2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)最新文献_第10页

High-speed Camera Motion Capture and Essence Extraction Algorithm in the Context of Feature Extraction 特征提取背景下的高速摄像机运动捕捉与精华提取算法

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010785

You Lin

引用次数: 0

Grid-tied Rooftop Solar PV System with the Integration of Smart Metering Scheme 集成智能电表方案的并网屋顶太阳能光伏系统

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10011020

Ahsan Kabir Nuhel, Md Rifat Al Jayed Utsho, Muhammad Al Amin, F. Rafi, Mir Mohibullah Sazid, Priyadarshini Hriddhi Roy

引用次数: 0

Modular Type Beach Cleaning Robot “Clean-B” 模块化沙滩清扫机器人“Clean-B”

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010711

Arafa Omer Qasim, Ajai Antoney Varghese, Arjun Sarkar, Saji Justus

引用次数: 1

A Review on Natural Language Processing based Automatic Question Generation 基于自然语言处理的自动问题生成研究进展

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010799

Pushpa M. Patil, R. Bhavsar, B. Pawar

{"title":"A Review on Natural Language Processing based Automatic Question Generation","authors":"Pushpa M. Patil, R. Bhavsar, B. Pawar","doi":"10.1109/ICAISS55157.2022.10010799","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010799","url":null,"abstract":"The advent of the Internet resulted in availability of e-content in huge quantities; this e-content includes information in different domains. This information is being exploited for various reasons and applications. As the formal evaluation and assessment techniques are undergoing transformations, there is also a need for a voluminous Question Bank (QB). The manual creation of questions is a time-consuming and expensive task as it requires domain experts and there is a growing trend towards question bank based question paper generation for assessment. Hence the problem of automatic question generation has attracted attention of the Natural Language Processing (NLP) research community; this problem can be handled by NLP. Automatic generation of high-quality questions is the long-term goal of the Question Generation (QG) research community. The automatic question generation aims to generate all possible questions from the input text or document. This survey article presents the issues, challenges and approaches as well as reviews the reported research work in the context of automatic question generation for different languages at national and international level.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124993304","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

Cloud Based Electrical Power Management System Using JDBC 基于JDBC的云电源管理系统

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010731

N. Rathore, Jarabala Ranga, B. Swapna, M. Veerraju, Krishna Tomar, Ayan Banik

{"title":"Cloud Based Electrical Power Management System Using JDBC","authors":"N. Rathore, Jarabala Ranga, B. Swapna, M. Veerraju, Krishna Tomar, Ayan Banik","doi":"10.1109/ICAISS55157.2022.10010731","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010731","url":null,"abstract":"Electricity is one of the most important features in life and it is the predominant part of life as most of our life is dependent on this only and electricity play a predominant role in the day-to-day activities. So, maintaining the electricity and the post-production through the unit of power consumption should be clear and neat. This necessitates the need to develop an engaging system that connects to the database and work flawlessly 24/7. The proposed system made the work easier and ensure full attention. The electricity bill management system effortlessly brings down the manpower and it produces a friendly environment between the consumer and admin. The proposed system uses Java for the front end and SQL for the back end. SQL is one of the leading platforms for the database. This doesn't need any mastery and they can be easily adapted within a past time. The proposed system is used to control the power consumption by the user by calculating the number of units. Thus the front end of the proposed system is designed by Java to enhance the feature of the system. As most of the systems are deployed with simple features this provides a higher version of credit to the system.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122081629","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

MDCLCG with Square Root Carry Select Adder Technique for Hardware Security 基于平方根进位选择加法器技术的MDCLCG硬件安全

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010741

M. Sushmitha, K. Jamal, M. Kiran, O. V. P. Kumar Manchalla, Ch Pratyusha Chowdari

{"title":"MDCLCG with Square Root Carry Select Adder Technique for Hardware Security","authors":"M. Sushmitha, K. Jamal, M. Kiran, O. V. P. Kumar Manchalla, Ch Pratyusha Chowdari","doi":"10.1109/ICAISS55157.2022.10010741","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010741","url":null,"abstract":"Three-operand adder performs the modular arithmetic operations like addition, multiplication and exponentiation by utilizing various cryptography algorithms. Here, the pseudo-random bit generator algorithm is used to perform addition operation. It performs in binary format and reduces the area, delay, power and increases the speed. In this adder application purpose, the MDCLCG is used to increase the hardware security and light-weighted core. In comparison to all other LCGs and present PBRG techniques, MDCLCG is the more secure and extremely random PRBG approach. The existing MDCLCG can work on the increased operand size but it does not perform well with the three-operand adder to improve the performance. Hence, the SRCSA in integrated to the MDCLCG to obtain better result than existing architectures. Square-Root Carry Save Adder (SRCSA) is one of the simplest techniques used to sequentially add all N partial products by using N-1 adders. This research study intends to improve the implementation of MDCLCG with three-operand binary adder technique for hardware security. The novel MDCLCG architecture can execute 32-bits in Xilinx tool to obtain a better simulation and synthesis result. This architecture is used in addition to the LCGs, FIR and IIR filters, ALU processor, randomness-based verification, etc. These adders execute 8-bits, 16-bits, 32-bits, 64-bits and 128-bits architecture and it is then implemented by using Verilog-HDL and further the synthesis shows the report of less area, less power consumption and high speed with reduced delay than existing architectures.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123234768","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

Automated Hyperparameter Tuned Deep Learning Enabled Reactive Power Optimization Model for Power Distribution System 基于自动化超参数调谐深度学习的配电系统无功优化模型

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010960

S. Sivasakthi, K. M. Devi, P. Yamunaa, N. Mahendran, R. Prakash, A. Vigneshwar, B. Jegajothi

{"title":"Automated Hyperparameter Tuned Deep Learning Enabled Reactive Power Optimization Model for Power Distribution System","authors":"S. Sivasakthi, K. M. Devi, P. Yamunaa, N. Mahendran, R. Prakash, A. Vigneshwar, B. Jegajothi","doi":"10.1109/ICAISS55157.2022.10010960","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010960","url":null,"abstract":"With a great quantity of Electric Vehicles and Distributed Generator (DG) complied in the power distribution system, the complications of distribution systems' function are higher, which generates the superior need for online Reactive Power Optimization (RPO). The RPO is a distribution network that could enhance the quality of voltage and the economical function, and diminish the power losses of a dispersal network. RPO could understand rational dispersal of reactive power in the dispersal network and decrease the node voltage deviations and power losses. Currently, only a few heuristic intellectual methods are broadly employed for RPO. Therefore, this article introduces a new Jellyfish Search Optimization with Deep Stacked Autoencoder (JSO-DSAE) model for RRO in power distribution systems. The proposed JSO-DSAE model enables the DSAE model to receive previous data from DGs to identify the connection among power control and system characteristics. To bolster the performance of the JSO-DSAE algorithm, the JSO method is used. The experimental validation of the JSO-DSAE model is tested and the outcomes are examined over distinct aspects. The simulation outcome demonstrated the supremacy of the JSO-DSAE model over the recent approaches.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128331816","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

Prediction of Rock and Mineral from Sound Navigation and Ranging Waves using Artificial Intelligence Techniques 利用人工智能技术从声导航和测距波中预测岩石和矿物

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10011104

Akshat Khare, Kanchana Mani

{"title":"Prediction of Rock and Mineral from Sound Navigation and Ranging Waves using Artificial Intelligence Techniques","authors":"Akshat Khare, Kanchana Mani","doi":"10.1109/ICAISS55157.2022.10011104","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10011104","url":null,"abstract":"Since sound waves penetrate the sea more deeply than radar and light waves, SONAR (Sound Navigation and Ranging) is used to explore and map the ocean. When working in the mining industry, engineers may find SONAR to be an invaluable tool for helping them visualize the location of rocks and minerals by charting frequency signals. Assuming an object is within the sound pulse's range, the sound pulse will reflect off the target and send an echo in the direction of the sonar transmitter if the target is within the range of the sound pulse. The transmitter uses the power source to receive signals and figure out how strong the signals are. It establishes the pause in time between the generation of the pulse and the receiving of its corresponding signal. It analyzes the duration between the emission of the pulse and its matching reception, which estimates the distance and location of the matter. Engineers determine the item using an audio wave. With the assistance of AI, the process of evaluating, organizing, and identifying the item is going to be circumvented in order to accomplish the objectives of immediately identifying the item based on the scheduled bandwidths. In this proposed method, PCA and t-SNE are employed to extract features. Utilizing classification approaches such as Logistic Regression and Random Forest Tree, an accuracy of 72% and 91%, respectively, was attained. Similarly, CNN and LSTM models are also employed and finally they have yielded an accuracy of about 80.77% and 99% respectively.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129484285","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

Web Scraping Technique for Prediction of Air Quality through Comparative Analysis of Machine Learning and Deep Learning Algorithm 基于机器学习和深度学习算法对比分析的网络抓取技术预测空气质量

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010968

G. Kalaivani, S. Kamalakkannan

{"title":"Web Scraping Technique for Prediction of Air Quality through Comparative Analysis of Machine Learning and Deep Learning Algorithm","authors":"G. Kalaivani, S. Kamalakkannan","doi":"10.1109/ICAISS55157.2022.10010968","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010968","url":null,"abstract":"Air contamination has turned into a significant and difficult issue all over the planet and its direct impact with human well-being has drawn a lot of consideration from numerous analysts. Individuals are turning out to be known better ways of checking air quality data which are essential to safeguard human wellbeing from the genuine medical conditions brought about via air contamination. Numerous specialists are working on current air quality observation and expectations to carry out different government arrangements connected with the climate or air contamination and give precise outcomes to assist with settling on significant choices. This paper employs a machine learning method to implement predictive analytics and create a more accurate prediction model. These models are created by analysing trends and patterns using historical time series data and then creating a prediction model to forecast future values. These prediction models will be used to execute our suggested approach, the Air Quality Prediction Model (AQPM). This model yields a prediction model that accurately predicts the Air Quality Index (AQI) through the data collected. The information will be scraped from the Central Pollution Control Board (CPCB) website using the web scraping technique. The comparative analysis of ML and DL suggests that Long Short-Term Memory (LSTM) is the best fit model to measure air quality using three different accuracy metrics. Finally, the data are analysed using the predicted AQI in the LSTM model.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"41 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129692005","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

Deep Learning Techniques for Dental Image Diagnostics: A Survey 牙科图像诊断的深度学习技术:综述

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010576

D. Salunke, Dr. Ram Joshi, Dr. Prasdu Peddi, Dr. D. T. Mane

{"title":"Deep Learning Techniques for Dental Image Diagnostics: A Survey","authors":"D. Salunke, Dr. Ram Joshi, Dr. Prasdu Peddi, Dr. D. T. Mane","doi":"10.1109/ICAISS55157.2022.10010576","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010576","url":null,"abstract":"Nowadays, due to advancement in computer technology, there is an interest amongst researcher for use of Artificial Intelligence in medical field. Deep learning computational models are made out of various layers to find significant patterns from enormous images. Therefore, Deep learning techniques like CNN, R-CNN, LSTM were increasingly used in medical image diagnosis. CNN had proved to have noteworthy forthcoming to help specialists in different clinical fields. This growing trend of using CNN has also ventured into dental study. Various CNN architectures were used in dentistry like u-net, ResNet, VGG16, AlexNet for dental disease classification, tooth classification, caries detection, tooth segmentation. The motivation behind this survey paper is to visualize the best in class of deep learning techniques primarily CNN in dental applications/dentistry, such as the detection of caries, teeth, vertical root fracture, filled teeth, dental implants, and crown treatment. This will help researchers who are just starting out in dentistry field to grasp the various deep learning algorithms for dental disease classification and their performance metrics. Keywords: Artificial intelligence, CNN, dental application, images, classification, performance evaluation","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131218344","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