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A Comparative Analysis of PGGAN with Other Data Augmentation Technique for Brain Tumor Classification PGGAN与其他数据增强技术在脑肿瘤分类中的比较分析
Saswati Sahoo, Sushruta Mishra
Nowadays, the number of brain tumor cases among people is increasing globally across the world due to several reasons such as obesity, overweight, excess levels of stress in life, exposure to ionizing radiation, and many more. In previous years, many investigators have provided a range of solutions and effective tools for the identification and categorization of brain tumors. Nevertheless, the existing developed models for brain tumor identification and categorization have diverse limitations such as minimal accuracy and precision values. In this paper, the authors developed a novel model for the comparative analysis of the Progressive Growing-Generative Adversarial Network (PGGAN) with other data augmentation techniques for brain tumor classification. Because of the availability of finite datasets, the brain tumor classification algorithm along with the convolutional neural networks (CNNs) must be enhanced to be more competent for brain tumor classification and identification in real-time diagnosis. The outcome of the proposed model demonstrates that PGGAN delivers higher accuracy, as well as precision, and the Recall with the F1 score is 99.22%, 98.11%, 98.66%, and 97.45%, respectively. In the future, the developed model performance could be measured with other data augmentation techniques for larger datasets for performance constraints computations for further study and implementation of the model for real-time diagnosis of the patients.
如今,由于肥胖、超重、生活压力过大、暴露于电离辐射等多种原因,全球范围内的脑肿瘤病例数量正在增加。在过去的几年里,许多研究者为脑肿瘤的识别和分类提供了一系列的解决方案和有效的工具。然而,现有开发的脑肿瘤识别和分类模型存在各种局限性,如最小的准确性和精度值。在本文中,作者开发了一种新的模型,用于比较分析渐进式生长-生成对抗网络(PGGAN)与其他数据增强技术在脑肿瘤分类中的应用。由于数据集有限,必须对脑肿瘤分类算法和卷积神经网络(cnn)进行改进,使其更能胜任实时诊断中的脑肿瘤分类和识别。该模型的结果表明,PGGAN具有更高的准确率和精密度,具有F1分数的召回率分别为99.22%,98.11%,98.66%和97.45%。在未来,开发的模型性能可以与其他数据增强技术一起测量,用于更大数据集的性能约束计算,以进一步研究和实现用于患者实时诊断的模型。
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引用次数: 0
Analyzing Student Performance in Programming Education Using Classification Techniques 用分类技术分析学生在编程教育中的表现
Mahesh Kumar Morampudi, Nagamani Gonthina, Dinesh Reddy, K. S. Rao
Programming Skills play a crucial role in any computer engineering student's life to apply the concepts in solving any real world problem as well to crack a secure job in the dream company. To achieve this they should assess their performance in programming, analyze and improve their skills regularly. Many students are even undergoing mental stress and depression and even attempting suicides out of the stress if the considered scores and performance are not met. With the help of analyzing the programming skills one can enhance their scores and performance on a regular basis, introspect and can deliberately practice for better improvement. This reduces the stress, anxiety and depression on students' minds in securing good scores in their academics and in building their career to achieve the goal. This analysis helps even professors to improvise the teaching and learning outcomes of students and increase their performance in whichever field they are working in. We made a comparison of different machine learning algorithms based on 200 classification instances. This analysis helped us in analyzing the statistics of students' performance.
编程技能在任何计算机工程专业的学生的生活中都扮演着至关重要的角色,可以应用这些概念来解决任何现实世界的问题,也可以在理想的公司找到一份稳定的工作。为了实现这一目标,他们应该评估自己在编程方面的表现,定期分析和提高自己的技能。许多学生甚至遭受精神压力和抑郁,甚至企图自杀,如果考虑的分数和表现不符合压力。在分析编程技能的帮助下,一个人可以定期提高他们的分数和表现,反省和有意识地练习,以更好地提高。这减少了学生在学业上取得好成绩和建立职业生涯以实现目标时的压力、焦虑和抑郁。这种分析甚至可以帮助教授即兴发挥学生的教学成果,并提高他们在任何领域的工作表现。我们基于200个分类实例对不同的机器学习算法进行了比较。这种分析有助于我们分析学生成绩的统计数据。
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引用次数: 0
Survey On Using Audio Video for True Random Number Generation 利用音频视频生成真随机数的研究
Binu P. K, Thejas Menon, Javed Harees
True random number generation is essential for modern and future security and cryptography. This paper surveys five existing methods of using audio and video to generate numbers, and compares their hardware, software, and randomness to find the best method for TRNG. The entropy of each method is compared, and the randomness of each method can be found. Each paper generates random numbers by utilizing the inherent noise created by transitioning analogue data to digital data, unlike other TRNG methods which use the conditions of internal hardware, erroneous data from wireless networks, or other non-noise-based methods.
真正的随机数生成对于现代和未来的安全性和密码学至关重要。本文调查了现有的五种使用音频和视频生成数字的方法,并对它们的硬件、软件和随机性进行了比较,以找到最适合TRNG的方法。比较了各方法的熵值,发现了各方法的随机性。每篇论文通过利用模拟数据转换为数字数据所产生的固有噪声来生成随机数,而不像其他TRNG方法使用内部硬件条件,来自无线网络的错误数据或其他非基于噪声的方法。
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引用次数: 0
Lightweight Intrusion Detection System(L-IDS) for the Internet of Things 物联网轻量级入侵检测系统(L-IDS)
D. D. Priya, A. Kiran, P. Purushotham
Internet of Things devices collect and share data (IoT). Internet connections and emerging technologies like IoT offer privacy and security challenges, and this trend is anticipated to develop quickly. Internet of Things intrusions are everywhere. Businesses are investing more to detect these threats. Institutes choose accurate testing and verification procedures. In recent years, IoT utilisation has increasingly risen in healthcare. Where IoT applications gained popular among technologists. IoT devices' energy limits and scalability raise privacy and security problems. Experts struggle to make IoT devices more safe and private. This paper provides a machine-learning-based IDS for IoT network threats (ML-IDS). This study aims to implement ML-supervised IDS for IoT. We're going with a centralised, lightweight IDS. Here, we compare seven popular categorization techniques on three data sets. The decision tree algorithm shows the best intrusion detection results.
物联网设备收集和共享数据(IoT)。互联网连接和物联网等新兴技术为隐私和安全带来了挑战,预计这一趋势将迅速发展。物联网入侵无处不在。企业正在加大投资,以检测这些威胁。机构选择准确的测试和验证程序。近年来,物联网在医疗保健领域的使用率越来越高。物联网应用在技术人员中受到欢迎。物联网设备的能量限制和可扩展性引发了隐私和安全问题。专家们努力使物联网设备更加安全和私密。本文提出了一种基于机器学习的物联网网络威胁检测方法(ML-IDS)。本研究旨在为物联网实现机器学习监督的IDS。我们将使用集中式轻量级IDS。在这里,我们在三个数据集上比较了七种流行的分类技术。决策树算法具有较好的入侵检测效果。
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引用次数: 1
Rectification of Electrical Energy Using Band Pass Filter 带通滤波器对电能的整流
Deepak Sharma, Anurag Saxena, Z. Ali, Neeraj Yadav
In wireless power transfer, does not require the flow of electrons in any material like conductor. In this process electrical energy is originated from the transmission line. It uses a wearable antenna like textile or cloths. The most important applications of the wearable antenna are Wi-Fi or WLAN. on simulating the design the S11 result of textile antenna gives one resonant frequency at 5.24 GHz. The thickness of the textile material is 1mm with dielectric constant 1.7. The transfer of electrical energy wirelessly is too difficult But with the help of receiver antenna makes it possible. Circuit with the feedback upon the frequency of the input voltage are also known as filters. Band pass filter is used in this because it passes the particular frequency range. After that bridge rectifier is utilized which converts radio frequency signal (AC) into DC signal.
在无线电力传输中,不需要电子在导体等任何材料中流动。在这个过程中,电能来源于输电线路。它使用像纺织品或布料一样的可穿戴天线。可穿戴天线最重要的应用是Wi-Fi或WLAN。在模拟设计中,纺织天线的S11结果为5.24 GHz谐振频率。纺织材料厚度为1mm,介电常数为1.7。无线传输电能是非常困难的,但有了接收天线的帮助,这就成为可能。对输入电压的频率进行反馈的电路也称为滤波器。带通滤波器用于此,因为它通过特定的频率范围。然后利用桥式整流器将射频信号(交流)转换成直流信号。
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引用次数: 0
A Reliable Protection Scheme for Smartgrid Based On Wavelet Transform and Ensemble Classifier 基于小波变换和集成分类器的智能电网可靠保护方案
Deepa U. Mishra, Preeti Jain
The advent of the “Smartgrid” is a result of the new trend of managing the increasing power demand by harnessing the potential of distributed energy resources (DER) within the current low voltage distribution framework. Even while the distribution networks benefit greatly from the Smartgrid, the integration problems with renewable and synchronous DERs have rendered protection jobs inherently difficult. When compared to synchronous DERs, which can endure fault current up to 10 times, renewable DERs' dynamic producing behaviour, which is restricted to carrying fault current up to 2–3 times the rated current, creates a clear distinction between the two in terms of operating circumstances. As a result of these factors, the accompanying security challenges become even more difficult. Because the magnitude of fault current varies according to mode, there is a significant variation in the amount of fault current between islanded and grid-connected modes. As a result, it is necessary to develop an accurate and dependable approach that can operate in both modes and fulfil the Smartgrid's protection needs without being influenced by harmonics associated with power electronic interface devices and non-linear loads. In this context, a protection strategy for the Smartgrid has been presented that is based on the joint framework of discrete wavelet transform (DWT) and Bagged decision tree based data-mining approach.
“智能电网”的出现是通过在当前的低压配电框架内利用分布式能源(DER)的潜力来管理不断增长的电力需求的新趋势的结果。尽管配电网从智能电网中受益匪浅,但可再生和同步der的整合问题使保护工作本身就很困难。与可以承受高达10倍故障电流的同步der相比,可再生der的动态生产行为仅限于承载高达额定电流2-3倍的故障电流,这在操作环境方面形成了两者之间的明显区别。由于这些因素,随之而来的安全挑战变得更加困难。由于故障电流的大小随模式的不同而变化,因此在孤岛模式和并网模式之间,故障电流的大小有很大的变化。因此,有必要开发一种准确可靠的方法,可以在两种模式下运行,并满足智能电网的保护需求,而不会受到与电力电子接口设备和非线性负载相关的谐波的影响。在此背景下,提出了一种基于离散小波变换(DWT)和Bagged决策树数据挖掘方法联合框架的智能电网保护策略。
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引用次数: 1
Image Encryption Using RSA and Advanced Caesar Cipher Method 使用RSA和高级凯撒密码方法进行图像加密
Arpan Maity, Ritobina Ghosh, Shidhu Bhadra
In the field of Computer Science, proper storage and analysis of data is one of the most trending topics. The development of modern tools and techniques, has come down as a blessing for this. But along with the blessing, comes the curse of being easily attacked and the privacy of the data being vulnerable. The attackers and the hackers are becoming very smart and with their modern equipment, they can break into any system. For this several methods have been developed to save the privacy of our data. Out of these methods, the symmetric key method and the asymmetric key method are the most popular ones. Though both of the methods are powerful enough, they come with their own set of disadvantages. In this research work, an approach has been taken, where the combination of both the above spoken methods are used, making use of the advantages of both the methods, where both of them are also cancelling out each others disadvantages. The results confirmed that the accuracy, efficiency and the security of the algorithms are good enough, so that it can be used to deal with real world problems.
在计算机科学领域,数据的正确存储和分析是最热门的话题之一。现代工具和技术的发展,已经被认为是一件幸事。但伴随着祝福而来的是容易被攻击和数据隐私易受攻击的诅咒。攻击者和黑客变得非常聪明,有了现代化的设备,他们可以侵入任何系统。为此,开发了几种方法来保护我们数据的隐私。在这些方法中,对称密钥方法和非对称密钥方法是最常用的方法。尽管这两种方法都足够强大,但它们也有自己的缺点。在这项研究工作中,已经采取了一种方法,其中使用上述两种方法的组合,利用两种方法的优点,其中两者也都抵消了彼此的缺点。结果表明,该算法的精度、效率和安全性都足够好,可以用于处理现实问题。
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引用次数: 0
Machine Intelligence Enabled Parametric Speaker: An Invention Towards Experience Sound 机器智能支持的参数扬声器:一项面向体验声音的发明
Uday Bhanu Ghosh, Rohan Sharma
This work proposes to channelize the conventional longitudinal behavior of sound which diverges in every direction after its generation to a beam like behavior seen in transverse waves, which is already conceived in a device named as parametric speaker. On top of this, using technologies such as AI, self-learning, and decision-making capabilities can be endorsed in the hardware-based device, exhausting its full capabilities. The goal of the proposed work is to provide an invisible screening and privacy to the individuals in public and semi-public areas associated with verbal mode of communication. The underlying work focuses on using the unconventional behavior of sound, possessing beam like properties produced through Artificial means by interference and Superposition principle, applicable to sound which is constructed by Parametric Speaker also known as directional Speaker. The following work in this paper attempts to showcase the possibilities of using and harnessing this specific sound properties with sophisticated technologies such as ML and Deep Learning to create semi private areas in public spaces which can not only help people within different age groups (mostly elderly population) but can also help people who are handicapped (such as visually impared people who can only receive information through auditory channels), the scope of the proposed work is not only limited to impared people but, also to general population, with the objective to increase the conventional information transfer system into personalized data delivery service through voice and speech.
这项工作提出了将传统的声音纵向行为引入通道,这种纵向行为在产生后在各个方向上发散到横波中看到的束状行为,这已经在一种名为参数扬声器的设备中得到了设想。除此之外,使用人工智能、自我学习和决策能力等技术可以在基于硬件的设备中得到认可,从而耗尽其全部功能。这项工作的目标是为公共和半公共区域的个人提供一个无形的屏障和隐私,这些区域与口头交流模式有关。基础工作侧重于利用声音的非常规行为,通过干涉和叠加原理通过人工手段产生的具有束状性质的声音,适用于参数扬声器也称为定向扬声器构建的声音。本文中的以下工作试图展示使用和利用这种特定声音属性的可能性,如ML和深度学习等复杂技术,在公共空间中创建半私人区域,不仅可以帮助不同年龄组的人(主要是老年人),还可以帮助残疾人(如只能通过听觉渠道接收信息的视障人士)。建议的工作范围不仅限于残障人士,而且还包括一般人群,目的是将传统的信息传递系统通过语音和语音增加到个性化的数据传递服务。
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引用次数: 0
Semi Circle Slotted Triangular Shape Antenna Using Flexible Material 半圆开槽三角形柔性材料天线
Deepak Sharma, Vinod Kumar Singh, Anupam Vyas, Neetendra Kumar, Rajesh Kumar Dwivedi
Nowadays microwave communities are working on the design and development of the dual band, triple band & wide band antennas with partial ground. The customers prefer compact devices for WLAN, Bluetooth, PCS, and WiMAX applications, which are frequently used in tablets, medical instruments, smart phones, portable laptops and handheld electronic gadgets. The proposed antenna is consisting of a partial ground and slotted circular patch with line feed. The Triple bandwidth of proposed antenna is 45.77%, 69.20% and 12.69% suitable for triple band application.
目前,微波界正致力于部分接地的双频、三频和宽带天线的设计与开发。客户更喜欢用于WLAN、蓝牙、pc和WiMAX应用的紧凑型设备,这些设备经常用于平板电脑、医疗器械、智能手机、便携式笔记本电脑和手持电子设备。所提出的天线由部分接地和带馈线的开槽圆形贴片组成。天线的三频带宽分别为45.77%、69.20%和12.69%,适合三频应用。
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引用次数: 0
Leaf Disease Identification and Remedy Recommendation System 叶片病害鉴定和补救建议系统
N. Sirisha, Pasunoori Devi, P. Purushotham, D. SaiSri, Vemuri Laxmi
Agriculture is one field that has a big impact on people's lives and their economic situation. Poor management is the cause of agricultural losses. Farmers' lack of knowledge about disease leads to reduced yields. Farmer helpline call-centers are accessible, although they do not provide assistance 24 hours a day, seven days a week, and communication might be problematic at times. Farmers who are unable to effectively describe disease over the phone require an investigation of the afflicted leaf area. Since photographs and videos of crops provide a better view of the crop and agricultural scientists can provide a better way to fix difficulties related to healthy crop, farmers have not been informed. Because to advancements in technology, equipment are now capable of recognizing and detecting plant illnesses. Recognizing disease early on can help to speed up treatment and reduce the impact on harvest. As a result, the focus of this research is on employing image processing to identify plant diseases.
农业是一个对人们的生活和经济状况有很大影响的领域。管理不善是造成农业损失的原因。农民缺乏疾病知识导致产量下降。农民帮助热线呼叫中心是可以访问的,尽管他们不是每周7天每天24小时提供帮助,而且有时沟通可能会出现问题。无法通过电话有效描述疾病的农民需要对患病的叶面积进行调查。由于作物的照片和视频可以更好地了解作物,农业科学家可以提供更好的方法来解决与健康作物有关的困难,因此农民没有被告知。由于技术的进步,设备现在能够识别和检测植物疾病。及早发现疾病有助于加快治疗,减少对收成的影响。因此,本研究的重点是利用图像处理技术来识别植物病害。
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引用次数: 0
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2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)
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