首页 > 最新文献

Recent Trends in Intensive Computing最新文献

英文 中文
IoT Based Smart Cradle Using PI 基于物联网的智能摇篮使用PI
Pub Date : 2021-12-01 DOI: 10.3233/apc210268
Kannan P, A. Devaraj, B.Pradheep T Rajan, Swathira P K, Subhikshaa Jayaranim, Shebna V
In this modern era, parents are busy building their lifestyle, carrier etc. As we know it has now become hard because parents have to take care of their children simultaneously, which paves a lot of work pressure and family pressure especially for women. Health of the child is affected and better care has also reduced. So, in order to handle such situation, we use temperature, Humidity, ultra-sonic Sensor. The conditions of the external atmosphere help to detect increased body temperature, babies voice while crying and their movements while they are continuously moving and also indicates the time for the diaper to be changed. If there are any abnormal activities are observed in baby’s atmosphere. An alert message is sent to the parents. In this system a video camera is attached and operated under the microcontroller’s instruction and it records a video when the motion sensor detects any continuous movements. The recorded video is broadcasted in a display to the parents which helps them to monitor baby in live. And in addition, this system detects and displays the status of the infant and alert the respective guardian by collecting values from sensor like temperature sensor, ultrasonic sensor, and also the location value from raspberry pi.
在这个现代时代,父母忙于建立他们的生活方式,载体等。正如我们所知,现在已经变得很难了,因为父母必须同时照顾孩子,这给女性带来了很大的工作压力和家庭压力。儿童的健康受到影响,更好的护理也减少了。因此,为了处理这种情况,我们使用了温度、湿度、超声波传感器。外部环境的条件有助于检测体温升高,婴儿哭闹时的声音和他们不断移动时的动作,也可以指示换尿布的时间。如果观察到婴儿的大气有任何异常活动。警报消息被发送给家长。在该系统中,摄像机在单片机的指令下工作,当运动传感器检测到任何连续的运动时,摄像机就会记录下视频。录制的视频通过显示器播放给父母,帮助他们实时监控婴儿。此外,该系统通过采集温度传感器、超声波传感器等传感器的数据,以及树莓派的位置数据,检测并显示婴儿的状态,并提醒相应的监护人。
{"title":"IoT Based Smart Cradle Using PI","authors":"Kannan P, A. Devaraj, B.Pradheep T Rajan, Swathira P K, Subhikshaa Jayaranim, Shebna V","doi":"10.3233/apc210268","DOIUrl":"https://doi.org/10.3233/apc210268","url":null,"abstract":"In this modern era, parents are busy building their lifestyle, carrier etc. As we know it has now become hard because parents have to take care of their children simultaneously, which paves a lot of work pressure and family pressure especially for women. Health of the child is affected and better care has also reduced. So, in order to handle such situation, we use temperature, Humidity, ultra-sonic Sensor. The conditions of the external atmosphere help to detect increased body temperature, babies voice while crying and their movements while they are continuously moving and also indicates the time for the diaper to be changed. If there are any abnormal activities are observed in baby’s atmosphere. An alert message is sent to the parents. In this system a video camera is attached and operated under the microcontroller’s instruction and it records a video when the motion sensor detects any continuous movements. The recorded video is broadcasted in a display to the parents which helps them to monitor baby in live. And in addition, this system detects and displays the status of the infant and alert the respective guardian by collecting values from sensor like temperature sensor, ultrasonic sensor, and also the location value from raspberry pi.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127632215","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
Content Filtering of Social Media Sites Using Machine Learning Techniques 使用机器学习技术的社交媒体网站内容过滤
Pub Date : 2021-12-01 DOI: 10.3233/apc210226
U. Tambe, N.R. Kakad, S. Suryawanshi, S. S. Bhamre
To build a social network or social relations between people, we use social networking platforms like Facebook, Twitter, apps, etc. Using this media, users can share their views and opinions about a particular thing. Many people use their media for personal interests, entertainment, the market stocks, or business purposes. Nowadays, user security is the major concern for social networking sites. Online social networks give a little bit of support regarding content filtering. In this article, we proposed a system that provides security regarding malicious content that is posted on their social networking sites. To filter the content that might be unwanted messages, labeled images, or vulgar images, we proposed three level architecture. The user can use the auto-blocking facility as well.
为了在人与人之间建立社交网络或社会关系,我们使用社交网络平台,如Facebook, Twitter,应用程序等。使用这种媒体,用户可以分享他们对特定事物的看法和意见。许多人出于个人兴趣、娱乐、炒股或商业目的使用他们的媒体。如今,用户安全是社交网站的主要关注点。在线社交网络在内容过滤方面提供了一点支持。在本文中,我们提出了一个系统,该系统为发布在社交网站上的恶意内容提供安全性。为了过滤可能是不需要的消息、标记图像或低俗图像的内容,我们提出了三层架构。用户也可以使用自动阻塞功能。
{"title":"Content Filtering of Social Media Sites Using Machine Learning Techniques","authors":"U. Tambe, N.R. Kakad, S. Suryawanshi, S. S. Bhamre","doi":"10.3233/apc210226","DOIUrl":"https://doi.org/10.3233/apc210226","url":null,"abstract":"To build a social network or social relations between people, we use social networking platforms like Facebook, Twitter, apps, etc. Using this media, users can share their views and opinions about a particular thing. Many people use their media for personal interests, entertainment, the market stocks, or business purposes. Nowadays, user security is the major concern for social networking sites. Online social networks give a little bit of support regarding content filtering. In this article, we proposed a system that provides security regarding malicious content that is posted on their social networking sites. To filter the content that might be unwanted messages, labeled images, or vulgar images, we proposed three level architecture. The user can use the auto-blocking facility as well.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132614802","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
Fundus Image Classification Using Convolutional Neural Network 基于卷积神经网络的眼底图像分类
Pub Date : 2021-12-01 DOI: 10.3233/apc210277
U. Savitha, Kodali Lahari Chandana, A. Cathrin Sagayam, S. Bhuvaneswari
Different eye disease has clinical use in defining of the actual status of eye, in the outcome of the medication and other alternatives in the curative phase. Mainly simplicity, clinical nature are the most important requirements for any classification system. In the existing they used different machine learning techniques to detect only single disease. Whereas deep learning system, which is named as Convolutional neural networks (CNNs) can show hierarchical representing of images between disease eye and normal eye pattern.
不同的眼病在临床上用于确定眼睛的实际状态,在治疗阶段的药物治疗和其他替代方法的结果。简单性、临床性是任何分类系统最重要的要求。在现有的研究中,他们使用不同的机器学习技术来检测单一疾病。而深度学习系统,即卷积神经网络(cnn),则可以对病眼和正常眼之间的图像进行分层表示。
{"title":"Fundus Image Classification Using Convolutional Neural Network","authors":"U. Savitha, Kodali Lahari Chandana, A. Cathrin Sagayam, S. Bhuvaneswari","doi":"10.3233/apc210277","DOIUrl":"https://doi.org/10.3233/apc210277","url":null,"abstract":"Different eye disease has clinical use in defining of the actual status of eye, in the outcome of the medication and other alternatives in the curative phase. Mainly simplicity, clinical nature are the most important requirements for any classification system. In the existing they used different machine learning techniques to detect only single disease. Whereas deep learning system, which is named as Convolutional neural networks (CNNs) can show hierarchical representing of images between disease eye and normal eye pattern.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134017971","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
Aero Engine Performance Monitoring Using Least Squares Regression and Spectral Clustering 基于最小二乘回归和谱聚类的航空发动机性能监测
Pub Date : 2021-12-01 DOI: 10.3233/apc210217
Kunaal Saxena, M. Nene
Threshold-based flight data recorder analysis techniques have been widely used across the aerospace industry for fault detection and accident prevention. These techniques can detect pre-programmed events but fail to capture unknown patterns in the dataset. This research proposes a machine learning (ML) algorithm to analyze and detect unusual aero engine performance of a turboshaft engine mounted on a single engine rotorcraft. The performance is first modelled from an FDR dataset consisting of hundred flights, using least squares regression (LSR). A technique to scale the model by adding flight data from subsequent flights is thereafter discussed. Spectral Clustering is used for testing and validating the hypothesis derived from the regression model, by employing synthetically generated FDR data for twenty-five flights.
基于阈值的飞行数据记录器分析技术已广泛应用于航空航天工业的故障检测和事故预防。这些技术可以检测预编程事件,但无法捕获数据集中的未知模式。本研究提出了一种机器学习(ML)算法来分析和检测安装在单发动机旋翼机上的涡轴发动机的异常航空发动机性能。首先使用最小二乘回归(LSR)从包含数百个航班的FDR数据集对性能进行建模。然后讨论了一种通过添加后续飞行数据来缩放模型的技术。光谱聚类用于测试和验证从回归模型中得出的假设,通过使用合成生成的25次飞行的FDR数据。
{"title":"Aero Engine Performance Monitoring Using Least Squares Regression and Spectral Clustering","authors":"Kunaal Saxena, M. Nene","doi":"10.3233/apc210217","DOIUrl":"https://doi.org/10.3233/apc210217","url":null,"abstract":"Threshold-based flight data recorder analysis techniques have been widely used across the aerospace industry for fault detection and accident prevention. These techniques can detect pre-programmed events but fail to capture unknown patterns in the dataset. This research proposes a machine learning (ML) algorithm to analyze and detect unusual aero engine performance of a turboshaft engine mounted on a single engine rotorcraft. The performance is first modelled from an FDR dataset consisting of hundred flights, using least squares regression (LSR). A technique to scale the model by adding flight data from subsequent flights is thereafter discussed. Spectral Clustering is used for testing and validating the hypothesis derived from the regression model, by employing synthetically generated FDR data for twenty-five flights.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134209106","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
Blockchain Technology: Rising Trend in Various Applications 区块链技术:各种应用的上升趋势
Pub Date : 2021-12-01 DOI: 10.3233/apc210228
Zalte S. S, Patil P. N, Deshmukh S. N, Patil M. G, Dr. Pallavi Katkar
In this tech world, size of block chain is exponentially growing in this covid pandemic year which was not predicted. This pandemic environment causes digital transformation drive in various areas, particularly via the utilization of block chain or distributed ledger technology. To enhance and accelerate business process in various organization and industry showed a growing interest to adopt this technology. This paper summarized various block chain applications which are widely used in number of sectors and also focus on some challenges becomes hurdle while adopting block chain technology.
在这个科技世界里,区块链的规模在covid大流行的这一年呈指数级增长,这是没有预料到的。这种大流行的环境导致了各个领域的数字化转型,特别是通过利用区块链或分布式账本技术。为了增强和加快业务流程,各种组织和行业对采用该技术表现出越来越大的兴趣。本文总结了区块链在许多领域的广泛应用,并重点介绍了采用区块链技术所面临的一些挑战和障碍。
{"title":"Blockchain Technology: Rising Trend in Various Applications","authors":"Zalte S. S, Patil P. N, Deshmukh S. N, Patil M. G, Dr. Pallavi Katkar","doi":"10.3233/apc210228","DOIUrl":"https://doi.org/10.3233/apc210228","url":null,"abstract":"In this tech world, size of block chain is exponentially growing in this covid pandemic year which was not predicted. This pandemic environment causes digital transformation drive in various areas, particularly via the utilization of block chain or distributed ledger technology. To enhance and accelerate business process in various organization and industry showed a growing interest to adopt this technology. This paper summarized various block chain applications which are widely used in number of sectors and also focus on some challenges becomes hurdle while adopting block chain technology.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133362106","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
A Wi-Fi Based Smart Irrigation Monitoring for an Agricultural Environment 基于Wi-Fi的农业环境智能灌溉监测
Pub Date : 2021-12-01 DOI: 10.3233/apc210237
N. Patankar, Manoli Charmal, Nikhil Bhaskar, Swati Janrao, Aniket Kamble
A producer who controls irrigation using a smartphone. A firebase that uses weather data to predict when to water crops. Sensors that read how much water is in the soil. From water availability and unpredictable weather patterns to regulations from outside entities, it can be a challenge to irrigate crops. Nowadays IoT has different solutions to overcome with this kind of problem. The particular research targeted successfully by development effected system using NodeMCU, Sensors, firebase, and assertive application. These tools which could conserve a good amount of water, it will become vital to success as the population groves and water availability dries up. The tool works by helping farmers with limited irrigation capacity determine the best time to water their crops. The main ai m of automating the system is to provide a certain amount of water required by crops by monitoring the moisture of soil and surrounding temperature. This obtains with the help of sensors and NodeMCU for interfacing their values. The values are displayed on a mobile application in real-time using Google’s firebase. Irrigation using IoT is a key component of precision agriculture. By changing manual irrigation with automatic valves and systems reduces the human error. Farmer can monitor his crop yield from anywhere at any time.
一个用智能手机控制灌溉的生产者。一个使用天气数据来预测何时给作物浇水的消防基地。传感器可以读取土壤中有多少水。从水的可用性和不可预测的天气模式到外部实体的法规,灌溉作物可能是一个挑战。如今,物联网有不同的解决方案来克服这类问题。通过使用NodeMCU、Sensors、firebase和自信应用程序开发了有效的系统,成功地完成了该研究。这些工具可以保存大量的水,随着人口的减少和可用水的枯竭,这将成为成功的关键。该工具的工作原理是帮助灌溉能力有限的农民确定灌溉作物的最佳时间。自动化系统的主要目的是通过监测土壤湿度和周围温度,为作物提供所需的一定水量。这是在传感器和NodeMCU的帮助下实现的,用于接口它们的值。这些值使用谷歌的firebase实时显示在移动应用程序上。物联网灌溉是精准农业的关键组成部分。通过改变手动灌溉与自动阀门和系统减少人为错误。农民可以随时随地监控作物产量。
{"title":"A Wi-Fi Based Smart Irrigation Monitoring for an Agricultural Environment","authors":"N. Patankar, Manoli Charmal, Nikhil Bhaskar, Swati Janrao, Aniket Kamble","doi":"10.3233/apc210237","DOIUrl":"https://doi.org/10.3233/apc210237","url":null,"abstract":"A producer who controls irrigation using a smartphone. A firebase that uses weather data to predict when to water crops. Sensors that read how much water is in the soil. From water availability and unpredictable weather patterns to regulations from outside entities, it can be a challenge to irrigate crops. Nowadays IoT has different solutions to overcome with this kind of problem. The particular research targeted successfully by development effected system using NodeMCU, Sensors, firebase, and assertive application. These tools which could conserve a good amount of water, it will become vital to success as the population groves and water availability dries up. The tool works by helping farmers with limited irrigation capacity determine the best time to water their crops. The main ai m of automating the system is to provide a certain amount of water required by crops by monitoring the moisture of soil and surrounding temperature. This obtains with the help of sensors and NodeMCU for interfacing their values. The values are displayed on a mobile application in real-time using Google’s firebase. Irrigation using IoT is a key component of precision agriculture. By changing manual irrigation with automatic valves and systems reduces the human error. Farmer can monitor his crop yield from anywhere at any time.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131916474","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
Highly Secured Dynamic Color QR Pattern Generation for Real Time Application 用于实时应用的高度安全的动态彩色QR模式生成
Pub Date : 2021-12-01 DOI: 10.3233/apc210290
R. Sanjjey, S. Abisheak, T. Dineshkumar, M. Kirthan, S. Sivasaravanababu
This work advances the state-of-art secured WBAN system and QR pattern enabled authentication for privacy measures. An attempt was made to integrate all the above process to build high performance WBAN system. In this work, a comprehensive statistical framework is developed with randomized key generation and secured cipher transformation for secured sensor node communication. We create primary colour channels based on three different QR codes that are widely used for colour printing and complementary channels for capturing colour images. Last but not least, we produced a colour QR pattern.
这项工作推进了最先进的安全WBAN系统和QR模式支持的隐私措施认证。并尝试将上述过程集成在一起,构建高性能无线宽带网络系统。在这项工作中,开发了一个具有随机密钥生成和安全密码转换的综合统计框架,用于安全传感器节点通信。我们基于三种不同的QR码创建原色通道,这些QR码广泛用于彩色打印,而互补通道用于捕获彩色图像。最后,我们制作了一个彩色QR图案。
{"title":"Highly Secured Dynamic Color QR Pattern Generation for Real Time Application","authors":"R. Sanjjey, S. Abisheak, T. Dineshkumar, M. Kirthan, S. Sivasaravanababu","doi":"10.3233/apc210290","DOIUrl":"https://doi.org/10.3233/apc210290","url":null,"abstract":"This work advances the state-of-art secured WBAN system and QR pattern enabled authentication for privacy measures. An attempt was made to integrate all the above process to build high performance WBAN system. In this work, a comprehensive statistical framework is developed with randomized key generation and secured cipher transformation for secured sensor node communication. We create primary colour channels based on three different QR codes that are widely used for colour printing and complementary channels for capturing colour images. Last but not least, we produced a colour QR pattern.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115999838","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 Systematic Review of Blockchain Technology and Its Applications 区块链技术及其应用系统综述
Pub Date : 2021-12-01 DOI: 10.3233/apc210230
Bharati H Naikwadi, K. Kharade, S. Yuvaraj, K. Vengatesan
Blockchain technology could radically transform our business environment in the decades to come. It has the power to redefine our views of business processes and may even impact our overall economy. The works comprehensively document the implementation of blockchain applications in various sectors. Our goal is to determine what state blockchain technology is in and what kinds of applications it has. A large majority of the current blockchain-related research is dedicated to crypto currencies, such as Bitcoin. Only a small percentage of work is dedicated to exploring the wide range of potential blockchain technology applications. Blockchain technology has multiple applications across multiple industries. This study attempts to determine the opportunities and threats presented by Blockchain Technology for current or future applications. The number of published studies that were studied carefully and critically and added to the Block chain’s body of knowledge was large.
区块链技术可以在未来几十年从根本上改变我们的商业环境。它有能力重新定义我们对业务流程的看法,甚至可能影响我们的整体经济。这些作品全面记录了区块链应用在各个部门的实施情况。我们的目标是确定区块链技术处于什么状态,以及它有什么样的应用。目前绝大多数与区块链相关的研究都致力于加密货币,如比特币。只有一小部分工作致力于探索广泛的潜在区块链技术应用。区块链技术在多个行业有多种应用。本研究试图确定区块链技术为当前或未来应用带来的机会和威胁。经过仔细和批判性的研究,并添加到区块链知识体系中的已发表的研究数量很大。
{"title":"A Systematic Review of Blockchain Technology and Its Applications","authors":"Bharati H Naikwadi, K. Kharade, S. Yuvaraj, K. Vengatesan","doi":"10.3233/apc210230","DOIUrl":"https://doi.org/10.3233/apc210230","url":null,"abstract":"Blockchain technology could radically transform our business environment in the decades to come. It has the power to redefine our views of business processes and may even impact our overall economy. The works comprehensively document the implementation of blockchain applications in various sectors. Our goal is to determine what state blockchain technology is in and what kinds of applications it has. A large majority of the current blockchain-related research is dedicated to crypto currencies, such as Bitcoin. Only a small percentage of work is dedicated to exploring the wide range of potential blockchain technology applications. Blockchain technology has multiple applications across multiple industries. This study attempts to determine the opportunities and threats presented by Blockchain Technology for current or future applications. The number of published studies that were studied carefully and critically and added to the Block chain’s body of knowledge was large.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121596498","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
Predicting COD and BOD Parameters of Greywater Using Multivariate Linear Regression 用多元线性回归预测污水COD和BOD参数
Pub Date : 2021-12-01 DOI: 10.3233/apc210199
Samir Sadik Shaikh, Rekha Shahapurkar
Greywater reuse furthermore, reusing can be an incredible method to get non-consumable water. Since it contains broke down pollutions, greywater can’t be utilized straightforwardly. As an outcome, it is critical to decide the nature of water prior to utilizing it. Body estimations require five days to finish, while COD estimations require only a couple of hours. Not exclusively improve models for evaluating water quality are required; however, a more coordinated methodology is additionally getting more normal. Most of these models require a wide scope of information that isn’t in every case promptly available, making it a costly and tedious activity. Because of different issues in the enlistment with estimation included in water quality boundaries like BOD as well as COD, the principal objective of this investigation is to track down the best multivariate direct relapse models for foreseeing complex water quality outcomes. The code was written in Python for multi-variable information sources, and a Linear Regression Model was created. The projected COD versus estimated COD chart shows that the noticed and expected qualities are practically the same. The R-squared worth was 0.9973. A plot of extended BOD as an element of COD is likewise remembered for the outcome.
此外,再利用可以是一个令人难以置信的方法来获得非消耗性水。由于中水含有分解的污染物,所以不能直接利用。因此,在利用水之前决定水的性质是至关重要的。身体估算需要5天才能完成,而COD估算只需要几个小时。并非只需要改进评价水质的模型;然而,一种更加协调的方法正变得越来越普遍。这些模型中的大多数都需要广泛的信息,而这些信息并不是在每种情况下都能立即获得,这使得它成为一项昂贵而乏味的活动。由于纳入水质边界的估算中存在BOD和COD等不同问题,本研究的主要目的是寻找预测复杂水质结果的最佳多元直接复发模型。代码是用Python编写的多变量信息源,并创建了一个线性回归模型。预估的COD与预估的COD图表表明,注意到的和预期的质量实际上是相同的。r²值为0.9973。扩展BOD的情节作为COD的一个元素同样被记住的结果。
{"title":"Predicting COD and BOD Parameters of Greywater Using Multivariate Linear Regression","authors":"Samir Sadik Shaikh, Rekha Shahapurkar","doi":"10.3233/apc210199","DOIUrl":"https://doi.org/10.3233/apc210199","url":null,"abstract":"Greywater reuse furthermore, reusing can be an incredible method to get non-consumable water. Since it contains broke down pollutions, greywater can’t be utilized straightforwardly. As an outcome, it is critical to decide the nature of water prior to utilizing it. Body estimations require five days to finish, while COD estimations require only a couple of hours. Not exclusively improve models for evaluating water quality are required; however, a more coordinated methodology is additionally getting more normal. Most of these models require a wide scope of information that isn’t in every case promptly available, making it a costly and tedious activity. Because of different issues in the enlistment with estimation included in water quality boundaries like BOD as well as COD, the principal objective of this investigation is to track down the best multivariate direct relapse models for foreseeing complex water quality outcomes. The code was written in Python for multi-variable information sources, and a Linear Regression Model was created. The projected COD versus estimated COD chart shows that the noticed and expected qualities are practically the same. The R-squared worth was 0.9973. A plot of extended BOD as an element of COD is likewise remembered for the outcome.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120916527","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
Hybrid Parallel Feature Subset Selection for High Dimensional Datasets 高维数据集的混合并行特征子集选择
Pub Date : 2021-12-01 DOI: 10.3233/apc210180
Archana Shivdas Sumant, D. Patil
High dimensional data analytics is emerging research field in this digital world. The gene expression microarray data, remote sensor data, medical data, image, video data are some of the examples of high dimensional data. Feature subset selection is challenging task for such data. To achieve diversity and accuracy with high dimensional data is important aspect of this research. To reduce time complexity parallel stepwise feature subset selection approach is adopted for feature subset selection in this paper. Our aim is to reduce time complexity and enhancing the classification accuracy with minimum number of selected feature subset. With this approach 88.18% average accuracy is achieved.
高维数据分析是数字世界中新兴的研究领域。基因表达微阵列数据、遥感数据、医疗数据、图像、视频数据都是高维数据的一些例子。对于这类数据,特征子集的选择是一项具有挑战性的任务。实现高维数据的多样性和准确性是该研究的重要方面。为了降低时间复杂度,本文采用并行逐步特征子集选择方法进行特征子集选择。我们的目标是用最少的特征子集来降低时间复杂度和提高分类精度。使用该方法,平均准确率达到88.18%。
{"title":"Hybrid Parallel Feature Subset Selection for High Dimensional Datasets","authors":"Archana Shivdas Sumant, D. Patil","doi":"10.3233/apc210180","DOIUrl":"https://doi.org/10.3233/apc210180","url":null,"abstract":"High dimensional data analytics is emerging research field in this digital world. The gene expression microarray data, remote sensor data, medical data, image, video data are some of the examples of high dimensional data. Feature subset selection is challenging task for such data. To achieve diversity and accuracy with high dimensional data is important aspect of this research. To reduce time complexity parallel stepwise feature subset selection approach is adopted for feature subset selection in this paper. Our aim is to reduce time complexity and enhancing the classification accuracy with minimum number of selected feature subset. With this approach 88.18% average accuracy is achieved.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127972802","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
期刊
Recent Trends in Intensive Computing
全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1