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2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)最新文献

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Pricing model for revenue generation using Recurrent Neural Network for Cloud service provider 云服务提供商使用递归神经网络生成收益的定价模型
Pub Date : 2019-04-01 DOI: 10.1109/ICOEI.2019.8862567
Meetu Kandpal, Kalyani Patel
Success of any product may depend on the price of product. Demand of a product is one of the factors to be considered for deriving price of the product. As many IT companies have started to move towards the cloud computing and cloud resources are delivered as product over internet. There are many companies providing cloud services like salesforce.com, Amazon AWS, Microsoft azure etc. Different cloud service providers have different pricing policies to enhance the revenue and user satisfaction. The cloud providers have pricing schemes for cloud resources under fixed pricing and dynamic pricing. Some of them favor cloud providers, other cloud consumers. The paper presents a model to predict the price of cloud resource using Recurrent Neural Network(RNN) and auctioning method based on the parameters (as demand). The paper would give insight to researchers and cloud service providers to derive the policies based on the demand and other features.
任何产品的成功都可能取决于产品的价格。产品的需求是推导产品价格时要考虑的因素之一。随着许多IT公司开始转向云计算,云资源作为产品通过互联网交付。有许多公司提供云服务,如salesforce.com、亚马逊AWS、微软azure等。不同的云服务提供商有不同的定价策略,以提高收入和用户满意度。云提供商对云资源有固定定价和动态定价两种定价方案。其中一些支持云提供商,另一些支持云消费者。提出了一种基于参数(按需)的云资源价格预测模型,采用递归神经网络(RNN)和拍卖方法进行预测。本文将为研究人员和云服务提供商提供基于需求和其他特征的策略。
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引用次数: 1
Design and Implementing Brain Tumor Detection Using Machine Learning Approach 利用机器学习方法设计和实现脑肿瘤检测
Pub Date : 2019-04-01 DOI: 10.1109/ICOEI.2019.8862553
G. Hemanth, M. Janardhan, L. Sujihelen
Nowadays, brain tumor detection has turned upas a general causality in the realm of health care. Brain tumor can be denoted as a malformed mass of tissue wherein the cells multiply abruptly and ceaselessly, that is there is no control over the growth of the cells. The process of Image segmentation is adopted for extracting abnormal tumor region within the brain. In the MRI (magnetic resonance image), segmentation of brain tissue holds very significant in order to identify the presence of outlines concerning the brain tumor. There is abundance of hidden information in stored in the Health care sector. With appropriate use of accurate data mining classification techniques, early prediction of any disease can be effectively performed. In the medical field, the techniques of ML (machine learning) and Data mining holds a significant stand. Majority of which is adopted effectively. The research examines list of risk factors that are being traced out in brain tumor surveillance systems. Also the method proposed assures to be highly efficient and precise for brain tumor detection, classification and segmentation. To achieve this precise automatic or semi-automatic methods are needed. The research proposes an automatic segmentation method that relies upon CNN (Convolution Neural Networks), determining small 3 × 3 kernels. By incorporating this single technique, segmentation and classification is accomplished. CNN (a ML technique) from NN (Neural Networks)wherein it has layer based for results classification. Various levels involved in the proposed mechanisms are: 1. Data collection, 2. Pre-processing, 3. Average filtering, 4. segmentation, 5. feature extraction, 6. CNN via classification and identification. By utilizing the DM (data mining) techniques, significant relations and patterns from the data can be extracted. The techniques of ML (machine learning) and Data mining are being effectively employed for brain tumor detection and prevention at an early stage.
如今,脑肿瘤的检测已成为医疗保健领域的普遍因果关系。脑肿瘤可以被认为是一种畸形的组织团块,其中细胞突然地、不断地繁殖,也就是说,细胞的生长是无法控制的。采用图像分割的方法提取脑内的异常肿瘤区域。在核磁共振成像(MRI)中,为了识别脑肿瘤的轮廓,脑组织的分割非常重要。有大量的隐藏信息存储在卫生保健部门。通过适当使用准确的数据挖掘分类技术,可以有效地进行任何疾病的早期预测。在医学领域,ML(机器学习)和数据挖掘技术占有重要地位。其中大部分被有效采纳。这项研究检查了脑肿瘤监测系统中正在追踪的一系列风险因素。该方法保证了脑肿瘤检测、分类和分割的高效性和准确性。要做到这一点,就需要采用自动或半自动的方法。本研究提出了一种基于CNN(卷积神经网络)的自动分割方法,确定小的3 × 3核。通过结合这一单一技术,完成了分割和分类。CNN(一种ML技术)来自NN(神经网络),其中它具有基于结果分类的层。拟议机制所涉及的各个层面是:2.数据收集;预处理、3。平均过滤,4。分割,5。6.特征提取;CNN通过分类和识别。利用DM(数据挖掘)技术,可以从数据中提取重要的关系和模式。ML(机器学习)和数据挖掘技术正被有效地用于脑肿瘤的早期检测和预防。
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引用次数: 60
Patch Antenna for ISM Band Application 适用于ISM波段的贴片天线
Pub Date : 2019-04-01 DOI: 10.1109/ICOEI.2019.8862700
Shambhavi S. Salelkar, Palhavi Kerkar
A Rectangular microsrip patch antenna with a semicircular slot is fabricated which is desirable for ISM band applications. The main objective of this antenna is to have less loss and substantial gain. The resonant frequency of this antenna which is at ISM band is 5.8 GHz. Three antennas are been designed. A patch antenna, an array of 2×1 and 2×2 is plotted on the FR4 substrate with the relative permittivity of 4.4. An amount of air gap is kept between the ground plane and the substrate. The software that is used for designing this antenna is IE3D. The designed antenna at 5.8 GHz provides the outcome that gives return loss of −16 dB, −23 dB and −39.9 dB, gain of 5.4 dB, 7.2 dB and 8.9 db, VSWR of 1.02, 1.1 and 1.2 respectively. The size of the antenna is very compact and hence it is easy to fabricate. WiFi, W-LAN, Bluetooth are the applications of ISM Band that is provide by this antenna.
制作了一种适合ISM波段应用的带半圆槽的矩形微带贴片天线。这种天线的主要目标是具有较小的损耗和可观的增益。该天线在ISM频段的谐振频率为5.8 GHz。设计了三根天线。在相对介电常数为4.4的FR4衬底上绘制了贴片天线、2×1和2×2阵列。在接地面和基板之间保持一定量的气隙。该天线的设计软件为IE3D。设计的5.8 GHz天线的回波损耗分别为- 16 dB、- 23 dB和- 39.9 dB,增益分别为5.4 dB、7.2 dB和8.9 dB,驻波比分别为1.02、1.1和1.2。天线的尺寸非常紧凑,因此很容易制造。WiFi、W-LAN、蓝牙是该天线提供的ISM频段的应用。
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引用次数: 1
Web Based Environment Monitoring System Using IOT 基于网络的物联网环境监测系统
Pub Date : 2019-04-01 DOI: 10.1109/ICOEI.2019.8862721
Pooja Ghule, Mansi Kambli
Nowadays people are very concerned about the environment because of the rapid changes in the environment which will harm to human health. Hence it is necessary to monitor environment where the people spend more time like at home, office, industry, any working area in real time and long term manner. Using internet of things we can control system as well as we can access system remotely using IoT. It first take information with help of different sensors and transfer sensors values on thingspeak directly, from which can be accessed at anytime and anywhere. Literature survey is done on use of wireless sensors, Cloud and Internet of things, and connection between devices with sensors and network connection will read sensor value which can be further monitored from the internet with the help of thingspeak. Monitoring environment is done through website & controlled manually and automatically by detecting sensor values. We can controlled it manually through website and it can automatically controlled by sensing values. The main Objective design of cloud storage environment is used to store data and to process the data. Internet of things allows physical devices or things which are not computer system, that only act very smartly and makes collaborations decision which are beneficial for different applications. That application allow things to capture value of devices. They transfer “things from being passively computing” and makes an individually decisions in active manner and communicate and collaborate to form single difficult decision. IoT technologies of computing, embedded sensors, communication protocol and internet protocol for communication allow internet of things to provide significant which impose number of challenges and introduces standards which require to specialize and communication
现在人们非常关心环境,因为环境的快速变化会对人类健康造成危害。因此,有必要对人们花费更多时间的环境,如家庭,办公室,工业,任何工作区域进行实时和长期的监测。使用物联网,我们可以控制系统,也可以使用物联网远程访问系统。它首先在不同传感器的帮助下获取信息,并将传感器的值直接传递到thingspeak上,可以随时随地访问。对无线传感器、云和物联网的使用做了文献调查,有传感器的设备之间的连接和网络连接将读取传感器值,这些传感器值可以通过thingspeak从互联网上进一步监测。环境监测通过网站完成,通过检测传感器值进行手动和自动控制。我们可以通过网站手动控制,也可以通过感应值自动控制。云存储环境的主要目标是实现数据的存储和数据的处理。物联网允许物理设备或非计算机系统的东西,它们只会非常聪明地行动,并做出有利于不同应用程序的协作决策。该应用程序允许事物捕捉设备的价值。它们将“事物从被动计算”转移到主动做出个体决策,并通过沟通和协作形成单一的困难决策。计算,嵌入式传感器,通信协议和通信互联网协议的物联网技术允许物联网提供重要的,这带来了许多挑战,并引入了需要专业化和通信的标准
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引用次数: 3
Review on Feature Extraction Methods in Neuromuscular Disease Diagnosis 神经肌肉疾病诊断中的特征提取方法综述
Pub Date : 2019-04-01 DOI: 10.1109/ICOEI.2019.8862601
C. J. Mariya, K. A. Nyni
This paper mainly focuses on various feature selection methods that is followed for achieving accurate diagnosis of neuromuscular diseases such as Amyotrophic Lateral Sclerosis (ALS) and Myopathy. Since both of these has similarity in the Electromyography (EMG) waveform of normal patients, this will create more difficulties in terms of diagnosis. Hence, proper feature selection is the essential part in the diagnosis. Two feature selection methods were adopted for evaluation. In the first method, time domain and frequency domain features are taken from each frame of EMG signal and in the second method, Discrete Wavelet Transform (DWT) features like maximum DWT coefficient and mean value of high energy DWT coefficients were analysed. For the purpose of classification, the Multi-Support Vector Machine (MSVM) classifier is employed.
本文主要针对肌萎缩性侧索硬化症(Amyotrophic Lateral Sclerosis, ALS)和肌病(Myopathy)等神经肌肉疾病的准确诊断所采用的各种特征选择方法进行研究。由于两者与正常患者的肌电图(EMG)波形相似,这将在诊断方面造成更多困难。因此,正确的特征选择是诊断的关键部分。采用两种特征选择方法进行评价。第一种方法从肌电信号的每一帧提取时域和频域特征,第二种方法分析离散小波变换(DWT)的最大DWT系数和高能DWT系数均值等特征。为了进行分类,采用了多支持向量机(MSVM)分类器。
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引用次数: 2
Health Record Management through Blockchain Technology 通过区块链技术进行健康记录管理
Pub Date : 2019-04-01 DOI: 10.1109/ICOEI.2019.8862594
V. Harshini, Shreevani Danai, H R Usha, Manjunath R. Kounte
The world is moving towards progress, to achieve the desired progress, the world should have a healthy population and health records are the projections of an individual's health over time. The centralised approach of maintaining the health records lead to data breaches. According to 2017 Ponemon Cost of Data Breach Study, the cost of the data breach for healthcare organizations estimated to be $380 per record. According to 2016 Breach Barometer Report, 27,314,647 patient records were affected. So we moved towards institution-driven approach of record maintenance, which didn't make much difference with the previously existing one. Since the patient have no control over the data, the chances of data being misused is high. So we need a patient-centered approach which is completely decentralised, which can identify data thefts, prevent data manipulation, and patient has the right in access control. Blockchain Technology serves as a best solution to address all the problems and fulfill the needs. Blockchain being a decentralised and distributed ledger it can also impact on billing, record sharing, medical research, identify thefts and financial data crimes in days to come. Implementation of smart contracts in health care can simplify things even better. Where invoking, record creation and validation will be done on Blockchain. This paper highlights on the patient-driven model of record maintenance using Blockchain technology where smart contracts can be incorporated in future days making it more potential in data exchange. Finding its huge scope, hoping that more researches will be carried out and practically implemented.
世界正在走向进步,为了实现预期的进步,世界应该有一个健康的人口,健康记录是一个人的健康随时间的预测。集中维护健康记录的方法会导致数据泄露。根据2017年波耐蒙数据泄露成本研究,医疗机构的数据泄露成本估计为每条记录380美元。根据2016年违规晴雨表报告,27,314,647例患者记录受到影响。因此,我们转向了制度驱动的记录维护方法,这与之前存在的方法没有太大区别。由于患者无法控制数据,因此数据被滥用的可能性很高。所以我们需要一个以病人为中心的方法,它是完全分散的,它可以识别数据被盗,防止数据被操纵,病人有访问控制的权利。区块链技术是解决所有问题和满足需求的最佳解决方案。区块链作为一种去中心化的分布式账本,在未来的日子里,它还可以影响计费、记录共享、医学研究、识别盗窃和金融数据犯罪。在医疗保健领域实施智能合约可以更好地简化事情。其中调用,记录创建和验证将在区块链上完成。本文重点介绍了使用区块链技术的患者驱动的记录维护模型,其中智能合约可以在未来被纳入其中,使其在数据交换中更具潜力。发现其巨大的应用范围,希望开展更多的研究并实际实施。
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引用次数: 23
Analysis of Image Segmentation Algorithms for the Effective Detection of Leukemic Cells 有效检测白血病细胞的图像分割算法分析
Pub Date : 2019-04-01 DOI: 10.1109/ICOEI.2019.8862696
T. Bhagya, K. Anand, D. S. Kanchana, Ajai A S Remya
Image segmentation plays a vital role in medical image processing. Different pre-processing methods yield different results. The pre-processing methods such as histogram stretching with erosion and dilation, average filter and median filter along with histogram stretching is applied to the four different segmentation algorithms which are Otsu's thresholding, Watershed based segmentation, Canny edge detection and K-mean clustering. These algorithms are used to segment Acute Lymphoblastic Leukemia datasets and the parameters such as precision, accuracy and sensitivity of the results are calculated so as to find a better algorithm which is suitable for segmentation of the leukemic cells.
图像分割在医学图像处理中起着至关重要的作用。不同的预处理方法产生不同的结果。对Otsu阈值分割算法、分水岭分割算法、Canny边缘检测算法和k均值聚类算法四种不同的分割算法分别采用侵蚀扩张直方图拉伸、平均滤波和中值滤波以及直方图拉伸等预处理方法。利用这些算法对急性淋巴细胞白血病数据集进行分割,并对结果的精密度、准确度、灵敏度等参数进行计算,以期找到一种更适合白血病细胞分割的算法。
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引用次数: 6
Robust Method to Detect and Track the Runway during Aircraft Landing Using Colour segmentation and Runway features 基于颜色分割和跑道特征的飞机着陆跑道检测与跟踪方法
Pub Date : 2019-04-01 DOI: 10.1109/ICOEI.2019.8862529
B. Ajith, S. Adlinge, Sudin Dinesh, U. Rajeev, E. S. Padmakumar
Airport runway detection and tracking can play an important role in landing an aircraft. In some situations the runway may not be visible to pilot due to adverse weather condition. Considering the case of Unmanned aerial vehicles, the runway detection and tracking algorithm is one of its essential part which enable them to position itself and land safely. This paper explains an algorithm which will track the runway when it is visible using a camera. The algorithm is based on identification of runway colour and runway characteristics. This method ensures the detection of runway accurately. Algorithm detects the runway boundaries by selecting the appropriate hough lines using runway characteristics and runway colour. Once the runway is detected it tracks the runway using feature matching techniques. In tracking phase the algorithm will track the runway and it will find out the accurate runway boundary and threshold stripes. This algorithm can be used to assist pilot during landing and it can be also used to detect runways in UAVs.
机场跑道探测与跟踪在飞机着陆中起着重要的作用。在某些情况下,由于恶劣的天气条件,飞行员可能无法看到跑道。对于无人机而言,跑道检测与跟踪算法是其实现自身定位和安全着陆的重要组成部分之一。本文介绍了一种利用摄像机跟踪跑道的算法。该算法基于跑道颜色和跑道特征的识别。该方法保证了对跑道的准确探测。算法利用跑道特征和跑道颜色选择合适的霍夫线来检测跑道边界。一旦检测到跑道,它使用特征匹配技术跟踪跑道。在跟踪阶段,算法对跑道进行跟踪,找出准确的跑道边界和阈值条纹。该算法可用于辅助飞行员着陆,也可用于无人机的跑道检测。
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引用次数: 4
Variants of phishing attacks and their detection techniques 网络钓鱼攻击的变体及其检测技术
Pub Date : 2019-04-01 DOI: 10.1109/ICOEI.2019.8862697
G. Jaspher Willsie Kathrine, P. M. Praise, A. Amrutha Rose, Eligious C Kalaivani
Phishing is a treacherous effort to steal private data from users like address, aadhar number, PAN card details, credit/debit card details, bank account details, password for online shopping sites, etc. Pinching or phishing of private information on the web has caused havoc on a majority of users due to the lack of internet security. Phishing attacks make use of fake emails or websites, intended to fool users into revealing personal or financial information by posing as the trusted bank/shopping site. The various types of phishing attacks and the recent approaches to prevent the attacks are discussed. A framework to detect and prevent phishing attacks is also proposed. A combination of supervised and unsupervised machine learning techniques is used to detect known and unknown attacks.
网络钓鱼是一种狡猾的手段,窃取用户的私人数据,如地址、身份证号码、PAN卡详细信息、信用卡/借记卡详细信息、银行账户详细信息、在线购物网站密码等。由于缺乏网络安全,网络上私人信息的窃取或网络钓鱼给大多数用户造成了严重破坏。网络钓鱼攻击利用虚假的电子邮件或网站,冒充受信任的银行/购物网站,欺骗用户透露个人或财务信息。讨论了各种类型的网络钓鱼攻击和最新的防止攻击的方法。提出了一个检测和防止网络钓鱼攻击的框架。有监督和无监督机器学习技术的组合用于检测已知和未知的攻击。
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引用次数: 18
Smart Gardening Automation using IoT With BLYNK App 智能园艺自动化使用物联网与BLYNK应用程序
Pub Date : 2019-04-01 DOI: 10.1109/ICOEI.2019.8862591
Mitul Sheth, Pinal Rupani
The Global Sensing enabled by Wireless Sensor Network (WSN) cut crosswise over numerous zones of current living. This provides the potentiality to compute, and understand the environmental indicators. In today's digital world, a person expects Automatization which makes the task easy, comfortable, fast and efficient. The idea is to advance our traditional system to a Smart Automated System for supplying water in home gardening, farms fields, etc. In this system, we use soil wetness detector, temperature detector and humidity detector that are mounted at the root space of the plants. The values recognize by the system are conveyed to the base station. The target is to fetch data and sync those values with internet using Wifi. It notifies the user as the water level goes down below the set point. This paper shows that making use of NodeMCU we can do observing of circuit diagrams using wireless technology and shows the result using Blynk App. As it detects low wetness and warm temperature, a message is passed between NodeMCU and Blynk App and it automatically starts the motor in home gardening, farm, etc.
无线传感器网络(WSN)实现的全球传感跨越了当前生活的许多区域。这提供了计算和理解环境指标的可能性。在当今的数字世界中,人们期望自动化使工作变得简单、舒适、快速和高效。这个想法是将我们的传统系统推进到一个智能自动化系统,为家庭园艺、农场、田地等供水。在这个系统中,我们使用了土壤湿度探测器、温度探测器和湿度探测器,这些探测器安装在植物的根空间。系统识别的值被传送到基站。目标是获取数据并使用Wifi与互联网同步这些值。当水位低于设定值时,它会通知用户。本文展示了利用NodeMCU可以使用无线技术观察电路图,并使用Blynk App显示结果。当NodeMCU检测到低湿度和温暖温度时,在NodeMCU和Blynk App之间传递消息,并自动启动家庭园艺,农场等电动机。
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引用次数: 32
期刊
2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)
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