2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)最新文献_第9页

Exploring the Effectiveness of Optimized Convolutional Neural Network in Transfer Learning for Image Classification: A Practical Approach 探索优化卷积神经网络在图像分类迁移学习中的有效性:一种实用方法

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141701

Srinivasa Rao Burri, S. Ahuja, Abhishek Kumar, Anupam Baliyan

{"title":"Exploring the Effectiveness of Optimized Convolutional Neural Network in Transfer Learning for Image Classification: A Practical Approach","authors":"Srinivasa Rao Burri, S. Ahuja, Abhishek Kumar, Anupam Baliyan","doi":"10.1109/InCACCT57535.2023.10141701","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141701","url":null,"abstract":"Transfer learning is a popular deep learning technique that involves fine-tuning a pre-trained CNN model on a new dataset to improve accuracy and speed. This article examines the effectiveness of transfer learning techniques in image classification tasks using CNNs. The paper reviews recent studies on transfer learning techniques, including their use in medical image analysis applications such as COVID-19 detection and Alzheimer’s disease classification. The study discusses the ImageNet dataset as a benchmark for pretraining CNN models and proposes an optimized CNN model that uses various optimization techniques to improve performance and efficiency. The article also includes a comparison table of various image classification techniques, including CNN, RNN, SVM, RF, and optimized CNN, with the optimized CNN offering the best performance and computational efficiency. The study emphasizes the importance of selecting the appropriate technique for specific applications based on factors such as available hardware and desired tradeoff between training time and prediction time. Overall, transfer learning techniques are shown to be effective in image classification tasks, particularly when labeled data is limited.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131963984","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: 4

Mobile Health Applications towards Sustainable Healthcare: A Healthcare Professionals’Perspective 面向可持续医疗保健的移动医疗应用:医疗保健专业人员的观点

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141765

Surya Bahadur Thapa, Aditi Rajput, A. Gandhi, R. Raman

{"title":"Mobile Health Applications towards Sustainable Healthcare: A Healthcare Professionals’Perspective","authors":"Surya Bahadur Thapa, Aditi Rajput, A. Gandhi, R. Raman","doi":"10.1109/InCACCT57535.2023.10141765","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141765","url":null,"abstract":"The objective of the study is to explore and examine the contextual factors towards the long-term sustainability of mobile health applications, as well as determine the elements influencing the effective implementation of mHealth technology from the perspective of healthcare providers. The basic idea of this paper is to include multi-disciplinary commentaries of healthcare professionals to evaluate the sustainability aspects of mHealth applications. The study is based on qualitative semi-structured interviews with healthcare experts and employs a Grounded Theory approach to explore and assess the efficacy and long-term sustainability of mHealth applications. A total of 12 healthcare practitioners were interviewed for the study. They were healthcare professionals, including medical practitioners and clinical consultants, as well as health researchers, academicians, specialists, and suppliers of healthcare apps. The findings depict that mHealth technology is widely beneficial in practices for healthcare management in the public health domain. To achieve sustainability of mHealth and realise its potential in public health governance, this assessment points out an integrated approach covering healthcare practitioners’ concerns and contextual considerations for effective implementation, sustainability, and scale-up of mHealth interventions.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"652 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132703839","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

Analysis Of Inflectional Behaviour In Indian Languages Using Features Extraction Techniques 用特征提取技术分析印度语的屈折变化行为

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141783

Bhairab Sarma, C. Nath

{"title":"Analysis Of Inflectional Behaviour In Indian Languages Using Features Extraction Techniques","authors":"Bhairab Sarma, C. Nath","doi":"10.1109/InCACCT57535.2023.10141783","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141783","url":null,"abstract":"Compared to English, Indian languages are highly inflectional in nature. Features extraction is a challenging task for Indian languages due to multiple reasons. First, alphabets called ‘Akshara’ are coded with Unicode unlike English, which is coded with ASCII. Second, upon inflection, the structure of the root word gets changed to a different format. Words get modified according to their added features as per tense, aspect, and modality. Thirdly, composite characters called ‘yuktAkshara’ are influenced with additive vowels or consonants. With these three prospects, this paper is aimed to address some practical difficulties for stemming root words with experimental reviews. Feature extraction is used in hidden information retrieval, root word stemming, text-to-speech conversion, and semantic analysis of Natural Language Processing. Analyzing features from an inflected word of Unicode language, one can recover the semantic and pragmatic meaning of the written text and further can be used in text-to-speech conversion. This paper discusses various techniques of feature extraction and its applications in some Indian languages.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132047087","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

Machine and Deep learning in Biometric Authentication: A Review 生物识别认证中的机器和深度学习:综述

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141692

Divya Singla, Neetu Verma

引用次数: 0

Analysis of Data Mining Algorithms in Market Basket Analysis 市场购物篮分析中的数据挖掘算法分析

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141816

Anshika Sharma, Himanshi Babbar

{"title":"Analysis of Data Mining Algorithms in Market Basket Analysis","authors":"Anshika Sharma, Himanshi Babbar","doi":"10.1109/InCACCT57535.2023.10141816","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141816","url":null,"abstract":"Data mining is the process of sorting massive volumes of data to uncover patterns and trends that could be utilized in data analysis to help solve business problems. Due to data mining skills and equipment, businesses can help in predicting and making more informed decisions. This paper has described several aspects of data mining and data mining technology. Market basket analysis (MBA) is one of the main applications of the data mining environment that this study primarily focuses on. Marketers frequently utilise MBA, a type of analytical technique, to comprehend the purchasing habits of their customers. The goal of the MBA is to find the similarities between similar products that are bought simultaneously as well as the co-occurring patterns. The association rule technique is used to do this. By identifying the commodities that buyers commonly combine, MBA helps businesses increase their sales and marketing strategies. Additionally, this study concentrates on distinct techniques for examining particular data mining trends. Analysis of the Apriori and Frequent Pattern (FP) Growth techniques performance revealed that 10000 transactions were required to analyze completion time, and a total of 5% support was required to examine Apriori and FP-Growth with a time reduction of 65%.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129736061","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 Review on diverse algorithms used in the context of Plagiarism Detection 论文抄袭检测中各种算法的综述

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141785

Anchal Pokharana, Urvashi Garg

{"title":"A Review on diverse algorithms used in the context of Plagiarism Detection","authors":"Anchal Pokharana, Urvashi Garg","doi":"10.1109/InCACCT57535.2023.10141785","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141785","url":null,"abstract":"Natural language processing is independent field of aI (artificial intelligence) that basically helps computer systems and mobile devices to understand, interpret and manipulate human language. This paper has been designed in three sections, in which section A is all about the basics of natural language processing, the technicalities and all its applications, section B is discussing about one of the major applications of natural language processing, which is plagiarism detection, in this section of paper we discussed about all possible techniques used by authors for detecting plagiarism. In section c we discussed the common findings and all key issues in the field of plagiarism, possible solution approaches and methodologies applied by different authors and compared them on different parameters. A detailed 5-stage review process has beenconducted for various research papers, in this we have sharply reviewed all the related work in last 20 years, extracted the main gaps and false situations in the research. With common findings we discussed all the strengths and shortcomings of the used methodologies.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"609 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133848713","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

Detecting Sentiment Polarities with Comparative Analysis of Machine Learning and Deep Learning Algorithms 用机器学习和深度学习算法的比较分析检测情感极性

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141741

Thi Ben, N. Ravikumar R, Poorna Chandra Reddy Alla, G. Komala, Krishnanand Mishra

{"title":"Detecting Sentiment Polarities with Comparative Analysis of Machine Learning and Deep Learning Algorithms","authors":"Thi Ben, N. Ravikumar R, Poorna Chandra Reddy Alla, G. Komala, Krishnanand Mishra","doi":"10.1109/InCACCT57535.2023.10141741","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141741","url":null,"abstract":"As technology develops, customer reviews are used to assess the quality of products due to the increasing number of selling products online. The extraction of useful minerals from reviews are extremely important for future buyers who are seeking thoughts and sentiments to help their decision-making. Sentiment polarity detection is the process of categorizing the emotions expressed with text, mainly to identify whether the subjectiveness of the writer’s attitude toward the product, or service is positive, neutral or negative. To decrease sentiment mistakes on increasingly complex training data, we deploy machine and hybrid learning models that integrate multiple types of deep neural networks in this study. Then, we apply TF-IDF vectorization for extraction of valuable information in reviews. The paper proposes the comparison of performance between machine learning models, deep learning models and the combination of deep learning models to discover the sentiment polarity on online product reviews. We use the dataset collected from an e-commerce website (Amazon), which includes various product reviews. The experimental results display that combination of deep learning models outperform more machine learning algorithms.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133166411","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

Early diabetes risk classification using supervised learning algorithms 基于监督学习算法的早期糖尿病风险分类

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141713

R. Deepa, M. Sakthivadivel, S. Saravanakumar, V. Ganesh Karthikeyan, S. Madumitha

{"title":"Early diabetes risk classification using supervised learning algorithms","authors":"R. Deepa, M. Sakthivadivel, S. Saravanakumar, V. Ganesh Karthikeyan, S. Madumitha","doi":"10.1109/InCACCT57535.2023.10141713","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141713","url":null,"abstract":"Diabetes is one of the most devastating diseases and affects many people. Diabetes can be caused by a variety of causes, including ageing, obesity, inactivity, genetics, a poor diet, high blood pressure, and others. Diabetes increases the likelihood of developing several illnesses, including heart disease, renal disease, stroke, eye problems, nerve damage, etc. The information needed to diagnose diabetes is currently gathered through a variety of tests used in hospitals, and the diagnosis is then used to determine the best course of treatment. The healthcare sector has a considerable application for machine learning (ML). Databases in the healthcare sector are very vast. Big datasets can be examined using ML techniques to find hidden information and patterns, allowing one to learn from the data and predict outcomes properly. Using the existing methods, the forecast’s accuracy is not very good. In this study, we proposed an early diabetes prediction model that incorporates several extrinsic characteristics that contribute to the development of diabetes together with more widely used measures like polyuria, weight loss, polyphagia, visual blurring, alopecia, obesity, etc. The Support Vector Machine (SVM), the Logistic Regression (LOR), the Boosted Tree (BOT), and the Bagged Tree (BAT) are four different classifiers that are utilized in this paper to predict diabetes early on. The device’s performance is assessed in terms of accuracy, recall, specificity, precision, and f-measure. Results show that among the classifiers, BAT has the highest accuracy, at 98%.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115180859","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

Analysing the Sentiments of a Higher Education Institute through Blogs 用博客分析高等教育学院的情绪

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141773

S. Vijayakumar Bharathi, Ajey Kumar, Dhanya Pramod

引用次数: 0

Platforms To Calculate Carbon Footprints: A Step Towards Environment Sustainability 计算碳足迹的平台:迈向环境可持续性的一步

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141821

Chinmayee Chatterjee, Rishab Gupta, Khushi Gupta, Nitasha Hasteer

引用次数: 0