2023 8th International Conference on Communication and Electronics Systems (ICCES)最新文献_第5页

An Efficient Drowsiness Detection and Driver Alert System using OCNN 一种基于OCNN的高效睡意检测与驾驶员警报系统

2023 8th International Conference on Communication and Electronics Systems (ICCES) Pub Date : 2023-06-01 DOI: 10.1109/ICCES57224.2023.10192655

T. S, P. L, S. K, R. Dhanapal

{"title":"An Efficient Drowsiness Detection and Driver Alert System using OCNN","authors":"T. S, P. L, S. K, R. Dhanapal","doi":"10.1109/ICCES57224.2023.10192655","DOIUrl":"https://doi.org/10.1109/ICCES57224.2023.10192655","url":null,"abstract":"To analyze traffic accident data and identify priority enhancement junctions, this research aims to build a high accident risk prediction model. To identify possible high accident risk locations for traffic management departments to use in developing countermeasures to reduce accident risk, an intersection accident risk prediction model was created using a variety of mechanical learning approaches. the creation and examination of an accident record. The research work focus on identifying the drowsiness using EEG signal. It identified environmental factors at intersections that affect accident risk levels using optimized CNN. An accident risk prediction model was developed using optimized Convolutional Neural Network (CNN)-Heuristic. To build up a drowsiness identification framework that can recognize weariness in drivers to forestall mishaps and the ground truth drowsiness detection system that is depending on the vigorous left, focus and right-AOEs and fixed back AOE (Area of eye vision). Additionally, this model can identify the crucial elements that influence the likelihood of high-risk crossings, giving traffic management organizations a strong foundation for choosing an intersection. This could be used to forecast future risk levels and aid in the reduction of traffic accidents by using the same climatic variables as high-risk crossings as model inputs. It can serve as a model for upcoming improvements to junction architecture and the surrounding area.","PeriodicalId":442189,"journal":{"name":"2023 8th International Conference on Communication and Electronics Systems (ICCES)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122149973","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

DeepASD Framework: A Deep Learning-Assisted Automatic Sarcasm Detection in Facial Emotions DeepASD框架:深度学习辅助的面部情绪自动讽刺检测

2023 8th International Conference on Communication and Electronics Systems (ICCES) Pub Date : 2023-06-01 DOI: 10.1109/ICCES57224.2023.10192647

Jiby Mariya Jose, S. Benedict

{"title":"DeepASD Framework: A Deep Learning-Assisted Automatic Sarcasm Detection in Facial Emotions","authors":"Jiby Mariya Jose, S. Benedict","doi":"10.1109/ICCES57224.2023.10192647","DOIUrl":"https://doi.org/10.1109/ICCES57224.2023.10192647","url":null,"abstract":"The vibrant human-machine research provides space for assessing sentiments in facial emotions. Capturing apt sarcasm-related emotions, especially in online meetings or stress interviews, is a challenging aspect. The purpose of this research is to apply deep learning algorithms to effectively assess the sarcasm in human facial emotions in an automatic fashion using the proposed Deep Learning-Assisted Automatic Sarcasm Detection (DeepASD) framework. Our framework trains facial sarcasm-related emotions from internet sources and applies deep learning algorithms to perform visual sarcasm detections. The proposed framework processes algorithms on edge-enabled compute nodes, including GPU-based machines. We evaluated the DeepASD framework using various deep learning algorithms such as EfficientNet, XceptionNet, InceptionNet, ResNet, DenseNet, ConvNext, MobileNet, and their variants; and, we observed that Mobilenetv3 achieved a better learning accuracy of 96.44 percent and energy consumption of 7959 Joules using minimal trainable/non-trainable parameters while detecting sarcasm in facial emotions. Our work will be beneficial for online interviewers, business enthusiasts, or future robotic machine developers for accomplishing accurate decisions considering sarcasm in facial emotions.","PeriodicalId":442189,"journal":{"name":"2023 8th International Conference on Communication and Electronics Systems (ICCES)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123903567","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

Revolutionizing Recruitment: A Comparative Study Of KNN, Weighted KNN, and SVM - KNN for Resume Screening 革命性招聘:KNN、加权KNN和SVM - KNN在简历筛选中的比较研究

2023 8th International Conference on Communication and Electronics Systems (ICCES) Pub Date : 2023-06-01 DOI: 10.1109/ICCES57224.2023.10192665

Rishabh Bathija, Vanshika Bajaj, Chandni Megnani, J. Sawara, Sanjay Mirchandani

引用次数: 1

Machine Learning based Cybersecurity Technique for Detection of Upcoming Cyber Attacks 基于机器学习的网络安全技术检测即将到来的网络攻击

2023 8th International Conference on Communication and Electronics Systems (ICCES) Pub Date : 2023-06-01 DOI: 10.1109/ICCES57224.2023.10192738

Kanchi Lohitha Lakshmi, S.Shobana, B. P. Kumar, K.B.Glory, Bonda Kiran Kumar, Sandya Rani

引用次数: 0

Innovative Deep Learning Model-based Stock Price Prediction using a Hybrid Approach of CNN and Gradient Recurrent Unit 基于CNN和梯度循环单元混合方法的创新深度学习模型股票价格预测

2023 8th International Conference on Communication and Electronics Systems (ICCES) Pub Date : 2023-06-01 DOI: 10.1109/ICCES57224.2023.10192634

B. Rao, Rajib Bhattacharya, M. Tiwari, K. A. Kumari, Mahavir Devmane, Kamlesh Singh

{"title":"Innovative Deep Learning Model-based Stock Price Prediction using a Hybrid Approach of CNN and Gradient Recurrent Unit","authors":"B. Rao, Rajib Bhattacharya, M. Tiwari, K. A. Kumari, Mahavir Devmane, Kamlesh Singh","doi":"10.1109/ICCES57224.2023.10192634","DOIUrl":"https://doi.org/10.1109/ICCES57224.2023.10192634","url":null,"abstract":"The fluctuation in stock prices from industry to industry are a major source of concern in the market. As the market attracts more participants and stock prices play a larger role in more transactions, the ability to accurately predict stock price movements becomes more valuable. When making an investment, many people first look at the share price and then try to anticipate whether or not that price will go up or down in the future. The traditional problem of forecasting the stock market using Machine Learning tools and methodologies has been thoroughly studied. Time dependence, volatility, and similar complicated dependencies are interesting aspects that make this modeling non-trivial. To overcome this the proposed method in this work is a deep learning-based hybrid strategy for predicting stock prices. Preprocessing is performed after input is delivered to increase precision. Selecting MPSOA features is the next step. In the end, it's put to use in MC-GRU model training. The proposed method achieves better results than both the CNN and GRU models.","PeriodicalId":442189,"journal":{"name":"2023 8th International Conference on Communication and Electronics Systems (ICCES)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128638944","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

Human Posture Monitoring using Flex Sensor 使用柔性传感器进行人体姿势监测

2023 8th International Conference on Communication and Electronics Systems (ICCES) Pub Date : 2023-06-01 DOI: 10.1109/ICCES57224.2023.10192780

N. S, Miriam Joshua E P, J. R., R. S, Amy Fedora F

{"title":"Human Posture Monitoring using Flex Sensor","authors":"N. S, Miriam Joshua E P, J. R., R. S, Amy Fedora F","doi":"10.1109/ICCES57224.2023.10192780","DOIUrl":"https://doi.org/10.1109/ICCES57224.2023.10192780","url":null,"abstract":"In healthcare network breach of privacy issues may arise from the implementation of vision cameras for continuous patient monitoring. To overcome this, a method for tracking the position of patients is proposed using a tiny sensor placed on a patient clothing. A flexible sensor based on polyvinylidene fluoride with flexible piezoelectric material is used. The flexible sensors are placed onto clothing of the patient that is close to the backbone of the patient. The electrical signals from the spinal cord are measured using the piezoelectric sensors during the bending or twisting of spine to the sides. This can be continuously monitored by transferring the captured data to the system through Bluetooth. A customized program is developed to detect the patient’s position through an algorithm, and the sensor results. From the experimental results it was noted that it is very essential to maintain the right posture. Not only the position determines posture. It is an adaptive response to everything that prevents you from being more or less upright and functional. It is a continual sequence of impulses, behaviors, and proprioception. Poor posture can result in injury to the spine leading to the consumption of heavy doses of pain killers which in turn may cause a bad impact on the functioning of the kidney. This study aims at measuring the deformation angle of the spine and the angle at which it has wrongly inclined and giving an alarm to the patient to set his/her posture right.","PeriodicalId":442189,"journal":{"name":"2023 8th International Conference on Communication and Electronics Systems (ICCES)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127141263","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

Finding an Optimal Route Path for Ambulance 寻找救护车的最优路径

2023 8th International Conference on Communication and Electronics Systems (ICCES) Pub Date : 2023-06-01 DOI: 10.1109/ICCES57224.2023.10192671

Chaitanya Balaji. I, Poorna Siva Sai. V, L. Sujihelen

引用次数: 0

Multisignature Crypto Wallet Paper 多重签名加密钱包纸

2023 8th International Conference on Communication and Electronics Systems (ICCES) Pub Date : 2023-06-01 DOI: 10.1109/ICCES57224.2023.10192591

A. Goel, Vibhor Singh Bisht, Shreyashi Chaudhary

引用次数: 0

Machine Learning based Mood Disorder Detection System 基于机器学习的情绪障碍检测系统

2023 8th International Conference on Communication and Electronics Systems (ICCES) Pub Date : 2023-06-01 DOI: 10.1109/ICCES57224.2023.10192877

Bhagyashree Dhamane, Saloni Badave, Anusree Mandal, Nivedita Daimiwal, R. Shriram

{"title":"Machine Learning based Mood Disorder Detection System","authors":"Bhagyashree Dhamane, Saloni Badave, Anusree Mandal, Nivedita Daimiwal, R. Shriram","doi":"10.1109/ICCES57224.2023.10192877","DOIUrl":"https://doi.org/10.1109/ICCES57224.2023.10192877","url":null,"abstract":"Mood disorder is often overlooked and there are people who think that mood disorder is \"all in your head\". As per the record of World Health Organization (WHO), 5% of the adults are suffering from it. If one has Mood disorder, the general emotional state or mood is distorted or inconsistent with various circumstances and interferes with one’s ability to function. Mental illness is still a taboo. People hesitate to consult a health specialist; hence a system is required as an early detection. The primary objective is to improve this situation by designing a user friendly application. In proposed application, condition of the people will be analyzed with the help of standard Mood Disorder Questionnaire (MDQ), Emotion analysis using face detection with the help of image processing in Python and EEG signals. The results received from above mentioned analysis will determine the severity level of mood disorder using machine learning algorithm. Depending on the severity several activities will be given. These activities will include some yoga, games, meditation and exercise. User is suggested to take the above three tests every week to check the progress. In case of high severity, according to user’s location, suggested list of health specialists will be recommended.","PeriodicalId":442189,"journal":{"name":"2023 8th International Conference on Communication and Electronics Systems (ICCES)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131030078","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

Business Process Automation using Robotic Process Automation (RPA) and AI Algorithm’s on Various Tasks 在各种任务中使用机器人过程自动化(RPA)和人工智能算法的业务流程自动化

2023 8th International Conference on Communication and Electronics Systems (ICCES) Pub Date : 2023-06-01 DOI: 10.1109/ICCES57224.2023.10192653

M. N. Dandale, Mazharunnisa, D. J. J. D. Daniel, R. Priya, Md. Abul Ala Walid, Thulasimani T

{"title":"Business Process Automation using Robotic Process Automation (RPA) and AI Algorithm’s on Various Tasks","authors":"M. N. Dandale, Mazharunnisa, D. J. J. D. Daniel, R. Priya, Md. Abul Ala Walid, Thulasimani T","doi":"10.1109/ICCES57224.2023.10192653","DOIUrl":"https://doi.org/10.1109/ICCES57224.2023.10192653","url":null,"abstract":"Robotic Process Automation (RPA) bots automate mundane, rules-based operations, allowing workers more time to focus on high-level, strategic projects. Meanwhile, AI be used to analyze data and spot trends, resulting in better choices and increased productivity for enterprises. Previous researches are less efficient, slowly working algorithms when classification is performed in a large set of databases. The existing methods could be doing better while comparing the error factors, and in the cross-verification process, they have made inappropriate results, leading to wrong classifications. Robotic Process Automation (RPA) bots automate mundane, rules-based operations, allowing workers more time to focus on high-level, strategic projects. Meanwhile, AI be used to analyze data and spot trends, resulting in better choices and increased productivity for enterprises. Previous research on email automation and invoice process automation have needed to improve classification model efficiency and they have less efficient, slowly working algorithms when doing classification in a large set of databases. In this work, the Random Forest algorithm is used for classification, and the Quest method is used to segment texts in emails and invoices, both of which can be automated more effectively. The results of existing categorization algorithms have been less than ideal, especially when used to huge datasets, and are often completely inaccurate. The suggested method outperforms previous ML/AI approaches because it produces highly accurate outcomes with little resource investment. There are a number of benefits to utilizing RPA with AI, such as cost reduction, increased output, and streamlined operations. The advantages of this automation, challenges that must be met, and potential answers to those questions are discussed in this study.","PeriodicalId":442189,"journal":{"name":"2023 8th International Conference on Communication and Electronics Systems (ICCES)","volume":"30 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132960320","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: 1