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Application of wireless sensor network technology based on artificial intelligence in security monitoring system 基于人工智能的无线传感器网络技术在安防监控系统中的应用
Q3 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-01-01 DOI: 10.1515/comp-2022-0280
Yajuan Zhang, Ru Jing, Xiang Ji, Nan Hu
Abstract The safety monitoring system has been used to monitor and manage engineering safety operation. The application scope of the safety monitoring system is very wide. It has a wide range of applications in the fields of pipeline safety monitoring, electrical safety monitoring and household safety monitoring. This article studied the application process of the household safety monitoring system. Many home safety accidents are caused by inadequate monitoring of safety problems. Therefore, it is very important to establish a household safety monitoring system. Traditional home safety monitoring systems only rely on cameras for safety monitoring, and the traditional home safety monitoring system uses too few sensors. With the continuous development of wireless sensor network (WSN) technology, it is possible to build a sensor node network, but provides real-time information for home security monitoring to the greatest extent. This article compared the home safety monitoring system based on the WSN technology of artificial intelligence (AI) with the traditional home safety monitoring system. The experimental results showed that in the large-scale home environment, the average monitoring accuracy of the traditional home security monitoring system and the home security monitoring system based on the WSN technology of AI was 77.76 and 89.36%, respectively. In the small-scale home environment, the average monitoring accuracy of the traditional home safety monitoring system and the home safety monitoring system based on the WSN technology of AI were 87.63 and 94.43%, respectively. Monitoring accuracy refers to the accuracy of the household safety monitoring system in detecting safety issues. Therefore, the application of the WSN technology based on artificial intelligence to the home safety monitoring system can effectively improve the accuracy of home safety monitoring.
摘要安全监控系统已被用于对工程安全运行进行监控和管理。安全监控系统的应用范围非常广泛。在管道安全监控、电气安全监控、家居安全监控等领域有着广泛的应用。本文研究了家庭安全监控系统的应用过程。许多家庭安全事故是由于对安全问题监测不足造成的。因此,建立一个家庭安全监控系统是非常重要的。传统的家庭安全监控系统仅依靠摄像头进行安全监控,传统的家庭安全监控系统使用的传感器太少。随着无线传感器网络(WSN)技术的不断发展,构建传感器节点网络成为可能,为家庭安防监控提供最大程度的实时信息。本文将基于人工智能WSN技术的家庭安全监控系统与传统的家庭安全监控系统进行了比较。实验结果表明,在大规模家庭环境下,传统家庭安防监控系统和基于AI的WSN技术的家庭安防监控系统的平均监控准确率分别为77.76和89.36%。在小规模家庭环境下,传统家庭安全监控系统和基于AI的WSN技术的家庭安全监控系统的平均监控准确率分别为87.63和94.43%。监控精度是指家庭安全监控系统检测安全问题的准确性。因此,将基于人工智能的WSN技术应用到家庭安全监控系统中,可以有效地提高家庭安全监控的准确性。
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引用次数: 0
Data preprocessing impact on machine learning algorithm performance 数据预处理对机器学习算法性能的影响
IF 1.5 Q3 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-01-01 DOI: 10.1515/comp-2022-0278
A. Amato, V. Di Lecce
Abstract The popularity of artificial intelligence applications is on the rise, and they are producing better outcomes in numerous fields of research. However, the effectiveness of these applications relies heavily on the quantity and quality of data used. While the volume of data available has increased significantly in recent years, this does not always lead to better results, as the information content of the data is also important. This study aims to evaluate a new data preprocessing technique called semi-pivoted QR (SPQR) approximation for machine learning. This technique is designed for approximating sparse matrices and acts as a feature selection algorithm. To the best of our knowledge, it has not been previously applied to data preprocessing in machine learning algorithms. The study aims to evaluate the impact of SPQR on the performance of an unsupervised clustering algorithm and compare its results to those obtained using principal component analysis (PCA) as the preprocessing algorithm. The evaluation is conducted on various publicly available datasets. The findings suggest that the SPQR algorithm can produce outcomes comparable to those achieved using PCA without altering the original dataset.
摘要人工智能应用的普及率正在上升,并且在许多研究领域产生了更好的结果。然而,这些应用程序的有效性在很大程度上取决于所使用数据的数量和质量。虽然近年来可用的数据量显著增加,但这并不总是能带来更好的结果,因为数据的信息内容也很重要。本研究旨在评估一种用于机器学习的新的数据预处理技术,称为半枢轴QR(SPQR)近似。该技术是为近似稀疏矩阵而设计的,并充当特征选择算法。据我们所知,它以前从未应用于机器学习算法中的数据预处理。该研究旨在评估SPQR对无监督聚类算法性能的影响,并将其结果与使用主成分分析(PCA)作为预处理算法获得的结果进行比较。评估是在各种公开可用的数据集上进行的。研究结果表明,SPQR算法可以在不改变原始数据集的情况下产生与使用PCA实现的结果相当的结果。
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引用次数: 0
Analysis of research results of different aspects of network security and Internet of Things under the background of big data 分析大数据背景下网络安全和物联网不同方面的研究成果
IF 1.5 Q3 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-01-01 DOI: 10.1515/comp-2022-0277
Ying Lu, Xiang Wang, Taotao Xie, Tian Xie
Abstract With the continuous development of big data (BD) and Internet of Things (IoT) technology, research in the fields of network security and IoT is also deepening. Big data provides more data support for network security and the IoT, while also bringing more security risks. Therefore, how to ensure the security of big data, prevent network attacks, and improve the security and reliability of the IoT has become a major issue in the current field of network security and the IoT. This article aims to analyze the research results of network security and the IoT in the context of big data and explore how to ensure big data security and improve the security and reliability of the IoT from a multidimensional perspective. Therefore, this article proposes BD technology, that is, through information mining, to ensure network security from the perspective of controlling information flow. At the same time, this article also proposes an LED lightweight encryption algorithm in the IOT, which is used to achieve secure communication between ordinary nodes and gateway nodes, effectively solving the security issues of data distribution in the network, resisting virus attacks and man-in--in-the--the-middle attacks, and has higher security and efficiency. Both of these methods can effectively protect network security: one is to control data flow, and the other is to start with communication protocols. Finally, this article analyzed the adoption of network security protection measures by netizens and found that only 13% of netizens frequently take network security protection measures, while 35% of netizens never take network security protection measures. This is also one of the important reasons for the increasing number of current network security issues.
随着大数据和物联网技术的不断发展,网络安全和物联网领域的研究也在不断深入。大数据为网络安全和物联网提供了更多的数据支撑,同时也带来了更多的安全风险。因此,如何保障大数据的安全,防范网络攻击,提高物联网的安全性和可靠性,成为当前网络安全和物联网领域的一大课题。本文旨在分析大数据背景下网络安全和物联网的研究成果,从多维角度探讨如何保障大数据安全,提高物联网的安全可靠性。因此,本文提出了BD技术,即通过信息挖掘,从控制信息流的角度来保证网络安全。同时,本文还提出了一种IOT中的LED轻量级加密算法,用于实现普通节点与网关节点之间的安全通信,有效解决了网络中数据分布的安全问题,抵御病毒攻击和中间人攻击,具有更高的安全性和效率。这两种方法都能有效地保护网络安全:一是控制数据流,二是从通信协议入手。最后,本文分析了网民采取网络安全保护措施的情况,发现只有13%的网民经常采取网络安全保护措施,而35%的网民从不采取网络安全保护措施。这也是当前网络安全问题日益增多的重要原因之一。
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引用次数: 0
Simulation evaluation of underwater robot structure and control system based on ADAMS 基于ADAMS的水下机器人结构与控制系统仿真评估
IF 1.5 Q3 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-01-01 DOI: 10.1515/comp-2022-0269
Donglin Tang, Long Li
Abstract The twenty-first century is the century of marine resources. The ocean is a treasure of biological resources, energy, water resources and mineral resources, and it would gradually become the “second space” of mankind. In the next few years, it would be more and more relevant to human life. Many scholars have realized the importance of the ocean and began to vigorously develop and use the ocean. Underwater robot is a means for human beings to explore and develop the ocean, and it would be widely used in this field. The development and promotion of underwater vehicles are of great significance to resource development, economic development, and national security. With the increasing shortage of land resources, the development and utilization of marine resources have received increasing attention. The direct exploitation of marine resources by humans would have adverse effects, so the underwater robot technology has developed rapidly in recent years. However, at present, most underwater robots are driven by electric turbines. The underwater working environment requires that the underwater motor has good sealing performance, so its structure is complex and expensive, and it is rarely used in ordinary underwater operations. In recent years, intelligent robots have been used more and more, but because of the complexity and uncertainty of the underwater working environment, there are many uncertain factors. Therefore, it is very meaningful to carry out stability control for it. The research results showed that the displacement, stability, and other corresponding test curves of each component can be obtained by establishing a simple model with software and through ADAMS (Automatic Dynamic Analysis of Mechanical Systems) simulation analysis. This can simulate the movement of real objects in the real environment and find the existing problems, so as to provide a reference for the actual underwater robot design. In this way, the development cycle and production costs can be reduced. This article analyzed the structure and control system of the underwater vehicle based on ADAMS simulation. The results showed that the dynamic stability of the underwater vehicle based on ADAMS simulation analysis was improved by 4.67% compared with the underwater vehicle before optimization.
摘要二十一世纪是海洋资源的世纪。海洋是生物资源、能源、水资源和矿产资源的宝库,它将逐渐成为人类的“第二空间”。在接下来的几年里,它将越来越与人类生活相关。许多学者已经意识到海洋的重要性,并开始大力开发和利用海洋。水下机器人是人类探索和开发海洋的一种手段,将在这一领域得到广泛应用。水下航行器的开发和推广对资源开发、经济发展和国家安全具有重要意义。随着陆地资源日益短缺,海洋资源的开发利用越来越受到重视。人类直接开采海洋资源会产生不利影响,因此水下机器人技术近年来发展迅速。然而,目前,大多数水下机器人都是由电动涡轮机驱动的。水下工作环境要求水下电机具有良好的密封性能,因此其结构复杂、价格昂贵,在普通水下作业中很少使用。近年来,智能机器人的应用越来越多,但由于水下工作环境的复杂性和不确定性,存在许多不确定因素。研究结果表明,利用软件建立简单的模型,并通过ADAMS(Automatic Dynamic Analysis of Mechanical Systems)仿真分析,可以得到各部件的位移、稳定性等相应的试验曲线。这样可以模拟真实物体在真实环境中的运动,发现存在的问题,为实际的水下机器人设计提供参考。通过这种方式,可以减少开发周期和生产成本。本文基于ADAMS仿真,对水下机器人的结构和控制系统进行了分析。结果表明,基于ADAMS仿真分析的水下机器人动力学稳定性比优化前提高了4.67%。
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引用次数: 0
Exploration on the application of electronic information technology in signal processing based on big data 电子信息技术在基于大数据的信号处理中的应用探索
IF 1.5 Q3 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-01-01 DOI: 10.1515/comp-2022-0272
Li Liu
Abstract Mobile phones are the most commonly used electronic devices in people’s daily life. The image, voice, and other information in these devices need to be processed through signal transmission. The role of signal processing is to process the acquired information in a certain way to get the final result. In order to ensure that the whole processing program can work normally, it is necessary to implement good control to achieve the desired effect. However, with the continuous progress and development of science and technology, its requirements are becoming increasingly strict. The traditional signal processing method is unreliable, has poor real time, and has error-prone characteristics, which can no longer meet the accuracy requirements of current information acquisition equipment. Therefore, people begin to study more complex and precise information processing methods and apply these algorithms to various advanced electronic devices to achieve better results. From the perspective of big data, electronic information technology is generated and developed based on massive data processing. It not only has a strong storage function but also has strong computing power and a wide range of application scenarios. It has strong applicability in real life. In this article, the signal to be processed was divided into several wavelet components in different frequency ranges by empirical mode decomposition technology, and then the signal was denoised by combining three wavelet denoising methods to obtain noise data with good signal-to-noise ratio and high classification accuracy. Finally, the corresponding feature information was extracted according to the signal-receiving model to improve the system recognition rate. This article compared the traditional signal processing methods with the signal processing approaches from the perspective of electronic information technology. The results showed that the processing method had a high computing speed and could better solve the problem of detection performance degradation caused by interference. User satisfaction had also increased by 2.87%, which showed that signal processing based on big data and information processing technology had broad application prospects in communication systems. The core of open computer science is to build a unified, efficient, and scalable computing platform based on massive data processing and use signal processing and computer technology to manage and optimize the scheduling of information resources to better meet various business needs.
手机是人们日常生活中最常用的电子设备。这些设备中的图像、语音等信息都需要通过信号传输进行处理。信号处理的作用就是对采集到的信息进行一定的处理,从而得到最终的结果。为了保证整个加工程序能够正常工作,必须实施良好的控制,以达到预期的效果。然而,随着科学技术的不断进步和发展,对其要求也越来越严格。传统的信号处理方法不可靠,实时性差,容易出错,已经不能满足当前信息采集设备的精度要求。因此,人们开始研究更复杂和精确的信息处理方法,并将这些算法应用到各种先进的电子设备中,以达到更好的效果。从大数据的角度来看,电子信息技术是在海量数据处理的基础上产生和发展起来的。它不仅具有强大的存储功能,而且具有强大的计算能力和广泛的应用场景。在现实生活中具有很强的适用性。本文通过经验模态分解技术将待处理信号分解成不同频率范围内的几个小波分量,然后结合三种小波去噪方法对信号进行去噪,得到信噪比好、分类精度高的噪声数据。最后,根据信号接收模型提取相应的特征信息,提高系统识别率。本文将传统的信号处理方法与电子信息技术视角下的信号处理方法进行了比较。结果表明,该处理方法计算速度快,能较好地解决干扰引起的检测性能下降问题。用户满意度提高2.87%,表明基于大数据和信息处理技术的信号处理在通信系统中具有广阔的应用前景。开放计算机科学的核心是构建基于海量数据处理的统一、高效、可扩展的计算平台,利用信号处理和计算机技术对信息资源进行管理和优化调度,更好地满足各种业务需求。
{"title":"Exploration on the application of electronic information technology in signal processing based on big data","authors":"Li Liu","doi":"10.1515/comp-2022-0272","DOIUrl":"https://doi.org/10.1515/comp-2022-0272","url":null,"abstract":"Abstract Mobile phones are the most commonly used electronic devices in people’s daily life. The image, voice, and other information in these devices need to be processed through signal transmission. The role of signal processing is to process the acquired information in a certain way to get the final result. In order to ensure that the whole processing program can work normally, it is necessary to implement good control to achieve the desired effect. However, with the continuous progress and development of science and technology, its requirements are becoming increasingly strict. The traditional signal processing method is unreliable, has poor real time, and has error-prone characteristics, which can no longer meet the accuracy requirements of current information acquisition equipment. Therefore, people begin to study more complex and precise information processing methods and apply these algorithms to various advanced electronic devices to achieve better results. From the perspective of big data, electronic information technology is generated and developed based on massive data processing. It not only has a strong storage function but also has strong computing power and a wide range of application scenarios. It has strong applicability in real life. In this article, the signal to be processed was divided into several wavelet components in different frequency ranges by empirical mode decomposition technology, and then the signal was denoised by combining three wavelet denoising methods to obtain noise data with good signal-to-noise ratio and high classification accuracy. Finally, the corresponding feature information was extracted according to the signal-receiving model to improve the system recognition rate. This article compared the traditional signal processing methods with the signal processing approaches from the perspective of electronic information technology. The results showed that the processing method had a high computing speed and could better solve the problem of detection performance degradation caused by interference. User satisfaction had also increased by 2.87%, which showed that signal processing based on big data and information processing technology had broad application prospects in communication systems. The core of open computer science is to build a unified, efficient, and scalable computing platform based on massive data processing and use signal processing and computer technology to manage and optimize the scheduling of information resources to better meet various business needs.","PeriodicalId":43014,"journal":{"name":"Open Computer Science","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43520273","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}
引用次数: 0
Application of fingerprint image fuzzy edge recognition algorithm in criminal technology 指纹图像模糊边缘识别算法在刑事技术中的应用
IF 1.5 Q3 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-01-01 DOI: 10.1515/comp-2022-0263
Xinhua Lv
Abstract In the context of the rapid development of science and technology and the modernization of the legal system, criminal activities are becoming more and more intelligent and technological, which also puts forward higher requirements for criminal technology. The current criminal technology equipment is relatively backward, and the technical level is not high enough, resulting in a low utilization rate of trace material evidence extraction, which directly affects the role of criminal technology in the investigation and solving of cases. In recent years, fingerprint recognition algorithms and image edge detection algorithms have been widely used in various fields. This work studied the application of fingerprint image fuzzy edge recognition algorithm in criminal technology, in order to improve the level of criminal technology and the utilization rate of physical evidence extraction. The criminal technology system is upgraded and optimized by combining fingerprint recognition algorithm and image edge detection algorithm. And fuzzy theory is added to ensure the feasibility of the research. The experimental results show that the fuzzy edge recognition algorithm of fingerprint image can improve the level of criminal technology and the utilization rate of material evidence to a certain extent. The utilization rate is increased by 7.04%. The recognition accuracy of the fuzzy recognition method is also 13.2% higher than that of the methods in the literature.
摘要在科学技术快速发展和法制现代化的背景下,犯罪活动越来越智能化、技术化,这也对犯罪技术提出了更高的要求。目前刑事技术装备相对落后,技术水平不够高,导致痕迹物证提取利用率低,直接影响了刑事技术在侦查破案中的作用。近年来,指纹识别算法和图像边缘检测算法在各个领域得到了广泛的应用。本文研究了指纹图像模糊边缘识别算法在刑事技术中的应用,以提高刑事技术水平和物证提取的利用率。将指纹识别算法和图像边缘检测算法相结合,对犯罪技术系统进行升级优化。并加入模糊理论以保证研究的可行性。实验结果表明,指纹图像的模糊边缘识别算法可以在一定程度上提高犯罪技术水平和物证利用率。利用率提高了7.04%,模糊识别方法的识别准确率也比文献中的方法提高了13.2%。
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引用次数: 0
Digital forensics analysis based on cybercrime and the study of the rule of law in space governance 基于网络犯罪的数字取证分析与空间治理法治研究
IF 1.5 Q3 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-01-01 DOI: 10.1515/comp-2022-0266
Cheng Chen, Bin Dong
Abstract With the rapid development of social informatization, the Internet has become an important channel for global information dissemination. The wireless network space and the real space are intertwined and have a significant impact on the political, economic, and cultural aspects of international society. For example, it can effectively solve the problem of information exchange between cities, regions, and countries. Wireless network crime and wireless network space security issues involve the development of information technology in various countries and, more importantly, involve all aspects of national security. In the age of science and technology, the current situation of cybercrime can be expressed by data as follows: the online crime rate is high. According to relevant statistics, nearly 5 million Internet users are involved in various cases every year due to the use of the Internet. This article starts with the digital forensics of wireless network crime and wireless network security management systems and discusses the composition, characteristics, existing problems, and future development directions of the current wireless network security management system. By comparing the wireless network security laws of China and the United States, using the latent Dirichlet allocation (LDA)-Gibbs model and the k-means algorithm to analyze the data, this article provides guidance for future research on wireless network space governance. The combination of digital forensics analysis based on cybercrime and space governance can improve the level of public security work. At present, the world has made some progress in cyberspace, but it still faces severe challenges. In the face of new situations and new measures, it is necessary to strengthen legislation, improve relevant systems, and strengthen supervision capacity. At the same time, it is necessary to establish perfect technical means and safeguards to ensure that this goal can be achieved.
摘要随着社会信息化的快速发展,互联网已成为全球信息传播的重要渠道。无线网络空间和现实空间交织在一起,对国际社会的政治、经济和文化方面产生了重大影响。例如,它可以有效地解决城市、地区和国家之间的信息交换问题。无线网络犯罪和无线网络空间安全问题涉及各国信息技术的发展,更重要的是涉及国家安全的方方面面。在科技时代,网络犯罪的现状可以用以下数据来表示:网络犯罪率高。据相关统计,每年有近500万网民因使用互联网而卷入各种案件。本文从无线网络犯罪的数字取证和无线网络安全管理系统入手,讨论了当前无线网络安全系统的组成、特点、存在的问题以及未来的发展方向。通过比较中美两国的无线网络安全法律,使用潜在的狄利克雷分配(LDA)-吉布斯模型和k-means算法对数据进行分析,为未来无线网络空间治理的研究提供指导。将基于网络犯罪的数字取证分析与空间治理相结合,可以提高公共安全工作水平。当前,世界在网络空间方面取得了一些进展,但仍面临严峻挑战。面对新情况新举措,要加强立法,完善相关制度,强化监管能力。同时,有必要建立完善的技术手段和保障措施,以确保实现这一目标。
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引用次数: 0
Dynamic system allocation and application of cloud computing virtual resources based on system architecture 基于系统架构的云计算虚拟资源动态系统分配与应用
IF 1.5 Q3 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-01-01 DOI: 10.1515/comp-2022-0259
Chunhua Lin, Longzi Li, Yuanyi Chen
Abstract Cloud computing is a system development method based on dynamic sharing, which allows a large number of systems to be combined to provide services. The purpose of this work is to study the design and implementation of a dynamic virtual resource allocation system in cloud computing, whose architecture allows load balancing between virtual resource pools and reduces resource wastage. Using the cluster network topology, the resource usage of the dynamic system cluster can be monitored in real time, and the total cluster load can be automatically determined based on the monitoring data. The experiment is divided into two parts. Performance testing and scenario testing. Performance tests examine execution time, processor, and memory performance. In the scenario test, JMeter is used to simulate the occurrence of a large number of concurrent application access requests, the loss rate, and processing time of these requests on the cloud platform, and load balancing tests are performed. The test results show that the system running time is about 22–27 ms, the CPU utilization is about 90–95%, and the RAM is about 3.5 ms. The results show that cloud technology can improve resource scheduling of large tasks and optimize resource load balance.
云计算是一种基于动态共享的系统开发方法,它允许大量的系统组合起来提供服务。本工作的目的是研究云计算中动态虚拟资源分配系统的设计与实现,该系统的架构允许虚拟资源池之间的负载均衡,减少资源浪费。通过集群网络拓扑,可以实时监控动态系统集群的资源使用情况,并根据监控数据自动确定集群的总负载。实验分为两个部分。性能测试和场景测试。性能测试检查执行时间、处理器和内存性能。在场景测试中,使用JMeter模拟大量并发应用访问请求在云平台上的发生情况、丢失率和处理时间,并进行负载均衡测试。测试结果表明,系统运行时间约为22-27 ms, CPU利用率约为90-95%,RAM约为3.5 ms。结果表明,云技术可以改善大型任务的资源调度,优化资源负载平衡。
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引用次数: 0
Visual inspection intelligent robot technology for large infusion industry 面向大型输液行业的视觉检测智能机器人技术
IF 1.5 Q3 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-01-01 DOI: 10.1515/comp-2022-0262
Qilang Liang, Bangshun Luo
Abstract The application of intelligent technology has realized the transformation of people’s production and lifestyle, and it has also promoted the development of the field of medicine. At present, the intensity of intelligence in the field of medicine is increasing. By using its cash methods and techniques combined with the mechanical field, this article proposes to use visual inspection technology to understand the fusion of the medical field and the mechanical field. It is helpful to analyze and solve objective problems such as low efficiency in current infusion and insufficient rigidity of large infusion plastic bottles. Drawing on the principles and laws of deep learning algorithms and neural networks, the technical research of intelligent robots for visual inspection is carried out to realize the intelligence of infusion robots. In the research accuracy of detection, the detection rate of standard particles higher than 85 µM has reached almost 100%, and the rate of 50 µM standard particles is lower and unstable. The detection effect of the control light bulb control was different, and the detection rate was between 50 and 80%, which was obviously worse than the detection robot effect. Therefore, the current research on the technology of intelligent robots is very important.
摘要智能技术的应用实现了人们生产生活方式的转变,也促进了医学领域的发展。目前,医学领域的智力强度正在提高。本文将其现金支付方法和技术与机械领域相结合,提出利用视觉检测技术来理解医学领域与机械领域的融合。有助于分析和解决目前输液效率低、大型输液塑料瓶刚性不足等客观问题。借鉴深度学习算法和神经网络的原理和规律,对用于视觉检测的智能机器人进行技术研究,以实现输液机器人的智能化。在研究检测精度时,标准颗粒物的检测率高于85 µM几乎达到100% µM标准颗粒较低且不稳定。控制灯泡控制的检测效果不同,检测率在50-80%之间,明显比检测机器人的效果差。因此,当前对智能机器人技术的研究具有十分重要的意义。
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引用次数: 1
Blockchain localization cloud computing big data application evaluation method 区块链本地化云计算大数据应用评估方法
Q3 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-01-01 DOI: 10.1515/comp-2023-0281
Lin Xu
Abstract Blockchain technology is a widely used emerging technology. It can integrate cloud computing technology and big data to form a distributed cloud computing system, providing efficient services for local enterprises and governments. In addition, local cloud computing is also widely used, and there are many big data in these applications. Blockchain and local cloud computing technology offers safe and reliable information exchange for data exchange and provides a practical method for analyzing big data. This article aims to study how to analyze and research the application analysis method of big data based on blockchain technology and improve the classical apriori algorithm (CAA). This article compares and analyzes the performance of CAA and improved apriori algorithm (IAA) in big data applications. When the number of key words in the query are 20 and 100, the result search time of the CAA are 1.08 and 9.24 s, respectively, and the IAA are 0.76 and 7.58 s, respectively. The result search cost of the CAA is 12.43 and 91.55 kB, respectively, and the IAA is 5.05 and 63.72 kB, respectively. It is not difficult to see that applying the IAA to the blockchain-based government data-sharing scheme had relatively excellent performance and was worth further promotion and application.
区块链技术是一项应用广泛的新兴技术。它可以将云计算技术与大数据相结合,形成分布式云计算系统,为当地企业和政府提供高效的服务。此外,本地云计算也被广泛使用,在这些应用中有很多大数据。区块链和本地云计算技术为数据交换提供了安全可靠的信息交换,为大数据分析提供了实用的方法。本文旨在研究如何分析和研究基于区块链技术的大数据应用分析方法,改进经典apriori算法(CAA)。本文对比分析了CAA和改进apriori算法(IAA)在大数据应用中的性能。当查询的关键字个数为20和100时,CAA的结果搜索时间分别为1.08和9.24 s, IAA的结果搜索时间分别为0.76和7.58 s。CAA和IAA分别为12.43和91.55 kB和5.05和63.72 kB。不难看出,将IAA应用于基于区块链的政府数据共享方案,具有较为优异的表现,值得进一步推广应用。
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