Internet Technology Letters最新文献_第9页

Data mining based network intrusion detection method in the environment of IoT 物联网环境下基于数据挖掘的网络入侵检测方法

Internet Technology Letters Pub Date : 2023-05-14 DOI: 10.1002/itl2.440

Guihua Wu, Lijing Xie

引用次数: 0

Physiological signal analysis in exercise fatigue detection application based on deep learning 基于深度学习的运动疲劳检测应用中的生理信号分析

IF 0.9

Internet Technology Letters Pub Date : 2023-05-14 DOI: 10.1002/itl2.439

Yongzhi Wang, Ruifang Li, Yunyun Zhang, Chunhai Cui

引用次数: 0

Intelligent language analysis method for multi-sensor data fusion 多传感器数据融合的智能语言分析方法

Internet Technology Letters Pub Date : 2023-05-10 DOI: 10.1002/itl2.441

Tengxiao Han

引用次数: 0

Yoga training injury detection method based on multi-sensor information fusion 基于多传感器信息融合的瑜伽训练损伤检测方法

IF 0.9

Internet Technology Letters Pub Date : 2023-05-09 DOI: 10.1002/itl2.435

Juan Liu, Yuanqing Li

{"title":"Yoga training injury detection method based on multi-sensor information fusion","authors":"Juan Liu, Yuanqing Li","doi":"10.1002/itl2.435","DOIUrl":"10.1002/itl2.435","url":null,"abstract":"Yoga, as a kind of body building exercise, has always been loved by people. However, many people suffer from yoga training injuries due to long-term incorrect posture and wrong exercise methods. There is an urgent need for a technology to help people detect and improve yoga training methods. Based on the past computer assistance method, this paper started from a new idea, and adopted the method of multi-sensor information fusion to detect yoga training, aiming to help the masses better participate in yoga training. In this study, 50 volunteers were invited to participate in the comparative experiment. Based on multi-sensor information fusion, and by building a human model, the tension and compression data before and after yoga training were compared to analyze the differences before and after calculation. It was concluded that the more sensors, the higher the degree of information fusion, and the lower the yoga training injury index. The injury index of yoga training without multi-sensor information fusion technology in the early stage was 0.39. With the increase of the number of sensors, the injury index of yoga training has gradually decreased to 0.02, which was more than 5 percentage points lower than that of the previous methods. The experiment showed that the method of yoga training damage detection based on multi-sensor information fusion was feasible, which also provided a new idea for the research of yoga training injury detection methods.","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83913798","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

Retinal image preprocessing techniques: Acquisition and cleaning perspective 视网膜图像预处理技术：采集和清洗视角

IF 0.9

Internet Technology Letters Pub Date : 2023-05-09 DOI: 10.1002/itl2.437

Anuj Kumar Pandey, Satya Prakash Singh, Chinmay Chakraborty

{"title":"Retinal image preprocessing techniques: Acquisition and cleaning perspective","authors":"Anuj Kumar Pandey, Satya Prakash Singh, Chinmay Chakraborty","doi":"10.1002/itl2.437","DOIUrl":"10.1002/itl2.437","url":null,"abstract":"Image preprocessing is a method to transform raw image data into clean image data. The objective of preprocessing is to improve the image data by suppressing undesired distortions. Enhancement of some image features which are relevant for further processing of image and analysis task is also done in preprocessing. Screening and diagnosis of various eye diseases like diabetic retinopathy, Choroidal Neovascularization(CNV), DRUSEN, etc. are possible using digital retinal images. This paper aims to provide a better understanding and knowledge of the computer algorithms used for retinal image preprocessing. In this paper, various image preprocessing techniques are incorporated such as color correction, color space selection, noise reduction, and contrast enhancement on retinal images. Retinal blood vessels are better seen in Green color space instead of Red or Blue color space. Noise reduction through Block matching and 3D(BM3D) techniques show a significant result as compared to Total Variation Filter (TVF) and Bilateral Filter (BLF). Contrast enhancement through Contrast Limited Adaptive Histogram Equalization (CLAHE) outperforms Global Equalization (GE) or Adaptive Histogram Equalization (AHE). Evaluation parameters such as Mean square error, Peak Signal Noise ratio, Structured similarity index measures, and Normalized root mean square error values for BM3D noise filtering are 0.0029, 25.3370, 0.6839 and 0.0998 respectively which shows that BM3D outperforms the others.","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76516141","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

Effective injection of adversarial botnet attacks in IoT ecosystem using evolutionary computing 使用进化计算在物联网生态系统中有效注入对抗性僵尸网络攻击

Internet Technology Letters Pub Date : 2023-05-05 DOI: 10.1002/itl2.433

Pradeepkumar Bhale, Santosh Biswas, Sukumar Nandi

引用次数: 0

Artificial intelligence analysis of electroencephalogram and evoked potential in patients with depression based on machine learning 基于机器学习的抑郁症患者脑电图和诱发电位的人工智能分析

IF 0.9

Internet Technology Letters Pub Date : 2023-05-05 DOI: 10.1002/itl2.438

Jianqi Ma

{"title":"Artificial intelligence analysis of electroencephalogram and evoked potential in patients with depression based on machine learning","authors":"Jianqi Ma","doi":"10.1002/itl2.438","DOIUrl":"10.1002/itl2.438","url":null,"abstract":"With the continuous improvement of people's mental pressure and life pace, people's study and life pressure would increase, leading to the increase of people's depression. Depression is a mental illness, a chronic mental illness that is inconsistent with the patient's physical condition. In recent years, as people know more and more about depression, and they have more and more research on depression, many research scholars have provided new ideas for the treatment of depression, and this paper takes this as the research direction and research basis. This paper introduces the background of EEG (electroencephalogram, EEG) and evoked potential and artificial intelligence (Artificial intelligence, AI) methods, and then analyzes the patients with depression based on AI, and summarizes the application of electronics. The concept analysis of depression, EEG and evoked potential is put forward. At the end of the article, the application of machine learning in depression is studied. At the same time, with the continuous development of machine learning in artificial intelligence, the EEG and evoked potential related work in patients with depression are also facing new opportunities and challenges.","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83083048","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

Development and application of a sports health cloud management platform model based on internet of things technology 基于物联网技术的运动健康云管理平台模型的开发与应用

IF 0.9

Internet Technology Letters Pub Date : 2023-05-03 DOI: 10.1002/itl2.431

Wei Han, Xinyu Zhang

引用次数: 0

Design of College Students' physical health monitoring APP based on sports health big data 基于运动健康大数据的大学生体质健康监测APP设计

IF 0.9

Internet Technology Letters Pub Date : 2023-05-03 DOI: 10.1002/itl2.432

Xiaoni Zhang, Ran Li, Yunwei Li, Yunsheng Wang, Feilong Wu

{"title":"Design of College Students' physical health monitoring APP based on sports health big data","authors":"Xiaoni Zhang, Ran Li, Yunwei Li, Yunsheng Wang, Feilong Wu","doi":"10.1002/itl2.432","DOIUrl":"10.1002/itl2.432","url":null,"abstract":"At present, the living habits of college students are relatively poor, and the amount of exercise is reduced, leading to their physical fitness getting worse and worse. Therefore, people began to study the physical health monitoring of college students. Machine learning and high-performance computing in medical applications provide technical support for intelligent medical technology. With the rapid development of computer network, human beings have entered the information and digital era, and sports health big data has become more and more popular. The combination of sports health big data and student physical health monitoring technology, in a sense, can realize automatic data processing through intelligent medical and sports health database and other information technologies, thus promoting the popularization of health monitoring technology. However, the current health monitoring equipment has many problems, such as complex collection, low accuracy and limited processing of health data. To solve this problem, this paper developed an Application (APP) based on sports health big data technology that can monitor multiple vital signs such as human heart rate and body temperature, and analyze the physical health of college students, so that college students can easily understand their health status in daily life, so as to promote the healthy development of students' physique and encourage them to actively participate in physical exercise. The experiment proved that, in the heart rate monitoring, when the speed is 6 km/h, the error rate of the college students' physical health monitoring APP designed in this paper is 8.15%. The average accuracy rate of student steps monitoring is 97.12%. This showed the accuracy and availability of the APP's monitoring function for human vital signs. It has certain application value and significance to help students improve their physical quality.","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78793039","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

Blockchain technology-based medical information sharing management 基于区块链技术的医疗信息共享管理

IF 0.9

Internet Technology Letters Pub Date : 2023-04-18 DOI: 10.1002/itl2.429

Kai Zhou, Huiyan Zhou, Weibin Zhao

引用次数: 0