Pub Date : 2022-01-10DOI: 10.1109/ICAECC54045.2022.9716630
Thati Sethu Sumanth, G.VenkataMallikarjjuna Reddy, A. Reddy
This paper presents the design of 1.8V/3.3V 100 Mbps General Purpose Input/Output (GPIO) transmitter for an Intel Max 10 FPGA. This transmitter works for both 1.8V and 3.3V IO supplies. The building blocks of this transmitter are level shifter and driver circuits. The level shifter is designed to level up the data levels from 0.8V to 1.8V/3.3V. A progressive sized driver circuit is designed to drive 50$Omega$ termination resistance and the load capacitance of 5pF as per the requirement of Intel Max10. The overall design is carried out with 22nm technology node on cadence virtuoso platform and is simulated across PVT. The simulation results shows that the proposed design supports up to a data rate of 100Mbps with a power consumption of 1.59mW at 1.8V supply and with a power consumption of 2.93mW at 3.3V supply.
本文介绍了基于Intel Max 10 FPGA的1.8V/3.3V 100 Mbps通用输入/输出(GPIO)变送器的设计。此发射器适用于1.8V和3.3V IO电源。该发射机的组成部分是电平移位器和驱动电路。电平移位器设计用于将数据电平从0.8V调至1.8V/3.3V。根据Intel Max10的要求，设计了一种递进式驱动电路，以驱动50$Omega$的终端电阻和5pF的负载电容。总体设计采用22nm技术节点在cadence virtuoso平台上进行，并在pvm上进行了仿真。仿真结果表明，所提出的设计在1.8V供电时支持高达100Mbps的数据速率，功耗为1.59mW，在3.3V供电时功耗为2.93mW。
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Pub Date : 2022-01-10DOI: 10.1109/ICAECC54045.2022.9716716
Venu Yarlagadda, R. Geshmakumari, J. Rao, L. Gadupudi
Modern Distributed systems are equipped with plenty of non-linear loads viz. Computers, Electronic Loads, SMPS and many more Power Electronics based loads. These loads are injecting both voltage and current harmonics into the utility grid and distribution systems. The presence of harmonics is very damaging to all equipment which has been connected to the point of common coupling (PCC). This article focuses engrossed on the distribution system, incorporated of feeders with Distribution GTO Thyristor controlled Series Capacitor (D-GCSC) fed R and RL loads. This article entrust the simulation results with FFT analysis focused on THD of current and voltage waveforms, in two stages, one is with D-GCSC feeding resistive load and second is RL load. The distribution systems have been simulated without and with DSTATCOM for both the stages of D-GCSC fed loads and presented the results. The DSTATCOM is designed and closed loop control circuit have been developed and simulated the same which is quite effective in mitigating the Voltage as well as Current harmonics in distributed systems comprising of nonlinear Loads.
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Pub Date : 2022-01-10DOI: 10.1109/ICAECC54045.2022.9716600
Manan Doshi, Jimil Shah, Rahul Soni, Soni Bhambar
Hairstyles contribute majorly to an individual’s physical appearance. It is commonly observed that there is a huge gap between customer’s expectations and the barber’s understanding leading to post-haircut dissatisfaction. A major cause of this problem is that users lack the understanding of utilizing feature information while selecting a suitable hairstyle. A model that extracts essential features for decision-making can improve customer satisfaction. In this paper, we propose the FHP architecture that extracts features from user-submitted images that are crucial to hairstyle recommendations. The architecture consists of two major pipelines for extracting facial and hair features. The process starts with image segmentation and parsing. The segmented facial and hair regions are given as input to the two pipelines for extracting face shape, skin tone, hair texture, and hair color. These four features can then be used in the development of an expert system for hairstyle recommendations.
{"title":"FHP: Facial and Hair Feature Processor for Hairstyle Recommendation","authors":"Manan Doshi, Jimil Shah, Rahul Soni, Soni Bhambar","doi":"10.1109/ICAECC54045.2022.9716600","DOIUrl":"https://doi.org/10.1109/ICAECC54045.2022.9716600","url":null,"abstract":"Hairstyles contribute majorly to an individual’s physical appearance. It is commonly observed that there is a huge gap between customer’s expectations and the barber’s understanding leading to post-haircut dissatisfaction. A major cause of this problem is that users lack the understanding of utilizing feature information while selecting a suitable hairstyle. A model that extracts essential features for decision-making can improve customer satisfaction. In this paper, we propose the FHP architecture that extracts features from user-submitted images that are crucial to hairstyle recommendations. The architecture consists of two major pipelines for extracting facial and hair features. The process starts with image segmentation and parsing. The segmented facial and hair regions are given as input to the two pipelines for extracting face shape, skin tone, hair texture, and hair color. These four features can then be used in the development of an expert system for hairstyle recommendations.","PeriodicalId":199351,"journal":{"name":"2022 IEEE Fourth International Conference on Advances in Electronics, Computers and Communications (ICAECC)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128968716","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}
Pub Date : 2022-01-10DOI: 10.1109/ICAECC54045.2022.9716673
S. Suma, Bharati Harsoor
Applications of Wireless Sensor Network (WSN) are widely used in different areas. Packet drop occurs due to congestion-related issues like limited bandwidth, link failure, and interference also misbehaving node drops the packet to harm the network thus, provisioning of quality of service (QoS) for routing in mobile nodes for WSN is a challenging issue. Securing the mobile nodes from attackers has become one of the crucial aspects of providing QoS since nodes are weak to different kinds of attacks and threats that impact network connectivity and functionality. In WSN differentiating packet loss due to congestion or malicious node is a tedious job. The black-hole attack is examined to be an epidemic and popular passive attack that degrades overall reliability and network performance by dropping all the incoming packets. In the course of Black-hole node pretends that it has the shortest route to destination and intent to deceive every node in the network. In this paper we differentiate packet loss due to congestion or by malicious node, our scheme utilizes on-demand link and energy-aware dynamic multipath (O-LEADM) routing scheme for WSN to detect black-hole node by integrating bait method, the behavior of node is analyzed using control messages destination-sequence (des-Seq) and reply-sequence (rep-Seq) while accessing the channel. During route discovery, each intermediated node in the network sends the des-Seq message to all its neighbor nodes, and then neighbor nodes intern replies to the intermediate node by sending a rep-Seq message. If des-Seq and req-Seq from the neighbors do not match, then the node is said to be malicious. Connection to the network layer is allowed to an intermediate node if des-Seq and rep-Seq match. Channel availability and link quality parameter estimate the link stability thus nodes select forwarding based on their behavior and are capable of achieving QoS parameters such as link quality, residual energy, and higher packet delivery. Simulation under various network conditions is experimented with using the Network simulator tool (NS2) and using parameters the performance metric is in terms of delay, packet delivery ratio, overhead, and energy are evaluated.
{"title":"Detection of malicious activity for mobile nodes to avoid congestion in Wireless Sensor Network.","authors":"S. Suma, Bharati Harsoor","doi":"10.1109/ICAECC54045.2022.9716673","DOIUrl":"https://doi.org/10.1109/ICAECC54045.2022.9716673","url":null,"abstract":"Applications of Wireless Sensor Network (WSN) are widely used in different areas. Packet drop occurs due to congestion-related issues like limited bandwidth, link failure, and interference also misbehaving node drops the packet to harm the network thus, provisioning of quality of service (QoS) for routing in mobile nodes for WSN is a challenging issue. Securing the mobile nodes from attackers has become one of the crucial aspects of providing QoS since nodes are weak to different kinds of attacks and threats that impact network connectivity and functionality. In WSN differentiating packet loss due to congestion or malicious node is a tedious job. The black-hole attack is examined to be an epidemic and popular passive attack that degrades overall reliability and network performance by dropping all the incoming packets. In the course of Black-hole node pretends that it has the shortest route to destination and intent to deceive every node in the network. In this paper we differentiate packet loss due to congestion or by malicious node, our scheme utilizes on-demand link and energy-aware dynamic multipath (O-LEADM) routing scheme for WSN to detect black-hole node by integrating bait method, the behavior of node is analyzed using control messages destination-sequence (des-Seq) and reply-sequence (rep-Seq) while accessing the channel. During route discovery, each intermediated node in the network sends the des-Seq message to all its neighbor nodes, and then neighbor nodes intern replies to the intermediate node by sending a rep-Seq message. If des-Seq and req-Seq from the neighbors do not match, then the node is said to be malicious. Connection to the network layer is allowed to an intermediate node if des-Seq and rep-Seq match. Channel availability and link quality parameter estimate the link stability thus nodes select forwarding based on their behavior and are capable of achieving QoS parameters such as link quality, residual energy, and higher packet delivery. Simulation under various network conditions is experimented with using the Network simulator tool (NS2) and using parameters the performance metric is in terms of delay, packet delivery ratio, overhead, and energy are evaluated.","PeriodicalId":199351,"journal":{"name":"2022 IEEE Fourth International Conference on Advances in Electronics, Computers and Communications (ICAECC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123694633","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}
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