2023 International Conference on Emerging Smart Computing and Informatics (ESCI)最新文献_第6页

A System for Language Translation using Sequence-to-sequence Learning based Encoder 基于序列到序列学习编码器的语言翻译系统

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099876

Sonia Sarode, Raghav Thatte, Kajal Toshniwal, Jatin Warade, Ranjeet Vasant Bidwe, Bhushan Zope

{"title":"A System for Language Translation using Sequence-to-sequence Learning based Encoder","authors":"Sonia Sarode, Raghav Thatte, Kajal Toshniwal, Jatin Warade, Ranjeet Vasant Bidwe, Bhushan Zope","doi":"10.1109/ESCI56872.2023.10099876","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10099876","url":null,"abstract":"Hindi is the mother tongue of nearly 133 crore Indians. Along with India, it is spoken in Nepal, Fiji, and Bangladesh. Since good knowledge of English is not common, there is a good opportunity for machine translation from English to Hindi and vice versa. Language translation is one task in which machines lag behind human power [1]. One task where machines fall short of human ability is language translation. Rule-Based Translation (RBT) systems and Statistical Machine Translation (SMT) systems are the conventional systems used for language translation. Rule Based Translation requires in-depth knowledge of the language. RBT is a fairly complicated system that can and must include many rules in order to improve quality. SMT is one of the traditional approaches to the machine translation issue. This technique works well with pairs of languages with comparable grammatical structures and requires enormous data sets. This paper proposes a better approach - a neural network model that uses “Recurrent Neural Network” (RNN) and “Gated Recurrent Unit” (GRU). The system consists of an RNN-encoder and RNN-decoder architecture and an attention mechanism to deal with long sentences.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128277442","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 Detailed Investigation and Analysis of Using Machine Learning Techniques for Thyroid Diagnosis 使用机器学习技术进行甲状腺诊断的详细调查与分析

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099542

N. K. Trivedi, R. Tiwari, A. Agarwal, Vinay Gautam

{"title":"A Detailed Investigation and Analysis of Using Machine Learning Techniques for Thyroid Diagnosis","authors":"N. K. Trivedi, R. Tiwari, A. Agarwal, Vinay Gautam","doi":"10.1109/ESCI56872.2023.10099542","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10099542","url":null,"abstract":"A Method of Classification Based on Norms Data mining greatly benefits several subfields within the healthcare industry. Detecting and treating diseases at an early stage is a challenging but essential objective in the healthcare field. If they are discovered early enough, many diseases can be diagnosed and treated while they are still in their early stages. Conditions that affect the thyroid are one example of this type of example. In the past, thyroid disorders were identified through a process that involved observing a patient's symptoms and doing a battery of blood tests. The primary goal is to enhance the accuracy with which diseases are detected in the initial stages of their progression. The healthcare business may gain a significant amount from using data mining techniques for decision-making, disease diagnosis, and the provision of superior treatment to patients at reduced prices. Thyroiditis is ongoing. The act of classifying things into different groups is significant. This study aims to determine the connection between TSH, T3, and T4 and hyperthyroidism and hypothyroidism. It also tries to determine the relationship between TSH, T3, T4, and gender. Additionally, the research will attempt to predict thyroid disease using several classification systems. Our study shows that the Neural network classifier generates the highest classification accuracy of 98.4%.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133569461","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

Malware Detection Using Efficientnet 使用Efficientnet检测恶意软件

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099693

Sandip Shinde, Aditya Dhotarkar, Dhanshree Pajankar, Kshitij Dhone, Sejal Babar

引用次数: 0

Automatic Question Generation from Textual data using NLP techniques 使用NLP技术从文本数据自动生成问题

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10100278

Snehal R. Rathi, Pawan Wawage, Amrut Kulkarni

引用次数: 0

Multi-Classification of Non-Proliferative Diabetic Retinopathy Through Integrated Machine Learning Approach in Fundus Images 基于眼底图像集成机器学习的非增殖性糖尿病视网膜病变多分类

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10100091

S. R, S. S, Thangerani Raajaseharan

{"title":"Multi-Classification of Non-Proliferative Diabetic Retinopathy Through Integrated Machine Learning Approach in Fundus Images","authors":"S. R, S. S, Thangerani Raajaseharan","doi":"10.1109/ESCI56872.2023.10100091","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10100091","url":null,"abstract":"Diabetic Retinopathy is an ocular sickness resulting in the visual disability, the treatment and cure of this eye disease becomes comfort if the disease is identified at the earliest. The present study conceives an integrated machine learning approach for the multi-level multi-classification of the earliest stage of diabetic retinopathy called Non-Proliferative Diabetic Retinopathy. At the first level, the disease features are classified and at the second level, the disease severities are classified. The implementation of the work ensues with the fundus images undergoing grayscale conversion and median filter for preprocessing. Then, the statistical feature vectors like local binary patterns, histogram of gradients, and gray level co-occurrence matrix are extracted and fed into a multi-class support vector machine for classifying the non-Proliferative diabetic retinopathy disease features called microaneurysm, intra-retinal hemorrhages, and hard exudates. The classified features are classified into non-proliferative-diabetic-retinopathy disease severities namely mild, moderate and severe with the k-Nearest neighbor, random forest, and naive bayes methods. The proposed classifiers are assessed and validated in terms of accuracy and execution time; comparatively the k-Nearest neighbor classifier achieved a better result of 99% accuracy and the least processing time.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133463981","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

Genetic Algorithm Based Energy Efficient and Load Balanced Clustering Approach for WSN 基于遗传算法的WSN高效负载均衡聚类方法

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099987

A. Shinde, R. Bichkar

{"title":"Genetic Algorithm Based Energy Efficient and Load Balanced Clustering Approach for WSN","authors":"A. Shinde, R. Bichkar","doi":"10.1109/ESCI56872.2023.10099987","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10099987","url":null,"abstract":"Consumption of energy in the wireless sensor networks is major constrain that restrict the impact of the application. It becomes crucial when a more nodes are deployed. Several energy-efficient solutions have been proposed by many researchers. Clustering is one of the most energy-efficient solution that has been proven for the large-size network. However, the performance of the clustering algorithm degrades because of the non-uniform cluster formation and non-uniform cluster heads distribution over the network. To resolve this problem, a Energy Efficient and Load Balanced Clustering Approach for Wireless Sensor Network Using Genetic Algorithm is presented in this paper. The proposed algorithm not only focused on the load balancing and uniform distribution of cluster head but also on the optimal cluster head selection which considers residual energy, inter-cluster, and intra-cluster communication distance. The performance parameters like, lifetime of the network and energy consumption of the proposed algorithm is analyzed with the existent algorithms. The outcomes of the experiment demonstrated that the presented algorithm performs better than the existent algorithms.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132437553","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

IOT Based Smart LandSlide Detection System (S-LDS) 基于物联网的智能滑坡检测系统(S-LDS)

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099562

Amruta Amune, Swapnil Patil, Devyani Ushir, Akshata Nangare

引用次数: 0

Alphabet Recognition using Air written Trajectories 使用空气书写轨迹的字母表识别

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099805

J. Karbhari, P. Mukherji

{"title":"Alphabet Recognition using Air written Trajectories","authors":"J. Karbhari, P. Mukherji","doi":"10.1109/ESCI56872.2023.10099805","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10099805","url":null,"abstract":"The enormous potential use of air-writing recognition in intelligent systems has made it highly popular. Some of the most fundamental issues in isolated writing are yet to be fully addressed. Writing a linguistic character or word in free space using a finger, marker, or handheld device is referred to as a trajectory-based writing method. It can be used where traditional pen-up and pen-down writing techniques are inconvenient. It has a significant upper hand over the gesture-based approach due to its simple writing style. However, because of the diverse characters and writing styles, it is a difficult process. In this paper, an alphabet recognition system for alphabets written in air, where the alphabet is recognised based on air trajectories which are three-dimensional (3D) and gathered by a single camera in this study. A reliable and effective colour-based segmentation is proposed to extract air recorded trajectories gathered by a standard web camera,. This solves the problem of push-to-write by removing limits on users' writing without the usage of an illusory box. The trajectory is normalized for improved recognition using convolutional neural network (CNN). We achieve recognition in real time with a high accuracy of 95% and negligible neural network complexity. It beats and surpasses the currently used techniques that involvewritten images as input.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127779289","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 Comprehensive Review of Machine Learning for Financial Market Prediction Methods 金融市场预测方法的机器学习综述

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099791

R. M. Dhokane, O. P. Sharma

引用次数: 1

Critical Analysis of Potato (Solanum Tuberosum) on Indian Overall Economy using Analytic Hierarchy Process 运用层次分析法对马铃薯(Solanum Tuberosum)对印度整体经济的关键性分析

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099483

S. Toney, Pathan Mohd. Shafi, P. Dhotre

引用次数: 0