2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)最新文献_第5页

Triple Band Filter with Cross Coupled SIR for Wireless Applications and Harmonic pass band Rejection with DGS 无线应用的交叉耦合SIR三带滤波器和DGS谐波通带抑制

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760523

A. Neogi, J. Panda

引用次数: 1

Design of 12T SRAM with improved stability for IOT application 为物联网应用设计稳定性更高的12T SRAM

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760666

M. Reddy, Deepakkumar Panda

{"title":"Design of 12T SRAM with improved stability for IOT application","authors":"M. Reddy, Deepakkumar Panda","doi":"10.1109/AISP53593.2022.9760666","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760666","url":null,"abstract":"IOT (Internet of Things) devices such as connected appliances,smart home security systems,wireless inventory trackers,ultra-high speed wireless internet etc. are a gravitating topic of research. In the trending electronic market we do have number of IOT devices flourishing. The IOT application requires such as compactness, lightness, manageability, form-factor, weight, etc. recite the hallmark of such devices. Tiny, slight, movable, and light weight Internet of Things devices use either rechargeable or Non-rechargeable and avoid the utilization of sources such as primary energy one’s. Because the lifespan of batteries and renewal span are condemnatory problems in battery-operated or partly energy-harvested IOT devices, ultralow-power(UL-P) system-on-chips (So-C) are becoming a extensive solution of chipmakers’ option. These kind of UL-P So-C needs logic as well as Static RAM in the processor to perform at low supply voltage’s. The proposed 12MOSFET SRAM(12T) proves itself operating at very low Supply Voltage. The reproving design metrics of introduced 12MOSFET SRAM Bit-Cell are calculated and differentiated with that of (6MOSFET) CON6T, (7MOSFET)CON7T, (8MOSFET)CON8T and (12MOSFET)CON12T SRAM Bit Cell. The RSNM of introduced 12MOSFET Static RAM Bit Cell reaches $1.7 times$ excessive as differentiated to 7MOSFET and 8MOSFET and rests identical as CON12T. The WSNM of introduced 12MOSFET SRAM Bit Cell reaches $1.8 times$ excessive as differentiated to 8MOSFET//7MOSFET and $1.4 times$ excessive differentiated to CON12T.The introduced 12MOSFET SRAM Bit Cell absorb $0.6127 times$ lower accessing power as compared to 8MOSFET and $0.4637 times$ lower accessing power compared to 7MOSFET and $0.253 times$ low accessing power compared to CON12T.The power of introduced 12MOSFET in Hold mode reaches $0.0499/0.055/ 0.0499 times$ lesser as differentiated to 7MOSFET/ 8MOSFET/ CON12T. EQM of 12MOSFET, as it represents the entire performance of SRAM, is greater when compared with remaining conventional methods.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"15 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90058021","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}

引用次数: 0

PereiraASLNet: ASL letter recognition with YOLOX taking Mean Average Precision and Inference Time considerations PereiraASLNet:考虑平均精度和推理时间的YOLOX手语字母识别

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760665

Noel Pereira

{"title":"PereiraASLNet: ASL letter recognition with YOLOX taking Mean Average Precision and Inference Time considerations","authors":"Noel Pereira","doi":"10.1109/AISP53593.2022.9760665","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760665","url":null,"abstract":"Sign language essentially allows for communication without the need to explicitly say words. It was developed by the American School for the Deaf in the early 90’s. It is a naturally generated language which incorporates facial movements and hand gestures to convey thoughts and ideas. In modern times, it is used predominantly by people who are deaf and hard of hearing. Unlike most languages, ASL isn’t widely taught which makes it difficult for the general population to communicate effectively with those people who predominantly use ASL as the sole means of communication. Therefore, arises the need for a system which detects and predicts letters from images and which can then be used in real time to overcome this language barrier. This research aims to develop a sign language recognition system atop of YOLOX, which is built on top of YOLOV3, which contains in its architecture, convolutional neural networks. Using the various backbones of YOLOX, this paper introduces and provides six models on every end of the accuracy-testing time spectrum from least accurate/fastest response time to the most accurate/slowest response time. I thereby propose PereiraASLNet, which trains YOLOX with custom classes from the letters A-Z and a Pascal VOC XML American Sign Language dataset developed by Roboflow and variants of YOLOX have been developed, taking into consideration the mean average precision and inference times of all the YOLOX backbone architectures namely the YOLOX-nano, YOLOX-tiny, YOLOX-small, YOLOX-medium, YOLOX-large and YOLOX-xlarge. The testing mean average precision for the models were found to be – 0.9046, 0.9070, 0.9227, 0.9304, 0.9329 and 0.9578 and the testing inference time was found to be 3.50ms, 12.97ms, 34.86ms, 64.56ms, 83.23ms and 97.56ms respectively","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"20 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86267345","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}

引用次数: 2

Effect of VCO Non-Linearity on Non-Contact Vital Signs Detection in CW and FMCW Radars VCO非线性对连续波和FMCW雷达非接触生命体征检测的影响

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760661

S. Lakhote, Sumit Kumar, Gaurab Banerjee

引用次数: 0

Leveraging Ensemble Time-series Forecasting Model to Predict the amount of Rainfall in Andhra Pradesh 利用集合时间序列预测模型预测安得拉邦的降雨量

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760553

S. J. Basha, G. L. V. Prasad, K. Vivek, Eedupalli Sai Kumar, Tamminina Ammannamma

{"title":"Leveraging Ensemble Time-series Forecasting Model to Predict the amount of Rainfall in Andhra Pradesh","authors":"S. J. Basha, G. L. V. Prasad, K. Vivek, Eedupalli Sai Kumar, Tamminina Ammannamma","doi":"10.1109/AISP53593.2022.9760553","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760553","url":null,"abstract":"Rainfall in India is becoming more unpredictable, leaving it harder to forecast. When it comes to predicting Indian summer monsoon rainfall, the Indian Meteorological Department (IMD) now uses Ensemble methods and Statistical methods. As a result of this, strategists are unable to foresee the socioeconomic consequences of floods (too many rains) or droughts (fewer rains). Precisely how much rain falls depends on several variables such as a measure of the warmth or coldness in the air, moisture, breeze, movement, and direction of the wind. This article will use Ensemble time-series forecasting model ARIMA (Autoregressive Integrated Moving Average)+ GARCH (Generalized Auto-Regressive Conditional Heteroskedasticity) to forecast the intensity of rainfall by considering various meteorological factors like sea-level pressure, moisture, dew point, min-max temperature, snowfall, geopotential height, speed and direction of the wind, humidity, and atmospheric pressure. The suggested Ensemble ARIMA+GARCH model has given good results when compared with individual models and state-of-the-art ensemble approaches in terms of RMSE, MAE, and MSE.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"24 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82608838","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}

引用次数: 11

Design and Analysis of Two Low Power SRAM Cell Structures 两种低功耗SRAM单元结构的设计与分析

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760587

G. V. Ganesh, Chittaluri Sahithi, Mathi Rashmi Sri, Vaddempudi Sony

引用次数: 0

Generation of Netlist from a Hand drawn Circuit through Image Processing and Machine Learning 通过图像处理和机器学习从手绘电路生成网表

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760577

Akshatha Mohan, Athulya B Mohan, B. Indushree, M. Malavikaa, C. Narendra

引用次数: 1

Power Consumption Prediction of Digital Circuits using Machine Learning 基于机器学习的数字电路功耗预测

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760542

Modi Divy Bhavesh, Nair Anoopkumar Anilkumar, Manish I. Patel, Ruchi Gajjar, D. Panchal

{"title":"Power Consumption Prediction of Digital Circuits using Machine Learning","authors":"Modi Divy Bhavesh, Nair Anoopkumar Anilkumar, Manish I. Patel, Ruchi Gajjar, D. Panchal","doi":"10.1109/AISP53593.2022.9760542","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760542","url":null,"abstract":"The demand for Integrated Circuits (ICs) is increasing exponentially, leading to the challenges of a more reliable and effective Electronic Design Tool (EDA) for the circuit design flow. To overcome such limitations Machine Learning (ML) is used, which can learn from the previous design data and can apply it to the unknown design given to it. In this context, the paper proposes the use of the regression technique of ML to estimate the power consumption of the MOSFET-based digital circuits. For this purpose, to train the ML-based regressor model, a dataset is created from the PMOS based Resistive Load Inverter (RLI), NMOS based RLI, and CMOS-based NAND gate layout. For the formation of the dataset, a 90nm MOS technology node is used and it inculcates the features like capacitance, resistance, number of MOSFET, their respective width and length, and the average power consumption of the respective layout. The regressor model used to predict the power consumption in this work is linear regressor, polynomial regressor, random forest regressor, decision tree regressor, and the extra tree regressor. At last, from the experimental results, it is observed that the extra tree regressor performs better for the RLI circuits with the MSE value of $4.02times 10^{-10}$ and $mathrm{R}^{2}$ value of 0.61, and for the NAND gate, the polynomial linear regressor excels with the MSE value of $7.27times 10^{-10}$ and $mathrm{R}^{2}$ value of 0.65.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"5 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75045246","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}

引用次数: 3

Energy Efficient VoD with Cache in TWDM PON ring TWDM PON环中带缓存的节能视频点播

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760612

Bhargav Ram Rayapati, N. Rangaswamy, A. V. Bhaskar

{"title":"Energy Efficient VoD with Cache in TWDM PON ring","authors":"Bhargav Ram Rayapati, N. Rangaswamy, A. V. Bhaskar","doi":"10.1109/AISP53593.2022.9760612","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760612","url":null,"abstract":"This work discusses the availability of cache memories for VoD service in Time and Wavelength Division Multiplexed Passive Optical Network (TWDM PON) ring topology. In a unidirectional ring topology with TWDM PON, the wavelength channels are enabled in an anti-cyclic manner through intermediate devices such as Remote Node (RN) and splitter as per traffic requirements. The provision of cache storage at subsystems of ring topology, namely, Optical Line Terminal (OLT), RN, and Optical Network Unit (ONU) enables the users to access the VoD service within reach rather than from a typical video server. Thus, this mechanism reduces the delay as well as power requirements. However, in this paper the analytical emphasis on the ring topology is confined only to power requirements through two situational cases. In the first case, the cache storage at OLT and ONU is only availed. While in the second case, the cache available at RN was also made to use. It is observed that the power consumption in the second case is lesser than in the first case. Due to more decentralization of cache availability in the second case, relatively 70 % more power savings are observed.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"3 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73175757","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}

引用次数: 0

Metamaterial Loaded Miniaturized Microstrip Annular Slot Antenna with Increased Gain 增加增益的超材料加载小型化微带环形缝隙天线

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760526

Uday A. Patil, A. Kakade, Sajeed S. Mulla

{"title":"Metamaterial Loaded Miniaturized Microstrip Annular Slot Antenna with Increased Gain","authors":"Uday A. Patil, A. Kakade, Sajeed S. Mulla","doi":"10.1109/AISP53593.2022.9760526","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760526","url":null,"abstract":"In this paper the microstrip annular slot antenna (MASA) loaded with surrounding metamaterial having permittivity and permeability less than zero is investigated with analytical and numerical methods. A solution to the source surrounded by an infinite inhomogeneous medium is obtained. Then the same technique is used to formulate the field equations of the microstrip annular slot antenna (MASA) surrounded by a homogeneous metamaterial. The power gain of the microstrip annular slot antenna (MASA) surrounded by the metamaterial medium relative to the dielectric medium is analyzed and calculated. The analysis of the reactance ratio and the reactive power of the MASA shows that the surrounding metamaterial acts as a natural impedance matching network for an antenna. The equivalent circuit model for the surrounding inhomogeneous medium with metamaterial has been proposed. It justifies the approval of the metamaterial as a natural impedance matching network. The radiated power of the MASA surrounded by metamaterial (with media constant $varepsilon_{2}=-varepsilon_{0}, mu_{2}=-mu_{0}$) has been increased by 73.66 times the radiated power of the MASA surrounded by a dielectric medium $(varepsilon_{2}=varepsilon_{0}, mu_{2}=mu_{0})$.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"69 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73601914","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}

引用次数: 0