2022 5th International Conference on Advances in Science and Technology (ICAST)最新文献_第10页

Breast Cancer Classification by Implementation of Deep-Learning with Dataset Analysis 基于数据集分析的深度学习实现乳腺癌分类

2022 5th International Conference on Advances in Science and Technology (ICAST) Pub Date : 2022-12-02 DOI: 10.1109/ICAST55766.2022.10039480

Saheel Patil, Akshay Pashte, Satyam Rai, Sejal Shah

{"title":"Breast Cancer Classification by Implementation of Deep-Learning with Dataset Analysis","authors":"Saheel Patil, Akshay Pashte, Satyam Rai, Sejal Shah","doi":"10.1109/ICAST55766.2022.10039480","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039480","url":null,"abstract":"Cancer is a fatal disease recognized and researched about, around the globe. Researchers and scientists have been investing their time and imparting their expertise, and knowledge for the advancements of traditional methods and treatments to tackle it. Recent surveys reveal that the mortality rate among the female populous, over the world, is also one of the results of breast cancer. The definition of breast cancer can be described as an uncontrolled aggressive growth of old cells which thereby aid the formation of a pernicious mass in the tissue of a breast. Gradually, this may result in the formation of a tumor of malignant nature. Deep learning, considered a sub-field of Machine Learning, enables experts to analyze, model, and study complicated or rather complex scientific data over a comprehensive list of medical applications. This study aims to create a user-friendly, adept system to perform the classification of breast tumors of malignant or benign nature. The proposed system is divided into two halves or stages. The initial stage is the pre-processing and analysis of the acquired dataset which also involves training of the neural network. The next and final stage is the classification of breast tumors by utilizing the created model and loading it onto an API through which users can upload tissue images and check what type of breast cancer the tissue contains. This would eliminate the time spent on studying every particular data using traditional clinical methods. This project would help support the radiologists in training, research, and diagnostic aspects and overall support the entire process of cancer diagnosis and treatment.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134483087","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

Artificial Intelligence based water Management System 基于人工智能的水管理系统

2022 5th International Conference on Advances in Science and Technology (ICAST) Pub Date : 2022-12-02 DOI: 10.1109/ICAST55766.2022.10039523

N. Ingle, Siddhant Deepak Sable, D. P. Ghadge, Sarika Y. Mane

{"title":"Artificial Intelligence based water Management System","authors":"N. Ingle, Siddhant Deepak Sable, D. P. Ghadge, Sarika Y. Mane","doi":"10.1109/ICAST55766.2022.10039523","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039523","url":null,"abstract":"The world is facing a water crisis. The lack of water resources is a major challenge for the health and wellbeing of the world's population. This project aims to develop an artificial intelligence based water management system to optimize water resources. The system will provide a platform for water users and water managers to access information, solve problems and make informed decisions for water resource management. Resources of water management involve the supply, allocation and use of water, and the impact of these factors on ecosystems and human well-being. The overall goal of this project is to provide a platform for data to be stored, analyzed, and presented in a user-friendly way. The system will also be able to predict future water resource usage and monitor the status of water resources. The data will be provided by sensors, which will provide the data for the artificial intelligence system. This project will involve the creation of an artificial intelligent system that will be able to predict the future quality of water resources using a combination of data from sensors in the field and artificial intelligence. The artificial intelligent system will be utilized on a water quality management system such as a water treatment plant. The project will also involve the use of artificial intelligence based sensors, which will be capable of detecting water quality and producing a visual representation in the form of graphs on a tablet or PC screen. The data from the sensors will be inputted into the artificial intelligence system.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125096919","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

Vedic Multiplier Using Carry look ahead adder 吠陀乘数使用进位向前加法器

2022 5th International Conference on Advances in Science and Technology (ICAST) Pub Date : 2022-12-02 DOI: 10.1109/ICAST55766.2022.10039667

Jayesh Suryawanshi, Deepak Gawade, Nidhi Tank, Shreya Worlikar, Shridhar Sahu

引用次数: 0

IOT based Research Proposal on Water Pump Automation System for Turbidity, Pipeline Leakage and Fluid Level Monitoring 基于物联网的浊度、管道泄漏和液位监测水泵自动化系统研究方案

2022 5th International Conference on Advances in Science and Technology (ICAST) Pub Date : 2022-12-02 DOI: 10.1109/ICAST55766.2022.10039633

Prasad Anand Apte, Shaikh Mohammad Bilal Naseem

引用次数: 0

Sugarcane Disease Detection using Deep Learning 基于深度学习的甘蔗病害检测

2022 5th International Conference on Advances in Science and Technology (ICAST) Pub Date : 2022-12-02 DOI: 10.1109/ICAST55766.2022.10039670

Vaishali Wadhe, Rashmi Dongre, Yash Kankriya, Anish Kuckian

引用次数: 0

Deep Learning Approach for Mammographic Breast Density Classification and Cancer Risk Prediction 乳房x线摄影乳腺密度分类和癌症风险预测的深度学习方法

2022 5th International Conference on Advances in Science and Technology (ICAST) Pub Date : 2022-12-02 DOI: 10.1109/ICAST55766.2022.10039600

Dharmik Joshi, A. Gaonkar, J. Bharambe, Abhijit Patil

{"title":"Deep Learning Approach for Mammographic Breast Density Classification and Cancer Risk Prediction","authors":"Dharmik Joshi, A. Gaonkar, J. Bharambe, Abhijit Patil","doi":"10.1109/ICAST55766.2022.10039600","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039600","url":null,"abstract":"Breast cancer is one among the various vulnerable types of cancer, after skin cancer and lung cancer. Although deaths from breast cancer have decreased over the years, it is still the major leading causes of women deaths of all races. Many research efforts have been taken to prevent breast cancer by using different breast cancer biomarkers in the last few decades. “Mammographic Breast Density” is amongst various significant markers utilized for the prevention of breast cancer. As there is an increase in the “Mammographic Breast Density”, the mammograms sensitivity also decreases causing wrong prediction of breast cancer. The primal motive behind this article is to study all the research innovations for Mammographic Breast Density classification. This survey article covered all Deep Learning methods proposed for mammographic breast density classification. From 2010-2017 there is an inclination towards the Machine Learning approach, and from 2017 onwards, there is more research inclination towards the Deep Learning approach. Statistics of classification accuracy of Deep Learning is in between 86%-98.87%. Due to the variations, no methods were found so precise and accurate. Hence, current mammographic breast density assessment is subjective, thus raising the need to develop an accurate and accurate mammographic Breast Density classification tool suitable for clinical practice. Implementing a successful CAD system for breast density classification is a social need and can act as a supporting mechanism for the precise classification of mammograms. More research efforts are required in this area to reduce faulty predictions.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129451875","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

An Innovative Approach of Personality Recognition for E-Recruitment 面向电子招聘的个性识别创新方法

2022 5th International Conference on Advances in Science and Technology (ICAST) Pub Date : 2022-12-02 DOI: 10.1109/ICAST55766.2022.10039605

Priyanka R Kamble, U. Kulkarni

{"title":"An Innovative Approach of Personality Recognition for E-Recruitment","authors":"Priyanka R Kamble, U. Kulkarni","doi":"10.1109/ICAST55766.2022.10039605","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039605","url":null,"abstract":"The field of online recruitment systems is becoming more popular in Artificial Intelligence because it is beneficial for both candidates and interviewers as it saves time and energy. In the manual process of recruitment, fitting the job specifications according to the resume and selecting the perfect candidate as per their behavior is a difficult task. With uses in psychiatric evaluations, human operator, and personality computing, automatic analysis of video interviews and automatic extraction of resumes for recognizing personality traits has consequently emerged as an important research subject. Convolutional neural network (CNN) models were introduced in some earlier studies as a result of developments in Deep Learning (DL)-based computer vision and pattern recognition. These models are capable of accurately predicting human non-verbal cues when used in conjunction with a web camera. In this paper, the candidate and interviewer both can achieve their goals by the one system. As per job specification included in the resume, candidates can get clarification of the job title and test their own personality by giving a psychometric assessment included in the system. The end-to-end AI interviewing system is developed with the aid of asynchronous video interview (AVI) processing, and automatic personality identification (APR) is carried out using features gleaned from the AVIs by the Tensorflow AI engine. The result shows that the interviewer can successfully recognize the Big five personality traits of a candidate at an accuracy above 95%. In the automatic personality recognition the semi supervised DL approach gives better performance.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123109596","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

Security Challenges in 5G Network: A technical features survey and analysis 5G网络的安全挑战:技术特征调查与分析

2022 5th International Conference on Advances in Science and Technology (ICAST) Pub Date : 2022-12-02 DOI: 10.1109/ICAST55766.2022.10039654

Sanjay M. Vidhani, A. Vidhate

引用次数: 3

Vulnerabilities and Threat Management in Relational Database Management Systems 关系型数据库管理系统中的漏洞和威胁管理

2022 5th International Conference on Advances in Science and Technology (ICAST) Pub Date : 2022-12-02 DOI: 10.1109/ICAST55766.2022.10039599

Nisha Gharpure, Aradhana Rai

{"title":"Vulnerabilities and Threat Management in Relational Database Management Systems","authors":"Nisha Gharpure, Aradhana Rai","doi":"10.1109/ICAST55766.2022.10039599","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039599","url":null,"abstract":"Databases are at the heart of modern applications and any threats to them can seriously endanger the safety and functionality of applications relying on the services offered by a DBMS. It is therefore pertinent to identify key risks to the secure operation of a database system. This paper identifies the key risks, namely, SQL injection, weak audit trails, access management issues and issues with encryption. A malicious actor can get help from any of these issues. It can compromise integrity, availability and confidentiality of the data present in database systems. The paper also identifies various means and ways to defend against these issues and remedy them. This paper then proceeds to identify from the literature, the potential solutions to these ameliorate the threat from these vulnerabilities. It proposes the usage of encryption to protect the data from being breached and leveraging encrypted databases such as CryptoDB. Better access control norms are suggested to prevent unauthorized access, modification and deletion of the data. The paper also recommends ways to prevent SQL injection attacks through techniques such as prepared statements.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115864541","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

Video Captcha Proposition based on VQA, NLP, Deep Learning and Computer Vision 基于VQA、NLP、深度学习和计算机视觉的视频验证码命题

2022 5th International Conference on Advances in Science and Technology (ICAST) Pub Date : 2022-12-02 DOI: 10.1109/ICAST55766.2022.10039625

E. Johri, Leesa Dharod, Rasika Joshi, Shreya Kulkarni, V. Kundle

{"title":"Video Captcha Proposition based on VQA, NLP, Deep Learning and Computer Vision","authors":"E. Johri, Leesa Dharod, Rasika Joshi, Shreya Kulkarni, V. Kundle","doi":"10.1109/ICAST55766.2022.10039625","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039625","url":null,"abstract":"Visual Question Answering or VQA is a technique used in diverse domains ranging from simple visual questions and answers on short videos to security. Here in this paper, we talk about the video captcha that will be deployed for user authentication. Randomly any short video of length 10 to 20 seconds will be displayed and automated questions and answers will be generated by the system using AI and ML. Automated Programs have maliciously affected gateways such as login, registering etc. Therefore, in today's environment it is necessary to deploy such security programs that can recognize the objects in a video and generate automated MCQs real time that can be of context like the object movements, color, background etc. The features in the video highlighted will be recorded for generating MCQs based on the short videos. These videos can be random in nature. They can be taken from any official websites or even from your own local computer with prior permission from the user. The format of the video must be kept as constant every time and must be cross checked before flashing it to the user. Once our system identifies the captcha and determines the authenticity of a user, the other website in which the user wants to login, can skip the step of captcha verification as it will be done by our system. A session will be maintained for the user, eliminating the hassle of authenticating themselves again and again for no reason. Once the video will be flashed for an IP address and if the answers marked by the user for the current video captcha are correct, we will add the information like the IP address, the video and the questions in our database to avoid repeating the same captcha for the same IP address. In this paper, we proposed the methodology of execution of the aforementioned and will discuss the benefits and limitations of video captcha along with the visual questions and answering.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115414470","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