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2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)最新文献

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A Voltage Level Shifter Design for High Performance Application in Near Threshold Voltage Regime 一种近阈值电压区高性能应用的电压电平转换器设计
Indra Kumar Chaudhry, Chaudhary Pratap Singh, Ravi Nandan Ray
An energy-efficient and optimized voltage CMOS voltage level shifter is proposed in this paper. There are several uses for the CMOS Voltage level shifters (LS) in power supply architecture. The voltage level shifter’s main function is to change the voltage level from low to high and vice versa. The proposed voltage LS circuit design uses a select signal (Vin) voltage switch logic, which accepts an input signal between 0.3 Volt and 0.6 Volt and produces an output signal with peak-to-peak voltage ranging from 1.2Volt to 0.6 Volt. The proposed LS circuit design is validated in ASAP7 7nm Fin-Fet technology, it outperforms a recently Wilson current mirror level shifter with Zero threshold voltage architecture in terms of latency and power dissipation by 42.76% and 39.6%, respectively. Power consumption and propagation delay are both significantly minimized by the proposed design topology.
本文提出了一种节能、优化的CMOS电压电平移位器。CMOS电压电平移位器(LS)在电源结构中有几种用途。电压电平移位器的主要功能是将电压电平从低变为高,反之亦然。所提出的电压LS电路设计使用选择信号(Vin)电压开关逻辑,它接受0.3伏特至0.6伏特之间的输入信号,并产生峰值电压范围为1.2伏特至0.6伏特的输出信号。所提出的LS电路设计在ASAP7 7nm Fin-Fet技术上进行了验证,其延迟和功耗分别优于最近采用零阈值电压架构的Wilson电流反射电平移位器42.76%和39.6%。所提出的拓扑结构显著地降低了功耗和传输延迟。
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引用次数: 0
Machine Learning Based Predictive Model for Intrusion Detection 基于机器学习的入侵检测预测模型
Somya Srivastav, Kalpna Guleria, Shagun Sharma
A software that examines network traffic and searches for inconsistencies is known as an Intrusion Detection System (IDS). Network changes that seem to be abnormal or unexpected could be evidence of fraud at any phase, from the beginning of an attempt through the end of an intrusion. Data sharing is required to be safe since it primarily relies on the internet. Encryption processes and verification are unsuitable for internet security, and firewalls are unable to recognize fragmented fake transmissions. Additionally, attackers frequently update their strategy, tools, techniques, and tactics, which can have bad consequences like productivity losses, financial harm, data loss, etc. Therefore, it is essential to set up a trustworthy IDS, which is an extremely difficult task. In this work, the accuracy of an IDS system is forecasted by using a variety of supervised Machine Learning (ML) algorithms, including Decision tree (DT), Random Forest (RT), K-Nearest Neighbor (KNN), and Logistic Regression (LR) models. For the analysis, the dataset is collected from Kaggle, and the method that produces the highest accuracy is recommended for making future forecasts of intrusion. Furthermore, the outcomes have resulted in accuracy, execution speed, precision, F-measure, and recall. Additionally, the random forest performed best with the highest accuracy of 98.65% which can be recommended for the enhanced dataset to be implemented for better results for an IDS.
一种检查网络流量并搜索不一致的软件被称为入侵检测系统(IDS)。看似异常或意外的网络变化可能是任何阶段(从尝试开始到入侵结束)欺诈的证据。数据共享必须是安全的,因为它主要依赖于互联网。加密过程和验证不适合互联网安全,防火墙无法识别碎片化的虚假传输。此外,攻击者经常更新他们的策略、工具、技术和战术,这可能会造成生产力损失、财务损失、数据丢失等不良后果。因此,建立一个值得信赖的IDS至关重要,这是一项极其困难的任务。在这项工作中,IDS系统的准确性是通过使用各种监督机器学习(ML)算法来预测的,包括决策树(DT)、随机森林(RT)、k近邻(KNN)和逻辑回归(LR)模型。为了进行分析,数据集是从Kaggle收集的,并且推荐产生最高准确性的方法来进行未来的入侵预测。此外,结果对准确性、执行速度、精度、f测量和召回率产生了影响。此外,随机森林表现最好,准确率高达98.65%,这可以推荐用于实现增强数据集,以获得更好的IDS结果。
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引用次数: 0
An Optimized Filter Design with Cuckoo Search Algorithm for Industrial Microgrids 基于布谷鸟搜索算法的工业微电网滤波器优化设计
G. Sreeramulu Mahesh, M. Chandrashekar, A. Muni Sankar, S. Mohan, S. Chandra Sekhar, P. S. Ranjit
Most of the IT industries with microgrids are facing the impacts of harmonics on lighting loads, UPS, Elevators and Air Handling Units with Variable Frequency Drives, thus reduces the equipment performance and its life cycle. Many passive filters like single tuned filter, double tuned filter or combination of both single and double tuned filters et are implemented practically in the industries. It requires a careful tuning, otherwise, the resonance problems will arouse in the entire microgrid and leads to instability between the generation and loads, thus the design of an optimized passive filter is still a challenging problem for mitigating the harmonics. The Cuckoo Search Algorithm (CSA) is proposed in this paper to design the passive harmonic filter to reduce the Total Harmonic Distortion and size of the filter, which provides better tuning than the manual tuning. The advantages of this algorithm are: simple and provides less latency in processing in the iterations. This CSA is implemented on real time data from an IT industry with Fluke analyzer and the filter design is carried out using MATLAB simulation software and desired waveforms are presented.
大多数拥有微电网的IT行业都面临着谐波对照明负载、UPS、电梯和变频驱动空气处理机组的影响,从而降低了设备的性能和生命周期。许多无源滤波器如单调谐滤波器、双调谐滤波器或单调谐和双调谐滤波器的组合等在工业中得到了实际应用。无源滤波器的优化设计需要仔细的调谐,否则会引起整个微电网的谐振问题,导致发电机组和负荷之间的不稳定,因此优化无源滤波器的设计仍然是一个具有挑战性的问题。本文提出了杜鹃搜索算法(CSA)来设计无源谐波滤波器,以减少总谐波失真和滤波器的尺寸,从而提供比手动调谐更好的调谐。该算法的优点是:简单,在迭代过程中提供较少的处理延迟。利用Fluke分析仪对某IT行业的实时数据实现了CSA,并利用MATLAB仿真软件进行了滤波器设计,给出了所需波形。
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引用次数: 0
EV Sahayak: Android Assistance App for Electric Vehicle EV Sahayak:电动汽车安卓辅助应用
Swati V. Jadhav, Sidhesh Marne, Soham Phadke, Tilak Solunke, Tanmayee Suryawanshi
Electric Vehicles are powered by electric motors rather than internal combustion engines, and they use electricity as their primary fuel. A number of energy sources, such as batteries, fuel cells, and solar panels, can be used to power EVs. They are becoming increasingly popular as an alternative to traditional gasoline-powered vehicles because they produce fewer emissions and can be more efficient and cost-effective to operate. In general, electric vehicle technology is advancing and changing and has the potential to lessen our dependency on fossil fuels and contribute to the fight against climate change. So as we need fuel stations for fuel-based vehicles, we need charging stations for electrical vehicles. But as of now, use of the electric vehicles in India is very limited; thus, finding information on these charging stations or their exact location is very hard. One of the best ways to help overcome such situations is to make an application for the electrical vehicle which will display the appropriate information about charging stations and give directions, on the location of the charging stations. EV Sahayak is one such helping application that gives the location of the charging station, helps the user with their payments, manages their files or documents, and gives some information about the parts of the vehicle, and hardware.
电动汽车是由电动机而不是内燃机驱动的,它们使用电力作为主要燃料。许多能源,如电池、燃料电池和太阳能电池板,都可以用来为电动汽车提供动力。作为传统汽油动力汽车的替代品,它们正变得越来越受欢迎,因为它们排放的废气更少,运行效率更高,成本效益更高。总的来说,电动汽车技术正在进步和变化,有可能减少我们对化石燃料的依赖,并为应对气候变化做出贡献。因此,正如我们需要燃料汽车的燃料站一样,我们也需要电动汽车的充电站。但到目前为止,电动汽车在印度的使用非常有限;因此,找到这些充电站的信息或它们的确切位置是非常困难的。帮助克服这种情况的最佳方法之一是申请电动汽车,它会显示有关充电站的适当信息,并指示充电站的位置。EV Sahayak就是这样一个帮助应用程序,它提供充电站的位置,帮助用户付款,管理他们的文件或文档,并提供有关车辆部件和硬件的一些信息。
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引用次数: 0
A Comprehensive Study of Time-Frequency Analysis of Musical Signals 音乐信号时频分析的综合研究
K. R. Chithra, M. Sinith
Time-frequency analysis is an efficient tool for analyzing an audio signal due to its quasi stationary nature. The spectral analysis gives important information about an audio signal such as pitch, onset detection, feature extraction etc. Time-frequency analysis combine both time and frequency domain analysis to provide better understanding of an audio signal. By analyzing a signal in both domains simultaneously, we can track how the frequency content of signal changes over time and how time varying properties impact its spectral characteristics. In this paper a comprehensive study on various methods for time-frequency analysis for musical signals is presented.
时频分析由于音频信号的准平稳特性而成为分析音频信号的有效工具。频谱分析给出了音频信号的重要信息,如基音、起始检测、特征提取等。时频分析结合了时域和频域分析,可以更好地理解音频信号。通过同时分析两个域中的信号,我们可以跟踪信号的频率内容如何随时间变化以及时变特性如何影响其频谱特性。本文对音乐信号时频分析的各种方法进行了全面的研究。
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引用次数: 0
Performance Analysis of RIS Assisted Power Domain NOMA System with Discrete Phase Shifter RIS辅助离散移相器功率域NOMA系统性能分析
Roshini Parameswaran, V. P. G. Sivabalan, Shrinithi Rajendran, T. S. Jayaraman
Reconfigurable Intelligent Surface (RIS/IRS) technology has the potential of improving coverage, capacity, and energy efficiency in wireless communication. RIS has control over the scattering and propagation of the transmitted signal to the receiver and it improves the Signal to Noise Ratio (SNR). The new encoding Non-Orthogonal Multiple Access (NOMA) system provide immense connectivity to the users from the base station at low latency. In an ideal scenario, the RIS completely compensate the phase of the signal, but this is not possible in a practical environment. The RIS using discrete phase shifters are analyzed with power variation for the near and far users. The probability error of the RIS-assisted NOMA system is analyzed for the various quantized bits of phase shifter which are one-bit shifter $(0, pi)$, two-bit shifter $(0, pi/2, pi, 3pi/2)$ and three-bit shifter $(0, pi/4,pi/2,3pi/4, pi, 5pi/4,3pi/2,7pi/4)$. The quantized phase shifters at the RIS degrade the Bit Error Rate (BER) performance and are compared with the ideal continuous phase shifter. This research shows that, while using a one-bit phase shifter the presence of residue reduces the system’s performance. Further, increasing the levels of the phase shifter to two-bit and three-bit improves the system performance compared to the one-bit phase shifter.
可重构智能表面(RIS/IRS)技术具有提高无线通信覆盖范围、容量和能效的潜力。RIS控制了发射信号到接收机的散射和传播,提高了信噪比(SNR)。新的编码非正交多址(NOMA)系统以低延迟为基站用户提供巨大的连接。在理想情况下,RIS完全补偿信号的相位,但这在实际环境中是不可能的。分析了采用离散移相器的RIS系统在近端和远端的功率变化情况。分析了ris辅助NOMA系统对移相器的不同量子化位元的概率误差,移相器分别为1位移相器$(0, pi)$、2位移相器$(0, pi/2, pi, 3pi/2)$和3位移相器$(0, pi/4,pi/2,3pi/4, pi, 5pi/4,3pi/2,7pi/4)$。在RIS中量化移相器降低了误码率(BER)性能,并与理想的连续移相器进行了比较。研究表明,当使用1位移相器时,残留的存在会降低系统的性能。此外,与1位移相器相比,将移相器的电平增加到2位和3位可以提高系统性能。
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引用次数: 0
A Review on 2D Photonic Crystal based All Optical Logic Gates 基于二维光子晶体的全光逻辑门研究进展
S. Nithya, T. Sridarshini
In recent year, every optical computing system and optical communication system depends on the photonic crystal. Based on their design, techniques and application the six all optical logic gates such as AND, OR, NOT, XOR, NOR and NAND are analyzed with contrast ratio and response time. Comparison is done based on types of defects, preferred structures for designing the logic gates. Gates designed with T, Y, E etc. where analysed and are reported. Most commonly they form a suitable candidature for high speed optical systems.
近年来,光学计算系统和光通信系统都离不开光子晶体。根据与、或、非、异或、非或、非与等六种全光逻辑门的设计、技术和应用,分析了它们的对比度和响应时间。根据缺陷类型和设计逻辑门的首选结构进行了比较。用T、Y、E等设计了闸门,并对其进行了分析和报道。最常见的是,他们形成了一个合适的候选高速光学系统。
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引用次数: 0
Unsupervised change detection analysis using deep clustering frameworks 使用深度聚类框架的无监督变更检测分析
S. E. F. Sherley, K. Harshitha, R.Siva Subetha, T. Thanigaivasan, R. Prabakaran, S. Lakshmi
Change detection involves quantifying temporal effects with a multi-temporal dataset. Remote sensing data have been extensively utilised for change detection in recent decades. Unsupervised learning is used to analyse satellite imagery or remote sensing data to find changes in land cover or land use over time without the use of labelled training data. Unsupervised learning is a type of machine learning that identifies patterns in data without the use of labels or prior knowledge. The general goal of change detection in remote sensing is to recognise the type of changes in specific geographic locations, and then quantify and assess changes in the regions. In this work, land change detection is analysed using various deep clustering techniques with multitemporal satellite images from different geographical locations. Two models, namely a deep-embedded clustering model, a sparse auto-encoding model are built and trained using both K-Means Clustering and FuzzyC-Means Clustering algorithms in clustering layer. The implemented models address the issue of mixed pixel clustering by using Fuzzy-C Means Clustering to determine whether region has changed over time using satellite images. The implementation is carried out in constrained environment with limited dataset and computational facilities. Deep clustering approaches necessitate high-quality data in order to produce accurate results. Poor-quality data can result in inaccurate clustering results, which can have an impact on the interpretation and application of the results. Due to cloud cover, atmospheric interference, and sensor limitations, environmental data can frequently have issues with noise, missing values, and data gaps, which can impair the quality of the clustering results and in turn, it misleads generation of changed regions. These constraints can have an impact on the quality of the data and make deep clustering approaches difficult to implement. The results of the implemented work have been assessed using Mean Square Error which is a function used to calculate the loss of a model and the effectiveness of a clustering technique is assessed by the silhouette score.
变化检测涉及使用多时间数据集量化时间效应。近几十年来,遥感数据已广泛用于变化探测。无监督学习用于分析卫星图像或遥感数据,以发现土地覆盖或土地利用随时间的变化,而不使用标记训练数据。无监督学习是一种机器学习,它在不使用标签或先验知识的情况下识别数据中的模式。遥感变化检测的总体目标是识别特定地理位置的变化类型,然后量化和评估该区域的变化。在这项工作中,利用不同地理位置的多时相卫星图像,使用各种深度聚类技术分析了土地变化检测。在聚类层分别使用K-Means聚类算法和FuzzyC-Means聚类算法建立并训练了深度嵌入聚类模型和稀疏自编码模型。实现的模型通过使用Fuzzy-C Means clustering来确定区域是否随着卫星图像的时间变化,从而解决了混合像素聚类的问题。该算法是在数据集和计算设备有限的约束环境下实现的。为了产生准确的结果,深度聚类方法需要高质量的数据。质量差的数据可能导致不准确的聚类结果,这可能对结果的解释和应用产生影响。由于云层覆盖、大气干扰和传感器的限制,环境数据经常会出现噪声、缺失值和数据缺口等问题,这些问题会损害聚类结果的质量,反过来,它会误导生成变化区域。这些约束可能对数据质量产生影响,并使深度聚类方法难以实现。使用均方误差(用于计算模型损失的函数)评估了实施工作的结果,并通过剪影分数评估了聚类技术的有效性。
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引用次数: 0
MedSay-Tamil: A Pharmacological-Translator Mobile Application for the aid of Native Tamil Speakers MedSay-Tamil:一个帮助母语泰米尔语者的药理学翻译移动应用程序
J. Joshua Alfred, V. Sai Srivathsan, A. Sasithradevi, S. Roomi
Medication error is one of the major causes of death, as victims intake the wrong medicine or dosage which can cause chronic effects. One such cause of medication error comes from the misinterpretation of information due to language barrier. There is a need for translation of information in medicinal strips to create awareness to the user. For this purpose, we propose an Innovative Mobile Application Using Flutter and Dart, empowering all native-Tamil speakers who find difficulty in acquiring information from tablet strips. The app is designed to revolutionize the way people obtain information from tablet strips such as general information, dosage, side effects, etc. with the help of web scraping. With its advanced Optical Character Recognition (OCR) engine, the app can accurately recognize text from images and convert it into editable text. The app’s user-friendly interface with its state-of-art innovation mainly focusing native-Tamil speakers, built using the Flutter framework, allows users to quickly and easily scan and process strings. The application then translates and displays the information present in the Tamil language along with a text-to-speech feature. Upon testing, the application displayed a 90% accuracy in retrieving relevant information about the tablet present in images.
用药错误是死亡的主要原因之一,因为受害者服用了错误的药物或剂量,可能导致慢性影响。用药错误的一个原因是由于语言障碍造成的信息误解。有必要翻译医药贴中的信息,以提高用户的认识。为此,我们提出了一个使用Flutter和Dart的创新移动应用程序,使所有母语为泰米尔语的人都能从平板电脑上获取信息。该应用程序旨在通过网页抓取技术,彻底改变人们从平板电脑上获取信息的方式,如一般信息、剂量、副作用等。凭借其先进的光学字符识别(OCR)引擎,该应用程序可以准确地识别图像中的文本,并将其转换为可编辑的文本。该应用程序的用户友好界面采用最先进的创新技术,主要针对母语为泰米尔语的人,使用Flutter框架构建,允许用户快速轻松地扫描和处理字符串。然后,应用程序翻译并显示泰米尔语中的信息,并提供文本到语音的功能。经过测试,该应用程序在检索图像中有关平板电脑的相关信息方面显示出90%的准确性。
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引用次数: 0
Abstractive Text Summarization Using BERT and GPT-2 Models 基于BERT和GPT-2模型的抽象文本摘要
Narayana Darapaneni, R. Prajeesh, Payel Dutta, Venkat K Pillai, Anirban Karak, A. Paduri
This paper aims to study the research articles related to Covid-19 and provide abstractive summarization on the same, demystifying the myths related to covid-19 as well as finding the possible root cause of hesitation in taking the vaccine. As per the government of India’s official site, as on 20th Jan 2023, 1 billion people have been fully vaccinated out of India’s total population of 1.4 billion. To fully eradicate Covid - 19, which emerged 3 years ago, the entire population needs to be vaccinated, but that’s not the case as people hesitate to get vaccinated due to various articles published in newspapers, social media, etc., the authenticity of which are unknown. In this paper we will try to summarize all the articles, as available in the CORD-19 dataset, using BERT and GPT-2 models. For extractive summarization, BERT models performed well, but there is a scope for improvement in abstractive summarization. Our approach involves utilizing regularization to suppress local similarity while simultaneously promoting global similarity, using the distill-gpt2 version with higher computing resources. We used V100 GPU with 100 computing engines from google collab-pro for faster computation and higher accuracy. The result will elaborate on the Rouge and Bleu score and its relevant significance for summarization.
本文旨在通过对Covid-19相关的研究文章进行研究,并对其进行抽象总结,揭开与Covid-19相关的神话,找到犹豫接种疫苗的可能根本原因。根据印度政府的官方网站,截至2023年1月20日,印度14亿总人口中有10亿人接种了全面疫苗。为了彻底根除3年前出现的Covid - 19,所有人都需要接种疫苗,但事实并非如此,因为报纸、社交媒体等上发表的各种文章真实性不明,人们对接种疫苗犹豫不决。在本文中,我们将尝试使用BERT和GPT-2模型总结CORD-19数据集中可用的所有文章。对于抽取摘要,BERT模型表现良好,但在抽象摘要方面仍有改进的余地。我们的方法包括利用正则化来抑制局部相似度,同时提高全局相似度,使用具有更高计算资源的蒸馏-gpt2版本。我们使用了V100 GPU和google lab-pro的100个计算引擎,以实现更快的计算速度和更高的精度。结果将阐述Rouge和Bleu评分及其相关意义进行总结。
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引用次数: 0
期刊
2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)
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