The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the d...The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device itself.Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features.This paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in homes.We have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT devices.Our system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing devices.We have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache server.The feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time settings.It is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation systems.Additionally,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber threats.The trial results support the proposed system and demonstrate its potential for use in everyday life.展开更多
Artificial intelligence(AI)and deep learning are becoming increasingly powerful tools in diagnostic and radiographic medicine.Deep learning has already been utilized for automated detection of pneumonia from chest rad...Artificial intelligence(AI)and deep learning are becoming increasingly powerful tools in diagnostic and radiographic medicine.Deep learning has already been utilized for automated detection of pneumonia from chest radiographs,diabetic retinopathy,breast cancer,skin carcinoma classification,and metastatic lymphadenopathy detection,with diagnostic reliability akin to medical experts.In the World Journal of Orthopedics article,the authors apply an automated and AIassisted technique to determine the hallux valgus angle(HVA)for assessing HV foot deformity.With the U-net neural network,the authors constructed an algorithm for pattern recognition of HV foot deformity from anteroposterior highresolution radiographs.The performance of the deep learning algorithm was compared to expert clinician manual performance and assessed alongside clinician-clinician variability.The authors found that the AI tool was sufficient in assessing HVA and proposed the system as an instrument to augment clinical efficiency.Though further sophistication is needed to establish automated algorithms for more complicated foot pathologies,this work adds to the growing evidence supporting AI as a powerful diagnostic tool.展开更多
This paper analyzes how artificial intelligence (AI) automation can improve warehouse management compared to emerging technologies like drone usage. Specifically, we evaluate AI’s impact on crucial warehouse function...This paper analyzes how artificial intelligence (AI) automation can improve warehouse management compared to emerging technologies like drone usage. Specifically, we evaluate AI’s impact on crucial warehouse functions—inventory tracking, order fulfillment, and logistics efficiency. Our findings indicate AI automation enables real-time inventory visibility, optimized picking routes, and dynamic delivery scheduling, which drones cannot match. AI better leverages data insights for intelligent decision-making across warehouse operations, supporting improved productivity and lower operating costs.展开更多
The invention concept of Robotic Process Automation (RPA) has emerged as a transformative technology that has revolved the local business processes by programming repetitive task and efficiency adjusting the operation...The invention concept of Robotic Process Automation (RPA) has emerged as a transformative technology that has revolved the local business processes by programming repetitive task and efficiency adjusting the operations. This research had focused on developing the RPA environment and its future features in order to elaborate on the projected policies based on its comprehensive experiences. The current and previous situations of industry are looking for IT solutions to fully scale their company Improve business flexibility, improve customer satisfaction, improve productivity, accuracy and reduce costs, quick scalability in RPA has currently appeared as an advance technology with exceptional performance. It emphasizes future trends and foresees the evolution of RPA by integrating artificial intelligence, learning of machine and cognitive automation into RPA frameworks. Moreover, it has analyzed the technical constraints, including the scalability, security issues and interoperability, while investigating regulatory and ethical considerations that are so important to the ethical utilization of RPA. By providing a comprehensive analysis of RPA with new future trends in this study, researcher’s ambitions to provide valuable insights the benefits of it on industrial performances from the gap observed so as to guide the strategic decision and future implementation of the RPA.展开更多
This article explores the topic of fault diagnosis and maintenance strategies for instrument automation control systems,analyzing them through specific cases.The aim of this research is to improve the stability and re...This article explores the topic of fault diagnosis and maintenance strategies for instrument automation control systems,analyzing them through specific cases.The aim of this research is to improve the stability and reliability of the system by conducting a thorough investigation of faults and maintenance in instrument automation control systems.By doing so,this research hopes to provide a strong guarantee for the smooth progress of industrial production.展开更多
Under the background of the new era,higher requirements are put forward for colleges and universities to carry out teaching reform.Teachers of electrical automation control courses should update their teaching ideas r...Under the background of the new era,higher requirements are put forward for colleges and universities to carry out teaching reform.Teachers of electrical automation control courses should update their teaching ideas regularly,innovate teaching methods,and take novel and effective measures to carry out related work.Because electrical automation control courses tend to be technology-oriented,teachers can help students consolidate basic knowledge.They should also focus on developing practical skills so students can easily adapt to future job positions.However,there are many problems in the actual teaching process,which hampers the improvement of the teaching quality to a certain extent.In view of this,this paper presents an in-depth exploration based on theories and practical experiences.It starts with an analysis of the current teaching status of electrical automation control courses in colleges and universities,followed by suggestions to improve them based on their characteristics and students’needs.展开更多
Briefing: This perspective introduces the concept and framework of knowledge factories with knowledge machines for knowledge workers to achieve knowledge automation for Industry 5.0 and intelligent industries.Introduc...Briefing: This perspective introduces the concept and framework of knowledge factories with knowledge machines for knowledge workers to achieve knowledge automation for Industry 5.0 and intelligent industries.Introduction The big hit of Chat GPT makes it imperative to contemplate the practical applications of big or foundation models [1]-[5]. However, as compared to conventional models, there is now an increasingly urgent need for foundation intelligence of foundation models for real-world industrial applications.展开更多
This article introduces a novel approach for tricone bit wear condition monitoring and failure prediction for surface mining applications.A successful bit health monitoring system is essential to achieve fully autonom...This article introduces a novel approach for tricone bit wear condition monitoring and failure prediction for surface mining applications.A successful bit health monitoring system is essential to achieve fully autonomous blasthole drilling.In this research in-situ vibration signals were analyzed in timefrequency domain and signals trend during tricone bit life span were investigated and introduced to support the development of artificial intelligence(AI)models.In addition to the signal statistical features,wavelet packet energy distribution proved to be a powerful indicator for bit wear assessment.Backpropagation artificial neural network(ANN)models were designed,trained and evaluated for bit state classification.Finally,an ANN architecture and feature vector were introduced to classify the bit condition and predict the bit failure.展开更多
This research paper explores the significance of the “A360 Bot Framework” in Automation 360 (A360) platform. A360 is Automation Anywhere’s cloud-based automation platform designed to make business processes more ef...This research paper explores the significance of the “A360 Bot Framework” in Automation 360 (A360) platform. A360 is Automation Anywhere’s cloud-based automation platform designed to make business processes more efficient. It’s known for its user-friendly interface, which allows both technical and non-technical users to use it effectively. Automation 360 is versatile, offering a range of tools to automate tasks, manage complex workflows, and integrate various applications. It empowers users to create customized solutions for their specific needs. Being cloud-based it ensures scalability, security, and real-time updates, making it a top choice in the fast-paced digital world. As demand for A360 rises, having a structured way to develop bots becomes crucial. The paper introduces the “A360 Bot Framework” as a guiding approach for bot developments. This framework ensures consistency and scalability, especially when working with both professional developers and non-technical users. It outlines key elements like setting up work folders, managing logs, dealing with errors, and ensuring secure bot execution. Ultimately, the “A360 Bot Framework” is presented as a foundational structure that enhances consistency, resiliency, and development efficiency. By following predefined practices and templates, bot developers can mitigate risks and streamline debugging processes. This framework accelerates the bot development lifecycle, allowing developers to focus on specific functionalities and value-added features. The research paper aims to provide insights into the benefits of adopting the A360 Bot Framework and its potential to revolutionize A360 bot development practices, leading to more efficient and effective automation solutions.展开更多
BACKGROUND:To evaluate whether a simplified self-instruction card can help potential rescue providers use automated external defibrillators(AEDs)more accurately and quickly.METHODS:From June 1,2018,to November 30,2019...BACKGROUND:To evaluate whether a simplified self-instruction card can help potential rescue providers use automated external defibrillators(AEDs)more accurately and quickly.METHODS:From June 1,2018,to November 30,2019,a prospective longitudinal randomized controlled simulation study was conducted among 165 laypeople(18–65 years old)without prior AED training.A self-instruction card was designed to illuminate key AED operation procedures.Subjects were randomly divided into the card(n=83)and control(n=82)groups with age stratification.They were then individually evaluated in the same simulated scenario to use AED with(card group)or without the self-instruction card(control group)at baseline,posttraining,and at the 3-month follow-up.RESULTS:At baseline,the card group reached a significantly higher proportion of successful defibrillation(31.1%vs.15.9%,P=0.03),fully baring the chest(88.9%vs.63.4%,P<0.001),correct electrode placement(32.5%vs.17.1%,P=0.03),and resuming cardiopulmonary resuscitation(CPR)(72.3%vs.9.8%,P<0.001).At post-training and follow-up,there were no significant differences in key behaviors,except for resuming CPR.Time to shock and time to resume CPR were shorter in the card group,while time to power-on AED was not different in each phase of tests.In the 55–65 years group,the card group achieved more skill improvements over the control group compared to the other age groups.CONCLUSION:The self-instruction card could serve as a direction for first-time AED users and as a reminder for trained subjects.This could be a practical,cost-effective way to improve the AED skills of potential rescue providers among different age groups,including seniors.展开更多
Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable...Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable measurements.However,such professional instrumentation is notably expensive while remote sensing from a number of stations is paramount.This imposes challenges on the large-scale weather station deployment for broad monitoring from large observation networks such as in Cemaden—The Brazilian National Center for Monitoring and Early Warning of Natural Disasters.In this context,in this paper,we propose a Low-Cost Automatic Weather Station(LCAWS)system developed from Commercial Off-The-Shelf(COTS)and open-source Internet of Things(IoT)technologies,which provides measurements as reliable as a reference PWS for natural disaster monitoring.When being automatic,LCAWS is a stand-alone photovoltaic system connected wirelessly to the Internet in order to provide real-time reliable end-to-end weather measurements.To achieve data reliability,we propose an intelligent sensor calibration method to correct measures.From a 30-day uninterrupted observation with sampling in minute resolution,we show that the calibrated LCAWS sensors have no statistically significant differences from the PWS measurements.As such,LCAWS has opened opportunities for reducing maintenance costs in Cemaden's observational network.展开更多
The recent trends in Industry 4.0 and Internet of Things have encour-aged many factory managers to improve inspection processes to achieve automa-tion and high detection rates.However,the corresponding cost results of...The recent trends in Industry 4.0 and Internet of Things have encour-aged many factory managers to improve inspection processes to achieve automa-tion and high detection rates.However,the corresponding cost results of sample tests are still used for quality control.A low-cost automated optical inspection system that can be integrated with production lines to fully inspect products with-out adjustments is introduced herein.The corresponding mechanism design enables each product to maintain afixed position and orientation during inspec-tion to accelerate the inspection process.The proposed system combines image recognition and deep learning to measure the dimensions of the thread and iden-tify its defects within 20 s,which is lower than the production-line productivity per 30 s.In addition,the system is designed to be used for monitoring production lines and equipment status.The dimensional tolerance of the proposed system reaches 0.012 mm,and a 100%accuracy is achieved in terms of the defect reso-lution.In addition,an attention-based visualization approach is utilized to verify the rationale for the use of the convolutional neural network model and identify the location of thread defects.展开更多
In the process of food testing,human operation is an important variable affecting the experimental results.In order to reasonably avoid the influence of human subjective operation behavior on the accuracy of detection...In the process of food testing,human operation is an important variable affecting the experimental results.In order to reasonably avoid the influence of human subjective operation behavior on the accuracy of detection results,the laboratory information management system was used as the information platform to design a high-throughput laboratory automation pre-treatment system based on the deep integration of mechanical principles,visual analysis,high-speed conduction,intelligent storage and other technical systems.The experimental results showed that the system could shorten the sample circulation cycle,effectively improve the laboratory biosafety,and meet the requirements of high-throughput processing of samples.展开更多
Objective: This paper takes the example of a Panax notoginseng extraction workshop and designs an automated production workshop with advanced domestic capabilities. Methods: 1) Based on the small-scale Panax notoginse...Objective: This paper takes the example of a Panax notoginseng extraction workshop and designs an automated production workshop with advanced domestic capabilities. Methods: 1) Based on the small-scale Panax notoginseng extraction process, the feasibility of the workshop production process is demonstrated. 2) The workshop process design for Panax Notoginseng saponin extraction is completed, including production organization plans and the selection of key equipment. 3) For the Panax notoginseng extraction workshop process, an automated production control system is designed. Conclusion: Through optimized design of the production process and automation system, continuous and automated production of traditional Chinese medicine extraction is achieved, leading to improvements in drug quality and production efficiency.展开更多
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2024R333)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device itself.Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features.This paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in homes.We have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT devices.Our system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing devices.We have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache server.The feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time settings.It is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation systems.Additionally,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber threats.The trial results support the proposed system and demonstrate its potential for use in everyday life.
文摘Artificial intelligence(AI)and deep learning are becoming increasingly powerful tools in diagnostic and radiographic medicine.Deep learning has already been utilized for automated detection of pneumonia from chest radiographs,diabetic retinopathy,breast cancer,skin carcinoma classification,and metastatic lymphadenopathy detection,with diagnostic reliability akin to medical experts.In the World Journal of Orthopedics article,the authors apply an automated and AIassisted technique to determine the hallux valgus angle(HVA)for assessing HV foot deformity.With the U-net neural network,the authors constructed an algorithm for pattern recognition of HV foot deformity from anteroposterior highresolution radiographs.The performance of the deep learning algorithm was compared to expert clinician manual performance and assessed alongside clinician-clinician variability.The authors found that the AI tool was sufficient in assessing HVA and proposed the system as an instrument to augment clinical efficiency.Though further sophistication is needed to establish automated algorithms for more complicated foot pathologies,this work adds to the growing evidence supporting AI as a powerful diagnostic tool.
文摘This paper analyzes how artificial intelligence (AI) automation can improve warehouse management compared to emerging technologies like drone usage. Specifically, we evaluate AI’s impact on crucial warehouse functions—inventory tracking, order fulfillment, and logistics efficiency. Our findings indicate AI automation enables real-time inventory visibility, optimized picking routes, and dynamic delivery scheduling, which drones cannot match. AI better leverages data insights for intelligent decision-making across warehouse operations, supporting improved productivity and lower operating costs.
文摘The invention concept of Robotic Process Automation (RPA) has emerged as a transformative technology that has revolved the local business processes by programming repetitive task and efficiency adjusting the operations. This research had focused on developing the RPA environment and its future features in order to elaborate on the projected policies based on its comprehensive experiences. The current and previous situations of industry are looking for IT solutions to fully scale their company Improve business flexibility, improve customer satisfaction, improve productivity, accuracy and reduce costs, quick scalability in RPA has currently appeared as an advance technology with exceptional performance. It emphasizes future trends and foresees the evolution of RPA by integrating artificial intelligence, learning of machine and cognitive automation into RPA frameworks. Moreover, it has analyzed the technical constraints, including the scalability, security issues and interoperability, while investigating regulatory and ethical considerations that are so important to the ethical utilization of RPA. By providing a comprehensive analysis of RPA with new future trends in this study, researcher’s ambitions to provide valuable insights the benefits of it on industrial performances from the gap observed so as to guide the strategic decision and future implementation of the RPA.
文摘This article explores the topic of fault diagnosis and maintenance strategies for instrument automation control systems,analyzing them through specific cases.The aim of this research is to improve the stability and reliability of the system by conducting a thorough investigation of faults and maintenance in instrument automation control systems.By doing so,this research hopes to provide a strong guarantee for the smooth progress of industrial production.
文摘Under the background of the new era,higher requirements are put forward for colleges and universities to carry out teaching reform.Teachers of electrical automation control courses should update their teaching ideas regularly,innovate teaching methods,and take novel and effective measures to carry out related work.Because electrical automation control courses tend to be technology-oriented,teachers can help students consolidate basic knowledge.They should also focus on developing practical skills so students can easily adapt to future job positions.However,there are many problems in the actual teaching process,which hampers the improvement of the teaching quality to a certain extent.In view of this,this paper presents an in-depth exploration based on theories and practical experiences.It starts with an analysis of the current teaching status of electrical automation control courses in colleges and universities,followed by suggestions to improve them based on their characteristics and students’needs.
基金partially supported by the Science and Technology Development Fund of Macao SAR (0050/2020/A1)。
文摘Briefing: This perspective introduces the concept and framework of knowledge factories with knowledge machines for knowledge workers to achieve knowledge automation for Industry 5.0 and intelligent industries.Introduction The big hit of Chat GPT makes it imperative to contemplate the practical applications of big or foundation models [1]-[5]. However, as compared to conventional models, there is now an increasingly urgent need for foundation intelligence of foundation models for real-world industrial applications.
基金The authors appreciate generous supports from Canada Natural Sciences and Engineering Research Council,McGill University Engine Centre as well as Faculty of Engineering.
文摘This article introduces a novel approach for tricone bit wear condition monitoring and failure prediction for surface mining applications.A successful bit health monitoring system is essential to achieve fully autonomous blasthole drilling.In this research in-situ vibration signals were analyzed in timefrequency domain and signals trend during tricone bit life span were investigated and introduced to support the development of artificial intelligence(AI)models.In addition to the signal statistical features,wavelet packet energy distribution proved to be a powerful indicator for bit wear assessment.Backpropagation artificial neural network(ANN)models were designed,trained and evaluated for bit state classification.Finally,an ANN architecture and feature vector were introduced to classify the bit condition and predict the bit failure.
文摘This research paper explores the significance of the “A360 Bot Framework” in Automation 360 (A360) platform. A360 is Automation Anywhere’s cloud-based automation platform designed to make business processes more efficient. It’s known for its user-friendly interface, which allows both technical and non-technical users to use it effectively. Automation 360 is versatile, offering a range of tools to automate tasks, manage complex workflows, and integrate various applications. It empowers users to create customized solutions for their specific needs. Being cloud-based it ensures scalability, security, and real-time updates, making it a top choice in the fast-paced digital world. As demand for A360 rises, having a structured way to develop bots becomes crucial. The paper introduces the “A360 Bot Framework” as a guiding approach for bot developments. This framework ensures consistency and scalability, especially when working with both professional developers and non-technical users. It outlines key elements like setting up work folders, managing logs, dealing with errors, and ensuring secure bot execution. Ultimately, the “A360 Bot Framework” is presented as a foundational structure that enhances consistency, resiliency, and development efficiency. By following predefined practices and templates, bot developers can mitigate risks and streamline debugging processes. This framework accelerates the bot development lifecycle, allowing developers to focus on specific functionalities and value-added features. The research paper aims to provide insights into the benefits of adopting the A360 Bot Framework and its potential to revolutionize A360 bot development practices, leading to more efficient and effective automation solutions.
基金National Natural Science Foundation of China(No.72074144)Sanming Project of Medicine in Shenzhen(No.SZSM201911005)+1 种基金Innovative Research Team of High-level Local Universities in Shanghai(No.SHSMU-ZDCX20212801)Laerdal Foundation(No.2022-0133).
文摘BACKGROUND:To evaluate whether a simplified self-instruction card can help potential rescue providers use automated external defibrillators(AEDs)more accurately and quickly.METHODS:From June 1,2018,to November 30,2019,a prospective longitudinal randomized controlled simulation study was conducted among 165 laypeople(18–65 years old)without prior AED training.A self-instruction card was designed to illuminate key AED operation procedures.Subjects were randomly divided into the card(n=83)and control(n=82)groups with age stratification.They were then individually evaluated in the same simulated scenario to use AED with(card group)or without the self-instruction card(control group)at baseline,posttraining,and at the 3-month follow-up.RESULTS:At baseline,the card group reached a significantly higher proportion of successful defibrillation(31.1%vs.15.9%,P=0.03),fully baring the chest(88.9%vs.63.4%,P<0.001),correct electrode placement(32.5%vs.17.1%,P=0.03),and resuming cardiopulmonary resuscitation(CPR)(72.3%vs.9.8%,P<0.001).At post-training and follow-up,there were no significant differences in key behaviors,except for resuming CPR.Time to shock and time to resume CPR were shorter in the card group,while time to power-on AED was not different in each phase of tests.In the 55–65 years group,the card group achieved more skill improvements over the control group compared to the other age groups.CONCLUSION:The self-instruction card could serve as a direction for first-time AED users and as a reminder for trained subjects.This could be a practical,cost-effective way to improve the AED skills of potential rescue providers among different age groups,including seniors.
基金partially funded by Sao Paulo Research Foundation(FAPESP),Brazil,grant numbers#2015/18808-0,#2018/23064-8,#2019/23382-2.
文摘Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable measurements.However,such professional instrumentation is notably expensive while remote sensing from a number of stations is paramount.This imposes challenges on the large-scale weather station deployment for broad monitoring from large observation networks such as in Cemaden—The Brazilian National Center for Monitoring and Early Warning of Natural Disasters.In this context,in this paper,we propose a Low-Cost Automatic Weather Station(LCAWS)system developed from Commercial Off-The-Shelf(COTS)and open-source Internet of Things(IoT)technologies,which provides measurements as reliable as a reference PWS for natural disaster monitoring.When being automatic,LCAWS is a stand-alone photovoltaic system connected wirelessly to the Internet in order to provide real-time reliable end-to-end weather measurements.To achieve data reliability,we propose an intelligent sensor calibration method to correct measures.From a 30-day uninterrupted observation with sampling in minute resolution,we show that the calibrated LCAWS sensors have no statistically significant differences from the PWS measurements.As such,LCAWS has opened opportunities for reducing maintenance costs in Cemaden's observational network.
基金supported partially by the Ministry of Science and Technology,Taiwan,under contracts MOST-110-2634-F-009-024,109-2218-E-150-002,and 109-2218-E-005-015.
文摘The recent trends in Industry 4.0 and Internet of Things have encour-aged many factory managers to improve inspection processes to achieve automa-tion and high detection rates.However,the corresponding cost results of sample tests are still used for quality control.A low-cost automated optical inspection system that can be integrated with production lines to fully inspect products with-out adjustments is introduced herein.The corresponding mechanism design enables each product to maintain afixed position and orientation during inspec-tion to accelerate the inspection process.The proposed system combines image recognition and deep learning to measure the dimensions of the thread and iden-tify its defects within 20 s,which is lower than the production-line productivity per 30 s.In addition,the system is designed to be used for monitoring production lines and equipment status.The dimensional tolerance of the proposed system reaches 0.012 mm,and a 100%accuracy is achieved in terms of the defect reso-lution.In addition,an attention-based visualization approach is utilized to verify the rationale for the use of the convolutional neural network model and identify the location of thread defects.
文摘In the process of food testing,human operation is an important variable affecting the experimental results.In order to reasonably avoid the influence of human subjective operation behavior on the accuracy of detection results,the laboratory information management system was used as the information platform to design a high-throughput laboratory automation pre-treatment system based on the deep integration of mechanical principles,visual analysis,high-speed conduction,intelligent storage and other technical systems.The experimental results showed that the system could shorten the sample circulation cycle,effectively improve the laboratory biosafety,and meet the requirements of high-throughput processing of samples.
文摘Objective: This paper takes the example of a Panax notoginseng extraction workshop and designs an automated production workshop with advanced domestic capabilities. Methods: 1) Based on the small-scale Panax notoginseng extraction process, the feasibility of the workshop production process is demonstrated. 2) The workshop process design for Panax Notoginseng saponin extraction is completed, including production organization plans and the selection of key equipment. 3) For the Panax notoginseng extraction workshop process, an automated production control system is designed. Conclusion: Through optimized design of the production process and automation system, continuous and automated production of traditional Chinese medicine extraction is achieved, leading to improvements in drug quality and production efficiency.