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2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)最新文献

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The optimal on-site generation allocation in a radial distribution system using GA and PSO 基于遗传算法和粒子群算法的径向配电系统现场发电优化分配
K. Rajesh, J. Rao
In electrical power systems the application of Distributed Generation (DG) is quickly expanding because it provides a long-term solution to many distribution system challenges, like Management of Voltage and reduction in power loss. Power loss reduction is critical to the cost-effective operation of a power system. This paper investigated the suitable location and size of on-site generation using an optimization approach i.e the Particle Swarm Optimisation (PSO) and Genetic algorithm with the objective of reducing power loss and enhancing the voltage profile in distribution networks. The inability to properly find the DG position may have a contrary influence on the system’s efficiency. Appropriate location and size play a very effective and vital function in boosting system efficiency by decreasing active power loss and optimising the voltage on each and every bus in the system. The forward-backward sweep method is used in distribution load flow research. The results of the simulation show that PSO can produce the largest reductions in power loss.
在电力系统中,分布式发电(DG)的应用正在迅速扩大,因为它为许多配电系统的挑战提供了长期的解决方案,如电压管理和降低功率损耗。降低功率损耗对电力系统的经济高效运行至关重要。本文采用粒子群优化和遗传算法研究了现场发电的合适位置和规模,以降低配电网的功率损耗和改善电压分布。不能正确地找到DG位置可能对系统的效率产生相反的影响。适当的位置和尺寸对降低有功功率损耗和优化系统各母线电压,提高系统效率起着非常有效和重要的作用。在配电网潮流研究中,采用了正向-反向扫描方法。仿真结果表明,粒子群优化能最大程度地降低功率损耗。
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引用次数: 0
Smart Approaches to Measure Soil Fertility for Sustainable Agriculture 测量可持续农业土壤肥力的智能方法
R. S. Upendra, M. R. Ahmed, A. Omkar, Jhanvi Goyal, V. Chaitra, H. Muskan, Pragati Kamath, K. Thirumala Akash
India is basically agriculture driven country and our GDP is principally directed by the yield of Rabi and Kharif crops. Most of the farmers of our country practices traditional way of agriculture. Since the amount of soil nutrients regulates the growth and quality of the crop, a systematic and quantitative analysis of soil nutrients is essential for good and adequate agricultural produce. Many small and large-scale farmers of the country India were not aware about the soil fertility nutrients and hence are unable to make use of their farming land efficiently for enhanced crop yield. The motive of the present work is to emphasize the significance of soil vitamins and the sensor based smart way of nutrient evaluation practices for measuring each essential nutrients i. e., Nitrogen, Phosphorus, and Potassium of Agri land. It was understood from the literature that, insufficient levels of essential elements (N, P, K) in farming lands can cause major issues connected with crop growth, productivity, and crop failure. To enlighten farmers and the readers with the smart farming practices, present study submitted a cumulative review on soil nutrient analysis methods with special emphasis on sensors based smart methods to measure the quantities of soil essential elements such as N, P, K. It has been concluded that potentiometric based electrochemical sensors are beneficial for soil testing and were found to be advantageous to farmers in keeping a constant check on their soil health, which intern enable the farmers to grow healthier crops and to maintain the surrounding soil biodiversity.
印度基本上是一个农业驱动的国家,我们的GDP主要由拉比和哈里夫作物的产量决定。我国大多数农民实行传统的农业生产方式。由于土壤养分的数量调节着作物的生长和质量,因此对土壤养分进行系统和定量分析对于优质和充足的农产品至关重要。印度的许多小型和大型农民不了解土壤肥力营养,因此无法有效地利用他们的耕地来提高作物产量。本研究的目的是强调土壤维生素的重要性和基于传感器的智能方法的养分评估实践,以测量农业土地的每一种必需营养素,即氮、磷、钾。从文献中可以理解,农田中基本元素(N, P, K)水平不足会导致与作物生长,生产力和作物歉收相关的重大问题。为了启发农民和读者的智慧农业实践,本研究提交了对土壤养分分析方法的累积综述,特别强调基于传感器的智能方法来测量土壤基本元素(如N, P, k)的数量。结论是基于电位的电化学传感器有利于土壤测试,并被发现有利于农民保持对其土壤健康的持续检查。这些实习生使农民能够种植更健康的作物,并保持周围土壤的生物多样性。
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引用次数: 1
A Review of Blockchain Based Approach for Secured Communication in Internet of Vehicle (IoV) Scenario 基于区块链的车联网(IoV)场景安全通信方法综述
F. Azam, Arun Biradar, Neeraj Priyadarshi, S.Vijaya kumari, Shrikant S. Tangade
Technology advances through time and fast development accompanies over the time. Telecommunications and wireless technology are pioneers among the emerging technologies. Vehicular Ad-hoc Network is the most progressive and foreseen research field under wireless communications as they are able to provide a large variety of ubiquitous services. They are a growing technology which provides a vast range of safety applications for the vehicle passengers. With an increase in such services, there will be an increase in the vulnerabilities which could be compromise the VANET communication. Successfully defending against such VANET’s attacks is continuously under research and growth. Blockchain offers decentralized, distributed, collective maintenance to counter malicious attacks. In view of the aforesaid issues, in this paper a dedicated discussion of various research works related to privacy and authentication schemes in VANETS using Blockchain has been made.
技术随着时间的推移而进步,快速发展伴随着时间。电信和无线技术是新兴技术中的先驱。由于车载自组织网络能够提供各种各样的泛在服务,因此是无线通信领域中最具发展前途的研究领域。它们是一项不断发展的技术,为车辆乘客提供了广泛的安全应用。随着此类服务的增加,可能危及VANET通信的漏洞也会增加。成功防御VANET的攻击一直在研究和发展中。区块链提供去中心化、分布式、集体性的维护,以对抗恶意攻击。鉴于上述问题,本文专门讨论了使用区块链的VANETS中与隐私和认证方案相关的各种研究工作。
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引用次数: 0
Logistic Regression versus XGBoost: Machine Learning for Counterfeit News Detection 逻辑回归与XGBoost:假新闻检测的机器学习
V. C. S. Rao, Pulyala Radhika, Niranjan Polala, Siripuri Kiran
In this age of globalization, the unstoppable spreading of fake news via the internet is unstoppable. The spread of false news cannot be supported due to the negative consequences. Society is extremely concerning. In addition, itleads to more serious problems and possible threats, like confusion, misunderstandings, defamation and falsehoods that induce users to share inflammatory content. With the convenience and tremendous increase in information gathering on social networks, it is becoming difficult to differentiate between what is false and what is real. Information can be easily disseminated through sharing, which has contributed to the exponential growth of their forgeries. Machine learning played an important role, in classifying information, although there are some limitations. This article explores various machine learning techniques used to detect fake and fabricated messages. The limitations are discussed using deep learning implementation. In this project, the methodology used is model development and Logistic Regression classifier is considered to detect false news. Based on previous research, this classifier performed well in classification tasks. In this approach, TF-IDF feature is used for the construction of this fake news model to get higher accuracy. The goal of this project is to detect false news using NLP and Machine Learning based on the news content of the article. Following the development of the appropriate Machine Learning model to detect fake/true news, it is deployed into a web interface using Python Flask.
在这个全球化的时代,假新闻通过互联网的传播是不可阻挡的。由于负面后果,虚假新闻的传播无法得到支持。社会对此非常担忧。此外,它还会导致更严重的问题和可能的威胁,比如混淆、误解、诽谤和虚假信息,从而诱使用户分享煽动性的内容。随着社交网络上信息收集的便利和大量增加,区分真假变得越来越困难。信息通过共享很容易传播,这导致了伪造的指数级增长。机器学习在信息分类方面发挥了重要作用,尽管存在一些局限性。本文探讨了用于检测虚假和伪造消息的各种机器学习技术。使用深度学习实现讨论了局限性。在这个项目中,使用的方法是模型开发和逻辑回归分类器被认为是检测假新闻。根据以往的研究,该分类器在分类任务中表现良好。在这种方法中,利用TF-IDF特征来构建假新闻模型,以获得更高的准确率。这个项目的目标是基于文章的新闻内容,使用NLP和机器学习来检测假新闻。在开发了适当的机器学习模型来检测假/真新闻之后,它被部署到使用Python Flask的web界面中。
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引用次数: 1
High Performance VLSI Architecture of Multiplexer and Demultiplexer Using various Adiabatic Logic 采用各种绝热逻辑的多路复用器和解路复用器的高性能VLSI架构
S. Karunakaran, P. Snehith
Using adiabatic logics, we proposed the design and evaluation of a 1:16 Multiplexer and a 16:1 De-Multiplexer in this paper. We used traditional static CMOS logic to implement a 1:16 Multiplexer and a 16:1 De-multiplexer to compare the strength of static cmos logic and adiabatic logic. In many vlsi designs, power consumption is the most important factor. We used adiabatic logics to implement a 1:16 Multiplexer and 16:1 Demultiplexer in static CMOS logic to minimize power consumption. The adiabatic logics are 2N2P and 2N2N2P where in both the adiabatic logics use cross-coupled transistor for adiabatic operation. Adiabatic logic uses reverse logic and energy recovery technique that results in less power dissipation when compared to static CMOS logic. In static CMOS logic, we will give constant power source as Vdd. So, the total energy gets dissipated across the resistor, the energy stored by the capacitor will be very less because of this energy recovery is not happened as in case of static CMOS logic. In adiabatic logic we will give slowly varying ramp signal as vdd. So, the total energy is not dissipated across resistor and the capacitor starts charging. In the discharging phase the energy stored by the capacitor is sent back to the source because of this energy consumption is reduced. This is the energy recovery technique which happens in adiabatic logics.
本文采用绝热逻辑,提出了1:16复用器和16:1解复用器的设计和评价。我们使用传统的静态CMOS逻辑来实现1:16的多路复用器和16:1的解复用器,以比较静态CMOS逻辑和绝热逻辑的强度。在许多超大规模集成电路设计中,功耗是最重要的因素。我们使用绝热逻辑在静态CMOS逻辑中实现1:16的多路复用器和16:1的解路复用器,以最大限度地降低功耗。绝热逻辑是2N2P和2N2N2P,在这两个绝热逻辑中都使用交叉耦合晶体管进行绝热操作。绝热逻辑采用反向逻辑和能量回收技术,与静态CMOS逻辑相比,功耗更低。在静态CMOS逻辑中,我们将恒定电源作为Vdd。因此,总能量在电阻上耗散,电容器存储的能量将非常少,因为这种能量回收没有发生在静态CMOS逻辑的情况下。在绝热逻辑中,我们将缓慢变化的斜坡信号表示为vdd。因此,总能量不会在电阻器上耗散,电容器开始充电。在放电阶段,电容器储存的能量被送回电源,因为这种能量消耗减少了。这是绝热逻辑中的能量回收技术。
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引用次数: 0
A Discrete Fourier Transform Based Fault Identification Scheme for IEEE 9-bus System 基于离散傅立叶变换的IEEE 9总线系统故障识别方法
B. Chatterjee, Subhrajyoti Sarkar
This study proposes a fault detection and classification algorithm for IEEE 9-bus system using discrete Fourier transform (DFT) and sequence component analysis (SCA). This scheme makes use of only voltage data from single-end of the line. Wide range of simulation has been run to asses the utility and robustness of the scheme. Simulation results reveal that this scheme can be successfully applied on a test system, as fault classification accuracy is 100%.
提出了一种基于离散傅立叶变换(DFT)和序列分量分析(SCA)的IEEE 9总线系统故障检测与分类算法。该方案仅利用线路单端电压数据。为了评估该方案的实用性和鲁棒性,进行了大量的仿真。仿真结果表明,该方法可以成功地应用于测试系统,故障分类准确率达到100%。
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引用次数: 0
ConvNet Based Detection and Segmentation of Brain Tumor from MR Images 基于卷积神经网络的脑肿瘤MR图像检测与分割
Valaparla Rohini, Kuchipudi Prasanth Kumar
One of the diseases that affects humans is brain tumor. It is a type of malignancy disease. A brain tumor is aberrant brain cells that has grown out of control in the brain. This sickness affects many people, and it might be difficult to survive in large groups. When allowing people for early detection of brain tumor, it will help to survive and reduce the death rate of people. Detection of aberrant cells formation in brain is very difficult in medical imaging. The Detection is done by using magnetic resonance imaging (MRI). In this paper, ConvNet architecture is proposed with transfer learning to detect tumor and it aims to differentiate the tumor area by using ROI and non-ROI. The data set is taken from open source Kaggle repository. This model obtained 98.1% accuracy on test data set. This model performed state of the art work.
脑肿瘤是影响人类的疾病之一。它是一种恶性肿瘤。脑瘤是大脑中生长失控的异常脑细胞。这种疾病会影响许多人,在大群体中可能很难生存。当允许人们对脑肿瘤进行早期发现时,将有助于人们的生存,降低人们的死亡率。脑异常细胞形成的检测是医学影像学中的一个难点。检测是通过使用磁共振成像(MRI)完成的。本文提出了一种基于迁移学习的卷积神经网络结构来检测肿瘤,其目的是利用感兴趣区域和非感兴趣区域来区分肿瘤区域。数据集取自开源Kaggle存储库。该模型在测试数据集上获得了98.1%的准确率。这个模型完成了最先进的工作。
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引用次数: 1
Machine Learning based Cardiac Magnetic Resonance Imaging (CMRI) for Cardiac Disease Detection 基于机器学习的心脏磁共振成像(CMRI)用于心脏病检测
M. Ramesh, S. Mandapati, B. Prasad, B. Kumar
The electrocardiogram (ECG) is a graphical representation of the heart’s electrical activity generated by contraction and relaxation of the heart muscle. An ECG is a vital tool for diagnosing heart conditions. The ECG flag is required for patient care. Early detection of heart disease allows specialists to differentiate between heart illnesses. A growing number of heart diseases necessitated the development of automatic abnormality detection techniques to relieve physicians. Cardiac magnetic resonance (CMR) images are becoming increasingly important in the diagnosis and monitoring of cardiovascular diseases in the nanomaterial of the kernels. As a result of the large amount and diversity of the data available, there are still many unanswered questions when it comes to the description and characterization of nanomaterial. Biomaterials characterization requires minimal information, which can be provided by AI and machine learning algorithms. These representations are also intended to provide an estimate of the CMR image quality in order to facilitate better interpretation and analysis of the CMR images. Also investigated, how quantitative analysis can be used to benefit from the use of these learned image representations during the process of image synthesis.
心电图(ECG)是由心肌收缩和松弛产生的心脏电活动的图形表示。心电图是诊断心脏病的重要工具。心电图标志是病人护理所必需的。心脏病的早期检测使专家能够区分不同的心脏病。越来越多的心脏疾病需要开发自动异常检测技术来减轻医生的负担。心脏磁共振(CMR)图像在核纳米材料中的心血管疾病的诊断和监测中变得越来越重要。由于可用数据的数量和多样性,在纳米材料的描述和表征方面仍有许多未解决的问题。生物材料表征需要最少的信息,这可以由人工智能和机器学习算法提供。这些表示还旨在提供CMR图像质量的估计,以便更好地解释和分析CMR图像。还研究了在图像合成过程中如何使用定量分析来受益于这些学习到的图像表示。
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引用次数: 0
Head Motion Controlled Wheelchair for Physically Disabled People 残疾人士头部运动控制轮椅
Farah Binte Haque, Tawhid Hossain Shuvo, R. Khan
Physically disabled people face difficulties in daily life because of their body impairment from their birth or due to an accident or illness. The project’s goal is to design a wheelchair that could function for a disable-person who cannot move other parts of the body correctly, keeping their words in mind with the help of head movements. Medical equipment manufactured to assist disabled peoples are very complicated, limited, and costly. A head motion controlled wheelchair is an intelligent wheelchair with facilities for navigating, recognizing obstacles, and moving automatically by managing detectors and motions. The prototype of the wheelchair performs head motion through a microcontroller. Furthermore, data processing is performed with the help of an accelerometer. The controller filters the indication and allows the action of the wheelchair for its navigation. The ultrasound detector helps to resist impediments. Usually, it is expensive, but we have designed it at an inadequate cost so that ordinary people from underdeveloped or developing countries can use it. The system memorizes the head gesture for further referencing it as the stable gesture or “neutral position” after identifying the start signal. The dc motors will drive the wheelchair during the gesture of control mode. The motors will not work, and consequently, the wheelchair will not run when the head is neutral.
身体残疾人士在日常生活中面临困难,因为他们的身体从出生起就有缺陷,或由于事故或疾病。该项目的目标是设计一种轮椅,可以为残疾人服务,他们不能正常移动身体的其他部位,通过头部运动来记住他们的话。为帮助残疾人而制造的医疗设备非常复杂、有限且昂贵。头部运动控制轮椅是一种智能轮椅,具有导航、识别障碍物、通过管理探测器和运动自动移动的功能。轮椅的原型通过微控制器执行头部运动。此外,数据处理是在加速度计的帮助下进行的。控制器过滤指示并允许轮椅的导航动作。超声波探测仪有助于抵抗障碍物。通常,它是昂贵的,但我们设计了一个不适当的成本,使不发达国家或发展中国家的普通人可以使用它。系统会记住头部手势,以便在识别启动信号后将其作为稳定手势或“中立位置”进行参考。在手势控制模式下,由直流电机驱动轮椅。马达将不工作,因此,轮椅将不会运行时,头部是中性的。
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引用次数: 9
14nm FinFET based 0.8V Supply 25Gbps Subsampler and Phase Detector Circuits for All Digital CDR 基于14nm FinFET的全数字CDR 0.8V电源25Gbps下采样器和鉴相电路
Sai Bhargav Sriramoju, Subhakumar Reddy Ankireddypalli
In this paper, the design of subsampler and phase detector circuits at 14nm technology node (FinFET) is presented. The design is carried out on cadence virtuoso with a supply voltage of 0.8V and across process corners (ss, sf, tt, fs, ff). The designed subsampler and phase detector circuits are in compliance with the All-digital clock and data recovery (ADCDR) circuit and which is applicable to passive optical networks of 4 channels with a speed of 25Gbps per channel by consuming a power dissipation of 0.9728 mW.
本文介绍了14nm技术节点(FinFET)下采样器和鉴相器电路的设计。设计是在cadence virtuoso上进行的,电源电压为0.8V,跨工艺角(ss, sf, tt, fs, ff)。所设计的下采样器和鉴相器电路符合全数字时钟和数据恢复(ADCDR)电路,适用于每通道速度为25Gbps的4通道无源光网络,功耗为0.9728 mW。
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引用次数: 0
期刊
2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)
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