared detection and heating technologies, real-time icing detection and rapid de-icing are achieved. The icing state on the cable surface is analyzed using infrared imaging and image processing techniques. The accuracy of icing detection and the effectiveness of de-icing are validated by comparing infrared images and data distributions before and after de-icing. Experimental results demonstrate that the integrated infrared detection and de-icing system exhibits reliable performance in cable de-icing, providing a novel solution for cable maintenance in low-temperature environments.
Text-dependent English pronunciation learning system based on GMMChang, Shuyuan; Chen, Chinta; Wang, Lihui; Chen, Weiyi
doi: 10.1117/12.3057529pmid: N/A
With the advancement of computer and human speech signal processing technology, the functionality and practicality of English pronunciation learning systems have been further enhanced. Gaussian Mixed Model (GMM) is a model that accurately quantifies things using Gaussian probability density function, decomposes a thing into several models based on Gaussian probability density function, and can directly approximate any probability distribution. GMM also combines the advantages of a single Gaussian density function and vector quantization, which can more effectively describe the distribution of speaker speech features. After extracting speech features using mel scale frequency cepstral coefficients (MFCC), the GMM algorithm is used for text-dependent English pronunciation learning system. The designed English pronunciation learning system is implemented on MATLAB software. This design collected the speech of 50 people with text-dependent for similarity English pronunciation, and after testing, the similarity reached over 93 under normal conditions.
Health assessment system of zone controller based on gray prediction modelHe, Lingqi; Sun, Hui; Xiao, Yao
doi: 10.1117/12.3056970pmid: N/A
As the key subsystem in the signaling system for urban rail transit, the stable operation of the zone controller(ZC) is very important to the safe operation of urban rail transit. The health assessment system of zone controller based on gray prediction model is proposed to solve the problem of lack of preventive maintenance of ZC. Firstly, according to the actual deployment, historical operating status and expert experience of ZC, the health evaluation index system and index deduction standard are constructed. Secondly, the analytic hierarchy process is used to determine the index weight. Then, fault analysis is performed on the status data obtained in real time, and the health score and health grade of ZC are calculated based on the evaluation model. Then the health trend of ZCis calculated using the gray prediction model based on the historical health score. Finally, the fault alarm, health assessment, trend analysis and maintenance suggestions of ZC are displayed through the browser interface. The field application verifies that the system can reflect the working state of the equipment reasonably, and has a good guiding effect for maintenance personnel to maintain ZC.
A small target detection method based on different scales for unmanned aerial vehiclesQi, Xiuyuan; Wang, Zheng; Liu, Zherong; Wei, Haojie; Hao, Shuang; Zhai, Yufei; Liang, Qing; Liu, Ye
doi: 10.1117/12.3057797pmid: N/A
With the continuous iteration and development of computer vision technology, intelligent applications and devices centered around this technology are gradually playing an increasingly important role in human daily life and military operations. Among these, technologies based on object recognition and detection are widely applied in fields such as robotics, drones, and aircraft combat. These areas require precise localization information provided by object detection technology to achieve functions like navigation or attack. However, due to the characteristics of the targets being detected, their scale changes according to their distance, resulting in significant scale variations in images for the same target. Timely detection of distant targets is crucial for aircraft control and early warning, making small target recognition a key factor limiting the widespread application of recognition algorithms. To address this issue, this paper processes the original images based on color space level, global level, and pixel level, proposing a small target recognition method for RGB images. This method involves separately processing different color spaces of the RGB image, followed by information fusion, analysis of the entire image and local regions, and pixel-level filtering in local areas. Experimental results demonstrate that our algorithm can accurately recognize targets of varying sizes and observation angles.
GCNN specific information sound change filtering model based on relaxed normalization of high- and low-membership sample contribution adjustmentShen, Ya-ting; Jin, Ye-ying; Xiao, Yang; Huang, Yuan
doi: 10.1117/12.3057241pmid: N/A
As one of the more advanced algorithms, the gating convolutional neural network (Gated Convolutional Neural Network, GCNN), has the advantages of parallelized computing, sparsity, multi-layer feature extraction, gating mechanism, and so on. GCNN uses SmoothL1Loss (smooth L1 loss) as the loss function. To improve the smoothness of the loss function, the sample membership, namely SmoothL1Loss L (based on the smoothness loss of sample membership L), should be used. However, SmoothL1Loss L, whose membership sum is one, has normalization, with the problem of excessive contribution of noisy samples and too low contribution of high membership samples. Therefore, this paper uses the relaxed normalization condition to derive a new membership division method and proposes a new loss function SmoothL1Loss L (L function to adjust the membership under the relaxed normalization condition). To facilitate the comparison of the effect before and after the loss function, the filtering model of SmoothL1Loss L is called GCNN L ; the filtering model of SmoothL1Loss L is called GCNN L. Experiments on the same data set, the results show that the mean absolute error of GCNN L model 3.8 higher than GCNN L, respectively, so the SmoothL1Loss L function is competitive.
Discussion on scientific research project management in colleges and universities based on PDCA cycle theoryZhao, Yifeng
doi: 10.1117/12.3057574pmid: N/A
The research and development of scientific research projects benefit from efficient management. PDCA cycle management mode is an effective measure of current scientific research project management. The PDCA cycle theory describes a continuous management process that encompasses four key stages: planning, doing, checking, and acting. It aims to enhance project execution efficiency, mitigate project risks, and optimize resource allocation. Through this system to carry out research project management work to achieve the purpose of improving the overall management effect. This paper thoroughly explores the application of the PDCA cycle management model in the operations of schools. It not only analyzes the foundation of its rationality, but also dissects its effectiveness in practice. By thoroughly examining each step of the PDCA (Plan-Do-Check-Act) cycle management model, this paper aims to uncover its significant role in ensuring the efficient and orderly progress of scientific research projects.