International Journal of Advanced Network, Monitoring and Controls最新文献

{"title":"Research on Pilots ’ Mental Workload Classification in Simulated Flight","authors":"Jinna Xue, Changyuan Wang","doi":"10.2478/ijanmc-2023-0048","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0048","url":null,"abstract":"Abstract The problem of human-computer interaction mental workload in flight driving has great reference value for the prevention of safety hazards in aviation driving. This paper analyzes and studies the classification method of mental workload in flight driving by designing different simulated flight experiment tasks. This study uses a combination of EEG signals and subjective evaluation, through the use of convolutional neural networks and long short-term memory network method of combining EEG signals for research and analysis. The accuracy of EEG signal classification is as high as 94.9 %. NASA-TLX evaluation results show that there is a positive correlation between task load difficulty and evaluation score. The results show that the combination of convolutional neural network and long short-term memory network is suitable for pilots ’ mental workload classification. This study has important practical significance for flight accidents caused by pilots ’ mental workload.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123299497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Compound Optimization Greedy Strategy with Reverse Correction Mechanism","authors":"Han Shen, Zhongsheng Wang","doi":"10.2478/ijanmc-2023-0043","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0043","url":null,"abstract":"Abstract Greedy strategy is an algorithm thinking with local optimization as the core idea, but only when the problem has no after-effect, the global optimization can be achieved. Therefore, greedy strategy is not the first choice for researchers to solve the problem. Based on the greedy strategy, this paper adds the mechanism of reverse correction thinking, transfers the local optimal solution to the global optimal solution, and puts forward a compound optimal greedy strategy integrating reverse correction thinking. Based on the actual application scenario of blood robot operating costs, the overall “simple greedy strategy model” is constructed and tested based on the greedy strategy as the main modeling basis according to the application needs. On this basis, the interaction relationship between local optimal solutions is deeply analyzed, and the reverse correction mechanism is integrated to optimize the system through the two steps of reverse allocation and reverse merge repair. Gradually improve the model to get the optimized “reverse modified greedy strategy model”, the algorithm can effectively reduce the operating cost. On this basis, in order to test the optimization effect, the effectiveness and stability of the reverse correction mechanism were verified by modifying some parameters of the application scene and randomly generating multiple arrays for re-test, etc., and new parameters were selected to re-run the application scene, and satisfactory verification results were obtained. Compared with other modeling ideas of the same topic, this model weakens the expression of the overall function and emphasizes the change relationship and action mechanism between data, and obtains better operation results. Greedy strategy is very conducive to the analysis of the relationship between requirements, constraints and variables. According to the actual application needs, combined with the mathematical analysis method, the reverse correction mechanism is added to the greedy strategy modeling. In the demand sequence test of 100 groups of simulation, the maximum saving rate can be close to 1.6%, while the lowest saving rate is less than 0.6%, and the average saving rate is 0.9677%. It can save tens of thousands of operating costs for application scenarios.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"50 40","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131500226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on Extraction Method of Financial Knowledge Based on How Net","authors":"Chaoyang Geng, Jiejie Zhao, Peng Liu, Dan Yang","doi":"10.2478/ijanmc-2023-0045","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0045","url":null,"abstract":"Abstract In order to obtain the knowledge information of financial texts more efficiently and make the extracted information such as entity relation attribute more accurate, this paper studies the grammatical features of financial news texts and the semantic features of How Net, and puts forward the scheme of financial information extraction based on How Net. First, the phrase matching is carried out in the dictionary. Then the neural network is used for weighting, BiLSTM is used for character vector feature enhancement training, and then conditional random field (CRF) is used to complete named entity recognition, and then the relationship extraction of entity pairs from the dependency syntax is carried out to complete the research on the construction method of knowledge extraction of text in the financial field. The experimental results show that this model is superior to the other three models in entity recognition, and the overall performance is improved by about 1.2%. In relation extraction, the accuracy and recall rate of the model algorithm adopted in this paper are improved by 5% and 1.5% respectively, which shows that the improvement of the algorithm is effective.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129419775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research and Simulation of Negative Group Delay and Superluminal Propagation","authors":"Yueyao Wang, Zhongsheng Wang, Xinzhuo Li, Han Shen","doi":"10.2478/ijanmc-2023-0050","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0050","url":null,"abstract":"Abstract In recent years, negative group delay circuits have attracted much attention due to their propagation characteristics and wide application prospects. In the history of human exploration, the exploration of the speed of light has never stopped. The theory of relativity points out that the speed of light in vacuum is the limit speed of signal propagation. However, it is found through research that phase velocity and group velocity appear faster than the speed of light, which does not violate the causal relationship. This paper first introduces the related concepts of negative group delay and superluminal phenomenon, the second focuses on the principle of negative group delay and superluminal phenomenon in-depth analysis and research, finally using the principle of Multisim software, the bandwidth of two different job, different structure of circuit design, the virtual simulation experiment to negative group delay phenomenon and measurement data. It is of great significance to explore the field of faster-than-light and negative group delay in today's rapidly developing information age, and it can try to meet the high requirements for signal transmission. In the future, the interdisciplinary research direction of this research topic also has great development space.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116891061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-time Satellite Anomaly Data Tagging Based on DAE-LSTM","authors":"Caiyuan Xia, Qianshi Yan","doi":"10.2478/ijanmc-2023-0044","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0044","url":null,"abstract":"Abstract Spacecraft is the main carrier of human exploration of outer space, exploration and understanding of the Earth and the universe, and the development of spaceflight can promote human civilization andsocial development, and can meet the nee-ds of economic construction, scientific and technological development, security construction, social progress and other aspects. The current global number of satellites in orbit reaches 5,465, of which China has 541. The vigorous development of the space industry symbolizes the steady improvement of the country’s comprehensive national power and overall technology. During the operation, the satellite in orbit needs to transmit data to the ground, these data may be subject to interference from various aspects, or even equipment failure, we find these data in real time is very important to reduce losses. The data transmitted by satellite has obvious temporal characteristics, and Long Short-Term Memory (LSTM) network has obvious advantages for processing temporal data, so this paper proposes a BER marking model based on the combination of LSTM network and self-coding technology. By comparing the data before and after noise reduction, a threshold value can be determined, and the BERs can be accurately distinguished by this method. After testing with real satellite temperature data, the accuracy of the model detection reaches a high level.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133217714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on Visibility Estimation Model Based on DenseNet","authors":"Guang Li, Zhiqiang Chang","doi":"10.2478/ijanmc-2023-0042","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0042","url":null,"abstract":"Abstract In recent years, the road visibility detection method based on video has been paid more and more attention. It has overcome the deficiency of laser visibility meter to some extent. Deep learning has a good effect in image processing and analysis. This paper firstly analyzes the current situation of deep learning, and then compares DenseNet and ResNet to propose a visibility estimation model based on deep DenseNet. The model firstly integrates airport video data and visibility data. Secondly, the DenseNet algorithm is used to automatically extract the features of the airport data set. Finally, Softmax classifier is constructed to evaluate the visibility accuracy. They reduce the problem of disappearing gradient, enhance feature propagation, encourage functional reuse, and greatly reduce the number of parameters, well train the deep model, has a good visibility estimation effect. On this basis, this paper based on Canny operator lane dividing line extraction edge extraction and visibility analysis based on edge detection, and do the corresponding test. Finally, a video visibility analysis model based on Kalman filter is built based on the given data, and Gaussian process regression model is used to predict the fog change trend.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131369460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabricate the Auto-aquaculture Structure with Android Monitoring System","authors":"Zhiyao Zhang, Yueyao Tian, Shujuan Chang, Lei Tian","doi":"10.2478/ijanmc-2023-0049","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0049","url":null,"abstract":"Abstract Based on the Android monitoring system, the automated fish feeder has been developed. The system provides a convenient and reliable solution for fish farmers. This system includes a fish feeder that distributes food at predetermined intervals. The Android application allows farmers to monitor and control the feeding process remotely. The application displays the current feeding schedule. At the same time, the users can adjust the frequency and amount of food dispensed. The alarm function can send the notification information to the farmer’s mobile phone if the feeder experiences any issues or requires maintenance. By automating the feeding process and providing real-time monitoring, the system can help farmers optimize fish growth and health while reducing the time and effort required for artificial feeding.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123779723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Product Recommendation System Based on Deep Learning","authors":"Pin Lu, Pingping Liu","doi":"10.2478/ijanmc-2023-0041","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0041","url":null,"abstract":"Abstract With the development of Internet big data and e-commerce, the widespread popularity of information, information acquisition and personalized recommendation technologies have attracted extensive attention. The core value of personalized recommendation is to provide more accurate content and services around users. The recommended scenarios are not uniform, and different dimensions need to be considered. For example, we are facing enterprises or individuals, different age groups, different levels of education, social life and other aspects. In this paper, the classic DNN (Deep Neural Networks) double tower recommendation algorithm in the recommendation algorithm is used as the ranking algorithm of the recommendation system. It is divided into user and item for embedding respectively. The network model is built using tensorflow. The data processed by the initial data through feature engineering is sent into the model for training, and the trained DNN double tower model is obtained. Recall adopts collaborative filtering algorithm, and applies tfidf, w2v, etc. to process feature engineering, so as to better improve the accuracy of the system and balance the EE problem of the recommendation system. The recommendation module of this system is divided into data cleaning as a whole. Feature engineering includes the establishment of user portraits, the analysis of multiple recall and sorting algorithms, the adoption of multiple recall mode, and the implementation of a classic recommendation system with in-depth learning. This makes the recommendation system better balance the interests of both the platform and users, and achieve a win-win situation.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116306317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on Super-resolution Image Based on Deep Learning","authors":"Tong Han, Li Zhao, Chuang Wang","doi":"10.2478/ijanmc-2023-0046","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0046","url":null,"abstract":"Abstract Image super-resolution is a kind of important image processing technology in computer vision and image processing. It refers to the process of recovering high-resolution image from low-resolution image. It has a wide range of real-world applications, such as medical imaging, security and others. In addition to improving image perception quality, it also helps improve other computer vision tasks. Compared with traditional methods, deep learning methods show better reconstruction results in the field of image super-resolution reconstruction, and have gradually developed into the mainstream technology. This article will study the depth in the super resolution direction is important method of types of introduction, combed the main image super-resolution reconstruction method, expounds the depth study of several important super-resolution network model, the advantages and disadvantages of different algorithms and adaptive application scenarios are analyzed and compared, this paper expounds the different ways in the super resolution to liquidate, Finally, the potential problems of current image super-resolution reconstruction techniques are discussed, and the future development direction is prospected.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115453977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of Driving Condition Based on Discrete Fourier Transform and Improved K-Means Clustering Algorithm","authors":"Shuping Xu, Yueqiu Huang","doi":"10.2478/ijanmc-2023-0047","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0047","url":null,"abstract":"Abstract In view of the low execution efficiency and slow convergence speed of traditional clustering algorithms, the initial clustering center has a greater impact on the clustering results, which leads to the problem of reduced algorithm accuracy. This paper proposes an improved K-means algorithm (Grid-K-means), that is, the Grid density is used to determine the initial clustering center; According to the density, the grid points are sorted to eliminate the idea of noise grid points and invalid grid points, so as to improve the efficiency and accuracy of the algorithm. First, the discrete Fourier transform was used to filter the original data, and then the principal component analysis and the improved K-means clustering algorithm were used to reduce and classify the kinematics fragments respectively, so as to construct the driving conditions of the vehicle. The experimental results show that this method can effectively improve the construction accuracy and reduce the construction time, and the fitted driving conditions can effectively reflect the local actual traffic conditions.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121918716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}