2023 4th International Conference for Emerging Technology (INCET)最新文献_第10页

Classifying Sign Language Gestures using Decision Trees: A Comparison of sEMG and IMU Sensor Data 用决策树对手语手势进行分类:表面肌电信号和IMU传感器数据的比较

2023 4th International Conference for Emerging Technology (INCET) Pub Date : 2023-05-26 DOI: 10.1109/INCET57972.2023.10170736

Akhtar I. Nadaf, S. Pardeshi

引用次数: 0

Prediction of Diseases in Potato Plant using Pre-trained and Traditional Machine Learning Models 基于预训练和传统机器学习模型的马铃薯病害预测

2023 4th International Conference for Emerging Technology (INCET) Pub Date : 2023-05-26 DOI: 10.1109/INCET57972.2023.10170149

Swati Laxmi Sahu, Renta Chintala Bhargavi

{"title":"Prediction of Diseases in Potato Plant using Pre-trained and Traditional Machine Learning Models","authors":"Swati Laxmi Sahu, Renta Chintala Bhargavi","doi":"10.1109/INCET57972.2023.10170149","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170149","url":null,"abstract":"Potato, among the most vegetables is commercially significant and well-known vegetable which is known for its high nutritional content and delicious flavor. India is one of the world’s leading producers of potato. Unfortunately, plant diseases in potato have been one of the causes of decreased production. So, it is necessary to detect them. Collecting images of plants diseases is a big challenge as it is a very time-consuming process. Often, we do not have sufficient data to train our deep learning models, so data augmentation techniques are used for increasing the dataset which lead to poor generalization. This study focuses on detecting whether the plant is healthy or diseased. In this proposed method, limited dataset is used for potato plant disease classification without using any data augmentation techniques. Popular pre-trained models — VGG16, InceptionResNetV2, ResNet50V2 are used for feature extraction and traditional machine learning algorithms — XGBoost, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest are used as classifiers. From the study, it is observed that the combination of VGG16 model as a feature extractor and SVM as a classifier achieved the highest accuracy of 93% compared to rest of the combination of models and algorithms. The method proposed in this study can be used for potato plant disease detection with limited dataset.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123757433","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

Synopsis Creation for Research Paper using Text Summarization Models 使用文本摘要模型创建研究论文的摘要

2023 4th International Conference for Emerging Technology (INCET) Pub Date : 2023-05-26 DOI: 10.1109/INCET57972.2023.10170144

Sanskruti Badhe, Mubashshira Hasan, Vidhi Rughwani, Reeta Koshy

引用次数: 0

Working Path Optimization of AUV Manipulator Based on PSO-GA Algorithm 基于PSO-GA算法的AUV机械臂工作路径优化

2023 4th International Conference for Emerging Technology (INCET) Pub Date : 2023-05-26 DOI: 10.1109/INCET57972.2023.10169957

Pengyu Cheng

{"title":"Working Path Optimization of AUV Manipulator Based on PSO-GA Algorithm","authors":"Pengyu Cheng","doi":"10.1109/INCET57972.2023.10169957","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10169957","url":null,"abstract":"The work path optimization of AUV manipulator based on PSO GA algorithm is a method to find the best work path of AUV manipulator. It is an extension of the original PSO GA algorithm, and uses the concept of pseudo Gaussian distribution to find a better solution under multiple local optimizations. The working path optimization of the underwater robot manipulator is to make the control of the underwater robot manipulator move along the working path with the minimum energy consumption. It is realized by using some mathematical techniques and algorithms. The main idea behind this technology is to find out the best point of the mobile underwater robot manipulator to minimize its total energy consumption. This technology is used for many purposes, such as motion planning, path planning and control design.. The main idea behind this algorithm is that if there are multiple local optima, the global optimal can be found by minimizing the total cost function of all local optima. This can be achieved by using Lagrange multiplication (LMM). In addition, this technology requires less computing power. In the actual working environment and experimental environment, the magnetic field interference may have an impact on the attitude parameters of AUV, which leads to the unsatisfactory control effect of AUV motion. In order to accurately measure the attitude of AUV system, this paper proposes an anti-jamming and fault-tolerant processing algorithm for MEMS inertial navigation system. This algorithm first estimates the signal residual, then dynamically adjusts the confidence level of local filter through the residual value, and finally fuses sensor signals with different working principles through the confidence level, which can significantly improve the stability and reliability of attitude feedback signals.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122299950","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

A Comparision Study of Machine Learning Methods for Unit Price Estimation in Smartgrid 智能电网中单价估算的机器学习方法比较研究

2023 4th International Conference for Emerging Technology (INCET) Pub Date : 2023-05-26 DOI: 10.1109/INCET57972.2023.10170179

Satyabrata Sahoo, S. Swain, Ritesh Dash

引用次数: 0

Blockchain Trust based Authentication Protocol with Malicious Data Analysis Using Deep Learning Architectures: Electronic Medical Record Application 基于信任的认证协议与使用深度学习架构的恶意数据分析:电子病历应用

2023 4th International Conference for Emerging Technology (INCET) Pub Date : 2023-05-26 DOI: 10.1109/INCET57972.2023.10170390

R. Krishnamoorthy, K. Kaliyamurthie

{"title":"Blockchain Trust based Authentication Protocol with Malicious Data Analysis Using Deep Learning Architectures: Electronic Medical Record Application","authors":"R. Krishnamoorthy, K. Kaliyamurthie","doi":"10.1109/INCET57972.2023.10170390","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170390","url":null,"abstract":"New opportunities for effective patient data management have emerged as a result of introduction of electronic health records (EHRs). By utilizing ML to mine digital patient record datasets, for instance, preventative rather than reactive medical practice is feasible. EHR is vulnerable to both insider and external threats due to sensitive nature of data, but security applications typically face the network's outer perimeter. Using deep learning methods, this study aims to enhance cloud data storage and malicious data detection. Blockchain trust based authentication is used to improve security-based cloud data storage in this study. After that, fuzzy rule Bayesian discriminant analysis is used to find malicious data. Utilizing results of malware analysis as well as detection and ML methods to evaluate difference in correlation symmetry, it was demonstrated that it was possible to detect harmful traffic on computer systems, thereby increasing network security. Data transmission rate, random accuracy, computation cost, communication overhead, mean average precision, and specificity are all examined in the experimental analysis for various electronic medical record datasets.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"836 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128984943","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

Securing Data storage in Cloud after Migration using Immutable Data Dispersion 使用不可变数据分散保护迁移后的云数据存储

2023 4th International Conference for Emerging Technology (INCET) Pub Date : 2023-05-26 DOI: 10.1109/INCET57972.2023.10170274

Rajesh Kumar C, Aroul Canessane R

{"title":"Securing Data storage in Cloud after Migration using Immutable Data Dispersion","authors":"Rajesh Kumar C, Aroul Canessane R","doi":"10.1109/INCET57972.2023.10170274","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170274","url":null,"abstract":"Cloud computing has emerged as a technology behemoth with applications in a wide range of fields. When data is being migrated from offline data centres and stored in multiple cloud environments part of the control is always with the Cloud Service Providers(CSPs) leads to security concerns. The data stored in the cloud may sometimes be compromised even though the CSPs may take precautions to avoid such situations. In this paper, we discuss securely storing the data using the data dispersion technique by breaking the data into multiple segments and combining it with encryption along with replication. The division of data and storing it in the cloud helps in protecting the complete data even if an attacker tries to access the data it will not be easy for him to make sense of the retrieved data because the data is already being encrypted and combined with dispersion and replication adds to the complexity of retrieval. Security is achieved as the dispersed data is spread across multiple locations which makes it difficult for an attacker to get all the segments. In most scenarios be able it depends on traditional encryption techniques alone to protect the data. Here, We propose focusing more on how data is stored in the cloud to relieve the system of costly computational methodologies. In this strategy, the trade-off between security and the data retrieval time must also be considered.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129262617","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

Energy saving Ocean Garbage Collection Return Algorithm and System Based on Machine Vision 基于机器视觉的节能海洋垃圾回收算法与系统

2023 4th International Conference for Emerging Technology (INCET) Pub Date : 2023-05-26 DOI: 10.1109/INCET57972.2023.10170301

Xikang Du

引用次数: 0

Impact of COVID-19 Lockdowns on Air Quality in Bangladesh: Analysis and AQI Forecasting with Support Vector Regression COVID-19封锁对孟加拉国空气质量的影响:基于支持向量回归的分析和AQI预测

2023 4th International Conference for Emerging Technology (INCET) Pub Date : 2023-05-26 DOI: 10.1109/INCET57972.2023.10169997

Mohammed Tahmid Hossain, Afra Hossain, Sabrina Masum Meem, Md Fahad Monir, Md Saef Ullah Miah, Talha Bin Sarwar

{"title":"Impact of COVID-19 Lockdowns on Air Quality in Bangladesh: Analysis and AQI Forecasting with Support Vector Regression","authors":"Mohammed Tahmid Hossain, Afra Hossain, Sabrina Masum Meem, Md Fahad Monir, Md Saef Ullah Miah, Talha Bin Sarwar","doi":"10.1109/INCET57972.2023.10169997","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10169997","url":null,"abstract":"Over the past few decades, air pollution has emerged as a significant environmental hazard, causing premature deaths in Southeast Asia. The proliferation of industrialization and deforestation has resulted in an alarming increase in pollution levels. However, the COVID-19 pandemic has significantly reduced the amount of volatile organic compounds and toxic gases in the air due to the decrease in human activity caused by lockdowns and restrictions. This study aims to investigate the air quality in various geographical areas of Bangladesh, comparing the air quality index (AQI) during different lockdown periods to equivalent eight-year time spans in 10 of the country’s busiest cities. This study demonstrates a strong correlation between the rapid and widespread dispersion of COVID-19 and air pollution reduction in Bangladesh. In addition, we evaluated the performance of Support Vector Regression (SVR) in AQI forecasting using the time series dataset. The results can help improve machine learning and deep learning models for accurate AQI forecasting. This study contributes to developing effective policies and strategies for reducing air pollution in Bangladesh and other countries facing similar challenges.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130489197","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: 2

A Coherent Way of Detecting Learner’s Academic Emotions via Live Camera Using CNN and Deep LSTM 基于CNN和深度LSTM的实时摄像机连贯学习情绪检测方法

2023 4th International Conference for Emerging Technology (INCET) Pub Date : 2023-05-26 DOI: 10.1109/INCET57972.2023.10170151

Snehal R. Rathi, Samkit Oswal, Ayushi Ahuja

{"title":"A Coherent Way of Detecting Learner’s Academic Emotions via Live Camera Using CNN and Deep LSTM","authors":"Snehal R. Rathi, Samkit Oswal, Ayushi Ahuja","doi":"10.1109/INCET57972.2023.10170151","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170151","url":null,"abstract":"Academic Emotion Detection is fundamentally a system for detecting emotions. The system's main goal was to identify feelings expressed while attending online lectures during the COVID-19 epidemic. The topic Academic Emotion Detection using Machine Learning focuses on utilizing machine learning and deep learning to identify human face emotions in light of the shift to online learning.Our research has a limited scope, it focuses on four academic emotions: confusion, boredom, engagement, and frustration. A person may experience a wide range of other emotions as well. Here, we have used CNN and Deep LSTM for the prediction of said four emotions and it has been observed it increases the accuracy of prediction and effectiveness. We even incorporated a portion of a questionnaire into our research to compare our results with genuine human experiences.Concurrent Neural Network (CNN), Long-Short Term Memory (LSTM), and Recurrent Neural Network (RNN) are three different algorithms from the deep learning area that we have used in this study to examine how they operate and identify similarities and differences.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131078372","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