bluuebunny/crossref_metadata_2025 huggingface dataset:
A Rate Control Algorithm Based on Psnr-Hvs For Hevc
Authors: Du Yunfei
Published: April 2021

HEVC/H.265 is the latest video coding standard. It has a higher compression rate under the requirement of ensuring video image quality. However, the currently used video image quality evaluation indicators cannot better fit the subjective perception of the human visual system and cannot effectively allocate target bits and update parameters so that results in reduced video image coding quality. This paper proposes a CTU-level rate control algorithm based on the image quality evaluation factor PSNR-HVS which is more in line with the perception of the human visual system. According to the PSNR-HVS of the CTU as the weight, the target bit is assigned to the current frame to be encoded. Then calculate the actual bits and PSNR-HVS after encoding the current CTU to update the parameters of the CTU at the same position in the next frame. The experimental results show that compared with HM16.20, the subjective performance of the video after encoding is improved, and the image details are more delicate, BD-Rate = -4.6, BD-PSNR-HVS = 0.17, ΔT = 4.6%.
Remote Sensing Image Zero-Watermark Algorithm Based on Bemd
Authors: Xing Siming , Cheng Zhilin , Ji ChunYu , Chen Jiaying , Qi Luyu
Published: April 2021

In order to solve the problem of information security when acquiring and disseminating images and improve the performance of digital watermarking, this paper proposes a remote sensing image zero-watermarking algorithm based on Bidimensional Empirical Mode Decomposition (BEMD). Initially, to perform this algorithm the DCT transform is used to extract the characteristic image of the host image. In the next step, BEMD decomposition on the grayscaled image need to be performed. The number of watermarks embedding layers is determined according to the NC value of the original image without the i-th IMF layer and the original image. The information matrix of the watermark embedding layer is XORed with the characteristic image to obtain the image embedded with the watermark. The extraction of the watermark image is the XOR result of the first XOR and the attacked image. After the watermark is embedded, the image is processed with noise, enhanced processing attacks, etc., and the NC value of the extracted watermark and embedded watermark is mostly above 0.9. The experimental results show that the watermarking algorithm proposed in this paper has better anti-attack performance, stronger invisibility and robustness.
Analysis and Research on Influencing Factors of University Teachers and Students Management Based on Computer System
Authors: Wang Ming , Ni Ziqi , Zhou Xiaoxi , Shi Xiaoxue
Published: April 2021

Teacher computer application is the responsibility and mission of colleges and universities, whether Internet university teachers are willing to contribute much to student management and social progress. It is the responsibility and mission of colleges and universities to do well in Internet university teachers to perform their duties, play a good role, and establish moral education the important driving force and source of the key role of cultivating people are directly related to the healthy development of college student management. With the continuous development of technology. It is a basic skill for university teachers to master computer applications. The paper analyzes the most influential factors of university construction on student management through analysis and its own management experience, and explores an effective way and influencing factors to realize teacher and student management with the help of app management software downloads on the university Internet. The influencing factors in various aspects of student management are analyzed.
Application of artificial intelligence in computer network security
Authors: Zhang lei , Chen Zening , Yang Shufeng
Published: April 2021

At present, artificial intelligence technology is more and more common, and has a very broad development prospect. Nowadays, in people’s daily work and life cannot do without artificial intelligence devices, such as intelligent home appliances, intelligent society greatly improves the quality of life and work efficiency of people. At the same time, with the continuous improvement of the development level of information technology, the application of artificial intelligence technology has gradually expanded to all walks of life in the society, and plays a positive role in promoting and value, improving people’s lives, changing society, and gradually changing the world. In the computer network technology, the full use of artificial intelligence technology, can promote the computer network function more rich and powerful, improve the efficiency of the use of computer network.
Research on Multi-sensor Path Planning Based on Corridor Environment
Authors: Wang Fei , Song Ruilan , Zhao Qingshuai
Published: April 2021

Aiming at the problems of traditional A* algorithm with many inflection points, large turning angles and not adapting to dynamic environment, the current optimized A* algorithm is analyzed and researched. Designed and built a wheeled robot platform with 4WD trolley as the carrier, single-line lidar Rplidar_A3, depth camera Kinect V2 and ultrasonic sensor TeraRanger one as environmental detection sensors. The platform conducted simulation research on the three optimized A* algorithms in the indoor corridor environment, compared the pros and cons of the planned paths, and set up path planning experiments based on the static network improved A* algorithm and dynamic obstacles and static Obstacle avoidance experiment. Experiments prove that the trajectory planned by the improved A* algorithm based on the static network contains 7 inflection points, which is relatively smooth, takes 49.8s and can effectively avoid dynamic and static obstacles.
Research on Educational Information Management System Based on Computer Big Data
Authors: Zhao Xuemin
Published: April 2021

Aiming at the problem of computer network courses with more teaching content and rapid knowledge update, the paper builds a computer network adaptive learning system by collecting learning behaviour data in the education process and using the learning analysis technology of big data. The six modules of prediction and intervention can push learning content in a targeted manner, give feedback on learners’ learning effects in time, and recommend next learning strategies, so as to achieve the effect of teaching students in accordance with their aptitude and cultivating students’ independent learning ability.
Research on the Recent Development of Information Management Technology in the Field of E-commerce
Authors: Zhang Yuxiao
Published: April 2021

As e-commerce has become the new engine of my country’s economic development, information management technology has increasingly become the focus of various e-commerce platforms. Today’s information management technologies are divided into two categories: enterprise-oriented and user-oriented information management technologies based on their use objects. Specifically, it includes personalized information service technology, user query intention recognition technology, and e-commerce information cross-platform retrieval technology. This article elaborates on the basic principles or framework of the above-mentioned technology, analyzes the development and application of information management technology in the field of e-commerce, in order to promote the development of e-commerce and information management technology to promote each other and make progress together.
Research on The Protection System of Urban Garden Plants Based on Time-Space Analysis
Authors: Cheng Xiao , Hong Xiaoling
Published: April 2021

The paper selects a garden as a typical object to study urban garden plants, and uses methods such as video statistics, digital camera record analysis, manual counting, and questionnaire survey statistics (CTVM) to analyse the laws of garden plants in different time periods Based on the analysis and research, a mathematical model was established to explain the temporal and spatial behaviour of garden plants, so as to evaluate the landscape planning of urban gardens and provide a basis for studying the landscape planning of urban gardens. At the same time, the paper designs a web-based urban garden plant protection management system to improve the level of intelligent management of urban gardens.
Improved SFLA Algorithm with Hybrid SA Strategy for Multi-Objective Reactive Power Planning Optimization of Distribution Network
Authors: Zhang Meilun , Zhang Jin , Xu Maoda , Hao Wenbo
Published: April 2021

Aiming at the characteristics of high target dimensionality, strong nonlinearity and complex constraints of distribution network reactive power optimization problems, this paper proposes an improved shuffled frog leaping algorithm based on SA strategy (ISFLASAS) to solve the problem. Firstly, the algorithm uses the global optimization capability of SFLA to detect the optimal solution, and improves the standard SFLA. Incorporating a reciprocal strategy during population initialization to improve the uniform distribution ability of the initial solution and speed up the search for the optimal solution. Secondly, using the local escape ability of the SA strategy, in the later stage of the SFLA calculation, the SA strategy is assisted to jump out of the local optimum with a certain probability to improve the global detection ability. Finally, the IEEE 33-node system is used to simulate and analyze the proposed model algorithm to verify the proposed control strategy.
Research and Application of Facial recognition Algorithm in Audit Investigation
Authors: Wang Hairong , Li Weibo , Wan Quan , Yan Hua , Xiang Rui
Published: April 2021

Aiming at the application scene of face image recognition in audit investigation, firstly, a face data set with corresponding environmental interference is simulated to increase the diversity of data; in the preprocessing stage, the improved method of adaptive histogram illumination balance and simulated glasses covering is used for image enhancement; in the model training stage, an optimal weight re overloading model training algorithm is proposed. The experimental results show that the accuracy, robustness and efficiency of face recognition in the application scene are improved by the improvement of image enhancement preprocessing and the model training of optimal weight reloading.
Review of 3D reconstruction technology of UAV aerial image
Authors: Zhang Zhiping
Published: April 2021

The construction of “smart city” is the development direction of major cities. It is an important part of the construction of “smart city” to reconstruct urban buildings, land and roads into three-dimensional models through three-dimensional reconstruction technology. In this paper, the image-based three-dimensional reconstruction technology and UAV path planning technology are described, hoping to use UAV aerial images for three-dimensional reconstruction, and carry out relevant research on the three-dimensional reconstruction of outdoor large-scale scenes.
A Fast Audit Doubt Finding Model
Authors: Wan Quan , Li Weibo , Wang Hairong , Yan Hua , Xiang Rui
Published: April 2021

In order to improve the audit efficiency and accuracy under the condition of big data, an audit doubt discovery model (CLOWF) based on an adaptive clustering outlier detection algorithm is proposed. The model first uses the slope ratio method to obtain the K value of the K-means++ algorithm, thereby effectively ensuring the clustering effect; At the same time, for the problem of slow pruning speed, a parallel calculation method for the data radius and centroid of each cluster is proposed and designed; Combined with the weighted local outlier factor detection algorithm to calculate the outlier factor, the data greater than the epsilon threshold of outlier is proposed as an indicator to determine the audit doubt. Through auditing application cases, comparing the local outlier factor detection algorithm and the cluster-based outlier detection algorithm, the results show that the execution time of the CLOWF model is the shortest and the accuracy rate is 97.3%.
Portable Kiwi Variety Classification Equipment Based on Transfer Learning
Authors: Wang Qilong , Zhao Lijiang , Niu Zijie
Published: April 2021

China is a one of the largest countries producing kiwifruit, and there are many kinds of kiwifruit in China. The identification of kiwifruit varieties has important application value in kiwifruit automatic picking robots and kiwifruit sorting factories. The paper studies the classification of kiwifruit varieties based on deep learning, and studies the deployment and application of kiwifruit classification model on the Jetson Nano artificial intelligence development board. A portable device used for classification of kiwifruit varieties was designed and developed. This paper studied the selection of various parts of the portable device of kiwifruit classification and designed the portable device shell. The portable device shell was obtained through the 3D printer, assembled the parts, and obtained the portable kiwi variety classification equipment. The construction of the kiwifruit dataset of “Cuixiang”, “Qinmei”, “Xuxiang” and “Hayward” kiwis was studied and using data augmentation to introduce variations into the data. According to the characteristics of the problem of 4 types of kiwifruit classification, the methods and advantages of transfer learning are discussed. Using transfer learning based on three pre-training models Xception, ResNet50, DenseNet121. Comparative analysis of the model size, training speed, convergence, and recognition accuracy of the transfer learning model based on Xception, ResNet50, and DenseNet121, and concluded that in Xception, ResNet50, and DenseNet121, the transfer learning model based on DenseNet121 pre-trained model has the best effect on the classification of four kiwifruit varieties, with fast convergence speed, smallest model, and high recognition accuracy of 97.79%. This paper studied the deployment and experiment of the deep learning model on the Jetson Nano development board. Using the PyTorch to perform transfer learning based on the DenseNet121 pre-training model. After using the TensorRT acceleration engine, it took an average of 0.035s to classify each image, and the real-time classification FPS reached an average of 30, the accuracy rate of the model on the validation set is 93.63%, achieving fast and accurate classification of kiwi varieties.
Simulation Prediction and Control Strategy of COVID-19 Dynamic Contact Network in USA and Various States -- Based on Effective Regeneration Number and Improved Discrete SEIQDHR Model
Authors: Li Yichi , Liu Chenglin , Zhao Suling , Wang Zhen , Zhao Huan , Chu Shenglan , Xiong Zhouqiang , Geng Liang
Published: April 2021

Purpose: Based on the latest characteristics of the transmission mechanism of the COVID-19 epidemic in the United States, this article improves the classic dynamics model of the spread of infectious diseases, simulates and predicts the future trend of the COVID-19 epidemic in the United States and various states. According to the computer program of COVID-19 dynamic contact network, the results provide effective control strategies for the future epidemic prevention work of the United States. Method: The SEIR model is improved by the latest effective reproduction number of the COVID-19 epidemic in the United States, and an improved discrete SEIQDHR model is established for the spread of the COVID-19 epidemic in the United States and various states. MATLAB software is used to perform least square fitting of key parameters, and the computer simulation process of COVID-19 dynamic contact network is solved dynamically. Results: The improved discrete SEIQDHR model is reliable in the analysis of the spread of infectious diseases. The model well simulates the current dynamic contact network of the COVID-19 epidemic in the United States. The results of computer program show that mid-to-late November 2020 is the period with the largest number of new diagnoses before the end of the epidemic in the United States. In a long period of time in the future, the cumulative number of confirmed cases in the United States and states will continue to show a clear upward trend. The cumulative number of confirmed cases of the COVID-19 epidemic in the United States will reach its peak in early December 2021, which is about 37.11 million; the cumulative number of confirmed cases in Texas will reach its peak on March 15, 2021, about 3.21 million. Controlling the source of infection, blocking the route of transmission and strengthening the tracking and isolation are still effective measures to prevent and control the epidemic.
Analysis of key technology of computer artificial intelligence recognition
Authors: Wang Zekai , Shi Zekai , Zhang Mingqi
Published: April 2021

With the continuous development of science and technology, people for the research and development of artificial intelligence gradually in-depth, intelligent technology is widely used, can help people to improve the state of life, improve people’s quality of life. This paper will analyze the computer artificial intelligence identification technology, explore its practical application in life, and put forward some suggestions for the development of intelligent technology.
Dense Feature Fusion for Online Mutual Knowledge Distillation
Authors: Ni Dongsheng
Published: April 2021

Feature maps contain rich information about image intensity and spatial correlation. However, previous online knowledge distillation methods only utilize the class probabilities, Ignoring the middle-level supervision, resulting in low efficiency in training many models. Even if some methods have joined the middle-level supervision, the previous way is to define the characteristic loss, and the effect is general. We propose a new method of middle-level supervision, through the fusion of features between teacher academic network to enter the supervision. The specific method is to fuse the features of the teacher academic network, and establish an auxiliary fusion branch to process the fusion information, so that the feature fusion can effectively strengthen the feature interaction of the teacher academic network. At the same time, we added the normalized integrated distillation of the output, and our method reached the SOTA in online KD. We have done a lot of experiments on cifar-10, cifar-100 and ImageNet datasets, and proved that this method is more effective than other methods in the performance of sub network and fusion classifier, as well as generating meaningful feature maps.
The Model Design of Medical Data Life Cycle Based on Big Data Platform
Authors: Li Ziqing , Pei Shenglei , Feng Guiliang
Published: April 2021

With the gradual popularization of the mobile Internet and the Internet of Things, people’s lifestyles have undergone profound changes. In the medical field, the demand for smart medical remote care is gradually increasing. The continuous upgrading and updating of medical equipment and the precision operation of inspection equipment have made medical information systems contain more and more types of data. Based on data lifecycle management theory and big data processing technology such as Hadoop, this paper designs a corresponding data lifecycle management model for children’s chronic kidney disease remote rehabilitation system. Its role is to manage the data reasonably, thereby increasing the availability of information systems and improving the efficiency of system storage devices.
Research on the Integration Method of Intelligent Terminal Services Oriented to the Aged Cross-Border Platform
Authors: Feng Weijia , Yu Wenqing , Zhang Zheyu , Wang Juan , Tian Hongmei
Published: April 2021

To meet the needs of the elderly for smart, healthy, and elderly care, the paper uses the Internet, the Internet of Things, cloud computing, and other technical means to build a cloud platform-based smart health and elderly care cross-border platform service system. Designed and developed a health all-in-one smart terminal suitable for a home environment to realize physiological parameter collection and vital sign monitoring. This system promotes the intelligent upgrade of the cross-border platform for the elderly, and improves the quality and efficiency of the health of elderly services.
Research on Mathematical Genetic Algorithms Based on Evolutionary Computer Neural Network of Distribution Function Parameters
Authors: Han Yunna
Published: April 2021

Genetic algorithm and neural network are both ideas and algorithm skills. The flexibility of this method provides a stage for many researchers and applications. This paper discusses the neural network model based on the improved genetic algorithm under the parameters of the distribution function and its application in multi-variable, multi-step nonlinear economic forecasting. First of all, this article discusses the method of using improved genetic algorithm to learn neural network connection weights, and proposes a secondary optimization strategy. The main innovations or improvement techniques include: initial population generation strategy, crossover operation secondary optimization strategy, mutation operation Secondary optimization strategy, optimal chromosome inventory strategy, etc. This article uses VB for programming. The developed software has a certain versatility and can be used for prediction problems similar to nonlinear economic data.
Study on Intrusion detection model based on improved convolutional neural network
Authors: He Kaiyan
Published: April 2021

With the rapid development of information technology and cyberspace, information interactions between networks are becoming more frequent. At the same time, cyberattacks are posing more and more threats to network security through intrusions into computer systems or information systems. To address these problems, this paper proposes an improved convolutional neural network-based intrusion detection model (ICNN-IDS) to determine and classify specific types of intrusions after feature extraction and analysis of different network flow. The paper introduces the basic components of neural networks, including the convolutional layer, pooling layer and fully connected layer. Next, the experimental data set acquisition and pre-processing process are introduced, followed by the structural setup, the specific tuning process of the model, and the optimization of the model parameters are evaluated through experiments. In order to optimize the input feature matrix, the model adds a neuron mapping layer before the convolutional layer to convert sample data from 1D to 2D for the improvement of the model. The experimental results show that ICNN-IDS achieves 99.35% detection accuracy and a low false alarm rate of 0.21% on the KDD99 dataset with optimal parameter settings, which has significant improvement over existing detection models.
Long time prediction of human lower limb movement based on IPSO-BPNN
Authors: Jin Dongnan , Liu Yali , Ma Xunju , Song Qiuzhi
Published: April 2021

System delay caused by mechanical transmission, control calculation and data communication are the main factor affecting the man-machine collaborative control of lower extremity exoskeleton. Improved Particle Swarm Optimization Algorithm (IPSO) was proposed to optimize BPNN (Back Propagation Neural Network) to predict the future joint angle of human lower limb. The 3d motion capture system was used to collect the Angle data of human lower limb joints, and time span was added to reconstruct the time series, which was taken as the input of the model. Compared to PSO (Particle Swarm Optimization), IPSO added a three-route competitive optimization trajectory, the training feedback of BPNN and mutation operation, which accelerated the convergence of the algorithm and avoided local optimization. Besides, we established a prediction evaluation criterion with prediction duration, iteration efficiency, Root Mean Square Error (RMSE) and Determination Coefficient (DC) as the core to analyze the prediction results of BPNN, PSO-BPNN (Support Back Propagation Neural Network by Particle Swarm Optimization) and IPSO-BPNN (Support Back Propagation Neural Network by Improved Particle Swarm Optimization). The results show that the average RMSE of IPSO-BPNN is less than 0.75 and DC is more than 98%. IPSO-BPNN can make more accurate prediction of human lower limb joint angle, which is beneficial to improve the man-machine coordination performance of exoskeleton.
A Novel Structure-based Feature Extraction Approach for Financial Fraud Detection
Authors: Xia Hui , Ma Hui
Published: April 2021

In finance and economic area, financial fraud detection plays an important role for both corporate management and capital market system. Feature extraction is one of the most important procedure in fraudulent firm detection. Current feature extraction approaches pay large amounts of attention on their financial attributes, which have explicitly limited the representation of ‘normal’ pictures of firms, and furthermore, reduced the financial fraud detection performance. Hence it is necessary to search for a better set of functions as features to represent firms more accurately. In this work, notice that the imitation behaviors among firms often happen in business management, while this structure patterns have not been utilized in f inancial fraud detection so far, we extract features under the constraint of both financial characters and structure patterns of firms. We also design three measurements to quantify the structure patterns. Experimental results have shown a great performance of the proposed approach.
Application of Finite Difference Method in Image Reconstruction of Electrical Capacitance Tomography
Authors: Chen Huamin , Xue Xiao , Zheng Yangbing
Published: April 2021

Electrical capacitance tomography is to invert the medium distribution inside the object by using a limited set of measured capacitance values. In order to realize image reconstruction, the sensor sensitive field is solved by finite difference method under the condition of known sensor distribution and internal permittivity distribution of pipeline, and satisfactory results are obtained. According to the calculated sensitive field, the distribution image of the fluid on the fault plane is reconstructed by using the back-projection algorithm. Back-projection algorithm has the character of simple structure and fast speed of reconstructing images. However, the number of projections obtained by the capacitive tomography system is much smaller than the number of image pixels and the soft field characteristics of the imaging system make it difficult to accurately image, so only an approximate phase distribution image can be reconstructed.
Research on the application of Fama-French 5-factor model in the steel industry during COVID-19
Authors: Hou Dingwen , Chen Zirui
Published: April 2021

Based on the Fama-French 5-factor model (FF5), this paper analyzes the market changes of the American steel industry before and after the epidemic. In this paper, the Data from Kennethr French-Data Library were used to make multiple regression analysis of the U.S. steel industry before and after the epidemic. The Fama-French 5-factor model was also used for analysis. According to the results of multiple linear regression, due to the influence of COVID-19, the coefficient of market risk (Betam) decreased; Robust minus Week (RMW) changed from significant to insignificant; Small minus Big (SMB) and High minus Low (HML) were significant and the change of epidemic situation was not significant, while Conservative minus Aggressive (CMA) was not significant. The impact of the outbreak on the U.S. steel industry has been dramatic and has led to a huge decline in the entire industry.
The best input feature when using convolutional neural network for cough recognition
Authors: Cai Yunan , Xu Wenlong
Published: April 2021

In recent years, the use of convolutional neural networks has been successful in the task of cough recognition. This method mainly converts audio clips into the form of spectrograms, and then uses convolutional neural networks for classification, which prompts us to seek better input representation For more effective training to achieve better performance, in this article, we use STFT, Mel spectrogram, Log-Mel spectrogram and MFCC four different features as the input of the convolutional neural network, in the case of the same parameters Compare their performance below, where the Mel spectrum is used as input to achieve 92.5% classification accuracy. Secondly, we compared the classification performance of different Mel spectra generated by different window sizes and frame shifts under the same convolutional neural network. For a 320ms cough segment, the window size is 64, and the frame shift is 32, which has the best performance
Application of Collaborative Filtering Recommendation Algorithm in pharmacy system
Authors: Lv Yihang , Kong Jingjing
Published: April 2021

Recommendation algorithm has been widely used in Internet commerce. At present, the most widely used and successful algorithm is collaborative recommendation algorithm. It can be used in pharmacy marketing system based on user and project purpose. Based on the analysis of the current situation of retail drugstores, this paper constructs the marketing management system of retail drugstores, and establishes two recommendation models of the marketing system of retail drugstores and retail drugstores. The main goal of model 1 is to construct a user based collaborative filtering recommendation algorithm input, after the algorithm processing, to generate recommendation results, to achieve product recommendation to customers. The goal of model 2 is to construct a Project-based Collaborative filtering recommendation algorithm input, after the algorithm processing, produce the recommendation results, so as to find the target customers for the product. These two recommendation models are helpful to the research and improvement of pharmacy system algorithm.
Research on Efficient and Economical Power System Optimization Algorithm
Authors: Fei Qiu
Published: April 2021

The paper proposes to apply the particle swarm optimization algorithm to the dynamic optimization power flow calculation in the power system with distributed power generation, which takes all periods of time into consideration. The specific implementation method of the algorithm is given. According to the principle of nearby reactive power compensation, distributed power sources do not absorb reactive power from the system as much as possible. The reactive power required by distributed power sources is mainly provided by distributed power reactive power compensation devices. In order to verify the effectiveness of the algorithm, the economic load distribution of the power system with different unit numbers was tested, and compared with other optimization algorithms. The result proves that the algorithm can find the optimal solution efficiently and accurately, effectively avoiding the problem of falling into the local optimal, and ensuring a faster running speed.
Research on Vehicle Recognition Algorithm based on Convolution Neural Network
Authors: Zhang Pai , Chen Hanqing , Li Qinrui
Published: April 2021

In order to effectively identify vehicle types in intelligent transportation system, based on the analysis of Inception V3 model, a deep learning model of vehicle classification based on transfer learning theory is proposed in this paper. In this model, the last full connection layer is removed on the basis of Inception V3 model, and the parameter optimization layer is added, and then Dropout and global average pooling layer are adopted. Theoretical analysis and experimental results show that the performance of this model is better than that of VGG-16-based vehicle classification model, Xception-based vehicle classification model and Resnet-50-based vehicle classification model. The experimental results show that the training accuracy of the method proposed in this paper is more than 96.48% and the test accuracy is more than 83.86%.
Intelligent Path Planning Algorithm for UAV Group Based on Machine Learning
Authors: Li Ronghao , Xiong Yuhan , Zhang Tao
Published: April 2021

Aiming at the minimum and local minimum problems existing in the artificial potential field algorithm for obstacle avoidance of UAV, a new path planning method is proposed by using the improved artificial potential field algorithm. Different from the current artificial potential field method, this model starts from the interaction between two aircraft. On the basis of obstacle repulsion, the repulsion force between UAV is increased, and the pre-centroid of the cluster is defined as another source of gravity. The analysis of the algorithm shows that this method can effectively prevent the UAV from falling into the local minimum and enhance the control and obstacle avoidance ability of the UAV cluster. Based on the UAV control model, the path planning design is given and the simulation experiment is carried out. The experimental results show that the UAV cluster control based on this model has better obstacle avoidance performance and target tracking ability.
Identifying Clinical Detection in Disease Context by Computational Mining of PubMed
Authors: Fu Xiaoxue , Zhou Yi
Published: April 2021

To propose a novel informatics-based strategy for identifying candidate clinical tests for pancreatic cancer. We implement experiments on 6483, 27372, 28449 and 13017 publications respectively associated with risk, diagnosis, treatment and prognosis of this disease searched from PubMed and two query sets composed of 3880 clinical detection terms and 109 genes. By integrating gene-disease database, clinical information of tests, we determine the most likely terms related to the risk, diagnosis, treatment and prognosis of the disease and rank them according to our statistical scheme. We found 21, 42, 38 and 28 detection terms respectively related to risk, diagnosis, treatment and prognosis of pancreatic cancer. For risk assessment, “Adiponectin”, “Cholecystokinin (CCK)” and “Interleukin 2” with high New Term Frequency Inverse Document Frequency (NTFIDF) imply they take on greater importance to the documents where they occur in the corpus. “Carotene, Beta”,” Albumin, Serum” and “Prothrombin Fragment 1+2” with high Inverse Document Frequency (IDF) weightings indicate they provide more information. Furthermore, by incorporating 109 genes into query sets, we discovered “IGF Binding Protein-1 (IGFBP-1)” with the highest NTFIDF (0.088407) whereas “IGF Binding Protein-1 (IGFBP-1)”, “Leptin”, “Interleukin 2”, “5-Methyltetrahydrofolate” and “Gram” possessed high IDF (2.72). Similarly, for diagnosis, treatment and prognosis, “Cholecystokinin (CCK)”, “Gram”, “Neurotensin” gain the highest IDF while “Gastrin, Serum”, “Neurotensin”, “Gastrin, Serum” have the highest NTFIDF correspondingly. The findings suggest a unique opportunity for laboratory and clinical research and should be further validated in prospective research.
Research on System Dynamics Simulation of Building Materials Supply Chain
Authors: Chen Jianbiao , Zhong Jiezhi , Xie Baosheng
Published: April 2021

The bullwhip effect of supply chain under non-information sharing and information sharing environment is analyzed theoretically. The model of building materials supply chain in two environments is constructed, and the system dynamics flow chart is established by Vensim PLE simulation software. The correctness of the theoretical analysis is verified by an example simulation. The sensitivity analysis of transportation delay time and manufacturer’s production cycle shows that extending transportation time can reduce manufacturer’s inventory, but raw material inventory in transit will increase; Shortening the production cycle of producers under the information sharing environment is more conducive to reducing the bullwhip effect of the supply chain.
Nonlinear Parameter Estimation and Experimental Verification of Gravity Sensor Considering Quadratic Error Parameters
Authors: Xie Tianyi , Lu Shuhai , Cao Juliang , Yu Ruihang
Published: April 2021

With the rapid development of inertial navigation technology, the proportion of inertial navigation technology in navigation and positioning is getting higher and higher. The measurement accuracy requirements of inertial components are getting higher and higher. Based on the mature linear calibration method, this article calibrates the quadratic error of the accelerometer component in the inertial component and compensates the error term. In theory, the least squares estimation is used to solve the quadratic parameter. After considering the quadratic term, the measurement accuracy of the gravity sensor has been improved, and the laboratory gravimeter has been used for marine experiments. The experimental results show that the positioning deviation considering the quadratic error term is smaller than the positioning deviation considering only the first error term.
Research on the material fire risk index based on the GA-BP neural network
Authors: Chen Lei , Wang Yiqi
Published: April 2021

To improve the material fire risk index (IFHI) forecast precision and accuracy, we raise a way that the prediction model consists of the genetic algorithm (GA) and BP neural network. There are many merits in this model. For example, the weights and thresholds of BP neural networks can be improved by the advantages that the genetic algorithm can reach the peak of the forecasting accuracy of the whole situation. And we pose MSE, MAE, and MAPE to measure the effectiveness. The result of MSE, MAE, and MAPE is 0.005843, 0.0183, 1.08158. The experimental results show that the IFHI of the polymer can be accurately predicted by GA-BP neural networks.
Research on the Security Algorithm of Reversible Information Hiding in Communication Encrypted Image
Authors: Wang Jijun , Tan SooFun , Yuan Yi
Published: April 2021

Considering the embedding capacity and the security of the algorithm, the paper proposes a reversible information hiding algorithm for encrypted images based on. The information concealer can find the transformed pixel group in the encrypted image according to the same key and use the embedding key to replace the corresponding pixel’s LSB to complete the reversible embedding of secret information. Simulation tests show that the proposed hiding method can realize the lossless recovery of the carrier image and the original image, which effectively reduces the transmission load and has high security.
Numerical Simulation Study on Propellant Stability of Penetration Warhead
Authors: Zhang Menghua
Published: April 2021

For the problem of charge stability of penetration warhead with a booster device. The process of projectile penetrating concrete is simulated by ANSYS/LS-DYNA with two different algorithms (FEM and FEM-SPH), the calculation results of numerical simulation and experience formula were contrasted with the experimental data. The results show that the FEM-SPH coupling algorithm can overcome the shortage of traditional finite element algorithm for dealing with large deformation issue. and the calculation result of FEM-SPH is most closely with the experimental data. The propellant structure can withstand the maximum overload is 29134g. It can provide a reference for the design of the booster warhead.
Discussion on the Performance of M&A Transformation and Upgrading in Manufacturing Enterprises - Taking Hifuture Technology for Example
Authors: Li Yanqin
Published: April 2021

Under the background of “Made in China 2025 strategy” and the integrated development of “manufacturing + Internet”, traditional manufacturing enterprises have set their hands on the Internet one after another to boost their transformation and upgrading through mergers and acquisitions and seek new profitable growth and business development. Traditional manufacturing mergers and acquisitions Internet enterprises belong to cross-border mergers and acquisitions, there is a greater risk of mergers and acquisitions, mergers and acquisitions results are full of uncertainty. According to the data of stock market and the enterprise financial index, build events analysis model and entropy value method to analyze Hifuture M&A performance of science and technology, the results show that the M&A is advantageous to the enterprise new profit growth point, but no significant positive effect on M&A performance, the main manufacturing enterprises of industry competition, resources integration after the merger synergies.
Research on the Influencing Factors of Establishing Buyout Fund And Value Creation Benefits
Authors: Qiu Xiangning , Zhou Yan
Published: April 2021

Buyout funds have risen and developed rapidly in China since 2000. In 2011, “Paradise Dakang” set off a countrywide upsurge of establishing “PE + listed companies” buyout funds. Based on the data of buyout funds set up by listed companies and private equity investment institutions during 2011-2017, this paper studies the influence factors of their decision to set up buyout funds. The research finds that enterprise scale, cash holdings, operating performance and operating revenue growth are positively correlated with the possibility of establishing buyout funds, while leverage level and the proportion of the largest shareholders are negatively correlated with the possibility of establishing buyout funds.The establishment of “PE + listed company” model buyout funds can significantly increase shareholders’ wealth in the short term.
Research on Information Management of Production Workshop Based on MES System
Authors: Chen Pengfei
Published: April 2021

with the progress of science and technology, information technology is in rapid development, production manufacturers are under tremendous pressure, for modern production mode, the information management is an important part of constantly promoting the process of our modernization and informatization in recent years, the use of MES system make it possible to production management informationization, MES technology plays an important role in the process of enterprise informatization, this article mainly introduced the content of MES technology, the function of MES technology and its application in production management.
Current Development in Microsimulation and Experimental Innovation method in JUTTA Model
Authors: Zhou Meng , Men Yuting , Qing Xuwen
Published: April 2021

Nowadays, microsimulation method has been introduced to different fields, such as Social Science, Medicine research and Economic study. This method evaluates the effects of the proposed interventions or policies before they are implemented in the real world. In this article, we will concentrate on microsimulation method used in Social Science by firstly explaining two main streams in microsimulation world, Static approach and Dynamic approach. In the following section, the uncertainty of a Finnish static microsimulation model JUTTA is assessed and Toimtuki model, one of the sub-models in JUTTA is detected to have space to be more accurate. In order to do so, two experimental statistical models-Linear Regression model and Two-Stage Least Squares(2SLS) model are applied to it. From the results, we could conclude that both the Linear Regression and 2SLS successfully improves the accuracy of TOIMTUKI to some extent.
Multi-area Generation Dispatching Distributed Coordination and Optimization Algorithm
Authors: Ji Yuejin , Shi Zhiliang , Su Rongqiang , Zheng Hao
Published: April 2021

As the fast expansion and interconnection of power system, it makes higher requirements for Optimal Power Flow (OPF) calculation in modern power grid. A distributed coordination and optimization method is presented in this paper. Injection power equivalent of sub-system boundary bus is utilized to solve multi-area dispatching problem. Based on regional decomposition model, it decouples the integrated optimization and avoids complex computation of system parameters equivalent in conventional methods. Besides, it reduces the communication between different regions. The nonlinear primal-dual interior point method is used for optimization in each sub-system, outer coordination of boundary bus’s voltage correction is conducted to compute the optimized dispatching in the whole interconnected power system. Numerical simulations are taken in IEEE test systems. The results show that the proposed method is validated, effective and suitable for online application.
Research on Combating Epidemics based on Differential Equations and Cellular Automata
Authors: Xiao Meng , Zhan Qiyuan , Li Yanqing
Published: April 2021

The new crown pneumonia epidemic has swept the world, panic, anxious, and uneasy emotions flowed into the psychology of everyone. This epidemic not only puts many countries in economic crisis, but may also put some small countries in danger of disappearing forever, and even make it impossible for large-scale people to return home. Therefore, the World Health Organization (WHO) and countries around the world need to join hands and work together to further explore ways to effectively control the epidemic. Analyze the relevant data of the four modes of disease (susceptible persons, latent persons, asymptomatic persons, and recovered persons), establish a differential equation model, and combine the results of question 1 to get the trend of the number of asymptomatic infections (present The trend of first rising and then falling) and specific data (it peaked at about 2733 people on the 42nd day after the outbreak; it dropped to 10 people about 70 days after the outbreak; it decreased to 0 at about 80 days). Then we simulated the distribution of asymptomatic infections based on the data reported by the Beijing Municipal Health Commission and combined with the cellular automaton model: the clustering state appeared in the first 10 days, and it gradually dispersed over time, and the distribution became more distributed after about 50 days. Evenly. Finally, it summarizes the applicable fields of this model in life and effective and accurate suggestions for epidemic prevention and risk reduction.
Morphological Study of Bog Bulrush (Schoenoplectiella mucronata) from Rokan Hulu, Riau, Indonesia
Authors: Suhesti E. , Ratnaningsih A.T. , Suwarno E. , Effendi I.
Published: April 2021

Bog bulrush (Schoenoplectiella mucronata) is an aquatic flowering plant, considered as weeds. The stems can be used as material of mats, sacks, box, rope etc. so that it reduce the plastic use. This study aimed to describe the morphology of this aquatic plant collected from Rokan Hulu, Riau, Indonesia. It is a tufted perennial plant with an upright or horizontal rhizome; the stem reaches a height of 80–90) cm, 4–6 mm wide, has a sharp triangular section, has indistinct serrations. The tip leaf is conical into a sheath, 5–7 cm long, ending at a triangular apex, pale brown in color, absent; midrib, petiole, veins, ligule, and blade. Develops a pseudolateral, dense, head-like cluster of 3-20 spikelets; rod main stem, sharp triangle, 20-25 mm long, sharp tip, and usually upright. Fruit an obovoid nutlet, 1.0–2.5 mm × 1–1.5 mm, bluntly 3-angled, blackish, minutely wrinkled. Sessile grain, ovate to cylindrical, flowering length 4–5 mm, fruit length 310-20 mm, many flowers; the glume is spiral, oval, concave, 3–5 mm long, pale brown; bisexual flowers, perianth consisting of (4–) 6 brown hairs with recessed teeth, 3 stamens, superior and 1-locular ovaries, 2–3 stigmas.