Journal of Computational Methods in Sciences and Engineering最新文献

{"title":"Key technologies of smart antenna in WLAN based on adaptive array","authors":"Xiao-Ran Zheng, Rui Zhang","doi":"10.3233/jcm-247326","DOIUrl":"https://doi.org/10.3233/jcm-247326","url":null,"abstract":"In order to improve the communication quality and transmission rate of WLAN, the key technologies of smart antenna in WLAN based on adaptive array are proposed. The adaptive array is used to suppress the WLAN interference signal, and the feedback from the output is used to adjust the weight loaded on the signal, and the optimal weight corresponding to the linear constraint minimum variance is obtained to achieve beamforming optimization. On this basis, the optimal antenna selection algorithm and the sub-optimal antenna selection algorithm are designed, and the sub-channel matrix with the maximum capacity can be obtained by repeated iterative calculation, so as to realize the smart antenna selection and further optimize the performance of WLAN. Experimental results show that the smart antenna signal has 100% coverage in WLAN compared with conventional methods. When the transmission rate is greater than 35 mb/s, the delay of the study method is not jitter compared to the contrast method. When the transmission rate is greater than 35 mb/s, the packet loss rate of the proposed method remains stable, while the packet loss rate of the two comparison methods begins to increase. When the transmission rate is greater than 12 mb/s, the throughput of the proposed method is more stable than the other methods. In conclusion, this method has the characteristics of large signal coverage, low delay, low packet loss rate and high throughput, and can be widely used in practice. The contribution of this study is that the weight of the antenna array can be dynamically adjusted through the adaptive algorithm, thus optimizing the quality of the received signal and improving the receiving sensitivity.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140994040","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":"The application of deep learning in the innovation of intelligent English teaching mode","authors":"Yafang Chen","doi":"10.3233/jcm-237054","DOIUrl":"https://doi.org/10.3233/jcm-237054","url":null,"abstract":"With the rapid development of deep learning technology, its application in various fields is increasingly extensive. Especially in the field of education, the application of deep learning technology has brought great challenges and changes to the traditional teaching mode. This research is aimed at the application of deep learning in intelligent English teaching mode. Firstly, the theory of deep learning is studied in depth, and the application cases of deep learning in other fields are discussed. Secondly, the research designs and implements an intelligent English teaching model based on deep learning, and carries out a lot of experiments and tests. The experimental results show that this new teaching mode can effectively improve the efficiency and effect of students’ English learning. However, it is also found that the model has some problems, such as model training needs a lot of computing resources, has certain requirements for hardware equipment, and some students have poor adaptability to the new learning mode. To solve these problems, a series of solutions are proposed. In general, although there are still some challenges in the application of deep learning in intelligent English teaching mode, its potential is huge and it has a profound impact on improving the quality of teaching.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140991250","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":"Detection and analysis of student behavior in college labor education courses based on YOLOv5 network","authors":"Ke Zhang","doi":"10.3233/jcm-247308","DOIUrl":"https://doi.org/10.3233/jcm-247308","url":null,"abstract":"To improve the application of behavior detection technology in college education, the study proposes a new model built on deep CNN, which is used for student behavior detection and analysis in college labor education courses. The study first analyzed the target detection algorithm, and optimized the selected You Only Look Once version 5 (YOLOv5) algorithm and its network structure with a series of improvements, and based on this, embedded the attention module into the algorithm structure to finally obtain a new model, namely YOLOv5-O. After a series of experiments, YOLOv5-O reached an average accuracy of 90.1% on the test set, while the application test in the actual teaching environment showed that its average accuracy was 86.7%. This result is obviously superior to the existing technology, which proves the validity of the study and provides strong data support for the automatic detection of student behavior. In addition, in the teaching experiment, YOLOv5-O assisted teaching achieved the most significant teaching effect, and students’ achievement improved the most. The feasibility of this method is verified.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140991695","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":"Cooperative control method of multiple spacecraft formation based on graphtheory","authors":"Li Li, Lei Du, Yixuan Hu","doi":"10.3233/jcm-247333","DOIUrl":"https://doi.org/10.3233/jcm-247333","url":null,"abstract":"Spacecraft cluster is a new way of multi-vehicle cooperation and a major problem in the current space distribution system. A large number of core technologies of spacecraft cluster technology need to be simulated, analyzed and verified on the ground. On this basis, this article proposes the construction of a spacecraft system model and a dynamic model, and designs a path planning method that combines the spacecraft system model with the a* algorithm. And use the Morphin search tree algorithm to improve the A-star algorithm, and then simulate and analyze the spacecraft formation control scheme. The simulation results of trajectory planning show that after running the model for 21 ms, the improved A* algorithm achieved the expected error. Its MAE value is 10 - 4, achieving good path planning effect. The research plan can effectively achieve control of spacecraft formation and meet the needs of collaborative tasks and navigation route planning.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140991268","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 study of factors affecting the employment quality of contemporary college students through a structural equation model","authors":"Ji Sun","doi":"10.3233/jcm-237094","DOIUrl":"https://doi.org/10.3233/jcm-237094","url":null,"abstract":"OBJECTIVES: This paper aims to analyze factors affecting the employment quality of contemporary college students to improve it. METHODS: Data related to the influencing factors and employment quality were collected by means of a questionnaire. After verifying the effectiveness of the data, a structural equation model of employment quality was constructed. FINDINGS: The data collected by the questionnaire were effective. The structural equation model analysis results showed that individual factors, educational factors, and environmental factors were all significantly related to employment quality. NOVELTY: The novelty of this article lies in the use of a structural equation model to quantitatively analyze the relationship between influencing factors and employment quality, providing an effective reference for improving the employment quality of college students.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140991532","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":"Data acquisition and application of internet of things in financial management","authors":"Jiansen Qin, Yansha Zhu","doi":"10.3233/jcm-247306","DOIUrl":"https://doi.org/10.3233/jcm-247306","url":null,"abstract":"With the rapid development of information technology, Internet of Things technology has become a hot topic in today’s society. This study aims to explore how IoT technology impacts various aspects of financial management, in particular how it changes the collection, processing, and parsing of financial data. Through in-depth literature review, questionnaire survey and experimental design, the research found that IoT technology has a significant positive effect on sales, transaction times and inventory control. But at the same time, data security, privacy concerns and initial technology investment are also challenges that enterprises need to consider when adopting these technologies. Overall, IoT technology offers tremendous opportunities for financial management, but businesses must fully assess the potential risks and benefits when implementing it.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140992703","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":"Systematic evaluation of the elderly care industry based on energy factor inputs","authors":"Meng Xu, Ming Chen, Fangyuan Pan","doi":"10.3233/jcm-247317","DOIUrl":"https://doi.org/10.3233/jcm-247317","url":null,"abstract":"The energy factor is the foundation of economic and social development, and it is also an important prerequisite for the effective operation of the elderly care industry. Based on the perspective of energy factor input, this paper constructs the DPSR mechanism model of the energy-elderly care industry system. Taking Shanghai as an example, through its 2010–2019 15 index data such as energy factors and industrial economy, the Entropy-TOPSIS method is comprehensively used to evaluate the energy-elderly care industry system. Finally, the following conclusions are drawn: (1) The energy factor has an important impact on the operation of the elderly care industry through its effect on the driving force module, the pressure module and the state module; (2) The elderly care industry has an important impact on the energy factor through the conduction of the response module; (3) The evaluation results of the Shanghai energy-elderly care industry system showed a continuous improvement trend from 2010 to 2019.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140992004","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":"Smart urban management identification by integrating optical flow characteristics and HSV space","authors":"Dongya Chen","doi":"10.3233/jcm-247313","DOIUrl":"https://doi.org/10.3233/jcm-247313","url":null,"abstract":"n smart cities, sanitation workers are the key to urban construction. Accurate targeting of sanitation workers can help managers better monitor and manage them. Pedestrian detection is the core and key component of object detection technology. The difficulty of pedestrian detection in the actual feature recognition is still how to quickly and accurately identify the identity in the complex video scene. To realize the effective detection of sanitation workers, the study designs an identity identification scheme conducive to the friendly management of smart urban management. Since the optical flow feature extraction method and HSV color space extraction method can not meet the actual detection efficiency, this study innovatively integrates the two methods to improve the detection accuracy of the mode. Meanwhile, the study also introduces PCA algorithm to identify the specific identity of sanitation workers. In the actual detection of sanitation workers, the identification rate of two sanitation workers is high, and the similarity is 98.61%. This technology greatly reduces the false detection rate of actual detection and improves the detection accuracy.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140992718","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":"LSTM network optimization and task network construction based on heuristic algorithm","authors":"Zhongpeng Zhang, Guibao Wang","doi":"10.3233/jcm-237124","DOIUrl":"https://doi.org/10.3233/jcm-237124","url":null,"abstract":"This work aims to advance the security management of complex networks to better align with evolving societal needs. The work employs the Ant Colony Optimization algorithm in conjunction with Long Short-Term Memory neural networks to reconstruct and optimize task networks derived from time series data. Additionally, a trend-based noise smoothing scheme is introduced to mitigate data noise effectively. The approach entails a thorough analysis of historical data, followed by applying trend-based noise smoothing, rendering the processed data more scientifically robust. Subsequently, the network reconstruction problem for time series data originating from one-dimensional dynamic equations is addressed using an algorithm based on the principles of Stochastic Gradient Descent (SGD). This algorithm decomposes time series data into smaller samples and yields optimal learning outcomes in conjunction with an adaptive learning rate SGD approach. Experimental results corroborate the remarkable fidelity of the weight matrix reconstructed by this algorithm to the true weight matrix. Moreover, the algorithm exhibits efficient convergence with increasing data volume, manifesting shorter time requirements per iteration while ensuring the attainment of optimal solutions. When the sample size remains constant, the algorithm’s execution time is directly proportional to the square of the number of nodes. Conversely, as the sample size scales, the SGD algorithm capitalizes on the availability of more information, resulting in improved learning outcomes. Notably, when the noise standard deviation is 0.01, models predicated on SGD and the Least-Squares Method (LSM) demonstrate reduced errors compared to instances with a noise standard deviation of 0.1, highlighting the sensitivity of LSM to noise. The proposed methodology offers valuable insights for advancing research in complex network studies.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140991305","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":"Multi-time scale economic regulation model of virtual power plant considering multiple uncertainties of source, load and storag","authors":"Z. Dou, Chunyan Zhang, Chuanxu Duan, Xuan Wen, Chen Sun","doi":"10.3233/jcm-247299","DOIUrl":"https://doi.org/10.3233/jcm-247299","url":null,"abstract":"A novel multi-stage time scale economic dispatch scheme is proposed for virtual power plants, taking into account the uncertainties arising from the connection of distribution network sources. This research introduces specific scheduling schemes tailored to various time scales within distribution networks, including a fuzzy optimized day ahead scheduling scheme, an intra-day scheduling scheme combined with Deep Q Network, and an adaptive optimized real-time scheduling scheme. This plan mainly considers the impact of photovoltaic output and conducts scheduling one day in advance through fuzzy optimization. In the intraday scheduling, different strategies were adopted in the study. By combining with Deep Q Network, research on scheduling for intraday demand within the power system. The analysis is conducted through rigorous modeling. Experimental tests were conducted to evaluate the performance of the proposed schemes. The day ahead dispatching primarily considers the impact of photovoltaic output and calculates the cost associated with each link in the grid under three different meteorological conditions. In the intra-day scheduling, the total costs for Scenario 1, Scenario 2, and Scenario 3 are found to be 34,724.5 yuan, 36,296.5 yuan, and 33,275.8 yuan, respectively. Notably, strategies 1 and 2 demonstrate lower costs compared to the pre-day scheduling, with the exception of Scenario 3. In real-time scheduling, considering the matching between sources and sources, the matching rate between sources and sources can be maintained at over 95%, and the stability and cost of the power grid have significantly decreased. In summary, by proposing a multi-stage time scale economic scheduling scheme, this study fully considers the uncertainty of the power supply of the distribution network access, as well as the different needs of day, day and real-time scheduling, providing an effective solution for the power dispatching of virtual power plants and providing important technical support for the reliability and economy of the power system.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140990157","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}