Pub Date : 2024-01-25DOI: 10.56028/aetr.9.1.506.2024
Jiaojiao Chen, Yanling Ma, Xuan Lv, Shuo Sun, Yang Gao, Zijuan Li
In order to explore the influence of different storage conditions on the physical properties of cut tobacco during storage, this study measured the changes in moisture content, moisture activity, and physical properties of cut tobacco. Based on these indicators, the relationship between various physical properties was investigated. The selected storage conditions were a temperature of 23-25℃, humidity of 55%-65%, and storage time of 3-25 h. The results showed that maintaining the appropriate moisture content of 60% and a storage temperature of 25℃ was beneficial for preserving the physical properties of cut tobacco. Among the storage conditions, humidity had the most significant impact on the physical properties of cut tobacco, followed by temperature. Within the limited time range, the storage time had a relatively less noticeable effect on the quality of cut tobacco.
{"title":"Research on the Physical Properties of Cut Tobacco under Different Storage Conditions","authors":"Jiaojiao Chen, Yanling Ma, Xuan Lv, Shuo Sun, Yang Gao, Zijuan Li","doi":"10.56028/aetr.9.1.506.2024","DOIUrl":"https://doi.org/10.56028/aetr.9.1.506.2024","url":null,"abstract":"In order to explore the influence of different storage conditions on the physical properties of cut tobacco during storage, this study measured the changes in moisture content, moisture activity, and physical properties of cut tobacco. Based on these indicators, the relationship between various physical properties was investigated. The selected storage conditions were a temperature of 23-25℃, humidity of 55%-65%, and storage time of 3-25 h. The results showed that maintaining the appropriate moisture content of 60% and a storage temperature of 25℃ was beneficial for preserving the physical properties of cut tobacco. Among the storage conditions, humidity had the most significant impact on the physical properties of cut tobacco, followed by temperature. Within the limited time range, the storage time had a relatively less noticeable effect on the quality of cut tobacco.","PeriodicalId":355471,"journal":{"name":"Advances in Engineering Technology Research","volume":"34 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140495785","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}
Pub Date : 2024-01-25DOI: 10.56028/aetr.9.1.629.2024
Manfei Lo
The model of large-scale data processing and ML(machine learning) analysis based on DA(distributed algorithm) is a powerful computing method, which aims at processing huge data sets and performing efficient ML analysis. In this paper, a cluster topology driver module based on gradient switching and aggregate communication is designed, and its core goal is to adapt the distributed system to various underlying network topologies. By designing decentralized gradient exchange algorithm and aggregate communication framework, the parallel transmission ability of multi-interface network can be fully exerted, thus improving the model synchronization efficiency of ML task. The experimental results show that the cluster topology driver module can provide better performance than the existing methods in terms of training convergence, cluster scalability and communication overhead. Large-scale data processing and ML analysis model based on DA is widely used in processing massive data and realizing complex analysis tasks.
基于分布式算法（DA）的大规模数据处理和机器学习（ML）分析模型是一种强大的计算方法，旨在处理海量数据集并进行高效的ML分析。本文设计了基于梯度交换和聚合通信的集群拓扑驱动模块，其核心目标是使分布式系统适应各种底层网络拓扑结构。通过设计分散梯度交换算法和聚合通信框架，可以充分发挥多接口网络的并行传输能力，从而提高 ML 任务的模型同步效率。实验结果表明，集群拓扑驱动模块在训练收敛性、集群可扩展性和通信开销等方面的性能均优于现有方法。基于 DA 的大规模数据处理和 ML 分析模型被广泛应用于海量数据的处理和复杂分析任务的实现。
{"title":"Large-Scale Data Processing and Machine Learning Analysis Model Based on Distributed Algorithm","authors":"Manfei Lo","doi":"10.56028/aetr.9.1.629.2024","DOIUrl":"https://doi.org/10.56028/aetr.9.1.629.2024","url":null,"abstract":"The model of large-scale data processing and ML(machine learning) analysis based on DA(distributed algorithm) is a powerful computing method, which aims at processing huge data sets and performing efficient ML analysis. In this paper, a cluster topology driver module based on gradient switching and aggregate communication is designed, and its core goal is to adapt the distributed system to various underlying network topologies. By designing decentralized gradient exchange algorithm and aggregate communication framework, the parallel transmission ability of multi-interface network can be fully exerted, thus improving the model synchronization efficiency of ML task. The experimental results show that the cluster topology driver module can provide better performance than the existing methods in terms of training convergence, cluster scalability and communication overhead. Large-scale data processing and ML analysis model based on DA is widely used in processing massive data and realizing complex analysis tasks.","PeriodicalId":355471,"journal":{"name":"Advances in Engineering Technology Research","volume":"362 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140495268","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}
Pub Date : 2024-01-25DOI: 10.56028/aetr.9.1.502.2024
Bowen Zhang, Shiqi Mei, Haowei Ti
Secondhand tobacco smoke contains at least 69 carcinogens, such as nitrosamines, hydrocarbons, tar, and vinyl chloride. The liver is the main metabolic organ for these products. When the human body is exposed to these carcinogens for a long time, the carcinogens will cause "mutations" in the genes in the body and gradually accumulate, causing the cells to be unable to "function" normally, eventually leading to the occurrence of malignant tumors.Harmful substances such as nicotine in tobacco can activate cytokines and intermediate products of fiber formation, which accelerate the process of liver fibrosis and hinder the recovery of liver function in patients with liver disease. The condition will worsen with the increase in daily smoking, promoting the occurrence of liver cancer.
{"title":"The Effects of Second-hand Smoke on Liver Cancer","authors":"Bowen Zhang, Shiqi Mei, Haowei Ti","doi":"10.56028/aetr.9.1.502.2024","DOIUrl":"https://doi.org/10.56028/aetr.9.1.502.2024","url":null,"abstract":"Secondhand tobacco smoke contains at least 69 carcinogens, such as nitrosamines, hydrocarbons, tar, and vinyl chloride. The liver is the main metabolic organ for these products. When the human body is exposed to these carcinogens for a long time, the carcinogens will cause \"mutations\" in the genes in the body and gradually accumulate, causing the cells to be unable to \"function\" normally, eventually leading to the occurrence of malignant tumors.Harmful substances such as nicotine in tobacco can activate cytokines and intermediate products of fiber formation, which accelerate the process of liver fibrosis and hinder the recovery of liver function in patients with liver disease. The condition will worsen with the increase in daily smoking, promoting the occurrence of liver cancer.","PeriodicalId":355471,"journal":{"name":"Advances in Engineering Technology Research","volume":"102 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140495591","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}
Pub Date : 2024-01-25DOI: 10.56028/aetr.9.1.579.2024
Yuxiang Zhu
Stereoscopic display vision is significantly impacted by the color distortion of left and right eye images. When the human eye receives a specific range of dissimilar color information separately, the visual system combines them into a single color through binocular color fusion. In this study, we present experimental findings which compare the accuracy of a common binocular color-fusion model that was trained utilizing both linear fitting and back-propagation neural networks. Patient binocular color contrast test data was collected by eye care professionals working in private eye clinics. The results indicated that the back-propagation neural network produced RMSE errors of 0.9819 and 0.9662 for predicting binocular contrast, which were superior to the linear fitting method with errors of approximately 0.5. The BP neural network algorithm employed demonstrates predictive capabilities and lessens the occurrence of color redundancy. This reduction in redundancy holds the potential to decrease expenses associated with stereo imaging in future applications.
立体显示视觉受到左右眼图像色彩失真的严重影响。当人眼分别接收到特定范围的不同颜色信息时，视觉系统会通过双眼颜色融合将它们合并成单一颜色。在本研究中，我们展示了实验结果，比较了利用线性拟合和反向传播神经网络训练的普通双眼色彩融合模型的准确性。患者双眼颜色对比度测试数据由在私人眼科诊所工作的眼科专业人员收集。结果表明，反向传播神经网络预测双眼对比度的 RMSE 误差分别为 0.9819 和 0.9662，优于误差约为 0.5 的线性拟合方法。所采用的 BP 神经网络算法展示了预测能力，并减少了色彩冗余的出现。这种冗余的减少有可能在未来的应用中降低与立体成像相关的费用。
{"title":"Human binocular color fusion model based on BP Neural Networks prediction","authors":"Yuxiang Zhu","doi":"10.56028/aetr.9.1.579.2024","DOIUrl":"https://doi.org/10.56028/aetr.9.1.579.2024","url":null,"abstract":"Stereoscopic display vision is significantly impacted by the color distortion of left and right eye images. When the human eye receives a specific range of dissimilar color information separately, the visual system combines them into a single color through binocular color fusion. In this study, we present experimental findings which compare the accuracy of a common binocular color-fusion model that was trained utilizing both linear fitting and back-propagation neural networks. Patient binocular color contrast test data was collected by eye care professionals working in private eye clinics. The results indicated that the back-propagation neural network produced RMSE errors of 0.9819 and 0.9662 for predicting binocular contrast, which were superior to the linear fitting method with errors of approximately 0.5. The BP neural network algorithm employed demonstrates predictive capabilities and lessens the occurrence of color redundancy. This reduction in redundancy holds the potential to decrease expenses associated with stereo imaging in future applications.","PeriodicalId":355471,"journal":{"name":"Advances in Engineering Technology Research","volume":"10 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140496809","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}
Pub Date : 2024-01-25DOI: 10.56028/aetr.9.1.604.2024
Kairen Chen, Zihao Yang, Zhenyu Yang
One of the important directions of the application of artificial intelligence based on human bone behavior recognition is also a research hotspot in the field of computer vision in recent years. Human image video not only contains complex backgrounds, but also uncertain factors such as changes in illumination and changes in the appearance of the human body, which makes behavior recognition based on image videos have certain limitations. Compared with image video, human skeleton video can well overcome the influence of these uncertain factors, so be- havior recognition based on human skeleton has received more and more attention. The human skeleton sequence not only contains the tempo- ral features, but also the spatial structure features of the human body. How to effectively extract the discriminative spatial and temporal fea- tures from the human skeleton sequence is a problem to be solved. In recent years, many methods have been applied to bone-based behavior recognition, such as Recurrent Neural Network (RNN), Convolutional Neural Network (CNN) and Graph Neural Network (GCN). This article will introduce the content and characteristics of these three methods one by one. , And conduct a comparative analysis on it.
{"title":"Graph Neural Networks for Skeleton-based action recognition","authors":"Kairen Chen, Zihao Yang, Zhenyu Yang","doi":"10.56028/aetr.9.1.604.2024","DOIUrl":"https://doi.org/10.56028/aetr.9.1.604.2024","url":null,"abstract":" One of the important directions of the application of artificial intelligence based on human bone behavior recognition is also a research hotspot in the field of computer vision in recent years. Human image video not only contains complex backgrounds, but also uncertain factors such as changes in illumination and changes in the appearance of the human body, which makes behavior recognition based on image videos have certain limitations. Compared with image video, human skeleton video can well overcome the influence of these uncertain factors, so be- havior recognition based on human skeleton has received more and more attention. The human skeleton sequence not only contains the tempo- ral features, but also the spatial structure features of the human body. How to effectively extract the discriminative spatial and temporal fea- tures from the human skeleton sequence is a problem to be solved. In recent years, many methods have been applied to bone-based behavior recognition, such as Recurrent Neural Network (RNN), Convolutional Neural Network (CNN) and Graph Neural Network (GCN). This article will introduce the content and characteristics of these three methods one by one. , And conduct a comparative analysis on it.","PeriodicalId":355471,"journal":{"name":"Advances in Engineering Technology Research","volume":"7 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140495903","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}
Pub Date : 2024-01-25DOI: 10.56028/aetr.9.1.544.2024
Xianghe Meng
The glass transition temperature (Tg) plays a crucial role in defining polymer properties. Despite the widespread use of machine learning for material design and property prediction, there are still challenges concerning the interpretability and model performance when predicting Tg. In this study, Simplified Molecular Input Line Entry System strings are utilised to encode the polymer structure, which are then transformed into molecular descriptors for analytical training and prediction of Tg using Artificial Neural Network and Random Forest models. Meticulous hyperparameter tuning of the Random Forest model was performed, resulting in reasonable Tg predictions. This methodology forges a connection between polymer structure and Tg, opening up new avenues for research in the field of polymers.
{"title":"Efficient Prediction of Polymer Glass Transition Temperatures through Machine Learning Methods","authors":"Xianghe Meng","doi":"10.56028/aetr.9.1.544.2024","DOIUrl":"https://doi.org/10.56028/aetr.9.1.544.2024","url":null,"abstract":"The glass transition temperature (Tg) plays a crucial role in defining polymer properties. Despite the widespread use of machine learning for material design and property prediction, there are still challenges concerning the interpretability and model performance when predicting Tg. In this study, Simplified Molecular Input Line Entry System strings are utilised to encode the polymer structure, which are then transformed into molecular descriptors for analytical training and prediction of Tg using Artificial Neural Network and Random Forest models. Meticulous hyperparameter tuning of the Random Forest model was performed, resulting in reasonable Tg predictions. This methodology forges a connection between polymer structure and Tg, opening up new avenues for research in the field of polymers.","PeriodicalId":355471,"journal":{"name":"Advances in Engineering Technology Research","volume":"33 11-12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140496184","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}
Pub Date : 2024-01-25DOI: 10.56028/aetr.9.1.558.2024
Xinyi Li
This article proposes a novel optimization strategy for credit scoring systems that exploits the capabilities of SVM. Focusing on the importance of personal credit scoring in today's credit dynamics, the article explores SVM's versatility in various domains through a literature review. The theoretical background underscores the unique approach and computational efficiency of SVM. The optimization strategy encompasses four critical aspects: debt solvency, earning potential, operational prowess, and growth capability using metrics such as asset-liability ratios. Experimental validation with credit card datasets from Australia and Germany illustrates the nuanced relationship between different K-values and performance metrics, and demonstrates the adaptability of SVM in improving credit scoring. In short, the article presents an original, comprehensive approach to credit risk management that integrates theoretical foundations, literature findings, and empirical experiments to improve the accuracy of credit scoring in the dynamic economic landscaper.
{"title":"Optimization Strategy of Credit Scoring System based on Support Vector Machine","authors":"Xinyi Li","doi":"10.56028/aetr.9.1.558.2024","DOIUrl":"https://doi.org/10.56028/aetr.9.1.558.2024","url":null,"abstract":"This article proposes a novel optimization strategy for credit scoring systems that exploits the capabilities of SVM. Focusing on the importance of personal credit scoring in today's credit dynamics, the article explores SVM's versatility in various domains through a literature review. The theoretical background underscores the unique approach and computational efficiency of SVM. The optimization strategy encompasses four critical aspects: debt solvency, earning potential, operational prowess, and growth capability using metrics such as asset-liability ratios. Experimental validation with credit card datasets from Australia and Germany illustrates the nuanced relationship between different K-values and performance metrics, and demonstrates the adaptability of SVM in improving credit scoring. In short, the article presents an original, comprehensive approach to credit risk management that integrates theoretical foundations, literature findings, and empirical experiments to improve the accuracy of credit scoring in the dynamic economic landscaper.","PeriodicalId":355471,"journal":{"name":"Advances in Engineering Technology Research","volume":"318 3-4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140495246","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}
Pub Date : 2024-01-25DOI: 10.56028/aetr.9.1.670.2024
Chuanhao Zhang
With the progress of society and the development of productivity, the problem of water pollution and water shortage caused by water pollution is becoming more and more serious. Water-borne diseases caused by pathogenic microorganisms also bring great harm to human beings and other life forms. These microorganisms include bacteria, viruses, protozoa, and parasitic pathogens. Traditional detection methods are time-consuming and costly, and can’t meet the needs of water resource detection. Therefore, there is an urgent need for accurate, rapid, specific, and portable detection equipment for detecting pathogenic microorganisms in water. We analyzed and sorted out the detection methods and detection equipment for detecting pathogenic microorganisms that cause water-borne diseases, summarized these detection methods and detection equipment, and analyzed the advantages and disadvantages of these detection methods. We reasonably concluded that a good detection method for pathogenic microorganisms in water should have the advantages of low cost, low energy consumption, simple operation, strong specificity, and high portability, which can more easily meet the needs of the water quality detection field. Multifunctional small nucleic acid detection devices have been reported for decades, which reduce the reaction time of nucleic acid amplification from hours to minutes, and these miniaturized devices based on nucleic acid amplification are not only highly specific but also low cost, which is very suitable for resource-limited environments.
{"title":"Miniaturized detection devices powered by various heaters: A quick review under the background of water-borne disease epidemics","authors":"Chuanhao Zhang","doi":"10.56028/aetr.9.1.670.2024","DOIUrl":"https://doi.org/10.56028/aetr.9.1.670.2024","url":null,"abstract":"With the progress of society and the development of productivity, the problem of water pollution and water shortage caused by water pollution is becoming more and more serious. Water-borne diseases caused by pathogenic microorganisms also bring great harm to human beings and other life forms. These microorganisms include bacteria, viruses, protozoa, and parasitic pathogens. Traditional detection methods are time-consuming and costly, and can’t meet the needs of water resource detection. Therefore, there is an urgent need for accurate, rapid, specific, and portable detection equipment for detecting pathogenic microorganisms in water. We analyzed and sorted out the detection methods and detection equipment for detecting pathogenic microorganisms that cause water-borne diseases, summarized these detection methods and detection equipment, and analyzed the advantages and disadvantages of these detection methods. We reasonably concluded that a good detection method for pathogenic microorganisms in water should have the advantages of low cost, low energy consumption, simple operation, strong specificity, and high portability, which can more easily meet the needs of the water quality detection field. Multifunctional small nucleic acid detection devices have been reported for decades, which reduce the reaction time of nucleic acid amplification from hours to minutes, and these miniaturized devices based on nucleic acid amplification are not only highly specific but also low cost, which is very suitable for resource-limited environments.","PeriodicalId":355471,"journal":{"name":"Advances in Engineering Technology Research","volume":"5 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140495671","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}
Pub Date : 2024-01-25DOI: 10.56028/aetr.9.1.665.2024
Sitan Shen
In order to realize the early warning of abnormal crops, the photographing technology and image recognition technology of openMV and openCV are comprehensively applied to study the early warning of abnormal crops. The design take photos using openMV hardware platform and connects to the cloud through 5G module. Then it conducts in-depth processing such as gray processing, image denoising and boundary detection on the photos through the network server to obtain the location and size of abnormal areas, so as to help spray pesticides later and improve production efficiency.
{"title":"Abnormal crop warning system based on OpenMV","authors":"Sitan Shen","doi":"10.56028/aetr.9.1.665.2024","DOIUrl":"https://doi.org/10.56028/aetr.9.1.665.2024","url":null,"abstract":"In order to realize the early warning of abnormal crops, the photographing technology and image recognition technology of openMV and openCV are comprehensively applied to study the early warning of abnormal crops. The design take photos using openMV hardware platform and connects to the cloud through 5G module. Then it conducts in-depth processing such as gray processing, image denoising and boundary detection on the photos through the network server to obtain the location and size of abnormal areas, so as to help spray pesticides later and improve production efficiency.","PeriodicalId":355471,"journal":{"name":"Advances in Engineering Technology Research","volume":"55 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140495855","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}
Pub Date : 2024-01-25DOI: 10.56028/aetr.9.1.655.2024
Zhaocheng Xu
In recent years, with the continuous occurrence of accidents such as car accidents, wars, engineering accidents, natural disasters, tumors and vascular diseases, the number of patients with limb disability due to amputations or accidental injuries is also increasing. phantom limb pain (PLP), one of the main complications after amputation, has attracted increasing attention. Phantom limb pain, also known as phantom limb pain, refers to the subjective feeling that the amputated limb still exists, and is accompanied by varying degrees of pain, and the pain is mostly in the distal end of the amputated limb. Most phantom pain is combined with stump pain or phantom sensation. There are as many as 37 treatments for PLP, considering the high frequency of its occurrence and how much it affects patients. They can be broadly categorized as pharmacotherapy, physical therapy, and psychotherapy. Each of these therapies has its own drawbacks, which AR technology is well equipped to make up for.
近年来，随着车祸、战争、工程事故、自然灾害、肿瘤、血管疾病等意外事件的不断发生，因截肢或意外伤害导致肢体残疾的患者也越来越多。幻肢痛（phantom limb pain，PLP）作为截肢后的主要并发症之一，越来越引起人们的重视。幻肢痛又称幻肢痛，是指患者主观上感觉截肢肢体仍然存在，并伴有不同程度的疼痛，疼痛部位多在截肢肢体的远端。大多数幻痛与残肢痛或幻觉相结合。鉴于幻肢痛发生频率高、对患者影响大，治疗幻肢痛的方法多达 37 种。这些疗法大致可分为药物疗法、物理疗法和心理疗法。每种疗法都有其自身的缺点，而 AR 技术可以很好地弥补这些缺点。
{"title":"Application of AR technology in the treatment of Phantom Limb Pain","authors":"Zhaocheng Xu","doi":"10.56028/aetr.9.1.655.2024","DOIUrl":"https://doi.org/10.56028/aetr.9.1.655.2024","url":null,"abstract":"In recent years, with the continuous occurrence of accidents such as car accidents, wars, engineering accidents, natural disasters, tumors and vascular diseases, the number of patients with limb disability due to amputations or accidental injuries is also increasing. phantom limb pain (PLP), one of the main complications after amputation, has attracted increasing attention. Phantom limb pain, also known as phantom limb pain, refers to the subjective feeling that the amputated limb still exists, and is accompanied by varying degrees of pain, and the pain is mostly in the distal end of the amputated limb. Most phantom pain is combined with stump pain or phantom sensation. There are as many as 37 treatments for PLP, considering the high frequency of its occurrence and how much it affects patients. They can be broadly categorized as pharmacotherapy, physical therapy, and psychotherapy. Each of these therapies has its own drawbacks, which AR technology is well equipped to make up for.","PeriodicalId":355471,"journal":{"name":"Advances in Engineering Technology Research","volume":"81 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140495435","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}
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