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

ARIMA and RNN for Selection Sequences Prediction in Iowa Gambling Task 基于ARIMA和RNN的爱荷华赌博任务选择序列预测

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760558

Yuemeng Guo, Sensen Song, Hanbo Xie, Xiaoxue Gao, Jianlei Zhang

引用次数: 0

Smart Green House for Controlling & Monitoring Temperature, Soil & Humidity Using IOT 利用物联网控制和监测温度、土壤和湿度的智能温室

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760541

Akash Saha, Priyanka Sarkar Das, Bipasha Chakrabarti Banik

{"title":"Smart Green House for Controlling & Monitoring Temperature, Soil & Humidity Using IOT","authors":"Akash Saha, Priyanka Sarkar Das, Bipasha Chakrabarti Banik","doi":"10.1109/AISP53593.2022.9760541","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760541","url":null,"abstract":"Agricultural economics plays a vital role in the economics sector of development as because large portion of a country’s population depends on agriculture sector. Higher agricultural productivity also increases the income of the rural population, raising demand for industrial output. Almost 70 percent of the India’s population depends on the agriculture sector. Agricultural development makes a critical contribution to overall economic growth in many developing countries. As farmers’ incomes rise, so does their demand both for farm inputs and services, and for non-farm goods. Increased agricultural production also leads to increased demand for processing facilities. There are many factors, which slow this development. So Smart farming is a management concept using modern technology to increase the quantity and quality of agricultural products. Today’s agriculture routinely uses sophisticated technologies such as robots, temperature and moisture sensors, aerial images, and GPS technology. These advanced devices and precision agriculture and robotic systems allow businesses to be more profitable, efficient, safer, and more environmentally friendly. The main objective of this paper is to design a smartphone controlled green house with advanced monitoring system for controlling various parameters like temperature control, sob moisture & humidity control of any agricultural process. The prototype presented in this paper can monitor temperature, soil and humidity through sensors, IOT & ISP.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84357332","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: 4

A CNN based Hybrid Model for Pneumonia Classification Using Chest X-ray Images 基于CNN的胸片肺炎分类混合模型

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760525

Divyesh Ranpariya, Parin Parikh, Manish I. Patel, Ruchi Gajjar

{"title":"A CNN based Hybrid Model for Pneumonia Classification Using Chest X-ray Images","authors":"Divyesh Ranpariya, Parin Parikh, Manish I. Patel, Ruchi Gajjar","doi":"10.1109/AISP53593.2022.9760525","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760525","url":null,"abstract":"Pneumonia is a lung infection caused by bacteria, viruses, or fungi. It is one of the deadliest lung diseases among children under the age of five. An expert or radiologist can usually diagnose the condition using X-ray images of the chest. The use of machine learning in medical image processing helps to improve detection accuracy. This study aims to develop and present a combined Deep Learning model for classifying patients with Pneumonia disease based on chest X-rays. Three separate models are trained for the chest X-ray dataset in the proposed implementation, the first of which is the custom Convolutional Neural Network model. The other two models are Xception and EfficientNetB4. Various data augmentation and pre-processing methods are used, along with hyperparameter tuning. A combined model is created by assigning weights to the trained models based on their recall and accuracy values, and the classification results are obtained by a polling mechanism at the output, which gives an accuracy of 98.00%. The proposed work outperforms the existing literature in terms of several performance parameters.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85166304","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: 1

Secure ‘Text in Image’ Steganography Scheme Based on Alexnet and Contour-Let Transform 基于Alexnet和contourlet变换的安全“图像中的文本”隐写方案

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760538

Lingamallu Naga Srinivasu, Vijayaraghavan Veeramani

{"title":"Secure ‘Text in Image’ Steganography Scheme Based on Alexnet and Contour-Let Transform","authors":"Lingamallu Naga Srinivasu, Vijayaraghavan Veeramani","doi":"10.1109/AISP53593.2022.9760538","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760538","url":null,"abstract":"Nowadays, ‘text in image’ steganography is utilised in a variety of applications like military, surveillance, and remote sensing etc., in order to keep the secret information secure. This paper is presenting the unique steganography algorithm for improving data security, visual quality, quality metrics and withstand the attacks of the stego image. In proposed algorithm, the security of the confidential information is improved by utilizing the SLICE encryption algorithm. It is used to generate the cipher data from the confidential data. The alexnet is introduced in this paper to detect the facial area in human cover image. A total of 1987 images are used to train the network and got maximum accuracy. Contour-let transform is utilized to decomposition of alexnet output. The “random pixel embedding” (RPE) technique is utilized to embed the confidential data in facial area of the sub-band. The combination of alexnet and contourlet transform is used to generate good visual quality of the stego image. The proposed algorithm produces a stego image that has better visual quality, security, metric-values and withstand attacks compared to recent methods.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85308998","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

Rectangular Strip Loaded Circular Patch Antenna for Simultaneous Improvement of Co polar Gain and Co Polarization to Cross Polarization radiation Separation 同时改善Co极增益和Co极化的矩形带加载圆形贴片天线

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760575

Zonunmawii, L. L. K. Singh, S. Chattopadhyay, Abhijyoti Ghosh

引用次数: 0

Dielectric Modulated Double Gate Hetero Dielectric TFET (DM-DGH-TFET) Biosensors: Gate Misalignment Analysis on Sensitivity 介质调制双栅异质介质TFET (DM-DGH-TFET)生物传感器:灵敏度的栅极失调分析

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760561

N. Reddy, D. Panda

{"title":"Dielectric Modulated Double Gate Hetero Dielectric TFET (DM-DGH-TFET) Biosensors: Gate Misalignment Analysis on Sensitivity","authors":"N. Reddy, D. Panda","doi":"10.1109/AISP53593.2022.9760561","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760561","url":null,"abstract":"In this article, we have investigated the Gate misalignment effects on the performance of the Double gate hetero dielectric TFET(DGH-TFET) biosensor device in terms of subthreshold swing(SS), ON-current (I$_{mathbf{on}}$), OFF Current (I$_{mathbf{off}}$), Threshold voltage (Vth) and the ratio of ON-current (Ion) to the OF-current (I$_{mathbf{on}} {/mathbf{I}}_{mathbf{off}}$). For the first time, we have thoroughly investigated the misalignment of gate electrodes effect on the sensitivity of the double gate TFET based biosensor where actually considered the symmetric gate structure with no deviation in the gate alignment, however practically which is not possible. With due respect to the investigation carried in this work along with the sensitivity analysis, it observed that position and the alignment of both top and bottom gate show significant impact on the sensitivity of the biosensor. The misalignment of the double gate is executed by altering the position of the top gate in overlapped state and underlapped state concerning the bottom gate of the proposed double gate TFET biosensor. The underlapped gate structure degrades the performance device compared to the symmetric aligned gate structure, but the overlapped gate structure improves the device’s overall performance. The investigation is carried by taking the misalignment effect in the range of 10 nm in both overlapped and underlapped cases. The underlapped alignment gate structure falls of the subthreshold sensitivity by 30%, where the overlapped gate structure become the advantage for shoot up the sensitivity of the doublet gate hetero dielectric TFET biosensor by 25% and the underlapped gate structure improves the threshold voltage sensitivity 45% on an average.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89379678","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: 5

Machine Learning Aided Resource Allocation in a Downlink Multicarrier NOMA network with Coordinated Direct and Relay Transmission 机器学习辅助下多载波NOMA网络直接和中继协同传输的资源分配

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760683

S. Romera Joan, T. Manimekalai, T. Laxmikandan

引用次数: 1

Change Detection of SAR images based on Convolution Neural Network with Curvelet Transform 基于曲率变换卷积神经网络的SAR图像变化检测

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760534

Akula Jaswanth, N. Gupta, A. Mishra, Y. Hum

{"title":"Change Detection of SAR images based on Convolution Neural Network with Curvelet Transform","authors":"Akula Jaswanth, N. Gupta, A. Mishra, Y. Hum","doi":"10.1109/AISP53593.2022.9760534","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760534","url":null,"abstract":"Change detection is an essential task to study the changes of earth surfaces in remote sensing. It is extensively being investigated in SAR images nowadays. However, SAR images suffer from the speckle noise, which is a major drawback. To address the speckle noise problem, we propose the convolutional neural network with curvelet transform. As curvelet transform can suppress the noise, it is applied in preclassification, where the difference image is transformed using curvelet. Further, transformed image is classified by hierarchical fuzzy c-means (FCM) clustering, where each pixel is classified into different classes like changed class and unchanged class. From the preclassification, patches centered at the pixels belonging to these classes are generated as the training samples. Moreover, these training samples are passed through median filter before sending them to the convolutional neural network (CNN). The median filter helps in the reduction of noise. After the training of the CNN model, the trained model classifies the image pixels and provides the final binary change map. The experimental results obtained from the two SAR datasets confirm the effectiveness of the proposed method.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79527360","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: 1

An efficient Pulse Doppler Radar block level modeling with Xilinx System Generator 基于Xilinx System Generator的高效脉冲多普勒雷达块电平建模

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760687

Bujjibabu Penumutchi, Harichandraprasad Satti, Y. Ykuntam

{"title":"An efficient Pulse Doppler Radar block level modeling with Xilinx System Generator","authors":"Bujjibabu Penumutchi, Harichandraprasad Satti, Y. Ykuntam","doi":"10.1109/AISP53593.2022.9760687","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760687","url":null,"abstract":"RADAR (Radio Detection and Ranging) is an electromagnetic device used for detecting and locating objects from their reoccurrence signals. The received signal is then dealt with for information abstraction, like., target detection besides the velocity of the target. In CW radars the frequency measurement is done by de-modulating the received signal with respect to a transmitting. The matching velocity can be anticipated by passing the Doppler spectra through a filter bank. Finding the frequency in a pulse radar system is difficult than in CW radar. Thus, a better approach is the Doppler Processing state machine. The received signal is processed for required information. Detection is done by an algorithm called CFAR (Constant False Alarm Rate). In CFAR, a certain power threshold is determined. If the threshold is too high, then fewer targets are detected and conversely, if the threshold is too low then the false detection rate will increase. This threshold-based algorithm detects false targets in addition to original ones and to overcome this, a method called Cell Averaging Constant False Alarm Rate (CACFAR) would be used. Another parameter velocity is determined by Doppler frequency. The architecture is implemented in MATLAB/SIMULINK using Xilinx System Generator. To implement this model, three processing modules are required. Upon successful simulation, respective Verilog HDL code is generated and that code is run to observe design constraints like area, power, and delay. For CA-CFAR module at 2.5GHz frequency, the On-Chip power is 8.763W. At 0.95V, low On-chip power of 3.932W was observed at the frequency of 4GHz.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90623831","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

Applications of Raspberry Pi in Bio-Technology: A Review 树莓派在生物技术中的应用综述

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760691

Suseela Vappangi, Naveen Kumar Penjarla, Sudha Ellison Mathe, Hari Kishan Kondaveeti

{"title":"Applications of Raspberry Pi in Bio-Technology: A Review","authors":"Suseela Vappangi, Naveen Kumar Penjarla, Sudha Ellison Mathe, Hari Kishan Kondaveeti","doi":"10.1109/AISP53593.2022.9760691","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760691","url":null,"abstract":"The rapid growth in computational density and better computing, as well as the rise of worldwide knowledge transfer, have driven significant technological progress in the field of Biotechnology over the past few years. This is one of the primary technological advances expected to further transform this industry into low-cost single-board computers. So far, there hasn’t been a comprehensive analysis of the current adoption of these devices, as well as a general guide to assist researchers in incorporating them into their study. This study focuses on Raspberry Pi applicability in disciplines such as biotechnology, biosensors, bioprinters, biological, biosignal, bioaerosol, bioengineering, biochemical, biometrics and bioreactor. Since its initial introduction in 2012, the Raspberry Pi has gained popularity among a wide range of disciplines, as well as biologists in the lab, field and classrooms. A wide range of applications are available, from basic solutions such as nest box monitoring, wildlife camera capture, high-throughput behavioral recording, large-scale plant phenotyping, underwater video surveillance, closed-loop operant, to customized custom-built devices such as autonomous ecosystem monitoring. Despite the diversity of its applications, the Raspberry Pi has received only limited attention from the scientific community.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90631902","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