2022 International Conference on Emerging Smart Computing and Informatics (ESCI)最新文献_第8页

Performance Analysis of Massive MIMO Millimeter Wave NOMA HetNet 大规模MIMO毫米波NOMA HetNet性能分析

2022 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2022-03-09 DOI: 10.1109/ESCI53509.2022.9758313

Preksha Jain, Akhil Gupta

{"title":"Performance Analysis of Massive MIMO Millimeter Wave NOMA HetNet","authors":"Preksha Jain, Akhil Gupta","doi":"10.1109/ESCI53509.2022.9758313","DOIUrl":"https://doi.org/10.1109/ESCI53509.2022.9758313","url":null,"abstract":"It is anticipated that the number of devices will increase tremendously in the coming era of internet of things (IoT) technologies and massive machine-type communications (mMTC). Huge spectrum resources are required to serve such demands. The LTE networks have limited spectrum resources, and these resources have not been completely and efficiently utilized. Therefore, in dense network environments, LTE networks will not be able to evade data congestion and low access efficiency. To solve this problem, the paper uses millimeter Wave (mmWave) technology, as it has a huge unutilized spectrum available for communication. However, the mmWave channel cannot travel long distances, we deploy mmWave technology in smallcell along with massive multiple-input-multiple-output (mMIMO) non-orthogonal multiple access (NOMA) technologies. Smallcells have great potential to enhance cellular networks, and mMIMO and NOMA are promising technologies for next-generation wireless communications. Massive antenna array in massive MIMO offers high multiplexing gains. Whereas more than one user can access the same frequency-time resource simultaneously using NOMA, therefore, it helps in saving the spectrum resources. Moreover, a Heterogeneous Network (HetNet) model has the potential to provide high spatial reuse and high-frequency reuse. Therefore, the combination of mMIMO, mmWave, NOMA technologies employed in a HetNet can offer a significant increase in the rates. This paper carries out a performance analysis of a proposed system model employing mMIMO mmWave NOMA HetNet system model and compares it with a conventional HetNet system model. The simulation results show that the proposed HetNet system model outperforms the conventional HetNet system model in terms of spectral efficiency.","PeriodicalId":436539,"journal":{"name":"2022 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133168247","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

A Deep Learning Model for Human Emotion Recognition on Small Dataset 基于小数据集的人类情感识别深度学习模型

2022 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2022-03-09 DOI: 10.1109/ESCI53509.2022.9758261

Rupali Gill, Jaiteg Singh

引用次数: 1

Computer Vision-Based Smart Agriculture Storage with Quality and Quantity Analysis and Recipe Suggestion 基于计算机视觉的智能农业存储与质、量分析及配方建议

2022 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2022-03-09 DOI: 10.1109/ESCI53509.2022.9758220

V. K. Patil, Sunil Mahadev Pattar, Soumya Bhadani, Kalyani Kolte

{"title":"Computer Vision-Based Smart Agriculture Storage with Quality and Quantity Analysis and Recipe Suggestion","authors":"V. K. Patil, Sunil Mahadev Pattar, Soumya Bhadani, Kalyani Kolte","doi":"10.1109/ESCI53509.2022.9758220","DOIUrl":"https://doi.org/10.1109/ESCI53509.2022.9758220","url":null,"abstract":"A low-cost Computer Vision-based crop yield classifier for the crop stored inside the container is proposed with this experimentation. This system includes options for analyzing quantity and quality. In quantity analyses the crops such as wheat and rice are classified using a camera and computer vision algorithms and the data is saved in the firebase cloud. In quality analysis, the quality of fruits and vegetables is assessed using the TensorFlow object detection API, and the results are stored in the cloud alongside recipe ideas. Intelli-container also offers a function called monitoring mode for security purposes, in which content inside the system is periodically examined and the user is notified via a web application if there is any theft or missing objects. The web app was designed using HTML and Bootstrap. It displays the real-time updates and suggests a recipe based on the vegetables and eatables present inside the container with a help of the Computer Vision approach. The proposed system contains raspberry pi as the main unit and peripheral sensors like loadcell, HX711 module, and camera module. The system uses TensorFlow modules for classification and object detection using python. With this paper, we are proposing a new term for our implemented system as Intelli-Container (Intelligent +Container). This system is useful for machine learning-based smart agricultural purposes for quality, quantity, and security. As our system is capable of quality and quantity analysis, Also, our proposed system is useful for paying the minimum Support Price (MSP) directly to farmers without intervention middlemen, Thus, this paper has social application in good governance. Another application of our prototype is for giving recommendations for recipes using food in this Inteli_container.","PeriodicalId":436539,"journal":{"name":"2022 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130706838","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

Patch-Based Classification for Alzheimer Disease using sMRI 基于贴片的老年痴呆症sMRI分类

2022 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2022-03-09 DOI: 10.1109/ESCI53509.2022.9758317

Nitika Goenka, Ankit Goenka, Shamik Tiwari

{"title":"Patch-Based Classification for Alzheimer Disease using sMRI","authors":"Nitika Goenka, Ankit Goenka, Shamik Tiwari","doi":"10.1109/ESCI53509.2022.9758317","DOIUrl":"https://doi.org/10.1109/ESCI53509.2022.9758317","url":null,"abstract":"Alzheimer's disease, the most severe form of dementia, is a neuronal destructive brain ailment that worsens over time with no cure thereby realizing its importance in its early detection. Nowadays, convolutional neural network, especially 3-Dimensional networks are becoming popular for detecting medical illness due to its inherent nature of capturing spatial dimensions as well. In our study, we have worked on 3D patch-based feature extraction technique where these patches are generated using torch library and passed into 19 layered ConvNet for classification. The MRI images (Magnetic Resonance Imaging) are obtained from MIRIAD database (Minimal Interval Resonance Imaging in Alzheimer's disease) are pre-processed for bias correction, skull stripping and registration and further augmented by rotation algorithm to increase dataset size and finally classified into Normal Control (NC) and Alzheimer Disease (AD) with 99.79 percent accuracy. This classification will provide great assistance to all especially in lack of clinicians' availability during the time of pandemic and remote areas where experts are not in reach.","PeriodicalId":436539,"journal":{"name":"2022 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122890249","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

Intelligent Action Performed Load Balancing Decision Made in Cloud Datacenter Based on Improved DQN Algorithm 基于改进DQN算法的云数据中心智能动作负载均衡决策

2022 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2022-03-09 DOI: 10.1109/ESCI53509.2022.9758369

Arabinda Pradhan, S. Bisoy

引用次数: 0

An Intelligent Framework for Crime Prediction Using Behavioural Tracking and Motion Analysis 基于行为跟踪和运动分析的智能犯罪预测框架

2022 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2022-03-09 DOI: 10.1109/ESCI53509.2022.9758281

Rajat Shenoy, Deepak Yadav, Harshita Lakhotiya, Jignesh Sisodia

{"title":"An Intelligent Framework for Crime Prediction Using Behavioural Tracking and Motion Analysis","authors":"Rajat Shenoy, Deepak Yadav, Harshita Lakhotiya, Jignesh Sisodia","doi":"10.1109/ESCI53509.2022.9758281","DOIUrl":"https://doi.org/10.1109/ESCI53509.2022.9758281","url":null,"abstract":"Closed Circuit Television Systems are now being deployed in most public spaces to make the city more secure. Manual observation of these clips for the prevention of crime would take up a lot of manpower. This paper proposes an Intelligent Framework using the power of Artificial Intelligence to ensure the safety of the surroundings. The system will use different Computer Vision techniques for video analysis. It will monitor CCTV footage for any criminal offenders, violent objects, and suspicious behavior which could lead to crime. SSD Mobilenet Model, an architecture for concealed object detection, is trained for labeling weapons in the frame. The images captured are processed using Face Detection algorithms to identify human faces. Facial Recognition API using libraries in python is implemented to recognize the offenders from criminal records. A ResNet-GRU Model was trained for human behavior analysis which detects suspicious actions. An alert is generated when there are signs of crime and concerned authorities are notified. The proposed framework aims to make societies secure by correctly identifying criminals and crime-related objects.","PeriodicalId":436539,"journal":{"name":"2022 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129308072","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

An Event Study Analysis on Stock Market Reaction amid Geo-Political Crisis in India 印度地缘政治危机下股市反应的事件研究分析

2022 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2022-03-09 DOI: 10.1109/ESCI53509.2022.9758374

Rajit Verma, K. Sood, Shivani Inder

{"title":"An Event Study Analysis on Stock Market Reaction amid Geo-Political Crisis in India","authors":"Rajit Verma, K. Sood, Shivani Inder","doi":"10.1109/ESCI53509.2022.9758374","DOIUrl":"https://doi.org/10.1109/ESCI53509.2022.9758374","url":null,"abstract":"Geo-political conflicts have always impacted stock markets and valuation of companies either adversarly or inversaly, depending upon the magnitude and timing of such event. The present study focuses on the impact of Prime Minister Narendra Modi's speech on national security on 15th February 2019 on two major indices of Indian Capital Market i.e. BSE SENSEX 30 and CNX Nifty 50. The study included SENSEX 30 stocks and Nifty 50 stocks to examine the magnitude of PM Modi's brave and courageous speech on selected 76 sample stocks. The study found that PM's speech triggered the investors' sentiments in Indian capital market followed by a strong positive reaction by the two major capital market indices such as BSE SENSEX and CNX Nifty 50. The study showed the significant results during 31 days event study window. Further the study revealed that stocks continued to increase for consecutive 11 days and after Balakot air strike on militant camps both the share markets reflected negative trend in most of the stocks. The study concluded that if investors can link such speeches on national security with overall movements of share market, it would be beneficial for the investors and able to maximize the worth of their invested money in stocks","PeriodicalId":436539,"journal":{"name":"2022 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121351239","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

Design of Rubber Substrate based Flexible Antenna with DGS for WBAN Applications 基于橡胶基板的无线广域网DGS柔性天线设计

2022 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2022-03-09 DOI: 10.1109/ESCI53509.2022.9758201

Satyam, Neelima K, N. Divya, K. Karthikeyan, N. Kumar

引用次数: 6